Miracle-dz/UniFAR-FTUs huggingface dataset:
Reductive Dehalogenase Gene Expression as a Biomarker for Physiological Activity of Dehalococcoides spp

ABSTRACT This study characterizes the transcriptional expression of the reductive dehalogenase (RDase)-encoding tceA and vcrA genes and evaluates their applicability as potential biological markers of Dehalococcoides activity. When Dehalococcoides ethenogenes 195 was provided with trichloroethene (TCE) as the electron acceptor, the expression of the tceA gene increased by 90-fold relative to that in cells starved of chlorinated ethenes, demonstrating that tceA gene expression is indicative of the active physiological state of this strain. In a Dehalococcoides-containing enrichment culture that contains both the tceA and vcrA genes, the tceA gene was up-regulated in response to TCE and cis-1,2-dichloroethene (cDCE) exposure, while the vcrA gene was up-regulated in response to TCE, cDCE, and vinyl chloride (VC). When chlorinated ethenes were depleted, the RDase-encoding gene transcripts decayed exponentially, with a half-life between 4.8 and 6.1 h, until they reached a stable background level after 2 days. We found that while gene expression correlated generally to the presence of chlorinated ethenes, there was no apparent direct relationship between RDase-encoding transcript numbers and respective rates of TCE, cDCE, and VC dechlorination activities. However, elevated tceA and vcrA expression did correlate with chlorinated-ethene reduction beyond cDCE, suggesting that elevated RDase-encoding transcript numbers could serve as a biomarker for the physiological ability of Dehalococcoides spp. to dechlorinate beyond cDCE.
Trend-Aware User Modeling with Location-Aware Trends on Twitter

Microblogs are a phenomenon of modern social media. As there is much real-time social information in there, they are candidates to be used as a source for mining important information enhancing user experience in variety of web applications, especially those related with content adaptation and recommendation. In this paper we deal with microblog-based user models. We propose trend-aware user model with location-aware trends, which focuses on location aspects and trends. It is a general model, which can be used in various domains. We evaluated the model in a domain of news recommendations and we showed that recommendation based on this model outperforms state-of-the-art approaches.
A Randomized Study Assessing the Effect of Diet in Cats with Hypertrophic Cardiomyopathy

Background Diet might influence progression of hypertrophic cardiomyopathy (HCM). Objective To investigate whether diet composition could alter clinical, biochemical, or echocardiographic variables in cats with HCM. Animals Twenty‐nine cats with HCM (International Small Animal Cardiac Health Council stage 1b) examined at a university teaching hospital. Methods Randomized, placebo‐controlled trial. After physical examination, echocardiogram, and blood collection, cats were randomized to 1 of 3 diets, which varied in carbohydrate and fat content and ingredients. Measurements were repeated after 6 months. Results There were no significant differences among the 3 groups at baseline. After 6 months, there were no significant changes in the primary endpoints, left ventricular free wall (Group A, P = .760; Group B, P = .475; Group C, P = .066) or interventricular septal thickness in diastole (Group A, P = .528; Group B, P = .221; Group C, P = .097). Group A had significant increases in BUN (P = .008) and cholesterol (P = .021), while Group B had significant increases in BUN (P = .008), cholesterol (P = .007), and triglycerides (P = .005), and significant decreases in NT‐proBNP (P = .013) and hs‐troponin I (P = .043). Group C had significant decreases in body weight (P = .021), left atrial dimension (P = .035), interventricular septal thickness in systole (P = .038), and liver enzymes (P = .034–.038). Conclusions and Clinical Importance These data suggest that diet might influence some clinical, biochemical, and echocardiographic variables in cats with HCM.
How Fast Do Equilibrium Payoff Sets Converge in Repeated Games?

We provide tight bounds on the rate of convergence of the equilibrium payoff sets for repeated games under both perfect and imperfect public monitoring. The distance between the equilibrium payoff set and its limit vanishes at rate (1 - delta)^{1/2} under perfect monitoring, and at rate (1 - delta)^{1/4} under imperfect monitoring. For strictly individually rational payoff vectors, these rates improve to 0 (i.e., all strictly individually rational payoff vectors are exactly achieved as equilibrium payoffs for delta high enough) and (1 - delta)^{1/2}, respectively.
Adaptive Web Proxy Caching Algorithms

Web proxy caching is a well-known technique for reducing access latencies and bandwidth consumption. As in other caching systems, a replacement policy is necessary for determining when and what to evict from the cache, and many proxy caching algorithms have been proposed and evaluated over the years. Yet many of these algorithms were motivated by the Internet traffic trends in place during the design of the algorithms (1997–1999). The recent proliferation then subsequent decline in the use of peer-to-peer systems suggests that the performance of proxy caching algorithms may have changed dramatically since their inception. This paper analyzes the distribution of current web content and re-evaluates various proxy cache replacement algorithms including LFU, LRU and several GreedyDual variants. Based on the change in Internet traffic trends identified, two new web caching algorithms are proposed: a local policy that maintains a list of popular URLs and a global policy that partitions the cache into distinct regions, each of which is sized according to the popularity of the type of object being cached. Our results indicate that for small cache sizes LFU and LRU have higher byte-hit rates than several GreedyDual variants on modern Internet traffic. We also found that maintaining a hot list improves byte-hit rate, while a cache-by-regions approach improves hit rate.
Bayesian Probabilistic Vehicle Lane Matching for Link-Level In-Vehicle Navigation

Today's typical in-vehicle navigation systems that use the Global Positioning System (GPS) to measure longitudinal and latitudinal position of a vehicle do not have sufficient lane-positioning accuracy for detailed navigational tasks such as vehicle maneuvers and safety. This paper presents a unique estimation methodology that can determine a vehicle's lane position in real time by mapping the spatial position measurements onto the specific lane the vehicle is running on with reference to a lane-enhanced digital map. This vehicle lane positioning system is described, comprising a low-cost real-time differential GPS system, a high accuracy digital map, and a lane-determination algorithm. Further, the developed low-cost system has been tested on a number of roadways and has performed very well when used with accurately surveyed map data. Lane-level positioning opens up the door to a number of new applications such as link-level maneuvering and vehicle safety applications
Formal models of Web queries

Abstract We present a new formal model of query and computation on the Web. We focus on two important aspects that distinguish the access to Web data from the access to a standard database system: the navigational nature of the access and the lack of concurrency control. We show that these two issues have significant effects on the computability of queries. To illustrate the ideas and how they can be used in practice for designing appropriate Web query languages, we consider a particular query language, the Web calculus, an abstraction and extension of the practical Web query language WebSQL.
Improved Segmentation Based on Probabilistic Labeling

⎯This paper presents an improved multi-object segmentation algorithm based on probabilistic labeling. First, a critical look is focused on utilizing vector calculus operator and combinational operator to rewrite Dirichlet integral into a matrix form, and boundary condition is defined to obtain the needed harmonic function. The only unique parameter β that dominantly affects the segmentation performance is characterized. According to the result, we propose an improved parameter that changes the value of β on the basis of pixel-by-pixel, rather than the use of a fixed constant β throughout the whole image. Furthermore, a pre-process involving the use of watershed analysis is applied to smooth the effect of high frequency components in the input image, so that better noise tolerance and more accurate object contours can be obtained. Index Terms image segmentation, graph theory, Dirichlet problem, harmonic function, watershed analysis
Universal Kernel-Based Learning with Applications to Regular Languages

We propose a novel framework for supervised learning of discrete concepts. Since the 1970's, the standard computational primitive has been to find the most consistent hypothesis in a given complexity class. In contrast, in this paper we propose a new basic operation: for each pair of input instances, count how many concepts of bounded complexity contain both of them. Our approach maps instances to a Hilbert space, whose metric is induced by a universal kernel coinciding with our computational primitive, and identifies concepts with half-spaces. We prove that all concepts are linearly separable under this mapping. Hence, given a labeled sample and an oracle for evaluating the universal kernel, we can efficiently compute a linear classifier (via SVM, for example) and use margin bounds to control its generalization error. Even though exact evaluation of the universal kernel may be infeasible, in various natural situations it is efficiently approximable. Though our approach is general, our main application is to regular languages. Our approach presents a substantial departure from current learning paradigms and in particular yields a novel method for learning this fundamental concept class. Unlike existing techniques, we make no structural assumptions on the corresponding unknown automata, the string distribution or the completeness of the training set. Instead, given a labeled sample our algorithm outputs a classifier with guaranteed distribution-free generalization bounds; to our knowledge, the proposed framework is the only one capable of achieving the latter. Along the way, we touch upon several fundamental questions in complexity, automata, and machine learning.
Influence of Geological Conditions on Measured TBM Vibration Frequency

This paper examines TBM vibration as a source of information about geological conditions. An EPB TBM was outfitted with accelerometers to monitor vibration during excavation of the University Link light rail tunnel project (U230) in Seattle Washington. Impact-response testing of the TBM indicated that significant signal over a wide range of frequencies transfers from the cutterhead where vibration due to ground interactions emanate, to the bulkhead where sensors can be installed. Analysis of the vibration data collected during excavation indicates that both amplitude and frequency content appear to be influenced by TBM operating parameters and by geological conditions. INTRODUCTION The vibration characteristics of a system when subjected to external stimulus have long been used as a way to monitor the system itself. For example, the field of vibration based condition or health monitoring uses the measured vibration response and its changes to identify wear and damage of rotating shafts, wind turbines, hydroelectric turbines, bridges and buildings. The vibration characteristics of earth construction equipment have been used in the same manner and also to interrogate the condition of the ground with which the equipment is interacting. Examples include intelligent vibratory soil compactors and smart drilling (Mooney & Rinehart 2009, Richard et al. 2002). In the former case, the elastic stiffness and compacted state of the soil is estimated based on measured drum vibration. In the latter case, the rock hardness and strength is estimated based on measured drill bit vibration. The goal of the study described in this paper is to develop a similar approach where TBM vibration can be used to assess geological conditions. The underlying premise is that the measurable vibration characteristics of equipment interacting with the ground will be influenced by the ground properties under certain operating conditions. The ground conditions, therefore, can be estimated by back-analysis that uses either statistical or physical models of the ground/machine interaction. For example, a vibratory drum operating on soil can be physically modeled with lumped masses, springs and dashpots (see figure 1). The model predicts the contact force vs. deflection response that is a function of the roller parameters, operating frequency and amplitude, as well as the assumed ground stiffness and damping. Through a process of matching experimentally measured vibration response to modeled response, the ground stiffness and damping are estimated. This estimation of soil stiffness and compacted state is provided continuously and in real time, and is now routinely performed in earthwork construction practice. If a physical model is difficult to develop, statistical approaches can also be used. For example, in smart drilling, empirical relationships between measured vibration amplitudes and frequencies with rock types and stress conditions have been developed through statistical analysis. The rock type can then be estimated based on these empirical models.
Perceived Self-Efficacy and APIs

Application program interface (API) use and design is critical, non-optional, and cross-cutting in the construction of modern software systems. However, only recently has the explicit study of API design process and API designs been initiated from the perspective of usability, and little is known with respect to how various forms of information about an API aids programmers in the use of an API. In this paper, we present findings from our exploration of perceived self-efficacy (PSE) for API use. First, we describe the development of a novel PSE instrument that focuses on the task of using an API. Second, we evaluate the validity and sensitivity of the instrument with respect to changes in the information given professional programmers about an API. To accomplish this goal, we articulate and utilize two complementary forms of API documentation grounded in scenario-based design. Through this work, we demonstrate the validity of the evaluation tool and raise questions about the perceived value developers place on information about an API and its intended use.
Policy as Social Ecological Resilience Scaffolding for Leaving Care

This chapter’s authors argue that social policy on leaving care is a critical resilience process for promoting care leavers’ successful transition toward emerging adulthood. Care leaving literature has given limited attention to the wider policy contexts in which care leavers make this transition. This chapter argues for a better understanding of how these contexts can bolster the social ecology of care leaving by providing a policy scaffolding to the support and services required by care leavers. South Africa is used to illustrate the argument, capitalizing on the heightened political sensibilities of a society still grappling with the legacy of apartheid and committed to developmental social welfare as a strategic policy direction. The chapter concludes that the South African case study not only highlights the need to address the policy context of youth transitioning from out-of-home care, but also demonstrates the benefits of cross-national reflection on policy and practice development and implementation.
Impact of Propagation Environment on Energy-Efficient Relay Placement: Model and Performance Analysis

The performance of a relay-based cellular network is greatly affected by the relay location within a cell. Existing results for optimal relay placement do not reflect how the radio propagation environment and choice of the coding scheme can impact system performance. In this paper, we analyze the impact on relaying performance of node distances, relay height and line-of-sight conditions for both uplink and downlink transmissions, using several relay coding schemes. Our first objective is to propose a geometrical model for energy-efficient relay placement that requires only a small number of characteristic distances. Our second objective is to estimate the maximum cell coverage of a relay-aided cell given power constraints, and conversely, the averaged energy consumption given a cell radius. We show that the practical full decode-forward scheme performs close to the energy-optimized partial decode-forward scheme when the relay is ideally located. However, away from this optimum relay location, performance rapidly degrades and more advanced coding scheme, such as partial decode-forward, is needed to maintain good performance and allow more freedom in the relay placement. Finally, we define a trade-off between cell coverage and energy efficiency, and show that there exists a relay location for which increasing the cell coverage has a minimal impact on the average energy consumed per unit area.
Negative Pressure Wound Therapy Reduces the Effectiveness of Traditional Local Antibiotic Depot in a Large Complex Musculoskeletal Wound Animal Model

Objectives Negative pressure wound therapy (NPWT) has been used to help manage open wounds. Surgeons also often use local antibiotic depot as adjunctive therapy in an effort to reduce infection rates. These 2 techniques have been reported to be used in conjunction, but there are little data to support this practice. We sought to compare the contamination levels of wounds treated with the commonly used antibiotic bead pouch technique to wounds that received both antibiotic beads and NWPT. Methods The effectiveness of a bead pouch was compared with antibiotic beads with NPWT. The anterior compartment and proximal tibia of goats were injured and inoculated with Staphylococcus aureus. Six hours later, the wounds were debrided and the animals were assigned to a group; the bacteria level was quantified immediately before and after initial debridement and 2 days after treatment. Results The wounds in the antibiotic bead pouch group had 6-fold less bacteria than the augmented NPWT group, 11 ± 2% versus 67 ± 11% of baseline values, respectively (P = 0.01). As expected, high levels of the antibiotic were consistently recovered from the augmented NPWT effluent samples at all time points. Conclusions NPWT reduces the effectiveness of local antibiotic depot. These results can provide surgeons with the information to personalize the adjunctive therapies to individual patients, with the degree of difficulty in managing the wound and concern for infection being the 2 variables dictating treatment.
Kalman filtering and smoothing solutions to temporal Gaussian process regression models

In this paper, we show how temporal (i.e., time-series) Gaussian process regression models in machine learning can be reformulated as linear-Gaussian state space models, which can be solved exactly with classical Kalman filtering theory. The result is an efficient non-parametric learning algorithm, whose computational complexity grows linearly with respect to number of observations. We show how the reformulation can be done for Matérn family of covariance functions analytically and for squared exponential covariance function by applying spectral Taylor series approximation. Advantages of the proposed approach are illustrated with two numerical experiments.
Numerical renormalization-group calculations for similarity solutions and traveling waves.

We present a numerical implementation of the renormalization group (RG) for partial differential equations, constructing similarity solutions and traveling waves. We show that for a large class of well-localized initial conditions, successive iterations of an approximately defined discrete RG transformation in space and time will drive the system towards a fixed point. This corresponds to a scale-invariant solution, such as a similarity or traveling-wave solution, which governs the long-time asymptotic behavior. We demonstrate that the numerical RG method is computationally very efficient.
The Impact of Sexual Assault Training and Gender on Rape Attitudes

iii ACKNOWLEDGEMENTS . v CHAPTER ONE: SEXUAL ASSAULT TRAINING AND RAPE MYTH ACCEPTANCE Sexual Assault . 1 Sexual Assault Prevention . 5 Rape Myth Acceptance . 13 Behavioral Indices of Sexual Assault . 15 The Present Study . 22 CHAPTER TWO: METHOD Participants . 25 Measures . 26 Procedure . 30 CHAPTER THREE: RESULTS Design and Statistical Analysis . 32 Associations Between Variables . 33 Comparisons Between Men and Women . 33 Moderation Analyses . 34 CHAPTER FOUR: DISCUSSION . 35 APPENDIX A: IRB . 41 APPENDIX B: QUESTIONAIRRES AND VIGNETTE TRANSCRIPT . 44 APPENDIX C: DEMOGRAPHICS AND CHARACTERISTICS OF SAMPLE . 55
Intelligent spam classification for mobile text message

This paper analyses the methods of intelligent spam filtering techniques in the SMS (Short Message Service) text paradigm, in the context of mobile text message spam. The unique characteristics of the SMS contents are indicative of the fact that all approaches may not be equally effective or efficient. This paper compares some of the popular spam filtering techniques on a publically available SMS spam corpus, to identify the methods that work best in the SMS text context. This can give hints on optimized spam detection for mobile text messages.
Assessing the capability and maturity of capstone software engineering projects

This paper describes an approach for assessing the capability and maturity of undergraduate software engineering projects. The approach is based on a simple adaptation of the Capability Maturity Model ® Integration and a hybrid version of the Team Software Process (TSPi). The approach was evaluated using 6 capstone project teams comprising 23 undergraduate software engineering students. A capability and maturity baseline was established at the end of first semester. A second capability and maturity assessment was undertaken towards the end of second semester. The approach was shown to focus student attention on process improvement and on the attainment of realistic and measurable project management goals. The approach was also found to contribute to the development of teamwork and leadership skills, and to prepare students for professional practice.