Miracle-dz/UniFAR-FTUs huggingface dataset:
Localization of the binding site for the monocyte immunoglobulin (Ig) A- Fc receptor (CD89) to the domain boundary between Calpha2 and Calpha3 in human IgA1

Immunoglobulin (Ig) A serves as the first line of humoral defense at all mucosal surfaces and is present in large quantities of blood. In playing its role in humoral immunity, IgA interacts with a variety of effector molecules present both in serum and on the surfaces of immune and inflammatory cells. To study these interactions, we previously established expression of human IgA1 in insect cells using recombinant baculoviruses and showed that the expressed antibody is a structurally and functionally intact polypeptide useful for examining the molecular properties of IgA. Indeed, since the C alpha 2 N-linked glycosylation site lies near the Fab-distal pole of C alpha 2, the inability of a mutant IgA1 lacking C alpha 2 N-glycosylation to bind its cognate receptor suggested that the monocyte Fc alpha receptor (mFcalphaR) recognizes IgA at a hinge-distal site encompassing the boundary between the C alpha 2 and C alpha 3 domains. In this report, we utilize both domain-swapped IgA/IgG and point-mutated IgA chimeras to verify the above hypothesis. Using an antigen-specific rosetting assay and a mFc alpha R-expressing cell line, we show that (a) C alpha 2 and C alpha 3 together are necessary and sufficient for binding; (b) neither the IgA hinge nor the tailpiece is necessary for binding; (c) mutations away from the interdomain boundary do not affect binding; and (d) mutations located near the three-dimensional boundary between C alpha 2 and C alpha 3 completely disrupt binding. Taken together, these results localize the mFc alpha R recognition site on IgA to the boundary region between the second and third constant domains--a site analogous to that recognized by Staphylococcus aureus protein A on IgG. The use of this hinge-distal site is, to date, unique among Fc receptors of the Ig superfamily.
A Tale of Two Option Markets: Pricing Kernels and Volatility Risk

Using both S&P 500 option and recently introduced VIX option prices, we study pricing kernels and their dependence on multiple volatility factors. We first propose nonparametric estimates of marginal pricing kernels, conditional on the VIX and the slope of the variance swap term structure. Our estimates highlight the state-dependence nature of the pricing kernels. In particular, conditioning on volatility factors, the pricing kernel of market returns exhibit a downward sloping shape up to the extreme end of the right tail. Moreover, the volatility pricing kernel features a striking U-shape, implying that investors have high marginal utility in both high and low volatility states. This finding on the volatility pricing kernel presents a new empirical challenge to both existing equilibrium and reduced-form asset pricing models of volatility risk. Finally, using a full-fledged parametric model, we recover the joint pricing kernel, which is not otherwise identifiable.
Adaptive disturbance observer design for servo drive system with time-varying load inertia

Considering the variations of load inertia in industrial applications, an adaptive disturbance observer (ADOB) for the permanent magnet synchronous motor (PMSM) servo system is proposed in this paper. Firstly, an inertia identification method is employed to obtain the system inertia online. Secondly, a modified disturbance observer is proposed based on the identified inertia to estimate the disturbance torque, and feed the disturbance compensation forward to the torque controller. Lastly, speed controller gains are tuned automatically according to the identified inertia. Simulation results show the validity of the proposed ADOB and have better performance than general DOB.
A review and evaluation of penalty functions for Semi-Global Matching

Multi-view matching presents significant advantages regarding accuracy, radiometric fidelity or occlusion handling; however, the limitation of having only two available views remains common in many real-life scenarios. The Semi-Global Matching (SGM) approach has been proved to be robust against complex scenes (from aerial images to those from autonomous systems) and radiometrically challenging images, providing accurate disparity maps (compared to global and local methods) and computational efficiency. Recently, an entire class of methods has appeared relying on SGM. In the present study, a review of methods which define an adaptive function for the P2 cost penalty for disparity discontinuities is presented. The evaluation methodology includes use of absolute intensity differences and the distance on Census transformed images as cost functions, and extensive parameter tuning with comparisons under the demanding Middlebury College 2006 stereo dataset, which involves radiometric changes in illumination/exposure. Results are reported and evaluated as regards the performance of such variations of SGM.
Natural resource content of foreign trade and structural bias : an inter-country comparison of Czechoslovakia and Austria by means of input-output technique

﻿ The purpose of this study is to test the hypothesis that centrally- planned economies are characterized by what is called a bias towards absorption of natural resource intensive products (NRP) which is said to affect in turn the commodity structure of their foreign trade. While the study includes a detailed analysis of foreign trade structures and the absorption of NRP by final consumers, it is the intermediate demand for NRP and its determinants which are emphasized. Following the suggestions in the literature that the technologies used by the centrally- planned and market-type economies are different, the role of technology in determining intermediate demand for NRP has been examined in detail. Bias is defined here in terms of inter-country differences and the present comparison involves a case-study of Czechoslovakia as a centrally-planned economy and Austria as a market-type economy based on an input-output model. The use of the input-output model in inter- national comparisons of production and use of commodities has been criticized on the following grounds: (1) The distinction between technology and substitution is ignored in the model. (2) International differences in relative prices are normally ignored or assumed away in empirical work. (3) The comparisons may be severely affected by imperfections of input-output tables. This study attempts to answer the above criticism in an original way. New methods of sensitivity analysis were designed to test for the existence of the 'triangular' and other 'fundamental' properties of the technological matrices. In addition, the assumption of temporal stability of input-output coefficients is relaxed and an attempt is made to distinguish between technology and substitution with the help of the RAS method. Further analysis of the impact of relative prices on input-output flows was derived from an analysis of indirect taxation. The main conclusion of this study is that Czechoslovakia had a considerable NRP import bias which was primarily due to the pro-NRP absorption bias of final consumers. However, it is unlikely that 'excessive' aggregate demand for imports originated in 'NRP-biased' technology. This empirical analysis provides strong evidence that the production processes with regard to the use of NRP were highly similar in both countries.
Specializations of gastrin‐releasing peptide cells of the mouse suprachiasmatic nucleus

The suprachiasmatic nucleus (SCN) of the hypothalamus regulates daily rhythms in physiology and behavior. It is composed of a heterogeneous population of cells that together form the circuits underlying its master clock function. Numerous studies suggest the existence of two regions that have been termed core and shell. At a gross level, differences between these regions map to distinct functional differences, although the specific role(s) of various peptidergic cellular phenotypes remains unknown. In mouse, gastrin‐releasing peptide (GRP) cells lie in the core, are directly retinorecipient, and lack detectable rhythmicity in clock gene expression, raising interest in their role in the SCN. Here, we provide evidence that calbindin‐expressing cells of perinatal mouse SCN express GRP, identified by a green fluorescent protein (GFP+), but lack detectable calbindin later in development. To explore the intra‐SCN network in which GRP neurons participate, individual GFP+ cells were filled with tracer and their morphological characteristics, processes, and connections, as well as those of their non‐GFP‐containing immediate neighbors, were compared. The results show that GFP+ neurons form a dense network of local circuits within the core, revealed by appositions on other GFP+ cells and by the presence of dye‐coupled cells. Dendrites and axons of GFP+ cells make appositions on arginine vasopressin neurons, whereas non‐GFP cells have a less extensive fiber network, largely confined to the region of GFP+ cells. The results point to specialized circuitry within the SCN, presumably supporting synchronization of neural activity and reciprocal communication between core and shell regions. J. Comp. Neurol. 518:1249–1263, 2010. © 2009 Wiley‐Liss, Inc.
CRE/CREB-Driven Up-Regulation of Gene Expression by Chronic Social Stress in CRE-Luciferase Transgenic Mice: Reversal by Antidepressant Treatment

Background It has been suggested that stress provokes neuropathological changes and may thus contribute to the precipitation of affective disorders such as depression. Likewise, the pharmacological therapy of depression requires chronic treatment and is thought to induce a positive neuronal adaptation, presumably based on changes in gene transcription. The transcription factor cAMP-responsive element binding protein (CREB) and its binding site (CRE) have been suggested to play a major role in both the development of depression and antidepressive therapy. Methodology/Principle Findings To investigate the impact of stress and antidepressant treatment on CRE/CREB transcriptional activity, we generated a transgenic mouse line in which expression of the luciferase reporter gene is controlled by four copies of CRE. In this transgene, luciferase enzyme activity and protein were detected throughout the brain, e.g., in the hippocampal formation. Chronic social stress significantly increased (by 45 to 120%) CRE/CREB-driven gene expression measured as luciferase activity in several brain regions. This was also reflected by increased CREB-phosphorylation determined by immunoblotting. Treatment of the stressed mice with the antidepressant imipramine normalized luciferase expression to control levels in all brain regions and likewise reduced CREB-phosphorylation. In non-stressed animals, chronic (21 d) but not acute (24 h) treatment with imipramine (2×10 mg/kg/d) reduced luciferase expression in the hippocampus by 40–50%. Conclusions/Significance Our results emphasize a role of CREB in stress-regulated gene expression and support the view that the therapeutic actions of antidepressants are mediated via CRE/CREB-directed transcription.
Joint Discrete Rate Adaptation and Downlink Beamforming Using Mixed Integer Conic Programming

Multiuser downlink beamforming for sum-rate maximization has been intensively studied in the literature assuming that the achievable data rates of the mobile stations (MSs) are continuous and strictly increasing functions of the received signal-to-interference-plus-noise ratios (SINRs). However, in practical cellular networks that employ adaptive modulation and coding, the data rates of the MSs are determined by the specific modulation and coding schemes and thus attain discrete values. We consider in this paper discrete rate adaptation and downlink beamforming (RAB), where the discrete rate assignment is jointly optimized along with the beamformer design to achieve the maximum sum-rate with minimum total transmitted power of the base station. User admission control is embedded in the discrete rate assignment procedure. We address the RAB problem using a mixed integer second-order cone program (MI-SOCP) approach, proposing a standard big-M MI-SOCP formulation that supports the branch-and-cut (BnC) method. To reduce the complexity of the BnC algorithm, we further develop an improved extended MI-SOCP formulation. We analytically show that the extended formulation generally admits strictly tighter continuous relaxations (and thus less computational complexity) than that of the big-M formulation. Efficient strategies are proposed to customize the standard BnC method for the RAB problem. For applications in large-scale networks, we develop low-complexity SOCP based inflation and deflation procedures to find suboptimal solutions of the RAB problem. Simulations show that the inflation and deflation procedures yield sum-rates that are very close to that of the optimal solutions.
Comparing techniques for authorship attribution of source code

Attributing authorship of documents with unknown creators has been studied extensively for natural language text such as essays and literature, but less so for non‐natural languages such as computer source code. Previous attempts at attributing authorship of source code can be categorised by two attributes: the software features used for the classification, either strings of n tokens/bytes (n‐grams) or software metrics; and the classification technique that exploits those features, either information retrieval ranking or machine learning. The results of existing studies, however, are not directly comparable as all use different test beds and evaluation methodologies, making it difficult to assess which approach is superior. This paper summarises all previous techniques to source code authorship attribution, implements feature sets that are motivated by the literature, and applies information retrieval ranking methods or machine classifiers for each approach. Importantly, all approaches are tested on identical collections from varying programming languages and author types. Our conclusions are as follows: (i) ranking and machine classifier approaches are around 90% and 85% accurate, respectively, for a one‐in‐10 classification problem; (ii) the byte‐level n‐gram approach is best used with different parameters to those previously published; (iii) neural networks and support vector machines were found to be the most accurate machine classifiers of the eight evaluated; (iv) use of n‐gram features in combination with machine classifiers shows promise, but there are scalability problems that still must be overcome; and (v) approaches based on information retrieval techniques are currently more accurate than approaches based on machine learning. Copyright © 2012 John Wiley & Sons, Ltd.
Expert System for Power Plant Operator Performance Evaluation

The aim of this work is to design an intelligent system for evaluating knowledge level of power plant operators who have completed training program. To build the evaluation system, skilled plant operator performance during fault conditions is simulated through expert system techniques. Rule based expert system developed, stores domain knowledge as set of rules. The system is integrated with Supervisory Control And Data Acquisition (SCADA) System of the power plant. User input to the system is a set of SCADA alarm names. Through backward knowledge inferencing process all reason codes related to particular alarms are extracted by the expert system. The responses obtained from trainees are then compared with inferred knowledge and alarm configuration values obtained from data base. Score calculating programme running at the back ground prepares cumulative scores which is used to classify the knowledge level of employees. Traditional method of performance evaluation by operational experts requires their man-hours and results differ between experts, which prevents a systematic analysis. The proposed scheme follows a prototypical methodology, which provides means for comparing different operators in a systematic manner in less time.
Spectrophotometric Studies on Intact Muscle

The kinetics of the mitochondrial respiratory chain of intact muscle and the concomitant changes of the intercellular pH were investigated. Addition of lactate and pyruvate under resting conditions produces reductions of DPN and cytochrome b, and, occasionally, of cytochrome c and flavoprotein. Succinate gives similar but smaller changes. In recently excised muscles moderate contractile activity produces a reduction of cytochrome c and oxidations of DPNH, cytochrome b, and sometimes of the flavoproteins. Tetanic contractions and larger numbers of twitches produce reductions of DPN and of cytochromes b and c. In sartorii of the tropical toad, stored for approximately 2 days at 0–3°C, contractile activity always gives rise to long lasting oxidations of DPNH and cytochrome b. Addition of pyruvate or lactate shortens these oxidation cycles with a concomitant reduction of cytochrome c. These responses to contractions agree with those of mitochondria isolated from leg muscles of the toad upon the addition of ADP. Apparently the mitochondria in resting, excised muscles are not supplied with an excess of substrate. Measurements on the intercellular pH showed that even limited activity ( < 5 twitches) initiates glycolysis. The primary control of respiration resides, nevertheless, in the ADP concentration, rather than in the levels of substrate or inorganic phosphate. The results are quantitatively consistent with the view that ATP is the primary energy donor for muscular contraction.
A discrete choice sequence model: method and an illustrative application to automobile transactions

Opportunities for extending static discrete-choice models to incorporate temporal elements are increasing rapidly with the availability of panel data. An interest in discrete choices in discrete time arises as a natural extension of the static models of discrete choice. One appealing approach is to utilise constructs developed in the literature on latent traits and structures, enabling an explicit treatment of important representations of change. The intertemporal elements can be encapsulated by the conditions of nonstationarity and heterogeneity, or individual-specific effects which do not vary over time. In this paper we present a discrete choice model of outcome sequences through time of the beta-logistic form, and draw upon a four wave panel data set of household automobile transactions to illustrate the application of the method.
On Inertial Body Tracking in the Presence of Model Calibration Errors

In inertial body tracking, the human body is commonly represented as a biomechanical model consisting of rigid segments with known lengths and connecting joints. The model state is then estimated via sensor fusion methods based on data from attached inertial measurement units (IMUs). This requires the relative poses of the IMUs w.r. t. the segments—the IMU-to-segment calibrations, subsequently called I2S calibrations—to be known. Since calibration methods based on static poses, movements and manual measurements are still the most widely used, potentially large human-induced calibration errors have to be expected. This work compares three newly developed/adapted extended Kalman filter (EKF) and optimization-based sensor fusion methods with an existing EKF-based method w.r. t. their segment orientation estimation accuracy in the presence of model calibration errors with and without using magnetometer information. While the existing EKF-based method uses a segment-centered kinematic chain biomechanical model and a constant angular acceleration motion model, the newly developed/adapted methods are all based on a free segments model, where each segment is represented with six degrees of freedom in the global frame. Moreover, these methods differ in the assumed motion model (constant angular acceleration, constant angular velocity, inertial data as control input), the state representation (segment-centered, IMU-centered) and the estimation method (EKF, sliding window optimization). In addition to the free segments representation, the optimization-based method also represents each IMU with six degrees of freedom in the global frame. In the evaluation on simulated and real data from a three segment model (an arm), the optimization-based method showed the smallest mean errors, standard deviations and maximum errors throughout all tests. It also showed the lowest dependency on magnetometer information and motion agility. Moreover, it was insensitive w.r. t. I2S position and segment length errors in the tested ranges. Errors in the I2S orientations were, however, linearly propagated into the estimated segment orientations. In the absence of magnetic disturbances, severe model calibration errors and fast motion changes, the newly developed IMU centered EKF-based method yielded comparable results with lower computational complexity.
Are modern varieties always better? An economic analysis of maize varietal selection

Numerous high-yielding modern maize varieties have been developed for Malawi. However, their performance and returns when managed under real-world conditions are generally unknown. We have used new cross section data to generate insights into the performance of these maize varieties. We first determined optimal portfolios of maize using expected utility maximisation models under a variety of smallholder preference structures. The analysis revealed a trade-off between expected returns and their variability. Modern varieties are high yielding but also pose relatively more downside risk than traditional varieties, perhaps because they are more sensitive to optimal management conditions. Despite this risk, too many smallholders focus exclusively on traditional varieties, and in particular they exclude any modern variety from their portfolio. Factors inhibiting the adoption of modern varieties were examined econometrically. With respect to policy implications, the results suggest that a mix of modern and traditional varieties could be appropriate for many smallholders, and that extension efforts could target specific groups, such as femaleheaded farm households of low socioeconomic status, which face severe constraints in the adoption of modern varieties.
BodyLenses: Embodied Magic Lenses and Personal Territories for Wall Displays

Magic lenses are popular tools to provide locally altered views of visual data. In this paper, we introduce the concept of BodyLenses, special kinds of magic lenses for wall displays that are mainly controlled by body interactions. After motivating the rationale for body-centric lenses, we present a comprehensive design space of BodyLenses, where we analyse fundamental aspects such as appearance, function, interaction and use in multi-user contexts. Within that space, we investigated and implemented a number of design alternatives and propose solutions for lens positioning, dynamic shape modification, distance-based parameter mappings and the use of BodyLenses as portable tool belts. We demonstrate the practicality of our novel concepts with four realised application scenarios. With this work, we hope to lay the foundation for future research and systems based on body-driven lenses.
Providing Service-Connectivity in Delay Tolerant Networks

In delay tolerant networks (DTNs) such as wireless ad hoc networks, frequent and long-duration partitioning of networks causes continuous end-to-end connectivity to be non-guaranteed. Hence, in order to enable legacy applications to run in this DTN environment,the communication protocol stack should be modified to transparently provide applications with the service connectivity. In this paper, therefore, we propose a DTN service architecture and its corresponding protocols, where cross-layering techniques between transport and network layers are exploited. Using ns-2 simulator, we verify that our approach enables end-to-end applications to resume their communication after service disruption. It also has low routing overhead, as compared to the existing approach without this DTN service functionality.