Miracle-dz/UniFAR-FTUs huggingface dataset:
Ammonia Inhibition of Plasmid pRmeGR4a Conjugal Transfer between Rhizobium meliloti Strains

We have examined nutritional factors influencing conjugal transfer of the two nonsymbiotic large plasmids, pRmeGR4a and pRmeGR4b, of Rhizobium meliloti GR4. To monitor transfer, each plasmid was tagged with a different antibiotic resistance marker. Transfer of plasmid pRmeGR4b was dependent upon the presence of plasmid pRmeGR4a on the same donor cell. Transconjugants for pRmeGR4b were obtained at frequencies 5-to 10-fold higher than transconjugants carrying both plasmids, indicating that mobilization of pRmeGR4b by pRmeGR4a probably occurred in trans. Conjugal transfer of the tagged plasmids between R. meliloti strains was tested on minimal medium supplemented with single amino acids, nitrate, or ammonium as the single nitrogen source. A higher number of transconjugants was obtained when glutamate was the only nitrogen source, whereas conjugation was virtually undetectable on ammonium. No relationship was found between donor or recipient growth rate and plasmid transfer rate on a given nitrogen source. Furthermore, in media containing both glutamate and ammonium as nitrogen sources, transfer was reduced almost 100-fold compared with that in media containing glutamate alone. Inhibition was readily detected at 2.5 mM or higher concentrations of either ammonium chloride or ammonium sulfate and appeared to be specific for exogenously supplied ammonium. Inhibition of conjugal transfer between R. meliloti strains by ammonium was only observed for rhizobial plasmids, not for a heterologous plasmid such as RP4. Apparently, ammonium did not affect the plasmid-encoded transfer machinery, as it had no influence on rhizobial plasmid transfer from R. meliloti to Agrobacterium tumefaciens. The effect of ammonium seemed to take place on R. meliloti recipient cells, thereby reducing the efficiency of plasmid conjugation, probably by affecting mating pair formation or stabilization.
Design and Analysis of a Secure Three Factor User Authentication Scheme Using Biometric and Smart Card

Password security can no longer provide enough security in the area of remote user authentication. Considering this security drawback, researchers are trying to find solution with multifactor remote user authentication system. Recently, three factor remote user authentication using biometric and smart card has drawn a considerable attention of the researchers. However, most of the current proposed schemes have security flaws. They are vulnerable to attacks like user impersonation attack, server masquerading attack, password guessing attack, insider attack, denial of service attack, forgery attack, etc. Also, most of them are unable to provide mutual authentication, session key agreement and password, or smart card recovery system. Considering these drawbacks, we propose a secure three factor user authentication scheme using biometric and smart card. Through security analysis, we show that our proposed scheme can overcome drawbacks of existing systems and ensure high security in remote user authentication.
A new system for online quantitative evaluation of optical see-through augmentation

A crucial aspect in the implementation of an augmented reality (AR) system is determining its accuracy. The accuracy of a system determines the applications it can be used for. The aim of our research is measuring the overall accuracy of an arbitrary AR system. Once measurements of a system are made, they can be analyzed for determining the structure and sources of errors. From the analysis it may also be possible to improve the methods used to calibrate and register the virtual to the real. This paper describes an online system for measuring the registration accuracy of optical see-through augmentation. By online, we mean that the user can measure the registration error they are experiencing while they are using the system. We overcome the difficulty of not having retinal access by having the user indicate the projection of a perceived object on a planar measurement device. Our method provides information which can be used to analyze the structure of the system error in two or three dimensions. The results of the application of our method to two monocular optical see-through AR systems are shown.
Teachers' Perceptions, Teaching Practices, and Learning Opportunities for Inclusion.

Lack of expertise of general physical educators relative to teaching students with disabilities in inclusive general physical education (GPE) has been identified as a major challenge affecting the implementation of inclusion in the United States (Block & Obrusnikova, 2007). Several studies indicated that insufficient inclusion training (Hodge, Ammah, Casebolt, LaMaster, & O’Sullivan, 2004; Lieberman, Houston-Wilson, & Kozub, 2002; Smith & Green, 2004) during teacher preparation resulted in teachers’ negative feelings toward inclusion. The current study was designed to explore GPE teachers’ views of teaching students with disabilities in their GPE classes to gain understanding of teachers’ teaching practices, learning, needs, and challenges. Specific research questions related to inclusion focused on teachers’ (a) perceptions, (b) teaching practices, (c) learning, and (d) needs related to teaching inclusive GPE classes. Data consisted of individual interviews, teachers’ artifacts, and researcher’s journals . Seven elementary physical educators, whose teaching experiences ranged from 8 to 16 years, participated. Data were analyzed using content and constant comparison. Trustworthiness was established through triangulation of the data, peer review and debriefing, and member checking. Four themes emerged: (a) dedication to inclusion, (b) necessity of adaptation, (c) experimental practices, and (d) challenges to inclusion. These findings are discussed in light of a pedagogical framework (Feiman-Nemser, 2001) that provides insights about the ongoing professional development needs of teachers. These findings suggest “coherent and connected learning opportunities” (Feiman-Nemser, 2001, p. 1048) are needed across teachers’ careers.
Endothelial cytotoxicity mediated by serum antibodies to heat shock proteins of Escherichia coli and Chlamydia pneumoniae: immune reactions to heat shock proteins as a possible link between infection and atherosclerosis.

BACKGROUND Growing evidence suggests that an immunological reaction against heat shock proteins (HSPs) may be involved in atherogenesis. Because HSPs show a high degree of amino acid sequence homology between different species, from prokaryotes to humans, we investigated the possibility of "antigenic mimicry" caused by an immunological cross-reaction between microorganisms and autoantigens. METHODS AND RESULTS Serum antibodies against the Escherichia coli HSP (GroEL) and the 60-kDa chlamydial HSP (cHSP60) from subjects with atherosclerosis were purified by use of affinity chromatography. Western blot analyses and competitive ELISAs confirmed the cross-reaction of the eluted antibodies with human HSP60 and the bacterial counterparts. The cytotoxicity of anti-GroEL and anti-cHSP60 antibodies was determined on human endothelial cells labeled with 51Cr. A significant difference (40% versus 8%) was observed in the specific 51Cr release of heat-treated (42 degrees C for 30 minutes) and untreated cells, respectively, in the presence of these anti-HSP antibodies and complement. This effect was blocked by addition of 100 microg/mL recombinant GroEL. In addition, seropositivity against specific non-HSP60 Chlamydia pneumoniae antigens is more prominent among high-anti-HSP titer sera than low-titer sera. CONCLUSIONS Serum antibodies against HSP65/60 cross-react with human HSP60, cHSP60, and GroEL; correlate with the presence of antibodies to C pneumoniae and endotoxin; and mediate endothelial cytotoxicity. These findings suggest that humoral immune reactions to bacterial HSPs, such as cHSP60 and GroEL, may play an important role in the process of vascular endothelial injury, which is believed to be a key event in the pathogenesis of atherosclerosis.
Firefighter injuries are not just a fireground problem.

BACKGROUND Linking firefighter injury reporting to general motion patterns may provide insight into potential injury mechanisms and the development of prevention strategies. OBJECTIVE To characterize the injuries sustained by members of a large Canadian metropolitan fire department over a 5-year span. METHODS Data were taken from injury reports filed by career firefighters between 2007 and 2011. Injuries were described by job duty, type, body part affected, and the general motion pattern employed at the time of injury (e.g. lifting). RESULTS Of the 1311 injuries reported, 64% were categorized as sprains and strains (musculoskeletal disorders -MSDs), the most frequent of which affected the back (32%). Categorized by job duty, 65% of MSDs were sustained while working at the fire station or during physical training-related activities. Only 15% were attributed to fireground operations. Furthermore, the associated job duty could not differentiate the types of injuries sustained; back injuries occurred primarily while lifting, knee injuries while stepping, and shoulder injuries during pushing/pulling-related activities. CONCLUSIONS Firefighter injuries are not just a fireground problem. Injury causation may be better understood by linking the injury location and type with motion patterns rather than job duties. This information could assist in developing general prevention strategies for the fire service.
Internet Active Proxy Active Proxy Bases Active Proxies Units Path

The cooperation between the Ninja and SmartDust projects at the University of California at Berkeley has produced an operating system that runs on a set of networked sensors. The sensors are connected through a wireless radio. The error characteristics in the data transmissions are not well known or well understood; the knowledge of the error patterns will allow the system designers to pick an encoding scheme for the packets. We present a study of these error characteristics. In the process of characterizing these errors, we discovered several problems within Tiny OS. The error characteristics show that the current encoding scheme used by the designers of TinyOS is inappropriate.
Novel actions of aspirin and sodium salicylate: discordant effects on nitric oxide synthesis and induction of nitric oxide synthase mRNA in a murine macrophage cell line

Aspirin and sodium salicylate each inhibit to a similar extent the production of nitric oxide (NO) in the RAW 264.7 murine macrophage cell line following stimulation by either lipopolysaccharide (LPS) or interferon‐γ(IFN‐γ). The similar potencies of aspirin and sodium salicylate indicate that acetylation of cellular macromolecules is not essential for the observed effects. The failure of added prostaglandin E2 to overcome the effects of aspirin or sodium salicylate indicates that these effects are not simply the result of inhibition of prostaglandin synthesis. The inhibition of NO production occurs irrespective of the effect of these agents on induction of nitric oxide synthase (iNOS) mRNA by LPS or IFN‐γ. Aspirin and sodium salicylate inhibit iNOS mRNA induction in LPS‐stimulated cells but enhance iNOS mRNA induction in IFN‐γ‐stimulated cells. In contrast, these agents consistently inhibit induction of argininosuccinate synthetase mRNA in both LPS‐ and IFN‐γ‐stimulated cells. Concentrations of aspirin in the 3–10 mM range inhibit induced NO production and expression of iNOS protein without inhibiting induction of iNOS mRNA. Discordances between effects on NO synthesis and induction of iNOS mRNA indicate that aspirin and sodium salicylate have multiple sites of action in their effects on pathways that are involved in the production of NO by stimulated RAW 264.7 cells.
The impact of structured reflective practice on the teaching decisions of in-service teachers

THE IMPACT OF STRUCTURED REFLECTIVE PRACTICE ON THE TEACHING DECISIONS OF IN-SERVICE TEACHERS THOMAS E. KELLY, A.B. , HOLY CROSS COLLEGE M. Ed., BRIDGEWATER STATE COLLEGE M.B.A. UNIVERSITY OF MASSACHUSETTS at DARTMOUTH Ed.D. , UNIVERSITY OF MASSACHUSETTS Directed by: Professor William Lauroesch Utilizing a multi-method, in-depth, qualitative approach, this study investigates the impact of structured reflective practice on the teaching decisions of five in-service classroom teachers. Over a twelve week period, participants engaged in daily reflective practice about their teaching. Through the use of daily journals, a structured format for reflection, and regular sessions with a content-expert observer/facilitator, participants became specifically aware of their teaching decisions and engaged in a comprehensive analysis of them. Most participants developed their reflection to the stage of actively generating alternative decisions to those made during instruction. The findings of the study confirm that reflective practice is a developmental competence that can be nurtured in all teachers. Further, the model described in the study can be used to effectively support the acquisition of reflective practice capabilities by
Mind The Power Holes: Sifting Operating Points in Power-Limited Heterogeneous Multicores

Heterogeneous chip multicore processors (HCMPs) equipped with multiple voltage-frequency (V-F) operating points provide a wide spectrum of power-performance tradeoff opportunities. This work targets the performance of HCMPs under a power cap. We show that for any performance optimization technique to work under power constraints, the default set of V-F operating points in HCMPs must be first filtered based on the application’s power and performance characteristics. Attempting to find operating points of maximum performance by naively walking the default set of operating points leads the application to inefficient operating points which drain power without significant performance benefit. We call these points <italic>Power Holes (PH)</italic>. Contrary to intuition, we show that even using a power-performance curve of Pareto-optimal operating points still degrades performance significantly for the same reason. We propose PH-Sifter, a fast and scalable technique that sifts the default set of operating points and eliminates power holes. We show significant performance improvement of PH-Sifter compared to Pareto sifting for three use cases: (i) maximizing performance for a single application, (ii) maximizing system throughput for multi-programmed workloads, and (iii) maximizing performance of a system in which a fraction of the power budget is reserved for a high-priority application. Our results show performance improvements of 13, 27, and 28 percent on average that reach up to 52, 91 percent, and 2.3<inline-formula><tex-math notation="LaTeX">$\times$</tex-math><alternatives> <inline-graphic xlink:href="adileh-ieq1-2616339.gif"/></alternatives></inline-formula>, respectively, for the three use cases.
Reducing Semantic Drift with Bagging and Distributional Similarity

Iterative bootstrapping algorithms are typically compared using a single set of hand-picked seeds. However, we demonstrate that performance varies greatly depending on these seeds, and favourable seeds for one algorithm can perform very poorly with others, making comparisons unreliable. We exploit this wide variation with bagging, sampling from automatically extracted seeds to reduce semantic drift. However, semantic drift still occurs in later iterations. We propose an integrated distributional similarity filter to identify and censor potential semantic drifts, ensuring over 10% higher precision when extracting large semantic lexicons.
Mining and Predicting CpG islands

A DNA sequence can be described as a string composed of four symbols: A, T, C and G. Each symbol represents a chemically distinct nucleotide molecule. Combinations of two nucleotides are called dinucleotides and CpG islands represent regions of a DNA sequence, certain substrings, which are enriched in CpG dinucleotides (C followed by G). CpG islands represent a prominent and enigmatic feature of vertebrate genomes. They are associated with the promoters of more than 60% of all human genes and represent a critical target for transcriptional control. Methylation of these CpG islands leads to structural changes in the DNA that stops the expression of any associated gene (gene-silencing). The factors that provoke or impede methylation are currently all but unknown. In general, the maintenance of a particular pattern of methylated CpG dinucleotides represents a critical regulatory system during a host of normal developmental processes, but the erroneous methylation of CpG islands and the resulting gene-silencing can lead to the development of cancer. In this work, we present a novel unsupervised machine learning method that is capable of distinguishing biologically significant classes of CpG islands, including the separation of methylated and unmethylated CpG islands. This method represents an important novel approach that will aid in the computational prediction of methylation, which is commonly used in the pre-selection of worthwhile sequences for methylation experiments.
Design and Implementation of Stream Cipher Using Neural Network

The centaral problem in stream cipher cryptograph is the the difficulty to generate a long unpredicatable sequence of binary signals from short and random key. Unpredicatable sequence are desirable in cryptography because it is impossible, given a reasonable segment of its signals and computer resources, to find out more about them. Pseudorandom bit generators have been widely used to construct these sequences. The paper presents a PN sequence generator that uses neural network. Computer simulation tests have been carried out to check the randomness of the generated through statistical tests. There tests have shown the successful PN sequence generator passes all the recommended tests. The paper also proposes and validates the data encryption and decryption process using neural network instead of using traditional methods (Exclusive or). This task increases the difficulty in the breaking the cipher.
Unsupervised User Similarity Mining in GSM Sensor Networks

Mobility data has attracted the researchers for the past few years because of its rich context and spatiotemporal nature, where this information can be used for potential applications like early warning system, route prediction, traffic management, advertisement, social networking, and community finding. All the mentioned applications are based on mobility profile building and user trend analysis, where mobility profile building is done through significant places extraction, user's actual movement prediction, and context awareness. However, significant places extraction and user's actual movement prediction for mobility profile building are a trivial task. In this paper, we present the user similarity mining-based methodology through user mobility profile building by using the semantic tagging information provided by user and basic GSM network architecture properties based on unsupervised clustering approach. As the mobility information is in low-level raw form, our proposed methodology successfully converts it to a high-level meaningful information by using the cell-Id location information rather than previously used location capturing methods like GPS, Infrared, and Wifi for profile mining and user similarity mining.
In pursuit of off-task thought: mind wandering-performance trade-offs while reading aloud and color naming

The present study investigated whether the frequency of probe-caught mind wandering varied by condition and had any impact on performance in both an item-by-item reading aloud task and a blocked version of the classic Stroop task. Across both experiments, mind wandering rates were found to be quite high and were negatively associated with vocal onset latencies and error rates across conditions. Despite this however, we observed poor correspondence between the effects of task demands on mind wandering rates and the effects of mind wandering on primary task performance. We discuss these findings in relation to attentional resource accounts of mind wandering and suggest that individuals can adjust the relative distribution of executive/attentional resources between internal and external goals in a way that maximizes off-task thought while preserving primary task performance.
Some Aspects of Finite State Channel related to Hidden Markov Process

We have no satisfactory capacity formula for most channels with finite states. Here, we consider some interesting examples of finite state channels, such as Gilbert-Elliot channel, trapdoor channel, etc., to reveal special characters of problems and difficulties to determine the capacities. Meanwhile, we give a simple expression of the capacity formula for Gilbert-Elliot channel by using a hidden Markov source for the optimal input process. This idea should be extended to other finite state channels.
Reinforcement Learning in Continuous Time and Space

This article presents a reinforcement learning framework for continuous-time dynamical systems without a priori discretization of time, state, and action. Basedonthe Hamilton-Jacobi-Bellman (HJB) equation for infinite-horizon, discounted reward problems, we derive algorithms for estimating value functions and improving policies with the use of function approximators. The process of value function estimation is formulated as the minimization of a continuous-time form of the temporal difference (TD) error. Update methods based on backward Euler approximation and exponential eligibility traces are derived, and their correspondences with the conventional residual gradient, TD (0), and TD () algorithms are shown. For policy improvement, two methodsa continuous actor-critic method and a value-gradient-based greedy policyare formulated. As a special case of the latter, a nonlinear feedback control law using the value gradient and the model of the input gain is derived. The advantage updating, a model-free algorithm derived previously, is also formulated in the HJB-based framework. The performance of the proposed algorithms is first tested in a nonlinear control task of swinging a pendulum up with limited torque. It is shown in the simulations that (1) the task is accomplished by the continuous actor-critic method in a number of trials several times fewer than by the conventional discrete actor-critic method; (2) among the continuous policy update methods, the value-gradient-based policy with a known or learned dynamic model performs several times better than the actor-critic method; and (3) a value function update using exponential eligibility traces is more efficient and stable than that based on Euler approximation. The algorithms are then tested in a higher-dimensional task: cart-pole swing-up. This task is accomplished in several hundred trials using the value-gradient-based policy with a learned dynamic model.