Miracle-dz/UniFAR-FTUs huggingface dataset:
Mannose-Binding Lectin Blunts Macrophage Polarization and Ameliorates Lupus Nephritis

Background Deficiency in clearance of self nuclear antigens, including DNA, is the hallmark of systemic lupus erythematosus (SLE), a chronic autoimmnue disease characterized by the production of various autoantibodies, immune complex deposition and severe organ damage. Our previous studies revealed that administration of syngeneic BALB/c mice with activated lymphocyte-derived DNA (ALD-DNA) could induce SLE disease. Mannose-binding lectin (MBL), a secreted pattern recognition receptor with binding activity to DNA, has been proved to be a modulator of inflammation, but whether MBL takes responsibility for DNA clearance, modulates the DNA-mediated immune responses, and is involved in the development of DNA-induced SLE disease remain poorly understood. Methodology/Principal Findings The levels of serum MBL significantly decreased in lupus mice induced by ALD-DNA and were negatively correlated with SLE disease. MBL blunted macrophage M2b polarization by inhibiting the MAPK and NF-κB signaling while enhancing the activation of CREB. Furthermore, MBL suppressed the ability of ALD-DNA–stimulated macrophages to polarize T cells toward Th1 cells and Th17 cells. Importantly, MBL supplement in vivo could ameliorate lupus nephritis. Conclusion/Significance These results suggest MBL supplement could alleviate SLE disease and might imply a potential therapeutic strategy for DNA-induced SLE, which would further our understanding of the protective role of MBL in SLE disease.
Just in time classifiers: Managing the slow drift case

A classifier expected to work in a non-stationary environment has to: (i) detect changes in the process generating the data; (ii) suitably react to the change by adapting to the new working condition. Just-In-Time Adaptive classifiers, a classification structure addressing stationary and nonstationary conditions, have been recently presented to the computational intelligence community. Such classifiers require a temporal detection of a (possible) process deviation followed by an adaptive management of the knowledge base characterizing the classifier to cope with the process change. This paper improves Just-in-time Adaptive Classifiers by integrating temporal information about the state of the process under monitoring. An index for the process deviation is defined which, coupled with an adaptive weighted k-NN classifier, shows to be particularly effective in dealing with smooth process drifts and ageing phenomena.
Scenic photo quality assessment with bag of aesthetics-preserving features

In this paper, an aesthetic modeling method for scenic photographs is proposed. A bottom-up approach is developed to construct an aesthetic library with bag-of-aesthetics preserving features instead of top-down methods that implement the heuristic guidelines (rule-specific features) listed in the photography literature, which is employed in previous works. The proposed method can cover both implicit and explicit aesthetic features with a learning process. The experimental results show that the proposed features in the library (92.06% in accuracy) outperform the state-of-the-art rule-specific features (83.63% in accuracy) significantly in the aesthetic quality assessment for scenic photos, and the rule-specific features are also proved to be encompassed by the proposed features. Meanwhile, it is observed from experiments that the features extracted for contrast information are more effective than those for absolute information, which is consistent with the properties of human visual systems.
Pacific Asia Conference on Information Systems ( PACIS ) 2014 THE IMPACT OF STAKEHOLDER IDENTIFICATION AND SALIENCE ON THE SUPPLIER ’ S IT INFRASTRUCTURE INTEGRATION WITH CUSTOMERS

With the prevalence of electronic supply chain integration (e-SCI), increasingly more customers are asking their suppliers to integrate IT infrastructure for SCM and many suppliers indeed comply with their customers’ requests. However, a supplier can have multiple customers and limited resources . Therefore, the supplier typically responds to its customers’ requests for IT infrastructure integration selectively. To investigate this phenomenon, this study draws on Mitchell, Agle, and Wood’s (1997) stakeholder identification and salience framework to examine whether the customer’s stakeholder salience influences the supplier’s IT infrastructure integration for SCM. This study also examines whether the customer’s legitimacy, power, and urgency determine their salience perceived by the supplier. This study surveyed Taiwanese manufacturers. Based on one hundred and eight effective questionnaires, our findings showed that: (1) stakeholder salience is positively associated with IT infrastructure integration for SCM (i.e., data consistency and cross-functional application integration); (2) legitimacy and power have positive impacts on stakeholder salience while urgency does not. Our findings can facilitate customers to select appropriate suppliers for successful promotion of IT infrastructure integration for SCM.
The point-spread function measure of resolution for the 3-D electrical resistivity experiment

SUMMARY The solution appraisal component of the inverse problem involves investigation of the relationship between our estimated model and the actual model. However, full appraisal is difficult for large 3-D problems such as electrical resistivity tomography (ERT). We tackle the appraisal problem for 3-D ERT via the point-spread functions (PSFs) of the linearized resolution matrix. The PSFs represent the impulse response of the inverse solution and quantify our parameter-specific resolving capability. We implement an iterative least-squares solution of the PSF for the ERT experiment, using on-the-fly calculation of the sensitivity via an adjoint integral equation with stored Green's functions and subgrid reduction. For a synthetic example, analysis of individual PSFs demonstrates the truly 3-D character of the resolution. The PSFs for the ERT experiment are Gaussian-like in shape, with directional asymmetry and significant off-diagonal features. Computation of attributes representative of the blurring and localization of the PSF reveal significant spatial dependence of the resolution with some correlation to the electrode infrastructure. Application to a time-lapse ground-water monitoring experiment demonstrates the utility of the PSF for assessing feature discrimination, predicting artefacts and identifying model dependence of resolution. For a judicious selection of model parameters, we analyse the PSFs and their attributes to quantify the case-specific localized resolving capability and its variability over regions of interest. We observe approximate interborehole resolving capability of less than 1–1.5 m in the vertical direction and less than 1–2.5 m in the horizontal direction. Resolving capability deteriorates significantly outside the electrode infrastructure.
Functional Characterization of ZBTB20 and the Role of ZBTB20-Dependent Transcription Regulation in Autism Spectrum Disorders and Intellectual Disability

ii DEDICATION . iv ACKNOWLEDGEMENTS . v LIST OF TABLES . x LIST OF FIGURES . xi PREFACE.1 CHAPTER 1: LITERATURE REVIEW.3 Introduction . 3 The physiological roles of mouse Zbtb20 . 8 ZBTB20 gene defects in neurodevelopmental disorders . 17 SUMOylationA post-translational modification . 23 The biological functions of SUMOylation . 29 References . 34
Computing Support for Problem Solving in Virtual Communities of Practice

The paper presents a formal model for a knowledge repository shared by members of a Virtual Community of Practice (VCPs), describes how the repository can be used to underpin collaborative problem solving, and how to build computer support for such processes. The repository comprises the resources used and developed by VCPs particularly through problem solving. As a case study, the paper illustrates how the problem solving process and the underlying repository can be applied in disaster prevention and handling. The repository and the process are formally described using the RAISE Specification Language.
Preliminary evidence that different mechanisms underlie the anger superiority effect in children with and without Autism Spectrum Disorders

Previous studies have demonstrated that angry faces capture humans' attention more rapidly than emotionally positive faces. This phenomenon is referred to as the anger superiority effect (ASE). Despite atypical emotional processing, adults and children with Autism Spectrum Disorders (ASD) have been reported to show ASE as well as typically developed (TD) individuals. So far, however, few studies have clarified whether or not the mechanisms underlying ASE are the same for both TD and ASD individuals. Here, we tested how TD and ASD children process schematic emotional faces during detection by employing a recognition task in combination with a face-in-the-crowd task. Results of the face-in-the-crowd task revealed the prevalence of ASE both in TD and ASD children. However, the results of the recognition task revealed group differences: In TD children, detection of angry faces required more configural face processing and disrupted the processing of local features. In ASD children, on the other hand, it required more feature-based processing rather than configural processing. Despite the small sample sizes, these findings provide preliminary evidence that children with ASD, in contrast to TD children, show quick detection of angry faces by extracting local features in faces.
Landmark-based Feature Tracking for Endoscopic Motion Analysis

Automated image analysis and interpretation within computer assisted minimally invasive surgery (MIS) most often depend and rely on manually defined landmarks, visible in endoscopic views. More specific, within many types of applications, such landmarks must be tracked automatically during the intervention. Typical feature tracking approaches are able to track slightly changing landmarks over time, as they occur in endoscopic image sequences, but are originally most often designed to track automatically detected salient points. In this contribution an approach is presented, where the advantages of feature descriptors and corresponding matchers can be used to track manually defined landmarks. Based on such initiated landmark points, local feature detection and tracking utilizing SURF or KLT features as descriptors, is executed. Within the region of interest as a constraint, movements of the detected features can be used to approximate the original landmark movements.
A Classification of Adjectives for Polarity Lexicons Enhancement

Subjective language detection is one of the most important challenges in Sentiment Analysis. Because of the weight and frequency in opinionated texts, adjectives are considered a key piece in the opinion extraction process. These subjective units are more and more frequently collected in polarity lexicons in which they appear annotated with their prior polarity. However, at the moment, any polarity lexicon takes into account prior polarity variations across domains. This paper proves that a majority of adjectives change their prior polarity value depending on the domain. We propose a distinction between domain dependent and domain independent adjectives. Moreover, our analysis led us to propose a further classification related to subjectivity degree: constant, mixed and highly subjective adjectives. Following this classification, polarity values will be a better support for Sentiment Analysis.
Efficient Identification Based on Human Iris Patterns

This paper proposes a person identification system (PID), which works with non-illumination low-resolution eye images. Radial-Scan and threshold methods are used for Iris normalization and Iris segmentation from the eye image respectively. Conventional neural network is used for iris matching. The proposed algorithm works with 96 features of the iris. Space complexity is less and Iris codes are stored in an encrypted file. The Algorithm has been implemented and tested on 1500 iris patterns. Images include normal iris captured under in-door and out-door conditions and from disease affected eyes.
The Beginnings and Prospective Ending of “End-to-End”

October 2001 The technology of “the Internet” is not static. Although its “end-to-end” architecture has made this “connection-less” communications system readily “extensible,” and highly encouraging to innovation both in hardware and software applications, there are strong pressures for engineering changes. Some of these are wanted to support novel transport services (e.g. voice telephony, real-time video); others would address drawbacks that appeared with opening of the Internet to public and commercial traffic – e.g., the difficulties of blocking delivery of offensive content, suppressing malicious actions (e.g. “denial of service” attacks), pricing bandwidth usage to reduce congestion. The expected gains from making “improvements” in the core of the network should be weighed against the loss of the social and economic benefits that derive from the “end-to-end” architectural design. Even where technological “fixes” can be placed at the networks’ edges, the option remains to search for alternative, institutional mechanisms of governing conduct in cyberspace. Working Papers Index
The dynamics of change and continuity in plural legal orders

AbstractThis paper introduces this Special Number. The work of the Project Group Legal Pluralism at the Max Planck Institute for Social Anthropology in Halle aims to continue the rapid expansion of recent decades of studies of legal pluralism. The recently much discussed phenomenon of globalisation has provoked a wide variety of local responses. Encounters are occurring between state laws, transnational laws, customary laws and religious laws, all of which are liable as a result to be transformed by processes of adaptation, appropriation and vulgarisation. This may lead to increasing pluralisation of laws, but can also in some cases produce homogenisation, or de-pluralisation.The notion of ‘law’ should not be limited to state, international and transnational law, but should be used to refer to all those objectified cognitive and normative conceptions for which validity for a certain social formation is authoritatively asserted. Law becomes manifest in many forms, and is comprised of a variety of social ph.
Toxicity of Superparamagnetic Iron Oxide Nanoparticles on Green Alga Chlorella vulgaris

Toxicity of superparamagnetic iron oxide nanoparticles (SPION) was investigated on Chlorella vulgaris cells exposed during 72 hours to Fe3O4 (SPION-1), Co0.2Zn0. 8Fe2O4 (SPION-2), or Co0.5Zn0. 5Fe2O4 (SPION-3) to a range of concentrations from 12.5 to 400 μg mL−1. Under these treatments, toxicity impact was indicated by the deterioration of photochemical activities of photosynthesis, the induction of oxidative stress, and the inhibition of cell division rate. In comparison to SPION-2 and -3, exposure to SPION-1 caused the highest toxic effects on cellular division due to a stronger production of reactive oxygen species and deterioration of photochemical activity of Photosystem II. This study showed the potential source of toxicity for three SPION suspensions, having different chemical compositions, estimated by the change of different biomarkers. In this toxicological investigation, algal model C. vulgaris demonstrated to be a valuable bioindicator of SPION toxicity.
Feasibility of low-cost microarray printing with inkjet printer

The methods of microarray fabrication are categorized as contact printing and non-contact printing according to spot formation techniques. In contact printing, a printing device does physical contact at the substrate while depositing biological sample. In contrast, non-contact printing involves no physical contact between the device and the substrate. In non-contact printing, inkjet printing technology is relatively flexible, simple and less expensive, also reduced contamination and higher throughput. For inkjet printing, however, need nozzles that can eject several pl (pico-litter) volumes and the position control of nozzle to eject ink with accurate position. These necessities complicate organization of the system that can fabricate microarray using inkjet method, and increase costs. Therefore, this paper proposes such a microarray fabrication methodology using a commercial inkjet printer that is already consisting of ink ejection system.
Quantized Coordination Algorithms for Rendezvous and Deployment

In this paper we study motion coordination problems for groups of robots that exchange information through a rate-constrained communication network. For one-dimensional rendezvous and deployment problems with communication path graphs, we propose an integrated control and communication scheme combining a logarithmic coder/decoder with linear coordination algorithms. We show that the closed-loop performance is comparable to that achievable in the quantization-free model: the time complexity is, asymptotically on the size of the network, unchanged, and the exponential convergence factor degrades smoothly as the quantization accuracy becomes coarser.
Predicting Participation Styles using Co-occurrence Patterns of Nonverbal Behaviors in Collaborative Learning

With the goal of assessing participant attitudes and group activities in collaborative learning, this study presents models of participation styles based on co-occurrence patterns of nonverbal behaviors between conversational participants. First, we collected conversations among groups of three people in a collaborative learning situation, wherein each participant had a digital pen and wore a glasses-type eye tracker. We then divided the collected multimodal data into 0.1-second intervals. The discretized data were applied to an unsupervised method to find co-occurrence behavioral patterns. As a result, we discovered 122 multimodal behavioral motifs from more than 3,000 possible combinations of behaviors by three participants. Using the multimodal behavioral motifs as predictor variables, we created regression models for assessing participation styles. The multiple correlation coefficients ranged from 0.74 to 0.84, indicating a good fit between the models and the data. A correlation analysis also enabled us to identify a smaller set of behavioral motifs (fewer than 30) that are statistically significant as predictors of participation styles. These results show that automatically discovered combinations of multiple kinds of nonverbal information with high co-occurrence frequencies observed between multiple participants as well as for a single participant are useful in characterizing the participant's attitudes towards the conversation.
Service-Oriented Measurement Infrastructure

The paradigm of service-oriented solutions (e.g. as SaaS) in the area of quality assurance seems to be a flexible innovative solution in order to support different high dynamic requirements in software measurement and evaluation. Otherwise many existing solutions are used in practice and must be migrated to such powerful infrastructures. This paper describes a general approach as service-oriented measurement infrastructure and shows a first practical solution as an example of flexible worldwide or in an intranet useable quality assurance application.
ADANN: automatic design of artificial neural networks

In this work an improvement of an initial approach to design Artificial Neural Networks to forecast Time Series is tackled, and the automatic process to design Artificial Neural Networks is carried out by a Genetic Algorithm. A key issue for these kinds of approaches is what information is included in the chromosome that represents an Artificial Neural Network. In this approach new information will be included into the chromosome so it will be possible to compare these results with those obtained in a previous approach. There are two principal ideas to take into account: first, the chromosome contains information about parameters of the topology, architecture, learning parameters, etc. of the Artificial Neural Network, i.e. Direct Encoding Scheme; second, the chromosome contains the necessary information so that a constructive method gives rise to an Artificial Neural Network topology (or architecture), i.e. Indirect Encoding Scheme. The results for a Direct Encoding Scheme (in order to compare with Indirect Encoding Schemes developed in future works) to design Artificial Neural Networks to forecast Time Series are shown.
Towards Structural Network Analysis

Structural network analysis is an intricate problem. In fact, the majority of techniques that have been developed so far are only applicable to investigate deterministic network models. This gives rise to develop novel graph-theoretical methods for applying them to more complex graphs and especially to statistically inferred networks. In this regard, we review methods for analyzing complex networks structurally putting the special emphasis on network partitioning and quantifying network complexity. Both areas are of general importance in structural graph theory as well as useful for exploring biological networks. Mathematics subject classification: 68R01, 68R10, 90B10, 92E10.
Adaptive Topic Tracking Research Based on Title Semantic Domain andDouble-state Model

Aiming at problems of sparse training corpora and topic excursion existing in topic detection and tracking, this paper examines twenty one most recent references and patents, proposes an adaptive topic tracking strategy based on title semantic domain topic model and double-state model. Title semantic domain topic model can enhance the title-centric semantic domain cohesion of reports, and reduce dimensions of reports' feature space effectively. The double-state strat- egy is a tracking technology based on the combination of static model and dynamic model: static model uses a given number of training reports to construct topic model which is the basis of topic tracking; dynamic model uses the sliding text window mechanism to capture new contents of a topic, remove outdated ones and reflect the changes of topic's focus in a timely manner. Experimental results show that the combination of double-state model tracking strategy and title se- mantic domain topic model can improve the performance of adaptive topic tracking system.
A parsimonious model of mobile partitioned networks with clustering

Mobile wireless networks frequently possess, at the same time, both dense and sparse regions of connectivity; for example, due to a heterogeneous node distribution or radio propagation environment. This paper is about modeling both the mobility and the formation of clusters in such networks, where nodes are concentrated in clusters of dense connectivity, interspersed with sparse connectivity. Uniformly dense and sparse networks have been extensively studied in the past, but not much attention has been devoted to clustered networks.