Miracle-dz/UniFAR-FTUs huggingface dataset:
Francisella tularensis subsp. tularensis Induces a Unique Pulmonary Inflammatory Response: Role of Bacterial Gene Expression in Temporal Regulation of Host Defense Responses

Pulmonary exposure to Francisella tularensis is associated with severe lung pathology and a high mortality rate. The lack of induction of classical inflammatory mediators, including IL1-β and TNF-α, during early infection has led to the suggestion that F. tularensis evades detection by host innate immune surveillance and/or actively suppresses inflammation. To gain more insight into the host response to Francisella infection during the acute stage, transcriptomic analysis was performed on lung tissue from mice exposed to virulent (Francisella tularensis ssp tularensis SchuS4). Despite an extensive transcriptional response in the lungs of animals as early as 4 hrs post-exposure, Francisella tularensis was associated with an almost complete lack of induction of immune-related genes during the initial 24 hrs post-exposure. This broad subversion of innate immune responses was particularly evident when compared to the pulmonary inflammatory response induced by other lethal (Yersinia pestis) and non-lethal (Legionella pneumophila, Pseudomonas aeruginosa) pulmonary infections. However, the unique induction of a subset of inflammation-related genes suggests a role for dysregulation of lymphocyte function and anti-inflammatory pathways in the extreme virulence of Francisella. Subsequent activation of a classical inflammatory response 48 hrs post-exposure was associated with altered abundance of Francisella-specific transcripts, including those associated with bacterial surface components. In summary, virulent Francisella induces a unique pulmonary inflammatory response characterized by temporal regulation of innate immune pathways correlating with altered bacterial gene expression patterns. This study represents the first simultaneous measurement of both host and Francisella transcriptome changes that occur during in vivo infection and identifies potential bacterial virulence factors responsible for regulation of host inflammatory pathways.
Entanglement and electron correlation in quantum chemistry calculations

Electron–electron correlation in quantum chemistry calculations can be analysed in terms of entanglement between electrons. Two exactly solvable models: two fixed spin-1/2 particles and two-electron two-site Hubbard model are used to define and discuss the entanglement as a function of the system parameters. Ab initio configuration interaction calculation for entanglement is presented for the H2 molecule. Qualitatively, entanglement and electron–electron correlation have similar behaviour. Thus, entanglement might be used as an alternative measure of electron correlation in quantum chemistry calculations.
A Critique of “Moral and Character Development”

A critique was made in this essay about William G. Huitt’s （2004）article titled “Moral and Character Development”. The strong points of his article were discussed with his conclusion that social and cultural values influence the formation of children’s character traits, while school should play its own role as a sub-social unit to develop their characters and morality based on the cognitive, affective, conative and behavioral principles. The obvious weakness was presented by ignoring politics to be a vital factor influencing moral development. This essay aims to discuss why moral principles can be taught in school and how moral education can be practiced in classroom. It proposes what approaches are supposed to be significantly effective. Keywords: Moral education; Character development; Behavioral principles; Cognition; Psychological approaches
Using adaptive consultation of experts to improve convergence rates in multiagent learning

We present a regret-based multiagent learning algorithm which is provably guaranteed to converge (during self-play) to the set of Nash equilibrium in a wide class of games. Our algorithm, FRAME, consults experts in order to obtain strategy suggestions for agents. If the experts provide effective advice for the agent, then the learning process will quickly reach a desired outcome. If, however, the experts do not provide good advice, then the agents using our algorithm are still protected. We further expand our algorithm so that agents learn, not only how to play against the other agents in the environment, but also which experts are providing the most effective advice for the situation at hand.
Issues in reducing the cogging torque of mass-produced permanent-magnet brushless DC motor

A variety of techniques are available to reduce cogging torque in permanent-magnet brushless DC motors. Theoretically, all the techniques are quite effective for minimizing the cogging torque. This paper presents the efficacy of these methods in mass production subject to manufacturing tolerances/variations. The cogging torque minimization becomes a challenging task when the requirement is very stringent in applications such as electric power steering and robotics. Some of the known techniques for reducing the cogging torque are the magnet pole design, skewing, step skewing, and dummy slots in the stator lamination. They will be discussed in this paper considering manufacturing tolerances/variations when used in mass production. Finite-element analysis is carried out to determine the worst case scenarios. The research demonstrates that the cogging torque amplitude and frequency are highly sensitive to magnet shapes, dimensions, locations and magnetization pattern, as well as slot/pole combination. In reality, the cogging torque may not be eliminated completely but minimized to a satisfactory level depending on the application requirements.
Determining the Critical New Snow Depth for a Destructive Avalanche by Considering the Return Period

Snow avalanche danger assessment for avalanche paths threatening a highway or a resi- dential area is usually related to new snow depth. Given the extensive protection work in the Alps, the avalanche control service (also called avalanche commission) responsible for danger assessment will usually monitor the avalanche situation throughout the winter, but only become active in case of a major snow fall. Related safety concepts describing the procedures and measures to be taken in a given danger situation are therefore typically based on threshold values for new snow. By analysing the avalanche occurrence of a major avalanche path, we show that the return period of an avalanche to, for example, the road is about 5 years, whereas the return period for the corresponding new snow depth is substan- tially smaller, in our case slightly less than 2 years. Similar proportions were found for a number of other avalanche paths with different snow climate. The return period of the critical new snow depth is typically about 2-5 times smaller than the return period of the avalanche. This proportion is expected to increase with increasing return period. Hence, based on the return period of an avalanche path a first estimate for the critical new snow depth can be made. With a return period of the critical new snow depth of 1-2 years, avalanche prediction for individual avalanche path becomes very challenging since the false alarm ratio is expected to be high.
Documents as multiple overlapping windows into grids of counts

In text analysis documents are often represented as disorganized bags of words; models of such count features are typically based on mixing a small number of topics [1,2]. Recently, it has been observed that for many text corpora documents evolve into one another in a smooth way, with some features dropping and new ones being introduced. The counting grid [3] models this spatial metaphor literally: it is a grid of word distributions learned in such a way that a document's own distribution of features can be modeled as the sum of the histograms found in a window into the grid. The major drawback of this method is that it is essentially a mixture and all the content must be generated by a single contiguous area on the grid. This may be problematic especially for lower dimensional grids. In this paper, we overcome this issue by introducing the Componential Counting Grid which brings the componential nature of topic models to the basic counting grid. We evaluated our approach on document classification and multimodal retrieval obtaining state of the art results on standard benchmarks.
A theory of planned behaviour-based analysis of TIMSS 2011 to determine factors influencing inquiry teaching practices in high-performing countries

ABSTRACT Given the abundance of literature describing the strong relationship between inquiry-based teaching and student achievement, more should be known about the factors impacting science teachers’ classroom inquiry implementation. This study utilises the theory of planned behaviour to propose and validate a causal model of inquiry-based teaching through analysing data relating to high-performing countries retrieved from the 2011 Trends in International Mathematics and Science Study assessments. Data analysis was completed through structural equation modelling using a polychoric correlation matrix for data input and diagonally weighted least squares estimation. Adequate fit of the full model to the empirical data was realised. The model demonstrates that the extent the teachers participated in academic collaborations was positively related to their occupational satisfaction, confidence in teaching inquiry, and classroom inquiry practices. Furthermore, the teachers’ confidence with implementing inquiry was positively related to their classroom inquiry implementation and occupational satisfaction. However, perceived student-generated constraints demonstrated a negative relationship with the teachers’ confidence with implementing inquiry and occupational satisfaction. Implications from this study include supporting teachers through promoting collaborative opportunities that facilitate inquiry-based practices and occupational satisfaction.
Wind energy conversion system control using distinct controllers for different operating regions

This paper presents a control strategy based on two distinct controllers for different operating regions applied to a wind turbine benchmark. In previous works, we proposed the control of a wind turbine using two distinct controllers for all operating regions. The contribution of this work focus on the use of two distinct controllers for two different operation regions, the fuzzy proportional integral controller in the partial load region, i.e., Region II, and the use of model predictive controller in the full load region, i.e., Region III. The distinct controllers applied on the different operation regions are compared to a standard controller and the simulation results show the efficacy of the proposed control approach.
Feedback pre-equalization in the downlink for a wireless MC-CDMA system

This paper addresses the dynamic pre-equalization problem in the downlink of MC-CDMA systems by following a distributed feedback perspective, and including explicit quality-of-service (QoS) restrictions. The proposal for the downlink is synthesized taking into account implementation considerations. The QoS requirement for each active user is translated into a prescribed signal to interference-noise ratio (SINR) after detection at the receiver. An independent pre-equalization factor per subcarrier is assumed which induce diversity in the problem formulation. In addition, a simple matched-filter at the mobile units (MUs) is assumed for signal detection. In this formulation, the pre-equalization factors that minimize the transmission power and achieve the objective SINR can be accomplished. A general closed-loop control structure is addressed that allows to use distributed control algorithm previously proposed for power control in CDMA systems. Also, stability conditions are analytically deduced to guarantee convergence of the iterative algorithms. A simulation evaluation is presented which shows that the QoS requirements are always satisfied for different loads conditions in the MC-CDMA system.
EVALUATION OF DIFFERENTIAL EVOLUTION AND TABU SEARCH FOR BENCHMARK AND PHASE STABILITY PROBLEMS

Phase stability (PS) problems play a crucial role in the simulation, design and optimization of separation process such as distillation and extraction. The problem involves the global minimization of tangent plane distance function (TPDF) known as tangent plane criterion. In this work, two promising global optimization techniques: differential evolution (DE) and tabu search (TS) have been evaluated for the first time and compared for benchmark and PS problems. A local optimization technique is used at the end of both TS and DE to improve the accuracy of the final solution. Benchmark problems involve 2 to 20 variables with a few to hundreds of local minima whereas PS problems consist of multiple components and modeled with popular thermodynamic models. The results show that DE is more reliable but computationally less efficient compared to TS for benchmark and PS problems tested.
3,000-fps 3-D shape measurement using a high-speed camera-projector system

This paper proposes a high frame rate 3-D shape measurement system based on structured light projection using temporally-coded binary patterns. This system consists of a DMD (digital micromirror device) projector and a high-speed camera, both of which operate at over 6,000 fps. Introducing an image processing algorithm of detecting and tracking the projected light patterns enables frame-by-frame 3-D image measurement. Experimental results show that the proposed algorithms worked effectively, and the system achieved 3-D imaging at 3,350 fps.
Independent Component Analysis: Source Assessment Separation, a Bayesian Approach

The author presents a method of independent component analysis which assesses the most probable number of source sequences from a larger number of observed sequences and estimates the unknown source sequences and mixing matrix. The estimation of the number of true sources is regarded as a model-order estimation problem and is tackled under a Bayesian paradigm. The method is shown to give good results on both synthetic and real data.
Computing DSGE Models with Recursive Preferences

This paper compares different solution methods for computing the equilibrium of dynamic stochastic general equilibrium (DSGE) models with recursive preferences such as those in Epstein and Zin (1989 and 1991). Models with these preferences have recently become popular, but we know little about the best ways to implement them numerically. To fill this gap, we solve the stochastic neoclassical growth model with recursive preferences using four different approaches: second- and third-order perturbation, Chebyshev polynomials, and value function iteration. We document the performance of the methods in terms of computing time, implementation complexity, and accuracy. Our main finding is that a third-order perturbation is competitive in terms of accuracy with Chebyshev polynomials and value function iteration, while being an order of magnitude faster to run. Therefore, we conclude that perturbation methods are an attractive approach for computing this class of problems.
Transforming growth factor-beta-induced growth inhibition and cellular hypertrophy in cultured vascular smooth muscle cells

We have explored the hypothesis that hypertrophy of vascular smooth muscle cells may be regulated, in part, by growth inhibitory factors that alter the pattern of the growth response to serum mitogens by characterizing the effects of the potent growth inhibitor, transforming growth factor-beta (TGF-beta), on both hyperplastic and hypertrophic growth of cultured rat aortic smooth muscle cells. TGF-beta inhibited serum-induced proliferation of rat aortic smooth muscle cells (ED50 = 2 pM); this is consistent with previously reported observations in bovine aortic smooth muscle cells (Assoian et al. 1982. J. Biol. Chem. 258:7155-7160). Growth inhibition was due in part to a greater than twofold increase in the cell cycle transit time in cells that continued to proliferate in the presence of TGF-beta. TGF-beta concurrently induced cellular hypertrophy as assessed by flow cytometric analysis of cellular protein content (47% increase) and forward angle light scatter (32-50% increase), an index of cell size. In addition to being time and concentration dependent, this hypertrophy was reversible. Simultaneous flow cytometric evaluation of forward angle light scatter and cellular DNA content demonstrated that TGF-beta-induced hypertrophy was not dependent on withdrawal of cells from the cell cycle nor was it dependent on growth arrest of cells at a particular point in the cell cycle in that both cycling cells in the G2 phase of the cell cycle and those in G1 were hypertrophied with respect to the corresponding cells in vehicle-treated controls. Chronic treatment with TGF-beta (100 pM, 9 d) was associated with accumulation of cells in the G2 phase of the cell cycle in the virtual absence of cells in S phase, whereas subsequent removal of TGF-beta from these cultures was associated with the appearance of a significant fraction of cycling cells with greater than 4c DNA content, consistent with development of tetraploidy. Results of these studies support a role for TGF-beta in the control of smooth muscle cell growth and suggest that at least one mechanism whereby hypertrophy and hyperploidy may occur in this, as well as other cell types, is by alterations in the response to serum mitogens by potent growth inhibitors such as TGF-beta.
Interference Aggregation in Spectrum-Sensing Cognitive Wireless Networks

The increasing demand for the radio spectrum along with the inefficient usage of the licensed bands has led the regulatory bodies to consider opening up the under-utilized licensed frequency bands for dynamic access by unlicensed users. Such dynamic spectrum access is envisioned to resolve the spectrum scarcity by allowing unlicensed users to opportunistically utilize the white spaces across the licensed spectrum on a non-interfering basis. Cognitive radio networks offer a promising realization of this novel paradigm, thanks to their ability to autonomously identify the white spaces through spectrum sensing. Implementation of such networks, however, requires a model translating the regulatory constraint on the aggregate interference to the system-and device-level design parameters. In this paper a statistical model of interference aggregation in spectrum-sensing cognitive radio networks is developed. In particular, distribution of the aggregate interference is characterized in terms of parameters such as sensitivity, transmitted power, and density of the cognitive radios as well as the underlying propagation environment. The model is further extended to account for the effect of cooperative spectrum sensing on the distribution of the aggregate interference.
Optimizing Online Content Instruction for Effective Hybrid Teacher Professional Development Programs

ABSTRACT The Teacher Academy in the Natural Sciences (TANS) provided middle school (U.S. Grades 6–8) teachers (N = 81) with intensive professional development in chemistry, geosciences, and physics through 13 days of face-to-face instruction that was extended with 2 online science modules per discipline. Because we administered online module assessments before the summer academy (pretest), after the summer academy (Post 1), and after the online module was assigned (Post 2), we were able to analyze via dependent t tests the learning components contributed by the online module. Only 1 geosciences module resulted in significant gains after it was assigned. Other modules (2 physics, 1 geosciences) resulted in gains before module assignments, at the end of the 10-day summer academy. Although the 2 chemistry modules exhibited positive score increases, no significant gains were made. Calculated Pearson correlation coefficients revealed no association between participants’ online access times and science content gains. This research documents benefits of hybrid teacher professional development programs and offers recommendations for their optimized effectiveness, including more consistent instructor/participant online access.
Using RBF algorithm for landcover or clutter classification for mobile planning

The authors consider the problem of classifying the service area for the planning of a mobile network. A neural network (NN) algorithm based on the radial basis function (RBF) is proposed to classify land cover using information derived from a geographic information system (GIS). The comparison between the computed results and real data shows that the method is a practical approach with an accuracy of up to 935.
The Contagious Effect of Deviant Behavior in Adolescence

This article investigated how the development of deviant behavior in adolescence is influenced by the variability of deviant behavior in the peer group. Based on the social information-processing (SIP) model, we predicted that peer groups with a low variability of deviant behavior (providing normative information that is easy to process) should have a main effect on the development of adolescents’ deviant behavior over time, whereas peer groups in which deviant behavior is more variable (i.e., more difficult to process) should primarily impact the deviant behavior of initially nondeviant classroom members. These hypotheses were largely supported in a multilevel analysis using self-reports of deviant behavior in a sample of 16,891 adolescents in 1,308 classes assessed at two data waves about 1-year apart. The results demonstrate the advantages of studying cross-level interactions to clarify the impact of the peer environment on the development of deviant behavior in adolescence.
Research on Medium Access Control protocols for mobile sensor networks

Most Medium Access Control (MAC) protocols used in wireless sensor networks consider only static nodes. However, there is an increasing interest in sensor network applications where some or all of the nodes are mobile. In this paper, the issue of mobility in sensor networks is addressed, first at a high level, and then in terms of the additional requirements that are placed on the MAC layer by the presence of mobile nodes in the network. Existing proposals for sensor network MAC protocols are then compared under three different mobility scenarios. Finally, the status of current research is summarized and the open research issues of MAC protocols are identified.
Modeling , Design , Fabrication and Demonstration of RF Front-End 3 D IPAC Module with Ultra-thin Glass Substrates for LTE Applications

This paper demonstrates, for the first time, an integrated radio frequency (RF) front-end module (FEM) with precision matching circuits in ultra-miniaturized glass substrates for LTE applications. Through full-wave electromagnetic (EM) simulations, electrical performance of these glass-based long term evolution (LTE) packages is compared with traditional RF modules with surface mount devices (SMDs), and organic laminates with embedded passives and actives. RF front-end modules with 3D or double-side thinfilm passive components on glass-based substrates are fabricated and characterized to correlate their performance with EM simulations.