Miracle-dz/UniFAR-FTUs huggingface dataset:
A clathrin/dynamin- and mannose-6-phosphate receptor–independent pathway for granzyme B–induced cell death

The 280-kD cation-independent mannose-6-phosphate receptor (MPR) has been shown to play a role in endocytic uptake of granzyme B, since target cells overexpressing MPR have an increased sensitivity to granzyme B–mediated apoptosis. On this basis, it has been proposed that cells lacking MPR are poor targets for cytotoxic lymphocytes that mediate allograft rejection or tumor immune surveillance. In the present study, we report that the uptake of granzyme B into target cells is independent of MPR. We used HeLa cells overexpressing a dominant-negative mutated (K44A) form of dynamin and mouse fibroblasts overexpressing or lacking MPR to show that the MPR/clathrin/dynamin pathway is not required for granzyme B uptake. Consistent with this observation, cells lacking the MPR/clathrin pathway remained sensitive to granzyme B. Exposure of K44A-dynamin–overexpressing and wild-type HeLa cells to granzyme B with sublytic perforin resulted in similar apoptosis in the two cell populations, both in short and long term assays. Granzyme B uptake into MPR-overexpressing L cells was more rapid than into MPR-null L cells, but the receptor-deficient cells took up granzyme B through fluid phase micropinocytosis and remained sensitive to it. Contrary to previous findings, we also demonstrated that mouse tumor allografts that lack MPR expression were rejected as rapidly as tumors that overexpress MPR. Entry of granzyme B into target cells and its intracellular trafficking to induce target cell death in the presence of perforin are therefore not critically dependent on MPR or clathrin/dynamin-dependent endocytosis.
Multisensor fusion for simultaneous localization and map building

This paper describes how multisensor fusion increases both reliability and precision of the environmental observations used for the simultaneous localization and map-building problem for mobile robots. Multisensor fusion is performed at the level of landmarks, which represent sets of related and possibly correlated sensor observations. The work emphasizes the idea of partial redundancy due to the different nature of the information provided by different sensors. Experimentation with a mobile robot equipped with a multisensor system composed of a 2D laser rangefinder and a charge coupled device camera is reported.
Evaluating management accounting change according to the institutional theory approach

Purpose – The objective of this case study is to evaluate the change process, under the old institutional economics (OIE) approach, that had occurred within the management‐accounting system of Brazilian bank. The present study examines the efficacy of the change process in management accounting, from the perspective of system users, seven years after its beginning.Design/methodology/approach – The research is based on a case study. The study presents a literature review of institutional theory and a case study of Banco do Brasil – a large Brazilian bank that has implemented profound changes in its management‐accounting system.Findings – The results indicate that new concepts have been effectively institutionalised and converted into new values, habits, and routines inside the organisation. The study provides new insights into management‐accounting change.Research limitations/implications – A single case study does not allow the results to be generalised to other organisations.Originality/value – The study.
Environment for Fault Simulation Acceleration on FPGA

We present an environment to accelerate fault simulation by hardware emulation on FPGA. Fault simulation is an important subtask in test pattern generation and it is frequently used throughout the test generation process. We studied the feasibility of using reconfigurable hardware emulator instead of software simulation. Experiments showed that it is beneficial to use emulation for circuits/methods that require large numbers of test vectors, e.g., sequential circuits and/or genetic algorithms.
Wormhole Attack Avoidance Technique in Mobile Adhoc Networks

Security is an essential service for wired and wireless network communication. This work concerned with a particularly sever security attack that affects the ad hoc networks routing protocols, called "wormhole attack". There are many solutions to detect and prevent this attack like packet leashes, cluster base, hop count analysis etc., but none of them is perfect solution. This paper contains a proposal for new technique for wormhole avoidance. Proposed technique has been implemented with NS2 simulator over the DSR protocol. This technique for wormhole avoidance addresses the malicious nodes and avoids the routes having wormhole nodes without affecting the overall performance of the network. The performance metrics used for evaluating network performance are jitter, throughput and end to end delay. The performance of proposed techniques is good.
Forecasting of salmonellosis incidence in human using Artificial Neural Network (ANN)

Salmonellosis is one of the most common seasonal zoonosis. As from the definition, zoonosis refers to the transmission of infectious diseases from animal to human. This paper presents the prediction of Salmonellosis incidence using Artificial Neural Network (ANN) on the basis of monthly data. A series of Salmonellosis incidence in US from 1993 to 2006, published by Centers for Disease Control and Prevention (CDC), was collected for technical analysis. Multi Layer Perceptron (MLP) has been chosen for the ANN design. The model consists of three layers: input layer, hidden layer, and output layer. Number of nodes in hidden layer was varied in order to find the most accurate forecasting result. The comparisons of models were justified by using Mean Absolute Percentage Error (MAPE). Furthermore, MAPE and Theil's U were used to measure the result accuracy. The least MAPE derived from the best model was 10.761 and Theil's U value was 0.209. It implied that the model was highly accurate and a close fit. It was also indicated the capability of final model to closely represent and made prediction based on the tuberculosis historical dataset.
Distributed optimization design based on passivity technique

In this paper, we study distributed optimization based on passivity techniques. At first, we revisit the concept of passivity respect to non-zero equilibrium point and convert the stabilization problem into another problem that to find a function with relative monotonicity. Then, a passivity-based interpretation is proposed on existing centralized optimization algorithms by adopting a continuous-time dynamic system view. We utilize this passivity technique to solve a resource allocation problem via distribute algorithms. Its effectiveness is verified by a simulation example.
Turkish Resources for Visual Word Recognition

We report two tools to conduct psycholinguistic experiments on Turkish words. KelimetriK allows experimenters to choose words based on desired orthographic scores of word frequency, bigram and trigram frequency, ON, OLD20, ATL and subset/superset similarity. Turkish version of Wuggy generates pseudowords from one or more template words using an efficient method. The syllabified version of the words are used as the input, which are decomposed into their sub-syllabic components. The bigram frequency chains are constructed by the entire words’ onset, nucleus and coda patterns. Lexical statistics of stems and their syllabification are compiled by us from BOUN corpus of 490 million words. Use of these tools in some experiments is shown.
VERT : A METHOD FOR AUTOMATIC EVALUATION OF VIDEO SUMMARIES

Video Summarization has become an important tool for Multimedia Information processing, but the automatic evaluation of a video summarization system remains a challenge. A major issue is that an ideal “best” summary does not exist, although people can easily distinguish “good” from “bad” summaries. A similar situation arise in machine translation and text summarization, where specific automatic procedures, respectively BLEU and ROUGE, evaluate the quality of a candidate by comparing its local similarities with several human-generated references. These procedures are now routinely used in various benchmarks. In this paper, we extend this idea to the video domain and propose the VERT (Video Evaluation by Relevant Threshold) algorithm to automatically evaluate the quality video summaries. VERT mimics the theories of BLEU and ROUGE, and counts the weighted number of overlapping selected units between the computer-generated video summary and several human-made references. Several variants of VERT are suggested and compared, and the best variant is selected through experimentation. Index Items Summaries Evaluation, VERT, Rouge, Video Summarization
Evaluating a post-editing approach for handwriting transcription

Marriage license books are documents that were used for centuries by ecclesiastical institutions to register marriage licenses. These books, that were handwritten until the beginning of the 20th century, have interesting information, useful for demography studies and genealogical research. This information is usually collected by expert demographers that devote a lot of time to manually transcribe them. As the accuracy of automatic handwritten text recognizers improves, post-editing the output of these recognizers could be foreseen as a possible alternative. Unluckily, most handwriting recognition techniques require large amounts of annotated images to train the recognition engine. In this paper we carry out a study about how the handwritten recognition system accuracy improves with respect to the amount of training data, and how the human efficiency increases during the transcription of a marriage license book.
Theoretical reconstruction of field potentials and dendrodendritic synaptic interactions in olfactory bulb.

THE ORIGINAL OBJECTIVE of this research was to apply a mathematical theory of generalized dendritic neurons (36-39) to the interpretation and reconstruction of field potentials observed in the olfactory bulb of rabbit (32, 33). In the course of pursuing this objective, we were led to postulate dendrodendritic synaptic interactions which probably play an important role in sensory discrimination and adaptation in the olfactory system (40). More specifically, our initial aim was to develop a computational model, based on the known anatomical organization of the olfactory bulb and on generally accepted properties of nerve membrane, that could reconstruct the distribution of electric potential as a function of two variables, time and depth in the bulbar layers, following a synchronous antidromic volley in the lateral olfactory tract. The experimental studies of Phillips, Powell, and Shepherd (32, 33) had previously established that the recorded potentials at successive bulbar depths are highly reproducible and correlated with the histological layers of the bulb. These authors recognized the importance of this finding in relation to the symmetry and synchrony of activity in the mitral cell population; they deferred the interpretation of these potentials, in terms of specific neuronal activity, with a view to the present theoretical study.
Staufen1 Regulation of Protein Synthesis-Dependent Long-Term Potentiation and Synaptic Function in Hippocampal Pyramidal Cells

ABSTRACT Staufen1 (Stau1) is an RNA-binding protein involved in transport, localization, decay, and translational control of mRNA. In neurons, it is present in cell bodies and also in RNA granules which are transported along dendrites. Dendritic mRNA localization might be involved in long-term synaptic plasticity and memory. To determine the role of Stau1 in synaptic function, we examined the effects of Stau1 down-regulation in hippocampal slice cultures using small interfering RNA (siRNA). Biolistic transfection of Stau1 siRNA resulted in selective down-regulation of Stau1 in slice cultures. Consistent with a role of Stau1 in transporting mRNAs required for synaptic plasticity, Stau1 down-regulation impaired the late form of chemically induced long-term potentiation (L-LTP) without affecting early-LTP, mGluR1/5-mediated long-term depression, or basal evoked synaptic transmission. Stau1 down-regulation decreased the amplitude and frequency of miniature excitatory postsynaptic currents, suggesting a role in maintaining efficacy at hippocampal synapses. At the cellular level, Stau1 down-regulation shifted spine shape from regular to elongated spines, without changes in spine density. The change in spine shape could be rescued by an RNA interference-resistant Stau1 isoform. Therefore, Stau1 is important for processing and/or transporting in dendrites mRNAs that are critical in regulation of synaptic strength and maintenance of functional connectivity changes underlying hippocampus-dependent learning and memory.
Automatic Extraction and Verification of Page Transitions in aWeb Application

Demand for reliability in Web applications has increased greatly in recent years as they have begun to be used more for enterprise applications. Model checking is an effective way to increase software reliability, but because most Web applications have short delivery times, preparation and application costs make it difficult to introduce model-checking techniques into the development process. In this paper, we propose a technique for automatically extracting page transitions from a Web application that has been developed using a Web application framework, such as Struts configuration files and Java Server Page templates, and transforming it into a format that can be used by existing model-checking tools. Using the proposed technique, Web application developers will be able to reduce the preparation and application costs of introducing model-checking techniques.
Feature-based noise robust speech recognition on an Indonesian language automatic speech recognition system

Mel-frequency Cesptral Coefficients (MFCC) and Predictive Linear Prediction (PLP) coefficients are two popular representations of continuous speech in existing Hidden Markov Model (HMM) based Automatic Speech Recognition (ASR) systems. Cepstral Mean Normalization (CMN) is often used as a post-processing step in the extraction of MFCC and PLP features to further enhance noise robustness at almost negligible computational cost. In this paper we build a closed dictionary, large vocabulary HMM-based Indonesian language ASR system using the CMU Sphinx in speech recognition toolkit implementing MFCC and PLP feature extraction, and CMN. We test the effect of various types and levels of noise on the word error rate (WER) of speech recognition. Utilizing CMN, an average improvement of 2% recognition over standard MFCC and PLP extraction methods is obtained at signal-to-noise ratios (SNR) below 24 decibels. A significant drop in recognition is observed between 12 and 6 dB SNR.
Toward the Eco-Grid : A Harmoniously EVOLVED INTERCONNECTION ENVIRONMENT

I L L U S T R A T I O N B Y R I C H A R D D O W N S TheInternet, along with its myriad resources and users, constitutes a vast artificial virtual environment that benefits all of human society. But both the general public and the research community may be unaware of its developmental trend toward disorder due to the exponential growth of the numbers and types of its resources and users. By way of analogy, this trend can be explained with the help of the second law of thermodynamics, which states that if we regard the environment as a closed system with constant volume and energy, then every change to the system increases its tendency toward entropy. Web users are regularly dissatisfied with the Web’s information services [5], and IT professionals worldwide look to establish new interconnection environments through, say, the Semantic Web, the Grid, and peer-to-peer and intelligent technologies [1, 2]. But these efforts neglect the problem of how to prevent the new environment from falling into its own future disorder, especially when some factors (such as resources and users) change dramatically. The natural ecological environment is another vast and complex system that has evolved over billions of years. The health of any ecosystem depends on effective energy flow, material flow, and information flow cycles to maintain the dynamic balance of populations of species in the flow cycles by assimilating waste and being able to self-recover from damage. The harmonious characteristics of the natural ecological environment represent a new way for IT professionals to establish a future interconnection environment. An Eco-Grid is an open worldwide interconnection environment Toward the Eco-Grid: A Harmoniously EVOLVED INTERCONNECTION ENVIRONMENT
Streptococcus pneumoniae DNA Initiates Type I Interferon Signaling in the Respiratory Tract

ABSTRACT The mucosal epithelium is the initial target for respiratory pathogens of all types. While type I interferon (IFN) signaling is traditionally associated with antiviral immunity, we demonstrate that the extracellular bacterial pathogen Streptococcus pneumoniae activates the type I IFN cascade in airway epithelial and dendritic cells. This response is dependent upon the pore-forming toxin pneumolysin. Pneumococcal DNA activates IFN-β expression through a DAI/STING/TBK1/IRF3 cascade. Tlr4−/−, Myd88−/−, Trif−/−, and Nod2−/− mutant mice had no impairment of type I IFN signaling. Induction of type I IFN signaling contributes to the eradication of pneumococcal carriage, as IFN-α/β receptor null mice had significantly increased nasal colonization with S. pneumoniae compared with that of wild-type mice. These studies suggest that the type I IFN cascade is a central component of the mucosal response to airway bacterial pathogens and is responsive to bacterial pathogen-associated molecular patterns that are capable of accessing intracellular receptors. IMPORTANCE The bacterium Streptococcus pneumoniae is a leading cause of bacterial pneumonia, leading to upwards of one million deaths a year worldwide and significant economic burden. Although it is known that antibody is critical for efficient phagocytosis, it is not known how this pathogen is sensed by the mucosal epithelium. We demonstrate that this extracellular pathogen activates mucosal signaling typically activated by viral pathogens via the pneumolysin pore to activate intracellular receptors and the type I interferon (IFN) cascade. Mice lacking the receptor to type I IFNs have a reduced ability to clear S. pneumoniae, suggesting that the type I IFN cascade is central to the mucosal clearance of this important pathogen. The bacterium Streptococcus pneumoniae is a leading cause of bacterial pneumonia, leading to upwards of one million deaths a year worldwide and significant economic burden. Although it is known that antibody is critical for efficient phagocytosis, it is not known how this pathogen is sensed by the mucosal epithelium. We demonstrate that this extracellular pathogen activates mucosal signaling typically activated by viral pathogens via the pneumolysin pore to activate intracellular receptors and the type I interferon (IFN) cascade. Mice lacking the receptor to type I IFNs have a reduced ability to clear S. pneumoniae, suggesting that the type I IFN cascade is central to the mucosal clearance of this important pathogen.
Capital Structure: New Evidence from the Ownership Structure

This paper provides theory and empirical evidence supporting a complementary perspective on capital structure based on corporate ownership structure. According to our ownership view, capital structure is partly determined by the incentives and the goals of those who are in control of the firm. Our results strongly support this view. As a consequence of managerial entrenchment and rent expropriation phenomena, self‐interested agents (entrenched managers and controlling owners) chose the capital structure most appropriate for their own best interest. Additionally, we find evidence of an interaction effect between managerial ownership and ownership concentration, in particular, the larger debt increments promoted by outside owners when managers are entrenched.
AIS Electronic

Human factors are increasingly recognized as real culprits of failures in Information Security Management (ISM). Thus, the roles of Human Resource Management (HRM) become more salient with ISM. Unlike practitioners, researchers appear reluctant to acknowledge such emergence. Prior literature has not attempted to link ISM with HRM theoretically. ISM literature suggests that both technical and non-technical aspects be simultaneously considered. Similarly, HRM literature recommends that practices such as staffing and training be treated as a bundle. Evidently, both ISM and HRM teams require a pool of specialized knowledge and skills to manage each of their aspects. Moreover, both teams should collaborate in order to improve the ISM performance of the firm. However, the amount of the knowledge may become overloading to both teams. This paper posits that Transactive Memory System (TMS) can support not only knowledge coordination when each team operates independently, but also alleviate the knowledge overload when both teams collaborate. Furthermore, this paper proposes that such collaboration via TMS enables an organization to not only manage its ISM more effectively but ultimately produce sustainable competitive advantage. Implications are then discussed.
Stochastic Vector Mobility Model for Mobile and Vehicular Ad Hoc Network Simulation

In this paper, a random synthetic stochastic vector mobility model (VMM) to simulate vehicle traffic movement for mobile and vehicle ad hoc networks is proposed. The objective of the VMM is to be able to easily regenerate random mobility patterns that accurately match the stochastic characteristics of vehicles (e.g., cars and buses) better than other random synthetic stochastic mobility simulators, which include random walk, Gauss-Markov mobility, fluid flow, and random way point. An essential characteristic of vehicle mobility is that it has directionality and is targeted toward a destination while showing a certain degree of randomness in speed and angle changes as it moves toward its destination. To model these characteristics, a destination targeted VMM (DTVMM) is proposed, which can be made to randomly move toward the exact location or the neighborhood of the targeted destination based on the setting of the DTVMM stochastic parameters. When the stochastic parameters of actual traffic traces are used, the simulation results show that the DTVMM movement patterns are very similar to actual traces and have the same stochastic characteristics.