Miracle-dz/UniFAR-FTUs huggingface dataset:
Fuzzy OLAP association rules mining-based modular reinforcement learning approach for multiagent systems

Multiagent systems and data mining have recently attracted considerable attention in the field of computing. Reinforcement learning is the most commonly used learning process for multiagent systems. However, it still has some drawbacks, including modeling other learning agents present in the domain as part of the state of the environment, and some states are experienced much less than others, or some state-action pairs are never visited during the learning phase. Further, before completing the learning process, an agent cannot exhibit a certain behavior in some states that may be experienced sufficiently. In this study, we propose a novel multiagent learning approach to handle these problems. Our approach is based on utilizing the mining process for modular cooperative learning systems. It incorporates fuzziness and online analytical processing (OLAP) based mining to effectively process the information reported by agents. First, we describe a fuzzy data cube OLAP architecture which facilitates effective storage and processing of the state information reported by agents. This way, the action of the other agent, not even in the visual environment of the agent under consideration, can simply be predicted by extracting online association rules, a well-known data mining technique, from the constructed data cube. Second, we present a new action selection model, which is also based on association rules mining. Finally, we generalize not sufficiently experienced states, by mining multilevel association rules from the proposed fuzzy data cube. Experimental results obtained on two different versions of a well-known pursuit domain show the robustness and effectiveness of the proposed fuzzy OLAP mining based modular learning approach. Finally, we tested the scalability of the approach presented in this paper and compared it with our previous work on modular-fuzzy Q-learning and ordinary Q-learning.
Analysis of an Outpatient Consultation Network in a Veterans Administration Health Care System Hospital

Many healtcare organizations face the challenge of scaling up effective health care delivery. There is a growing agreement that a better understanding of the structure of the healthcare system is needed to achieve that goal. Networks analysis provides the formal framework of thought to understand such systems. Given the definition of health care system as as a network of actors who aim to provide health care, the links to network anlysis is made very clear [1]. The network can be an integrated delivery system, a centrally controlled multi-hospital system or a virtual system composed of many partners like the one we observe in tele-health. In the healthcare community there is a growing interest in the understanding of the relationship between the structure of a healthcare network and care delivery. In this regard network analysis provides the intellectual framework to reason on issues of outcomes and cost but more importantly that of scale (i.e. different healthcare delivery regions) as it allows to capture the complexity of structure (medical/non-medical providers, private/public insurers etc.) and dynamics of healthcare on any scale in a rigorous manner.
Novel directory service and message delivery mechanism enabling scalable mobile agent communication

Mobile agent technology has emerged as a promising programming paradigm for developing highly dynamic and large-scale service-oriented computing middlewares due to its desirable features. For this purpose, first of all, scalable location-transparent agent communication issue should be addressed in mobile agent systems despite agent mobility. Although there were proposed several directory service and message delivery mechanisms, their disadvantages force them not to be appropriate to both low-overhead location management and fast delivery of messages to agents migrating frequently. To mitigate their limitations, this paper presents a scalable distributed directory service and message delivery mechanism. The proposed mechanism enables each mobile agent to autonomously leave tails of forwarding pointers on some few of its visiting nodes depending on its preferences. This feature results in low message forwarding overhead and low storage and maintenance cost of increasing chains of pointers per host. Also, keeping mobile agent location information in the effective binding cache of each sending agent, the sending agent can communicate with mobile agents much faster compared with the existing ones.
Production and measurements of isolated single-wall carbon nanotubes

The production of isolated single wall carbon nanotubes (SWNTs) is accomplished using the laser oven process. Material is collected on quartz substrates at different locations in the laser oven for a variety of flow conditions. The lengths and diameter distributions of the nanotubes are measured directly (without additional processing steps) using AFM. Preliminary Raman data taken using 2D scans indicate the feasibility of this technique for length and diameter determination. The AFM study indicated the formation of long individual nanotubes, which then seem to coalesce into bigger bundles. The role of the inner tube of the flow-tube set up is confirmed to improve interactions between SWNTs resulting in formation of bundles. Flowing buffer gas seems to influence the dispersion of particulate material in the nanotube product.
3D spatial self-organization of a modular artificial skin

In this paper, we present a new approach to spatially self-organize a modular artificial skin in 3D space. We were motivated by the demand to efficiently and automatically acquire the position and orientation of a steadily growing number of artificial skin sensor elements. Here, we combine our 3D surface reconstruction algorithm for individual patches of artificial skin, with a common active visual marker approach. Light emitting diodes, built into every element of our modular artificial skin, enable us to turn each reconstructed patch of skin into an active 6 DoF visual marker. With the help of a calibrated monocular camera, we can then estimate the homogeneous transformations between multiple, at least partially visible skin patches e.g. when distributed on the body of a robot. Our approach allows to quickly combine distributed tactile and visual coordinate systems into one homogeneous rigid body representation. We demonstrate the robustness of our approach by calibrating several patches mounted on a robot arm using only a standard web-cam.
Dendro-dendritic bundling and shared synapses between gonadotropin-releasing hormone neurons

The pulsatile release of gonadotropin-releasing hormone (GnRH) is critical for mammalian fertility, but the mechanisms underlying the synchronization of GnRH neurons are unknown. In the present study, the full extent of the GnRH neuron dendritic tree was visualized by patching and filling individual GnRH neurons with biocytin in acute brain slices from adult GnRH-green fluorescent protein (GFP) transgenic mice. Confocal analysis of 42 filled GnRH neurons from male and female adult mice revealed that the dendrites of the great majority of GnRH neurons (86%) formed multiple close appositions with dendrites of other GnRH neurons. Two types of interactions were encountered; the predominant interaction was one of vertical dendritic bundling where dendrites were found to wrap around each other in the same axis. The other interaction was one in which a GnRH neuron dendrite intercepted other GnRH neuron dendrites in a perpendicular fashion. Electron microscopy using pre-embedded, silver-enhanced immunogold labeling for both GnRH and GFP peptides in GnRH-GFP transgenic mice, confirmed that GnRH neuron dendrites were often immediately juxtaposed. Membrane specializations, including punctae and zonula adherens, were found connecting adjacent dendritic elements of GnRH neurons. Remarkably, individual afferent axon terminals were found to synapse with multiple GnRH neuron dendrites at sites of bundling. Together, these data demonstrate that GnRH neurons are not isolated from one another but, rather, interconnected via their long dendritic extensions. The observation of shared synaptic input to bundled GnRH neuron dendrites suggests a mechanism of GnRH neuron synchronization.
Comparison of uncertainty representations for missing data in information retrieval

The aim of this paper is to assess the impact of the uncertainty representation for retrieving items with missing data. The problem of information retrieval from incomplete incident databases is addressed in this paper. After a brief survey on the problem of missing data with an emphasis on the information retrieval application, we propose a novel approach for retrieving case records with missing data. The general idea of the proposed data driven approach is to model the uncertainty pertaining to this missing data. We chose the general model of belief functions as it encompasses as special cases both classical and probability models. Several uncertainty models are then compared based on (1) an expressiveness criterion (non-specificity or randomness) and (2) objective measures of performance typical to the Information Retrieval domain. The results are illustrated on several datasets and a simulation controlled missing data mechanism.
Structure-Preserving Difference Search for XML Documents

Current XML differencing applications usually try to find a minimal sequence of edit operations that transform one XML document to another XML document (the so-called "edit script"). In our conviction, this approach often produces increments that are unintuitive for human readers and do not reflect the actual changes. We therefore propose in this article a different approach trying to maximize the retained structure instead of minimizing the edit sequence. Structure is thereby not limited to the usual tree structure of XML any kind of structural relations can be considered (like parent-child, ancestordescendant, sibling, document order). In our opinion, this approach is very flexible and able to adapt to the user's requirements. It produces more readable results while still retaining a reasonably small edit sequence. Structure-Preserving Difference Search for XML Documents Table of
Genomic Plasticity and the Diversity of Polyploid Plants

Polyploidy, a change whereby the entire chromosome set is multiplied, arises through mitotic or meiotic misdivisions and frequently involves unreduced gametes and interspecific hybridization. The success of newly formed angiosperm polyploids is partly attributable to their highly plastic genome structure, as manifested by tolerance to changing chromosome numbers (aneuploidy and polyploidy), genome size, (retro)transposable element mobility, insertions, deletions, and epigenome restructuring. The ability to withstand large-scale changes, frequently within one or a few generations, is associated with a restructuring of the transcriptome, metabolome, and proteome and can result in an altered phenotype and ecology. Thus, polyploid-induced changes can generate individuals that are able to exploit new niches or to outcompete progenitor species. This process has been a major driving force behind the divergence of the angiosperms and their biodiversity.
Distributed reinforcement learning for a traffic engineering application

In this paper, the authors describe how a distributed reinforcement learning problem, in which the returns of many agents are simultaneously updating a single shared policy, is addressed by applying novel reinforcement learning techniques. A traffic simulator is used in the learning process. Two new algorithms are introduced: a value function-based algorithm and one that uses a direct policy evaluation approach. Both algorithms are shown to perform comparably well.
Body-selective areas in the visual cortex are less active in children than in adults

Our ability to read other people’s non-verbal signals gets refined throughout childhood and adolescence. How this is paralleled by brain development has been investigated mainly with regards to face perception, showing a protracted functional development of the face-selective visual cortical areas. In view of the importance of whole-body expressions in interpersonal communication it is important to understand the development of brain areas sensitive to these social signals. Here we used functional magnetic resonance imaging (fMRI) to compare brain activity in a group of 24 children (age 6–11) and 26 adults while they passively watched short videos of body or object movements. We observed activity in similar regions in both groups; namely the extra-striate body area (EBA), fusiform body area (FBA), posterior superior temporal sulcus (pSTS), amygdala and premotor regions. Adults showed additional activity in the inferior frontal gyrus (IFG). Within the main body-selective regions (EBA, FBA and pSTS), the strength and spatial extent of fMRI signal change was larger in adults than in children. Multivariate Bayesian (MVB) analysis showed that the spatial pattern of neural representation within those regions did not change over age. Our results indicate, for the first time, that body perception, like face perception, is still maturing through the second decade of life.
Coordinated Activation of Candidate Proto-Oncogenes and Cancer Testes Antigens via Promoter Demethylation in Head and Neck Cancer and Lung Cancer

Background Epigenetic alterations have been implicated in the pathogenesis of solid tumors, however, proto-oncogenes activated by promoter demethylation have been sporadically reported. We used an integrative method to analyze expression in primary head and neck squamous cell carcinoma (HNSCC) and pharmacologically demethylated cell lines to identify aberrantly demethylated and expressed candidate proto-oncogenes and cancer testes antigens in HNSCC. Methodology/Principal Findings We noted coordinated promoter demethylation and simultaneous transcriptional upregulation of proto-oncogene candidates with promoter homology, and phylogenetic footprinting of these promoters demonstrated potential recognition sites for the transcription factor BORIS. Aberrant BORIS expression correlated with upregulation of candidate proto-oncogenes in multiple human malignancies including primary non-small cell lung cancers and HNSCC, induced coordinated proto-oncogene specific promoter demethylation and expression in non-tumorigenic cells, and transformed NIH3T3 cells. Conclusions/Significance Coordinated, epigenetic unmasking of multiple genes with growth promoting activity occurs in aerodigestive cancers, and BORIS is implicated in the coordinated promoter demethylation and reactivation of epigenetically silenced genes in human cancers.
High‐density molecular characterization and association mapping in Ethiopian durum wheat landraces reveals high diversity and potential for wheat breeding

Summary Durum wheat (Triticum turgidum subsp. durum) is a key crop worldwide, and yet, its improvement and adaptation to emerging environmental threats is made difficult by the limited amount of allelic variation included in its elite pool. New allelic diversity may provide novel loci to international crop breeding through quantitative trait loci (QTL) mapping in unexplored material. Here, we report the extensive molecular and phenotypic characterization of hundreds of Ethiopian durum wheat landraces and several Ethiopian improved lines. We test 81 587 markers scoring 30 155 single nucleotide polymorphisms and use them to survey the diversity, structure, and genome‐specific variation in the panel. We show the uniqueness of Ethiopian germplasm using a siding collection of Mediterranean durum wheat accessions. We phenotype the Ethiopian panel for ten agronomic traits in two highly diversified Ethiopian environments for two consecutive years and use this information to conduct a genome‐wide association study. We identify several loci underpinning agronomic traits of interest, both confirming loci already reported and describing new promising genomic regions. These loci may be efficiently targeted with molecular markers already available to conduct marker‐assisted selection in Ethiopian and international wheat. We show that Ethiopian durum wheat represents an important and mostly unexplored source of durum wheat diversity. The panel analysed in this study allows the accumulation of QTL mapping experiments, providing the initial step for a quantitative, methodical exploitation of untapped diversity in producing a better wheat.
Automated Detection and Segmentation of Vascular Structures of Skin Lesions Seen in Dermoscopy, With an Application to Basal Cell Carcinoma Classification

Blood vessels are important biomarkers in skin lesions both diagnostically and clinically. Detection and quantification of cutaneous blood vessels provide critical information toward lesion diagnosis and assessment. In this paper, a novel framework for detection and segmentation of cutaneous vasculature from dermoscopy images is presented and the further extracted vascular features are explored for skin cancer classification. Given a dermoscopy image, we segment vascular structures of the lesion by first decomposing the image using independent-component analysis into melanin and hemoglobin components. This eliminates the effect of pigmentation on the visibility of blood vessels. Using k-means clustering, the hemoglobin component is then clustered into normal, pigmented, and erythema regions. Shape filters are then applied to the erythema cluster at different scales. A vessel mask is generated as a result of global thresholding. The segmentation sensitivity and specificity of 90% and 86% were achieved on a set of 500 000 manually segmented pixels provided by an expert. To further demonstrate the superiority of the proposed method, based on the segmentation results, we defined and extracted vascular features toward lesion diagnosis in basal cell carcinoma (BCC). Among a dataset of 659 lesions (299 BCC and 360 non-BCC), a set of 12 vascular features are extracted from the final vessel images of the lesions and fed into a random forest classifier. When compared with a few other state-of-art methods, the proposed method achieves the best performance of 96.5% in terms of area under the curve (AUC) in differentiating BCC from benign lesions using only the extracted vascular features.
MICROSTRUCTURAL STUDIES OF PASTA AND STARCH PASTA

The processing methods for mung bean starch noodles were used to form “starch pasta” from various isolated wheat starches. The objective of this research was to evaluate the changes in the surface and internal structure of pasta and “starch pasta” made from various flours and wheat starch before and after cooking. Cooked “starch pasta” revealed a honeycomb-like internal structure similar to cooked pasta when viewed by scanning electron microscopy (SEM). The honeycomb-like structure of cooked pasta is mainly due to the coagulated protein embedded in the gelatinized starch. Swelling of cooked pasta is mainly due to the hydration and coagulation of protein rather than the gelatinized starch. The diameter of cooked starch pasta does not increase as much as that of cooked pasta. A fibrillar protein network of high cooking quality pasta was enveloped in a gelatinized starch, whereas low cooking quality products contained more diffuse gelatinized starch in a less extensive protein framework. Determination of pasta cooking quality was more dependent on a continuous protein network than the physicochemical properties of the gelatinized starch. In the absence of coagulated protein “starch pasta” strands fractured into small pieces and did not swell. This was in contrast to the pasta made from flour or durum wheat semolina which became swollen after 20 minutes of cooking.
DIVA: A Dynamic Approach to Microprocessor Verification

Building a high-performance microprocessor presents many reliability challenges. Designers must verify the correctness of large complex systems and construct implementations that work reliably in varied (and occasionally adverse) operating conditions. To further complicate this task, deep submicron fabrication technologies present new reliability challenges in the form of degraded signal quality and logic failures caused by natural radiation interference. In this paper, we introduce dynamic veri cation, a novel microarchitectural technique that can signi cantly reduce the burden of correctness in microprocessor designs. The approach works by augmenting the commit phase of the processor pipeline with a functional checker unit. The functional checker veri es the correctness of the core processor's computation, permitting only correct results to commit. In the event of an incorrect result, the checker xes the error and ushes any incorrect results from the core using the existing speculation recovery mechanism. Overall design costs can be dramatically reduced because designers need only verify the correctness of the checker unit. The core processor need not be fully correct, only suÆciently correct that its errors do not adversely a ect performance. We detail the DIVA checker architecture, a design optimized for simplicity and low cost. Using detailed timing simulation, we show that even resource-frugal DIVA checkers have little impact on core processor performance. To make the case for reduced veri cation costs, we argue that the DIVA checker should lend itself to functional and electrical veri cation better than a complex core processor. Finally, future applications of dynamic veri cation are suggested.
A NAC transcription factor and SNI1 cooperatively suppress basal pathogen resistance in Arabidopsis thaliana

Transcriptional repression of pathogen defense-related genes is essential for plant growth and development. Several proteins are known to be involved in the transcriptional regulation of plant defense responses. However, mechanisms by which expression of defense-related genes are regulated by repressor proteins are poorly characterized. Here, we describe the in planta function of CBNAC, a calmodulin-regulated NAC transcriptional repressor in Arabidopsis. A T-DNA insertional mutant (cbnac1) displayed enhanced resistance to a virulent strain of the bacterial pathogen Pseudomonas syringae DC3000 (PstDC3000), whereas resistance was reduced in transgenic CBNAC overexpression lines. The observed changes in disease resistance were correlated with alterations in pathogenesis-related protein 1 (PR1) gene expression. CBNAC bound directly to the PR1 promoter. SNI1 (suppressor of nonexpressor of PR genes1, inducible 1) was identified as a CBNAC-binding protein. Basal resistance to PstDC3000 and derepression of PR1 expression was greater in the cbnac1 sni1 double mutant than in either cbnac1 or sni1 mutants. SNI1 enhanced binding of CBNAC to its cognate PR1 promoter element. CBNAC and SNI1 are hypothesized to work as repressor proteins in the cooperative suppression of plant basal defense.
A Lightweight Architecture for Secure Two-Party Mobile Payment

The evolution of wireless networks and mobile devices has resulted in increased concerns about performance and security of mobile payment systems. In this paper we propose SA2pMP, a lightweight secured architecture for two-party mobile payments. SA2pMP employs a lightweightcryptography scheme that combines public key and symmetric key cryptography systems (ECDSA and AES), as well as a multi-factor authentication mechanism. These are coupled with a transaction log strategy to satisfy the properties of confidentiality, authentication, integrity and nonrepudiation. We simulate SA2pMP in a context of money transfer banking transaction, on three different emulators:Sun Java Wireless Toolkit 2.5. 2 for CLDC emulator, Sony Ericsson SDK 2.5. 0.3 Z800 emulator, and Nokia S60 3rd Edition emulator. We also compare SA2pMP to some existing mobile payment platforms. The result of simulation and comparison proves that SA2pMP is a lightweight secured mechanism that is feasible and suitable for two-party mobile payment transactions, e.g. mobile banking, over Java ME enabled, resource-limited mobile devices.