Miracle-dz/UniFAR-FTUs huggingface dataset:
eal-time automated spectral assessment of the BOLD response for eurofeedback at 3 and 7 T

Echo-planar imaging is the dominant functional MRI data acquisition scheme for evaluating the BOLD signal. To date, it remains the only approach providing neurofeedback from spatially localized brain activity. Real-time functional single-voxel proton spectroscopy (fSVPS) may be an alternative for spatially specific BOLD neurofeedback at 7 T because it allows for a precise estimation of the local T2* signal, EPI-specific artifacts may be avoided, and the signal contrast may increase. In order to explore and optimize this alternative neurofeedback approach, we tested fully automated real-time fSVPS spectral estimation procedures to approximate T2* BOLD signal changes from the unsuppressed water peak, i.e. lorentzian non-linear complex spectral fit (LNLCSF) in frequency and frequency-time domain. The proposed approaches do not require additional spectroscopic localizers in contrast to conventional T2* approximation based on linear regression of the free induction decay (FID). For methods comparison,
Interstitial and Interlayer Ion Diffusion Geometry Extraction in Graphitic Nanosphere Battery Materials

Large-scale molecular dynamics (MD) simulations are commonly used for simulating the synthesis and ion diffusion of battery materials. A good battery anode material is determined by its capacity to store ion or other diffusers. However, modeling of ion diffusion dynamics and transport properties at large length and long time scales would be impossible with current MD codes. To analyze the fundamental properties of these materials, therefore, we turn to geometric and topological analysis of their structure. In this paper, we apply a novel technique inspired by discrete Morse theory to the Delaunay triangulation of the simulated geometry of a thermally annealed carbon nanosphere. We utilize our computed structures to drive further geometric analysis to extract the interstitial diffusion structure as a single mesh. Our results provide a new approach to analyze the geometry of the simulated carbon nanosphere, and new insights into the role of carbon defect size and distribution in determining the charge capacity and charge dynamics of these carbon based battery materials.
Influence of perylenediimide–pyrene supramolecular interactions on the stability of DNA-based hybrids: Importance of electrostatic complementarity

Aromatic π–π stacking interactions are ubiquitous in nature, medicinal chemistry and materials sciences. They play a crucial role in the stacking of nucleobases, thus stabilising the DNA double helix. The following paper describes a series of chimeric DNA–polycyclic aromatic hydrocarbon (PAH) hybrids. The PAH building blocks are electron-rich pyrene and electron-poor perylenediimide (PDI), and were incorporated into complementary DNA strands. The hybrids contain different numbers of pyrene–PDI interactions that were found to directly influence duplex stability. As the pyrene–PDI ratio approaches 1:1, the stability of the duplexes increases with an average value of 7.5 °C per pyrene–PDI supramolecular interaction indicating the importance of electrostatic complementarity for aromatic π–π stacking interactions.
Regulation of PKC Mediated Signaling by Calcium during Visceral Leishmaniasis

Calcium is an ubiquitous cellular signaling molecule that controls a variety of cellular processes and is strictly maintained in the cellular compartments by the coordination of various Ca2+ pumps and channels. Two such fundamental calcium pumps are plasma membrane calcium ATPase (PMCA) and Sarco/endoplasmic reticulum calcium ATPase (SERCA) which play a pivotal role in maintaining intracellular calcium homeostasis. This intracellular Ca2+ homeostasis is often disturbed by the protozoan parasite Leishmania donovani, the causative organism of visceral leishmaniasis. In the present study we have dileneated the involvement of PMCA4 and SERCA3 during leishmaniasis. We have observed that during leishmaniasis, intracellular Ca2+ concentration was up-regulated and was further controlled by both PMCA4 and SERCA3. Inhibition of these two Ca2+-ATPases resulted in decreased parasite burden within the host macrophages due to enhanced intracellular Ca2+. Contrastingly, on the other hand, activation of PMCA4 was found to enhance the parasite burden. Our findings also highlighted the importance of Ca2+ in the modulation of cytokine balance during leishmaniasis. These results thus cumulatively suggests that these two Ca2+-ATPases play prominent roles during visceral leishmaniasis.
Mechanistic basis and clinical relevance of the role of transforming growth factor-β in cancer

Transforming growth factor-β (TGF-β) is a key factor in cancer development and progression. TGF-β can suppress tumorigenesis by inhibiting cell cycle progression and stimulating apoptosis in early stages of cancer progression. However, TGF-β can modulate cancer-related processes, such as cell invasion, distant metastasis, and microenvironment modification that may be used by cancer cells to their advantage in late stages. Corresponding mechanisms include angiogenesis promotion, anti-tumor immunity suppression, and epithelial-to-mesenchymal transition (EMT) induction. The correlation between TGF-β expression and cancer prognosis has also been extensively investigated. Results suggest that TGF-β pathway can be targeted to treat cancer; as such, the feasibility of this treatment is investigated in clinical trials.
Assessing the Fidelity of Ancient DNA Sequences Amplified From Nuclear Genes

To date, the field of ancient DNA has relied almost exclusively on mitochondrial DNA (mtDNA) sequences. However, a number of recent studies have reported the successful recovery of ancient nuclear DNA (nuDNA) sequences, thereby allowing the characterization of genetic loci directly involved in phenotypic traits of extinct taxa. It is well documented that postmortem damage in ancient mtDNA can lead to the generation of artifactual sequences. However, as yet no one has thoroughly investigated the damage spectrum in ancient nuDNA. By comparing clone sequences from 23 fossil specimens, recovered from environments ranging from permafrost to desert, we demonstrate the presence of miscoding lesion damage in both the mtDNA and nuDNA, resulting in insertion of erroneous bases during amplification. Interestingly, no significant differences in the frequency of miscoding lesion damage are recorded between mtDNA and nuDNA despite great differences in cellular copy numbers. For both mtDNA and nuDNA, we find significant positive correlations between total sequence heterogeneity and the rates of type 1 transitions (adenine → guanine and thymine → cytosine) and type 2 transitions (cytosine → thymine and guanine → adenine), respectively. Type 2 transitions are by far the most dominant and increase relative to those of type 1 with damage load. The results suggest that the deamination of cytosine (and 5-methyl cytosine) to uracil (and thymine) is the main cause of miscoding lesions in both ancient mtDNA and nuDNA sequences. We argue that the problems presented by postmortem damage, as well as problems with contamination from exogenous sources of conserved nuclear genes, allelic variation, and the reliance on single nucleotide polymorphisms, call for great caution in studies relying on ancient nuDNA sequences.
Speech Recognition Based on Support Vector Machine and Error Correcting Output Codes

A method is proposed based on application of Error Correcting Output Codes Support Vector Machine (ECOC-SVM) in order to get better results of speech recognition. Some uncorrelated SVMs are constructed based on ECOC matrix codes to improve the integrated performance of fault tolerance of classification model. This paper gives four commonly-used encodings of ECOC. By comparing the results with that of speech recognition based on HMM, the experiments indicate that the ECOC method is more suitable for speech recognition, among which the predicting accuracy of one-versus-one is the highest of all.
Genetic and Functional Analysis of the Biosynthesis of a Non-Ribosomal Peptide Siderophore in Burkholderia xenovorans LB400

B. xenovorans LB400 is a model bacterium for the study of the metabolism of aromatic compounds. The aim of this study was the genomic and functional characterization of a non-ribosomal peptide synthetase containing gene cluster that encodes a siderophore in B. xenovorans LB400. The mba gene cluster from strain LB400 encodes proteins involved in the biosynthesis and transport of a hydroxamate-type siderophore. Strain LB400 has a unique mba gene organization, although mba gene clusters have been observed in diverse Burkholderiales. Bioinformatic analysis revealed the presence of promoters in the mba gene cluster that strongly suggest regulation by the ferric uptake regulator protein (Fur) and by the alternative RNA polymerase extracytoplasmic function sigma factor MbaF. Reverse transcriptase PCR analyses showed the expression of iron-regulated transcriptional units mbaFGHIJKL, mbaN, mbaABCE, mbaO, mbaP and mbaD genes under iron limitation. Chrome azurol S (CAS) assay strongly suggests that strain LB400 synthesized a siderophore under iron limitation. Mass spectrometry ESI-MS and MALDI-TOF-MS analyses revealed that the siderophore is a non-ribosomal peptide, and forms an iron complex with a molecular mass of 676 Da. Based on bioinformatic prediction, CAS assay and MS analyses, we propose that the siderophore is L-Nδ-hydroxy-Nδ-formylOrn-D-β-hydroxyAsp-L-Ser-L-Nδ-hydroxy-Nδ-formylOrn-1,4-diaminobutane that is closely related to malleobactin-type siderophores reported in B. thailandensis.
Fast parallel image reconstruction using smacker for functional magnetic resonance imaging

SMACKER is a method of calculating sensitivity maps from k-space reconstruction coefficients using only a few lines of inner k-space. In this method the problem of sensitivities ending at object boundaries is eliminated, unlike in other established methods. The method allows for the rapid calculation of sensitivity profiles from images, and it is proposed here that the approach can be used in functional MRI to obtain reconstructed images in little time. Functional MRI relying on fast parallel reconstruction techniques naturally lends itself to a method that can generate and use sensitivity maps directly from images.
Patch Volumes : Multiple Fusion Volumes for Consistent RGB-D Modeling

Recent advances have allowed for the creation of dense, accurate 3D maps of indoor environments using RGB-D cameras. Some techniques are able to create large-scale maps, while others focus on accurate details using GPU-accelerated volumetric representations. In this work we describe patch volumes, a novel multiple-volume representation which enables the creation of globally consistent maps of indoor environments beyond the capabilities of previous high-accuracy volumetric representations.
Asymmetric flux models for particle-size segregation in granular avalanches

Abstract Particle-size segregation commonly occurs in both wet and dry granular free-surface flows through the combined processes of kinetic sieving and squeeze expulsion. As the granular material is sheared downslope, the particle matrix dilates slightly and small grains tend to percolate down through the gaps, because they are more likely than the large grains to fit into the available space. Larger particles are then levered upwards in order to maintain an almost uniform solids volume fraction through the depth. Recent experimental observations suggest that a single small particle can percolate downwards through a matrix of large particles faster than a large particle can be levered upwards through a matrix of fines. In this paper, this effect is modelled by using a flux function that is asymmetric about its maximum point, differing from the symmetric quadratic form used in recent models of particle-size segregation. For illustration, a cubic flux function is examined in this paper, which can be either a convex or a non-convex function of the small-particle concentration. The method of characteristics is used to derive exact steady-state solutions for non-diffuse segregation in two dimensions, with an inflow concentration that is (i) homogeneous and (ii) normally graded, with small particles above the large. As well as generating shocks and expansion fans, the new asymmetric flux function generates semi-shocks, which have characteristics intersecting with the shock just from one side. In the absence of diffusive remixing, these can significantly enhance the distance over which complete segregation occurs.
Sacrificial Ionic Bonds Need To Be Randomly Distributed To Provide Shear Deformability

Multivalent ions are known to allow for reversible cross-linking in soft biological materials, providing stiffness and extensibility via sacrificial bonds. We present a simple model where stiff nanoscale elements carrying negative charges are coupled in shear by divalent mobile cations in aqueous media. Such a shear coupling through a soft glue has, indeed, been proposed to operate in biological nanocomposites. While the coupling is elastic and brittle when the negative charges are periodically arranged, sufficient randomness in their distribution allows for large irreversible deformation.
Generalization of Object Manipulation Skills Learned without Limb Motion

Recent work suggests that human subjects may learn mappings between object motion and exerted torque during manipulation of freely pivoting or unstable objects. In the present work, we studied an object manipulation task involving no arm movement to determine how subjects internally represent the force—motion relationship of an object during a skilled manipulation task. Human subjects learned to balance a simulated inverted pendulum. The simulation was controlled by pressing on a fixed force sensor, and applied forces resulted in motion of the simulated pendulum on a computer screen according to its equation of motion. Each subject initially learned the task in one arm posture and was tested 1 d later in a new arm posture. In one test condition, the effects of arm torque were matched to the original task, and in the other test condition, the simulation was unchanged. The pattern of skill transfer to different arm postures suggested that subjects had learned joint torque responses rather than a general model of the object interface forces. A second experiment showed that the advantage of training with matched arm torques was object specific, because torque-matched training on a tracking task involving similar forces was not a substitute for training in the balancing task.
Human Action Recognition from Boosted Pose Estimation

This paper presents a unified framework for recognizing human action in video using human pose estimation. Due to high variation of human appearance and noisy context background, accurate human pose analysis is hard to achieve and rarely employed for the task of action recognition. In our approach, we take advantage of the current success of human detection and view invariability of local feature-based approach to design a pose-based action recognition system. We begin with a frame-wise human detection step to initialize the search space for human local parts, then integrate the detected parts into human kinematic structure using a tree structural graphical model. The final human articulation configuration is eventually used to infer the action class being performed based on each single part behavior and the overall structure variation. In our work, we also show that even with imprecise pose estimation, accurate action recognition can still be achieved based on informative clues from the overall pose part configuration. The promising results obtained from action recognition benchmark have proven our proposed framework is comparable to the existing state-of-the-art action recognition algorithms.
Gard – An Intelligent System for Distributed Exploration of Landmine Fields Simulated by a Team of Khepera Robots

It is absolutely clear that state-of-the-art robots cannot undertake the whole procedure of terrorist bombs neutralization, unexploded ordnances clean up and minefield demining in many environmental situations, such as urban areas, but the main force toward building of a robotic system in these dangerous tasks is to reduce the human presence. The study of robots for demining applications is indeed a scientifically challenging problem that offers wide possibilities of expanding the actual knowledge on several areas of robotics, ranging from localization devices to visual guidance systems, and from navigation on rough terrain to multi-agent co-operation. The GPS and SLAM methods are the most efficient tools for a robot localization and mapping. Their extension for a group of mobile robots is of an exceptional importance for the successful creation of the “landmines map”. In this paper a co-operative localization algorithm using three mobile robots equipped with localization capabilities for detecting each other has been simulated and tested. Further, navigation algorithms for a colony of mobile robots are proposed. Results demonstrate the localization algorithm applicability, where with a low precision and restricted range, the odometry errors, which normally present problems for mapping, are severely reduced. The simulations show that under certain conditions, successful localization is only possible if the team of multiple robots collaborate during localization by communication and data transferring.
Throughput Improvement in Two Dimensional Underwater Acoustic Networks by Interference Alignment

Link propagation delay has been shown theoretically to allow network throughput to exceed the channel capacity, a network with N links being limited to a total data rate of N/2 times the channel capacity. However this has not been confirmed by simulation or demonstration. We show by simulations of the 2D and 3D network scenarios proposed in the original theory that the throughput in a N-link network with large propagation delay can reach N/2 times that achievable in negligible propagation delay networks. In addition we show that the maximum throughput boundaries (N/2) for any number of links can be approached in two dimensional networks with simplex nodes, relaxing the half-duplex case and the need for scaling with the number of spatial dimensions anticipated in existing theory. We also demonstrate this via simulations of appropriate network geometries.
Segmentation-free MRF Recognition Method in Combination with P2DBMN-MQDF for Online Handwritten Cursive Word (パターン認識・メディア理解)

This paper describes an online handwritten English cursive word recognition method using a segmentation-free Markov random field (MRF) model in combination with an offline recognition method which uses pseudo 2D bi-moment normalization (P2DBMN) and modified quadratic discriminant function (MQDF). It extracts feature points along the pen-tip trace from pen-down to pen-up and uses the feature point coordinates as unary features and the differences in coordinates between the neighboring feature points as binary features. Each character is modeled as a MRF and word MRFs are constructed by concatenating character MRFs according to a trie lexicon of words during recognition. Our method expands the search space using a character-synchronous beam search strategy to search the segmentation and recognition paths. This method restricts the search paths from the trie lexicon of words and preceding paths, as well as the lengths of feature points during path search. Moreover, we combine it with a P2DBMN-MQDF recognizer that is widely used for Chinese and Japanese character recognition. Keyword Word Recognition, Segmentation-free, Markov Random Field, Modified Quadratic Discriminant Function, Trie Lexicon, Beam Search
Top-Down Analysis for Bottom-Up Development

Component-based software engineering (CBSE) is the construction of software systems from software components. Software components are independently deployable units of executable code that can be assembled into a system based on their externally visible properties, which are made available to system developers via the components interface specifications. Software components provide a means for large-scale reuse of intellectual property as well as coding, testing, and analysis effort. Benefits expected from developing an industry in CBSE include: reduced system development and maintenance costs, reduced time-to-market, and the availability of a marketplace of components that are bought and sold in massive quantities much like any other product. Component-based systems are constructed from a blend of locally developed and commercially available pieces enabling incremental development of complex systems. However, the full potential for software component reuse and a component marketplace can only be realized if tools and techniques are available to support the development and maintenance of these systems [2]. In this paper we address the specific problem of creating analytic assets, i.e. assets that summarize information about components that is required for compositional analysis. As a first step toward being able to create the analytic assets needed for component-based systems, we describe our in identifying and packaging analytic assets for program procedures for use in compositional program analysis.
The Impact of Misalignment of Organizational Structure and Product Architecture on Quality in Complex Product Development

Product architecture and organizational communication play significant roles in complex product development efforts. By using networks to characterize both product structure and communication patterns, we examine the impact of mismatches between these on new product development (NPD) performance. Specifically, we study the vehicle development process of a major auto company and use vehicle quality (warranty repairs) as our NPD performance metric. Our empirical results indicate that centrality in a product architecture network is related to quality according to an inverted-U relationship, which suggests that vehicle subsystems of intermediate complexity exhibit abnormally high levels of quality problems. To identify specific subsystems in danger of excessive quality problems, we characterize mismatches between product architecture and organizational structure by defining a new metric, called coordination deficit, and show that it is positively associated with quality problems. These results deepen our understanding of the impact of organizational structure and product architecture on the NPD process and provide tools with which managers can diagnose and improve their NPD systems.
Conflicts, Compromises, and Political Decisions: Methodological Challenges of Enterprise-Wide E-Business Architecture Creation

This article describes the architecture development process in an international ICT company, which is building a comprehensive e-business system for its customers. The implementation includes the integration of data and legacy systems from independent business units and the construction of a uniform Web-based customer interface. We followed the early process of architecture analysis and definition over a year. The research focuses on the creation of e-business architecture and observes that instead of guided by a prescribed method, the architecture emerges through somewhat non-deliberate actions obliged by the situation and its constraints, conflicts, compromises, and political decisions. The interview-based qualitative data is analyzed using grounded theory and a coherent story explaining the situation and its forces is extracted. Conclusions are drawn from the observations and possibilities and weaknesses of the support that UML and RUP provide for the process are pointed out.