Miracle-dz/UniFAR-FTUs huggingface dataset:
c-Jun NH2-Terminal Kinase 2 Inhibits Gamma Interferon Production during Anaplasma phagocytophilum Infection

ABSTRACT Gamma interferon (IFN-γ) plays a critical role in the early eradication of Anaplasma phagocytophilum. However, the mechanisms that regulate IFN-γ production upon infection remain poorly understood. Here we show that c-Jun NH2-terminal kinase 2 (JNK2) inhibits IFN-γ production during A. phagocytophilum infection. jnk2-null mice were more refractory to infection with A. phagocytophilum and produced increased levels of IFN-γ after challenge with the pathogen. The resistance of jnk2-null mice to A. phagocytophilum infection was due to elevated levels of IFN-γ secreted by conventional and natural killer (NK) T cells. The administration of α-galactosylceramide, a strong NK T-cell agonist, increased IFN-γ release and protected mice from A. phagocytophilum, further demonstrating the inhibitory effect of JNK2 on IFN-γ production. Collectively, these findings provide strong evidence that JNK2 is an important regulatory protein for IFN-γ secretion upon challenge with A. phagocytophilum.
The VATTAGE Regional Model VERM - A Dynamic, Regional, Applied General Equilibrium Model of the Finnish Economy

Applied general equilibrium models have become a standard tool for the analysis of structural policies in many countries and international research organisations. Their use has been prompted by both developments in economics, but also on the growing need for quantitative policy analysis. The analysis of actual policy options mandates the use of numerical methods, but there are several other reasons to suggest the use of AGE models in particular. Chief among these is the applicability of models that rely on explicit optimisation on the analysis of welfare impacts of structural policies. It may also be the case that many policy issues are intractable by theoretical models, for example, when the policies concern several sectors or regions of the economy, or involve contradicting effects. This report describes the VERM model used in VATT, the Government Institute for Economic Research. The model has been used to study the effects of various tax policies, regional policies, and environmental policies on the economy. Lately, the model has seen extensive use in the anticipation of regional development, especially in the labour markets. The report contains a full description of the model code and its underlying theory. With the help of examples, it also shows how simulation results can be interpreted.
Optimal code motion: theory and practice

An implementation-oriented algorithm for lazy code motion is presented that minimizes the number of computations in programs while suppressing any unnecessary code motion in order to avoid superfluous register pressure. In particular, this variant of the original algorithm for lazy code motion works on flowgraphs whose nodes are basic blocks rather than single statements, since this format is standard in optimizing compilers. The theoretical foundations of the modified algorithm are given in the first part, where t-refined flowgraphs are introduced for simplifying the treatment of flow graphs whose nodes are basic blocks. The second part presents the “basic block” algorithm in standard notation and gives directions for its implementation in standard compiler environments.
Design of Efficient Convolutional Layers using Single Intra-channel Convolution, Topological Subdivisioning and Spatial "Bottleneck" Structure

Deep convolutional neural networks achieve remarkable visual recognition performance, at the cost of high computational complexity. In this paper, we have a new design of efficient convolutional layers based on three schemes. The 3D convolution operation in a convolutional layer can be considered as performing spatial convolution in each channel and linear projection across channels simultaneously. By unravelling them and arranging the spatial convolution sequentially, the proposed layer is composed of a single intra-channel convolution, of which the computation is negligible, and a linear channel projection. A topological subdivisioning is adopted to reduce the connection between the input channels and output channels. Additionally, we also introduce a spatial "bottleneck" structure that utilizes a convolution-projection-deconvolution pipeline to take advantage of the correlation between adjacent pixels in the input. Our experiments demonstrate that the proposed layers remarkably outperform the standard convolutional layers with regard to accuracy/complexity ratio. Our models achieve similar accuracy to VGG, ResNet-50, ResNet-101 while requiring 42, 4.5, 6.5 times less computation respectively.
Learning Probabilistic Hierarchical Task Networks from Plan Examples to Capture User Preference

Hierarchical task networks provide an efficient way to encode user prescriptions about what constitute good plans using component methods. However, manual construction of these methods is complex and time consuming. In this paper, we propose a novel approach to learning probabilistic hierarchical task networks that capture the user preference by examining user-produced plans given no prior information about the methods. We introduce a theoretical basis to formally state the schema learning problem. We then make the connection between probabilistic grammar induction and probabilistic hierarchical task network learning, and propose a learning algorithm that shares ideas with probabilistic gram-
The Dimensions of Wage Inequality Among Aboriginal Peoples

In addition to confirming a wage gap between Canadian workers as a whole and those of Aboriginal origin, our research also generated new findings: there is greater disparity in the distribution of wages among Aboriginals than among Canadian workers as a whole, even after allowing for demographic differences. Our analysis does not stop there. Indeed, this analysis can hide considerable wage dispersions between Aboriginal groups since appreciable wage gaps were noted between these groups. Having said this, wage dispersion is most likely greater for certain Aboriginal groups than others. Since this aspect has never been studied before, the purpose of this paper is to document differences in wage dispersion for the four main Aboriginal groups. Our results show that North American Indians living on reserves are the most disadvantaged Aboriginal group because their earnings are substantially lower than those of the other groups.
Bone mesenchymal stem cell transplantation via four routes for the treatment of acute liver failure in rats

In the present study, we assessed the efficiency of four BMSC transplantation methods as a therapy for liver failure. A rat model (80 Sprague-Dawley rats) of D-galactosamine (D-gal)/lipopolysaccharide (LPS)-induced acute liver failure (ALF) was established and the rats were divided into 5 groups: a hepatic artery injection group, a portal vein injection group, a vena caudalis injection group, an intraperitoneal injection group and a control group (16 per group). Following transplantation, the liver tissue and blood samples were collected on days 1, 3 and 7, we detected the EdU (5-ethynyl-2′-deoxyuridine)-labeled cells homing to the liver tissue and assessed the proliferating cell nuclear antigen (PCNA) and cysteine-containing aspartate-specific protease (caspase)-3 expression in the liver tissue and detected the levels of stromal cell-derived factor 1 (SDF-1) and hepatocyte growth factor (HGF) in the liver tissues. Compared with the control group, the levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) and damage to the liver tissue in the hepatic artery group, the portal vein group and the vena caudalis group improved in vivo. The expression of PCNA and HGF in the liver was higher and caspase-3 expression was lower in the hepatic artery injection group, the portal vein injection group and the vena caudalis injection group than that in the intraperitoneal injection and control groups. The EdU-labeled BMSCs were only observed homing to the liver tissue in these three groups. However, no significant differences were observed between these three groups. Liver function in the rats with ALF was improved following BMSC transplantation via 3 endovascular implantation methods (through the hepatic artery, portal vein and vena caudalis). These 3 methods were effective in transplanting BMSCs for the treatment of ALF. However, the selection of blood vessel in the implantation pathway does not affect the transplantation outcome. Transplantation via intraperitoneal injection showed no therapeutic effect in our animal experiments.
Part Overview of the Probably Approximately Correct PAC Learning Framework

Here we survey some recent theoretical results on the e ciency of machine learning algorithms The main tool described is the notion of Probably Approximately Correct PAC learning intro duced by Valiant We de ne this learning model and then look at some of the results obtained in it We then consider some criticisms of the PAC model and the extensions proposed to address these criticisms Finally we look brie y at other models recently proposed in computational learning theory
Feasibility Study of Rain Rate Monitoring from Polarimetric GNSS Propagation Parameters

In this work, the feasibility of estimating rain rate based on polarimetric Global Navigation Satellite Systems (GNSS) signals is explored in theory. After analyzing the cause of polarimetric signals, three physical-mathematical relation models between co-polar phase shift (KHH, KVV), specific differential phase shift (KDP), and rain rate (R) are respectively investigated. These relation models are simulated based on four different empirical equations of nonspherical raindrops and simulated Gamma raindrop size distribution. They are also respectively analyzed based on realistic Gamma raindrop size distribution and maximum diameter of raindrops under three different rain types: stratiform rain, cumuliform rain, and mixed clouds rain. The sensitivity of phase shift with respect to some main influencing factors, such as shape of raindrops, frequency, as well as elevation angle, is also discussed, respectively. The numerical results in this study show that the results by scattering algorithms T-matrix are consistent with those from Rayleigh Scattering Approximation. It reveals that they all have the possibility to estimate rain rate using the KHH-R, KVV-R or KDP-R relation. It can also be found that the three models are all affected by shape of raindrops and frequency, while the elevation angle has no effect on KHH-R. Finally, higher frequency L1 or B1 and lower elevation angle are recommended and microscopic characteristics of raindrops, such as shape and size distribution, are deemed to be important and required for further consideration in future experiments. Since phase shift is not affected by attenuation and not biased by ground clutter cancellers, this method has considerable potential in precipitation monitoring, which provides new opportunities for atmospheric research.
Granular Flows

The epigrammatic quote by a French Nobel laureate is familiar to many in the field of granular mechanics and reflects a long-standing scientific fascination and practical interest. This is acknowledged by many others and summarized in the articles listed under Further Reading. As a general definition, we understand by granular medium a particle assembly dominated by pairwise nearest-neighbor interactions and usually limited to particles larger than 1 micrometer in diameter, for which the direct mechanical effects of Van der Waals and ordinary thermal (“Brownian”) forces are negligible. This includes a large class of materials, such as cereal grains, pharmaceutical tablets and capsules, geomaterials such as sand, and the masses of rock and ice in planetary rings. Most of the present article is concerned with dry granular materials in which there are negligible effects of air or other gases in the interstitial space, or else with granular materials completely saturated by an interstitial liquid. In this case, liquid surface-tension at “capillary necks” between grains, as in the wet sand of sand castles, or related forms of cohesion are largely negligible. There are several important and interrelated aspects of granular mechanics: (i) experiment and industrial or geotechnical applications, (ii) analytical and computational micromechanics (grainlevel dynamics), (iii) homogenization (“upscaling” or “coarse graining”) to obtain smoothed continuum models from the Newtonian mechanics of discrete grains, (iv) mathematical classification and solution of the continuum field equations for granular flow, and (v) development of continuum models (“constitutive equations”) for stress-deformation behavior. The present article focuses on (v), since the study of most of the preceding items either depends on it, or is strongly motivated by it. The following discussion of (iv) sets the stage for the subsequent coverage of (v).
Mobile Robot Position Determination

One of the most important reasons for the popularity of mobile robots in industrial manufacturing is their capability to move and operate freely. In order for the robots to perform to the expectations in manufacturing, their position and orientation must be determined accurately. In addition, there is a strong tendency to grant more autonomy to robots when they operate in hazardous or unknown environments which also requires accurate position determination. Mobile robots are usually divided into two categories of legged and wheeled robots. In this chapter, we focus on wheeled mobile robots. Techniques used for position determination of wheeled mobile robots (or simply, mobile robots) are classified into two main groups: relative positioning and absolute positioning (Borenstein, 1996, 1997). In relative positioning, robot’s position and orientation will be determined using relative sensors such as encoders attached to the wheels or navigation systems integrated with the robots. Absolute positioning techniques are referred to the methods utilizing a reference for position determination. The Global Positioning Systems, magnetic compass, active beacons are examples of absolute positioning systems. Calculating position from wheel rotations using the encoders attached to the robot’s wheels is called Odometry. Although odometry is the first and most fundamental approach for position determination, due to inherent errors, it is not an accurate method. As a solution to this problem, usually odometry errors are modeled using two different methods of benchmarks and multiple sensors. In this chapter, we will discuss odometry and two different methods to model and estimate odometry errors. At the end, an example for mobile robot position determination using multiple sensors will be presented.
Background albedo dynamics improve simulated precipitation variability in the Sahel region

Abstract. Using the general circulation model ECHAM5–JSBACH forced by observed sea surface temperatures (SSTs) for the 20th century, we investigate the role of vegetation and land surface albedo dynamics in shaping rainfall variability in the Sahel. We use two different land surface albedo schemes, one in which the albedo of the canopy is varying and one in which the albedo changes of the surface below the canopy are also taken into account. The SST forcing provides the background for simulating the observed decadal signal in Sahelian rainfall, though the response to SST forcing only is not strong enough to fully capture the observed signal. The introduction of dynamic vegetation leads to an increase in interannual variability of the rainfall, and gives rise to an increased number of high-amplitude rainfall anomaly events. The dynamic background albedo leads to an increased persistence of the rainfall anomalies. The increase in persistence means that the difference between the dry and the wet decades is increased compared to the other simulations, and thus more closely matching the observed absolute change between these two periods. These results highlight the need for a consistent representation of land surface albedo dynamics for capturing the full extent of rainfall anomalies in the Sahel.
2 INFORMATION TECHNOLOGY AND KNOWLEDGE WORKER PRODUCTIVITY : A TAXONOMY OF TECHNOLOGY CROWDING

This paper explores unintended consequences of information technology use on knowledge worker productivity in the workplace. Drawing upon economics principles and theoretical frameworks of bounded rationality, task-technology fit, and human interruption theory, we propose a taxonomy of technology crowding which is a phenomenon that occurs at the point in which more technology usage which otherwise improved productivity has reached the point of diminishing marginal returns. This shows that more technology does not always lead to increased productivity and can sometimes, in fact, be counterproductive. We conducted a preliminary field study of 61 knowledge workers using multidimensional scaling techniques to empirically develop and validate the taxonomy. Three salient dimensions of technology crowding were identified: software bloat, information overload, and communication overload. The findings provide initial evidence and an understanding of unintended outcomes of technology use on knowledge workers and offer interesting implications for managers to effectively deploy technology tools to boost their knowledge workers’ productivity.
A distributed index for efficient parallel top-k keyword search on massive graphs

Recently, a variety of indexing techniques have been proposed for optimizing keyword search on graph. However, graph indexing has very high space and time complexities, and thus these single-machine in-memory indices are usually not affordable for massive graphs. In this paper, we propose a novel distributed disk-based index, which organizes the local topology information in the graph to track and prune matched vertices that will not participate in the top-k answers to a specified query before search with heuristics. The distributed index can be constructed in a MapReduce manner. Moreover, a parallel search algorithm is also developed. It runs multiple asynchronous search instances that incrementally enumerate the current best local answers and then produces the global top-k answers from them. Lastly, we perform experiments on both synthetic and real graphs with various configurations. The results show that our approach can improve search efficiency on massive graphs significantly with affordable indexing overheads.
Monkeys benefit from reciprocity without the cognitive burden

The debate about the origins of human prosociality has focused on the presence or absence of similar tendencies in other species, and, recently, attention has turned to the underlying mechanisms. We investigated whether direct reciprocity could promote prosocial behavior in brown capuchin monkeys (Cebus apella). Twelve capuchins tested in pairs could choose between two tokens, with one being “prosocial” in that it rewarded both individuals (i.e., 1/1), and the other being “selfish” in that it rewarded the chooser only (i.e., 1/0). Each monkey’s choices with a familiar partner from their own group was compared with choices when paired with a partner from a different group. Capuchins were spontaneously prosocial, selecting the prosocial option at the same rate regardless of whether they were paired with an in-group or out-group partner. This indicates that interaction outside of the experimental setting played no role. When the paradigm was changed, such that both partners alternated making choices, prosocial preference significantly increased, leading to mutualistic payoffs. As no contingency could be detected between an individual’s choice and their partner’s previous choice, and choices occurred in rapid succession, reciprocity seemed of a relatively vague nature akin to mutualism. Having the partner receive a better reward than the chooser (i.e., 1/2) during the alternating condition increased the payoffs of mutual prosociality, and prosocial choice increased accordingly. The outcome of several controls made it hard to explain these results on the basis of reward distribution or learned preferences, and rather suggested that joint action promotes prosociality, resulting in so-called attitudinal reciprocity.
Importance sampling and the two-locus model with subdivided population structure

The diffusion-generator approximation technique developed by De Iorio and Griffiths (2004a) is a very useful method of constructing importance-sampling proposal distributions. Being based on general mathematical principles, the method can be applied to various models in population genetics. In this paper we extend the technique to the neutral coalescent model with recombination, thus obtaining novel sampling distributions for the two-locus model. We consider the case with subdivided population structure, as well as the classic case with only a single population. In the latter case we also consider the importance-sampling proposal distributions suggested by Fearnhead and Donnelly (2001), and show that their two-locus distributions generally differ from ours. In the case of the infinitely-many-alleles model, our approximate sampling distributions are shown to be generally closer to the true distributions than are Fearnhead and Donnelly's.
Automated Text Categorization Using Support Vector Machine

In this paper, we study the use of support vector machine in text categorization. Unlike other machine learning techniques , it allows easy incorporation of new documents into an existing trained system. Moreover, dimension reduction, which is usually imperative, now becomes optional. Thus, SVM adapts eeciently in dynamic environments that require frequent additions to the document collection. Empirical results on the Reuters-22173 collection are also discussed.
Deforestation and Ownership: Evidence from Historical Accounts and Contemporary Data

Historical accounts of forest cover changes over the last three millennia are compared to contemporaneous human history, to shed light on factors contributing to large scale changes in forest stocks. Insecure ownership, for example, during wartime and periods of unrest, tends to accompany deforestation, as does population growth, and as does declining agricultural yields. A simple model of forest stocks and agricultural yields that captures these relationships is formulated to guide empirical analysis. Estimates based on cross-country data support the proposition that agricultural yields tend to be low and deforestation rates rapid where ownership is inscure.
Finding the Connections Between Art and Teaching: A Case Study

Finding the connection between art and teaching can be a difficult task for preservice teachers who do not have a background in the arts. This qualitative case study explores the journey of a group of pre-service elementary teachers in an art methods course considering what it means to teach and to be an artist. The way in which these students defined the arts and teaching changed over the course of the semester and found connective threads, productively tying together the work of teaching and the creative process. Findings from pre-service teacher course work indicated three important themes: connections between art and teaching, finding connections to self, and becoming a teacher. Data revealed implications for pre-service teachers making productive connections, beginning to see themselves as capable, creative teachers, able to encourage the creativity of their future students. Practicing teachers and teacher educators are also implicated as art and teaching find authentic connections throughout an art methods course.