Miracle-dz/UniFAR-FTUs huggingface dataset:
Neutral Sphingomyelinase in Physiological and Measles Virus Induced T Cell Suppression

T cell paralysis is a main feature of measles virus (MV) induced immunosuppression. MV contact mediated activation of sphingomyelinases was found to contribute to MV interference with T cell actin reorganization. The role of these enzymes in MV-induced inhibition of T cell activation remained equally undefined as their general role in regulating immune synapse (IS) activity which relies on spatiotemporal membrane patterning. Our study for the first time reveals that transient activation of the neutral sphingomyelinase 2 (NSM2) occurs in physiological co-stimulation of primary T cells where ceramide accumulation is confined to the lamellum (where also NSM2 can be detected) and excluded from IS areas of high actin turnover. Genetic ablation of the enzyme is associated with T cell hyper-responsiveness as revealed by actin dynamics, tyrosine phosphorylation, Ca2+-mobilization and expansion indicating that NSM2 acts to suppress overshooting T cell responses. In line with its suppressive activity, exaggerated, prolonged NSM2 activation as occurring in co-stimulated T cells following MV exposure was associated with aberrant compartmentalization of ceramides, loss of spreading responses, interference with accumulation of tyrosine phosphorylated protein species and expansion. Altogether, this study for the first time reveals a role of NSM2 in physiological T cell stimulation which is dampening and can be abused by a virus, which promotes enhanced and prolonged NSM2 activation to cause pathological T cell suppression.
Design and optimization of c-Silicon solar cell using Process Compact Model (PCM)

We demonstrates a complete Technology CAD (TCAD) methodology that addresses the manufacturing challenges posed by rising technological complexity, increasing process variability and shrinking time-to-market windows. Using TCAD simulations as input, Process Compact Models are created to enable efficient analysis of complex and multivariate process-device relationships, with applications to enhancing process manufacturability and process control. The methodology is used for the design and optimization of silicon Solar Cell technologies. Transfer matrix method (TMM) is used for the calculation of solar cell characteristics; reflectance and transmittance spectra, quantum efficiency, and I–V characteristics.
A new algorithm for the detection of intercluster galaxy filaments using galaxy orientation alignments

We present a new algorithm for detecting intercluster galaxy filaments based upon the assumption that the orientations of constituent galaxies along such filaments are non-isotropic. We apply the algorithm to the 2dF Galaxy Redshift Survey catalogue and find that it readily detects many straight filaments between close cluster pairs. At large intercluster separations (> 15 h(-1) Mpc), we find that the detection efficiency falls quickly, as it also does with more complex filament morphologies. We explore the underlying assumptions and suggest that it is only in the case of close cluster pairs that we can expect galaxy orientations to be significantly correlated with filament direction.
Scalable leader election

In the leader election problem, there are n processors of which (1 - b)n are good. The problem is to design a distributed protocol to elect a good leader from the set of all processors. In this paper, we present a scalable leader election protocol. Our protocol is scalable in the sense that each good processor sends and processes a number of bits which is only polylogarithmic in n. (We assume no limit on the number of messages sent by bad processors.) For b < 1/3, our protocol elects a good leader with constant probability and ensures that a 1 - o(1) fraction of the good processors know this leader.We assume a point-to-point full information model. This is similar to the full information model, but harder in the sense that in a given round, a bad processor may send different messages to different processors, rather than having to broadcast the same message to every processor.To the best of our knowledge, we present the first leader election protocol that ensures that each good processor sends and processes a sublinear number of bits. Having reduced the problem of leader election to one of informing all good processors of a bit held by 1 − o(1) fraction of good processors, we conjecture that the solution to this problem is not possible within polylogarithmic message bounds.Our techniques can be used to provide scalable solutions to Byzantine agreement and other problems.
A theory of organizational information services

Organizational use of information technology (IT) is increasingly characterized as ‘services’ rather than ‘systems’ to more accurately reflect IT’s impact on organizational practices. We lack, however, frameworks that can help us understand, assess, and design information services in organizational contexts. This paper combines general notions of task, information, and service, to form a theory of organizational information services. Distinguishing between computational, adaptive, networking, and collaborative services, the theory suggests that work contexts should support portfolios of information services that enable effective and efficient responses to the equivocality and uncertainty profile of the involved tasks. The paper defines the four types of services, it suggests how they support different types of tasks, and it characterizes the semiotic processes through which they are enacted.
The effects of sensory stimuli on motorsports spectators

This study measures the effect of each of the five senses on arousal, satisfaction and intention to revisit a live racing event. Spectators' arousal was significantly influenced by sights, sounds and smells. Spectators' sense of smell, taste, and touch directly impacted satisfaction. Interestingly, olfactory stimuli had an effect on both arousal and satisfaction. Spectators' arousal had a significant indirect effect on their revisit intention. The study proposes that motorsports marketers make use of olfactory stimuli to provide racing spectators with memorable experiences.
More on the speed and accuracy of positive and negative responses.

The account given by the diffusion model (Ratcliff, 1985) of the relation between positive and negative responses has been criticized by Proctor, who argues that the diffusion model provides no theory of criterion setting and that it violates psychophysical principles. In reply, I argue that psychophysical principles are not violated and that a quantitative theory of criterion placement is currently outside the scope of the diffusion model and many other models of memory. I point out that the strength of the diffusion model lies in inability to account for aspects of the data other than just mean reaction time (RT), and in its generality across experimental paradigms.
What Is the Ideal Tumor Regression Grading System in Rectal Cancer Patients after Preoperative Chemoradiotherapy?

Purpose Tumor regression grade (TRG) is predictive of therapeutic response in rectal cancer patients after chemoradiotherapy (CRT) followed by curative resection. However, various TRG systems have been suggested, with subjective categorization, resulting in interobserver variability. This study compared the prognostic validity of four different TRG systems in order to identify the most ideal TRG system. Materials and Methods This study included 933 patients who underwent preoperative CRT and curative resection. Primary tumors alone were graded according to the American Joint Committee on Cancer (AJCC), Dworak, and Ryan TRG systems, and both primary tumors and regional lymph nodes were graded according to a modified Dworak TRG system. The ability of each TRG system to predict recurrence-free survival (RFS) and overall survival (OS) was analyzed using chi-square and C statistics. Results All four TRG systems were significantly predictive of both RFS and OS (p < 0.001 each), however none was a better predictor of prognosis than ypStage. Among the four TRGs, the mDworak TRG system was a better predictor of RFS and OS than the AJCC, Dworak, and Ryan TRG systems, and both the chi-square and C statistics were higher for the former, although the differences were not statistically significant. The combination of ypStage and the modified Dworak TRG better predicted RFS and OS than ypStage alone. Conclusion The modified Dworak TRG system for evaluation of entire tumors including regional lymph nodes is a better predictor of survival than current TRG systems for evaluation of the primary tumor alone.
A Signal-Dependent Evolution Kernel for Cohen Class Time-Frequency Distributions

Abstract Cohen class time–frequency distributions serve as alternatives to the traditional spectrogram and are known for their ability to provide simultaneous resolution in time and frequency. They employ a kernel along with the signal's Wigner distribution. Kernel design has witnessed significant attention. Very recently Costa and Boudreaux-Bartels have proposed a multiform tiltable exponential distribution kernel containing six parameters. This paper presents optimization of these parameters using evolution programs.
Why buy when you can rent ? Bribery attacks on Bitcoin consensus

The Bitcoin cryptocurrency system relies on a novel distributed consensus mechanism relying on economic incentives. It is often argued that Bitcoin is “incentive-compatible” in simplified models; that is, that the scenario in which all miners follow the Bitcoin protocol is a stable Nash Equilibrium in which no miner has any incentive to defect. We introduce the notion of a bribery attack in which an attacker can purchase mining power (perhaps at a cost premium) for a short duration, using it to profit by double-spending. Explaining the lack of such attacks in practice requires significant additional modeling assumptions, demonstrating the inadequacy of current models of Bitcoin consensus.
UQ RoboRoos: Preliminary Design of a Robot Soccer Team

The UQ RoboRoos have been developed to participate in the RoboCup robot soccer small size league. This paper describes the current level of implementation of the robots, including aspects of hardware design, as well as the software running on the robots and the controlling computer. Key features of the RoboRoos design include the agile and powerful mechanical frame, the robots’ navigational techniques and a coordinating planner system based on potential field methods.
CERTAIN CLASSES OF HARMONIC FUNCTIONS ASSOCIATED WITH FOX-WRIGHT GENERALIZED HYPERGEOMETRIC FUNCTION

The Fox-Wright generalization of the classical hypergeometric function is used to introduce a new class of complex valued harmonic functions which are orientation preserving and univalent in the open unit disc. Among the results presented in this paper include the coefficient bounds, distortion inequality and covering property, extreme points and certain inclusion results for this generalized class of functions. 2000 Mathematics Subject Classification: 30C45, 30C50.
Mediterranean Conference on Information Systems ( MCIS ) 2009 An Exploratory Study Of The Effects Of Virtuality On Team Effectiveness

Recent studies on virtual teams reveal that team virtuality may be considered from different levels which have a considerable impact on team processes and management. However, as a recent concept introduced to virtual team literature, virtuality and its effects on team effectiveness are still under studied. The purpose of this paper is twofold. On the one hand, it aims to define the concept of virtuality and provide a multidimensional approach to assess its different levels based on the main characteristics of virtual teams expressed in the literature. On the other hand, it analyzes how variations in virtuality influence team effectiveness. The effectiveness measures retained in this study are: work performance, attitudes and behaviours. A longitudinal qualitative study was conducted on ten virtual teams composed of three to five students involved in online Master degree programmes at a French university. The results highlighted the importance of differentiating technological and social virtuality to improve our understanding of team virtuality and to better apprehend its effects on team effectiveness.
On the stable passive dynamics of quadrupedal running

In this paper, we study the passive dynamics of quadrupedal bounding, based on a simplified model of our Scout II quadruped robot. Surprisingly, numerical return map studies reveal that passive generation of a large variety of cyclic bounding motion is possible. Most strikingly, local stability analysis shows that the dynamics of the open loop passive system alone can confer stability of the motion. Stability improves at higher speeds, which is in agreement with recent results from biomechanics. These results can be used in developing a general control methodology for legged robots, resulting from the synthesis of feed-forward and feedback models that take advantage of the mechanical system, and might explain the success of simple, open loop bounding controllers on our experimental robot.
Further evidence of a relationship between explaining, tracing and writing skills in introductory programming

This paper reports on a replication of earlier studies into a possible hierarchy of programming skills. In this study, the students from whom data was collected were at a university that had not provided data for earlier studies. Also, the students were taught the programming language "Python", which had not been used in earlier studies. Thus this study serves as a test of whether the findings in the earlier studies were specific to certain institutions, student cohorts, and programming languages. Also, we used a non-parametric approach to the analysis, rather than the linear approach of earlier studies. Our results are consistent with the earlier studies. We found that students who cannot trace code usually cannot explain code, and also that students who tend to perform reasonably well at code writing tasks have also usually acquired the ability to both trace code and explain code.
Research on torque-variable control method for stepping motors in service robot arm

Stepping motors are applied to service robots in many cases, unfortunately stepping motors often occur out-of-step situation when it is overload. In order to sense the occurrence of out-of-step without the help from external sensors, its feedback could only induce from its inner structure of the stepping motor. In other words, occurrence of out-of-step cause variable back electromotive force (emf) which cause fluctuation of phase current change. By detecting the change of phase current, the occurrence of out-of-step becomes more observable. Based on the feedback which is the phase current change, a new control system is introduced in this paper, which inserts feedback into a PID regulator to increase the input current and further increase output torque of motor shaft simultaneously. Based on the simulation result in Matlab, the stepping motor is able to make sure the shaft is in its static state even though load torque is larger than normal value. Therefore, service robot arm has much strength to hold heavy things than before.
SUPER-RESOLUTION : AN ITERATIVE APPROACH

Among all the techniques for 3D acquisition, stereo vision systems are the most common. More recently, Time-of-Flight (ToF) range cameras have been introduced. They allow real-time depth estimation in conditions where stereo does not work well. Unfortunately, ToF sensors still have a limited resolution (e.g., 200 × 200 pixels). The goal of this paper is to combine the information from the ToF with one or two standard cameras, in order to obtain a highresolution depth image. To this end, we propose a new bilateral filter for depth maps up-sampling, which exploits the additional information provided by a high-resolution color image. Moreover, we present an entire framework for the super-resolution of a real ToF depth map with a single camera color image. The algorithm allows to enhance the resolution of the ToF camera depth image up to 1920× 1080 pixels.
Antidepressant-Like and Antioxidant Effects of Plinia trunciflora in Mice

The jaboticaba tree, Plinia trunciflora (O. Berg) Kausel, is popularly named “jabuticabeira” in Brazil and is used in folk medicine to treat diabetes and chronic inflammation of the tonsils, but studies evaluating the central effects of this species are limited. This study evaluated the antidepressant-like and antioxidant effects of P. trunciflora (PT) aqueous extract, in which five different anthocyanins were identified. PT showed significant ferric-reduction power and DPPH radical scavenging activity in vitro and reduced lipid peroxidation both in vitro and ex vivo. At the behavioural level, PT (400 and 800 mg/kg, i.p.) dose-dependently reduced immobility time in the tail suspension test in Swiss male mice. The identification of bioactive compounds accompanied by the in vitro and ex vivo antioxidant activity of PT suggests that these activities might be related to the antidepressant-like activity of P. trunciflora.
Design of a Switched Reluctance Machine for Extended Speed Operation

This paper presents results from a design study on the feasibility of employing high-efficiency switched reluctance (SR) machines in minimal hybrid-electric vehicles. The application requirements are presented and highlight the constraining influences of the vehicle drive-line topology on the machine design. The benefit of continuous phase current excitation is reported for the first time, demonstrating that constant power at an extended-speed operation can be realized with a higher number of phase winding turns per pole than would otherwise be achieved with conventional discontinuous current control. Thus, the torque/Ampere capability, when operating at or below base speed, is not as significantly compromised, an important consideration for the power inverter rating and, hence, drive system cost. The design procedure and simulated results are validated by measurements from a prototype machine. The results demonstrate the potential of SR technology for high-performance low-cost automotive applications, which often combine arduous environmental and volumetric constraints. In addition, the results highlight the benefits of continuous current control for extended-speed operation.
Identifiability and improvement of adjoint error approach for serial robot calibration

In this paper, we first analyze the identifiability of POE based Adjoint error approach. By carefully examining the linear dependence between calibration Jacobian columns, it is proved that joint offsets and Adjoint errors cannot be identified simultaneously, and the maximum dimension of identifiable parameters is 4r + 2t + 6. Some more scenarios are considered to augment the Adjoint error approach. To satisfy the constraints on joint relations, constrained method and projection method are proposed. Moreover, we present the identifiability of reduction ratios and joint pitches. Simulations of a 6 Degree-of-Freedom robot and a SCARA robot are given to illustrate and compare our methods. It shows that the constrained method can handle such situations effectively and yields better results.
NP-Completeness of Outcome Optimization for Partial CP-Nets

CP-nets (Boutilier 2004) represent qualitative conditional preferences using a graphical model similar in concept to a belief network. A CP-net describes the preferences over the values of each problem variable, possibly conditioned on the values of other variables. For example, a user might describe her ideal dinner by expressing an (unconditional) preference for a meat entree over a fish entree, and a preference for wine that depends on the particular choice of entree (red wine with meat, and white wine with fish). The CP-net for this diner would look like the one in Figure 1, with the exception that a preference would be expressed for the value of
Mining Multiple Models

Data mining is much more than simply building statistical models from large collections of data. In particular, this paper records a core task of mining as exploring through the space of models that are built in a data mining project. The idea was first introduced through the concept of multiple inductive learning (MIL) (Williams, 1988, 1991) and further developed in practise as mining the data mine (Williams and Huang, 1997). Many data mining advances that have since emerged have further developed the idea: multiple modelling, ensemble learning, bagging, and boosting all help the data miner explore different ideas and look for different insights in modelling. In this paper we review these ideas and a number of data mining projects that highlight the significant role played by mining the data mine.
AUTOMATIC TEXT SUMMARIZATION BASED ON PRAGMATIC ANALYSIS

The rapid growth of online information has encumbered the user with colossal amount of information. It is difficult to access large amount of data. This problem has increased the research in the field of automatic text summarization. Automatic text summarization is a technique where the text is input to the computer and it returns the clipped and concise extract of the original text and also sustains the overall meaning and main information content. In this paper, text summarization technique is designed for the documents having the fixed format. The proposed system generates the summary of the fixed format documents by analyzing all the different parts of the documents. The system consists of five stages. In first stage each sentence is partitioned into the list of tokens and stop words are removed. In second stage, frequency usage is counted for each word. In third stage, assign POS tag for each weighted term and Word sense disambiguation is done. In the fourth stage, pragmatic analysis is performed. After Pragmatic Analysis, summarized sentences will be store in a database.
Combinatorial construction of Morse-Smale complexes for topology-based data analysis and visualization

The main focus of my research has been developing an efficient algorithm to construct the Morse-Smale complex for volumetric data. The Morse-Smale complex encodes the scalar topology of a dataset, and can be used to extract features from the data. My initial attempts to compute the complex based on numerical methods proved to be unreliable, intricate, and ultimately doomed to failure. This motivated an approach based on combinatorial decisions. The notions for topology based analysis of triangulated data familiar from previous work done by others in two dimensions were insufficient to address the range of complexities encountered in three dimensions: additional components of the complex had to be computed, new data structures introduced, and additional degenerate configurations identified and resolved. Even the notion of cancellation of critical points proved to be a non-trivial extension from two dimensions. We overcame these problems by simplifying; we introduced simple cancellation operations, and applied them to a previously known Morse-Smale complex to extract features from volumetric domains. We optimized the new approach using a streaming procedure along with new data structures, and showed the applicability of our methods for finding features in a material science dataset. Our algorithm was robust, but the implementation suffered from prohibitive memory and computational overheads. However, developing this algorithm gave insights into the problems associated with computing the Morse-Smale complex, and sufficient motivation to try a new approach. Using this new wisdom, along with notions borrowed from discrete Morse theory, we will develop an algorithm for computing the Morse-Smale complex for general dimensional data. The focus of my research will be on developing this new algorithm into an efficient implementation that will be useful in a wide variety of applications.