Miracle-dz/UniFAR-FTUs huggingface dataset:
An energy-efficient reconfigurable circuit-switched network-on-chip

Network-on-chip (NoC) is an energy-efficient on-chip communication architecture for multi-tile system-on-chip (SoC) architectures. The SoC architecture, including its run-time software, can replace inflexible ASICs for future ambient systems. These ambient systems have to be flexible as well as energy-efficient. To find an energy-efficient solution for the communication network we analyze three wireless applications. Based on their communication requirements we observe that revisiting of the circuit switching techniques is beneficial. In this paper we propose a new energy-efficient reconfigurable circuit-switched network-on-chip. By physically separating the concurrent data streams we reduce the overall energy consumption. The circuit-switched router has been synthesized and analyzed for its power consumption in 0.13 /spl mu/m technology. A 5-port circuit-switched router has an area of 0.05 mm/sup 2/ and runs at 1075 MHz. The proposed architecture consumes 3.5 times less energy compared to its packet-switched equivalent.
Efemp1 and p27Kip1 modulate responsiveness of pancreatic cancer cells towards a dual PI3K/mTOR inhibitor in preclinical models

Pancreatic ductal adenocarcinoma (PDAC) remains a dismal disease with a poor prognosis and targeted therapies have failed in the clinic so far. Several evidences point to the phosphatidylinositol 3-kinase (PI3K)-mTOR pathway as a promising signaling node for targeted therapeutic intervention. Markers, which predict responsiveness of PDAC cells towards PI3K inhibitors are unknown. However, such markers are needed and critical to better stratify patients in clinical trials. We used a large murine KrasG12D- and PI3K (p110αH1047R)-driven PDAC cell line platform to unbiased define modulators of responsiveness towards the dual PI3K-mTOR inhibitor Bez235. In contrast to other tumor models, we show that KrasG12D- and PI3K (p110αH1047R)-driven PDAC cell lines are equally sensitive towards Bez235. In an unbiased approach we found that the extracellular matrix protein Efemp1 controls sensitivity of murine PDAC cells towards Bez235. We show that Efemp1 expression is connected to the cyclin-dependent kinase inhibitor p27Kip1. In a murine KrasG12D- driven PDAC model, p27Kip1 haploinsufficiency accelerates cancer development in vivo. Furthermore, p27Kip1 controls Bez235 sensitivity in a gene dose-dependent fashion in murine PDAC cells and lowering of p27Kip1 decreases Bez235 responsiveness in murine PDAC models. Together, we define the Efemp1-p27Kip1 axis as a potential marker module of PDAC cell sensitivity towards dual PI3K-mTOR inhibitors, which might help to better stratify patients in clinical trials.
Infarct-related artery occlusion, tissue markers of ischaemia, and increased apoptosis in the peri-infarct viable myocardium.

AIMS Unfavourable cardiac remodelling often complicates acute myocardial infarction (AMI) as a result of increased cardiomyocyte apoptosis. It is currently unclear whether ongoing or recurrent ischaemia is an independent determinant for increased apoptosis in peri-infarct viable myocardium. METHODS AND RESULTS In order to assess the link between infarct-related artery (IRA) occlusion, ischaemia, and apoptosis, 30 subjects dying 7-120 days after AMI (16 with IRA occlusion and 14 with patent IRA) and five control subjects were selected at autopsy. Cardiomyocytes were defined as apoptotic if co-expressing TUNEL and activated caspase-3. Expression of both hypoxia-inducible factor-1 and cyclo-oxygenase-2 was assessed in the peri-infarct myocardium and considered as tissue markers of ischaemia. Evidence of ischaemia was significantly more frequent in cases with IRA occlusion (53%) than in cases with patent IRA (15%) or control hearts (0%, P=0.026). The finding of IRA occlusion and markers of ischaemia identified cases with higher apoptotic rates (ARs) in the peri-infarct viable myocardium [12.2% (8.2-14.0), P<0.001 vs. others], whereas IRA occlusion without ischaemia was associated with lower AR, not significantly different from patent IRA [3.0% (1.0-7.9) vs. 2.2% (1.0-5.8), respectively, P=0.42] CONCLUSION Ischaemia in the peri-infarct viable myocardium is present in over 50% of subjects dying late after AMI with IRA occlusion, and it is associated with increased apoptosis. Relief of ischaemia after AMI may prove of benefit in preventing apoptosis and its consequences.
Some experimental results with a two level memory management system in the multilevel darwinist brain

This paper provides a description and discussion of several experiments carried out with simulated and real agents that operated with the Multilevel Darwinist Brain cognitive mechanism including a two level memory management system. The agents interacted with real environments, including teachers, and the results show the interplay between the parameters that regulate replacement strategies in both, short term and long term memories. This type of structures allow the agents to learn autonomously, paying attention to the relevant information and to transform data into knowledge, creating subjective internal representations that can be easily reused or modified to adapt them to new situations.
ARCH-Based Traffic Forecasting and Dynamic Bandwidth Provisioning for Periodically Measured Nonstationary Traffic

Network providers are often interested in providing dynamically provisioned bandwidth to customers based on periodically measured nonstationary traffic while meeting service level agreements (SLAs). In this paper, we propose a dynamic bandwidth provisioning framework for such a situation. In order to have a good sense of nonstationary periodically measured traffic data, measurements were first collected over a period of three weeks excluding the weekends in three different months from an Internet access link. To characterize the traffic data rate dynamics of these data sets, we develop a seasonal autoregressive conditional heteroskedasticity (ARCH) based model with the innovation process (disturbances) generalized to the class of heavy-tailed distributions. We observed a strong empirical evidence for the proposed model. Based on the ARCH-model, we present a probability-hop forecasting algorithm, an augmented forecast mechanism using the confidence-bounds of the mean forecast value from the conditional forecast distribution. For bandwidth estimation, we present different bandwidth provisioning schemes that allocate or deallocate the bandwidth based on the traffic forecast generated by our forecasting algorithm. These provisioning schemes are developed to allow trade off between the underprovisioning and the utilization, while addressing the overhead cost of updating bandwidth. Based on extensive studies with three different data sets, we have found that our approach provides a robust dynamic bandwidth provisioning framework for real-world periodically measured nonstationary traffic.
Learning Semantic Combinatoriality from the Interaction between Linguistic and Behavioral Processes

We present a novel connectionist model for acquiring the semantics of a simple language through the behavioral experiences of a real robot. We focus on the “compositionality” of semantics and examine how it can be generated through experiments. Our experimental results showed that the essential structures for situated semantics can self-organize themselves through dense interactions between linguistic and behavioral processes whereby a certain generalization in learning is achieved. Our analysis of the acquired dynamical structures indicates that an equivalence of compositionality appears in the combinatorial mechanics self-organized in the neuronal nonlinear dynamics. The manner in which this mechanism of compositionality, based on dynamical systems, differs from that considered in conventional linguistics and other synthetic computational models, is discussed in this paper.
Somatotopy of the Anterior Cingulate Cortex and Supplementary Motor Area for electric stimulation of the median and tibial nerves : an fMRI study

In this study, we used functional magnetic resonance imaging (fMRI) to test the hypothesis of a somatotopy in the anterior cingulate cortex (ACC) and in the supplementary motor area (SMA) due to electrical stimulation of the wrist and the medial malleolus. Preliminary results showed a somatotopic organization in both ACC and SMA. Keywords— Functional magnetic resonance imaging (fMRI), electrical stimulation, Somatotopy.
Color demosaicing with contour stencils

Demosaicing is the problem where, given a color image that has been subsampled by a color filter array, to interpolate the complete color information at each pixel. Many demosaicing methods adapt the interpolation according to estimated edge orientations. However, while the accuracy of these orientations is important for success, they are difficult to estimate from the mosaiced image. This paper extends contour stencils, a method for estimating image contours based on total variation along curves, to estimating contour orientations directly on mosaiced images. A method for demosaicing using these contour orientation estimates is proposed and compared with existing methods. The proposed demosaicing is performed as an energy minimization, using a graph regularization adapted according to the orientation estimates.
Traversability analysis for mobile robots in outdoor environments: A semi-supervised learning approach based on 3D-lidar data

The ability to safely navigate is a crucial prerequisite for truly autonomous systems. A robot has to distinguish obstacles from traversable ground. Failing on this task can cause great damage or restrict the robots movement unnecessarily. Due to the security relevance of this problem, great effort is typically spent to design models for individual robots and sensors, and the complexity of such models is correlated to the complexity of the environment and the capabilities of the robot. We present a semi supervised learning approach, where the robot learns its traversability capabilities from a human operating it. From this partially and only positive labeled training data, our approach infers a model for the traversability analysis, thereby requiring very little manual effort for the human. In practical experiments we show that our method can be used for robots that need to reliably navigate on dirt roads as well as for robots that have very restricted traversability capabilities.
Mispronunciation detection and diagnosis in l2 english speech using multi-distribution Deep Neural Networks

This paper investigates the use of multi-distribution Deep Neural Networks (DNNs) for mispronunciation detection and diagnosis (MD&D). Our existing approach uses extended recognition networks (ERNs) to constrain the recognition paths to the canonical pronunciation of the target words and the likely phonetic mispronunciations. Although this approach is viable, it has some problems: (1) deriving appropriate phonological rules to generate the ERNs remains a challenging task; (2) the acoustic model (AM) and the phonological rules are trained independently and hence contextual information is lost; and (3) phones missing from the ERNs cannot be recognized even if we have a well-trained AM. Hence we propose an Acoustic Phonological Model (APM) using a multi-distribution DNN, whose input features include acoustic features and corresponding canonical pronunciations. The APM can implicitly learn the phonological rules from the canonical productions and annotated mispronunciations in the training data. Furthermore, the APM can also capture the relationships between the phonological rules and related acoustic features. As we do not restrict any pathways as in the ERNs, all phones can be recognized if we have a perfect APM. Experiments show that our method achieves an accuracy of 83.3% and a correctness of 88.5%. It significantly outperforms the approach of forced-alignment with ERNs whose correctness is 75.9%.
A Nodes Deployment Algorithm in Wireless Sensor Network Based on Distribution

Wireless sensor network coverage is a basic problem of wireless sensor network. In this paper, we propose a wireless sensor network node deployment algorithm base on distribution in order to form an efficient wireless sensor network. The iteratively greedy algorithm is used in this paper to choose priority nodes into active until the entire network is covered by wireless sensor nodes, the whole network to multiply connected. The simulation results show that the distributed wireless sensor network node deployment algorithm can form a multiply connected wireless sensor network. Copyright © 2014 IFSA Publishing, S. L.
Hard Decision Based Cooperative Spectrum Sensing over Different Fading Channel in Cognitive Radio

Spectrum sensing is the key component of cognitive radio technology. However, detection is compromised when a user experiences shadowing or fading effects. In such cases, user cannot distinguish between an unused band and a deep fade. Thus, cooperative spectrum sensing is proposed to optimize the sensing performance. We focus performance of cooperative CR user based on spectrum sensing using energy detector in non-fading channel AWGN and fading channels such as Rayleigh, Ricean and Nakagami. This paper presents a simulation comparison of these fading channels based on hard decision combining fusion rule (OR-rule, AND-rule and MAJORITY-rule). Fusion rule is performed at fusion center (FC) to make the final decision about the presence of PU. We observe that spectrum sensing is harder in presence of Rayleigh and Nakagami fading and performance of energy detection degrades more in Nakagami channels than Rayleigh and Ricean channels. It also found that Spectrum sensing in Ricean fading has better results than others.
Developmental Changes in Cue Weighting for Voiceless Sibilants in Brazilian Portuguese

ABSTRACT An important issue regarding developmental changes in cue weighting is whether children weight the dynamic cue of vowel formant transitions relatively more than do adults, whereas adults depend more on the static cue of the fricative noise level. We investigated this issue in Brazilian Portuguese. Additionally, we inserted the segment to be classified as either [ʃ] or [s] in words versus pseudo-words. Results show that age affects the use of fricative noise level, but not of vowel transition, at least after the four years of age. These results favor the view that phonetic differences are essential for the task at hand, not only within a language but also cross-linguistically. A significant main effect of lexical status means that the experience with one’s language is crucial for the distinction of phonetic segments, something so far absent from studies on developmental changes in cue weighting.
Cardiolipin provides an essential activating platform for caspase-8 on mitochondria

Cardiolipin is a mitochondria-specific phospholipid known to be intimately involved with apoptosis. However, the lack of appropriate cellular models to date restricted analysis of its role in cell death. The maturation of cardiolipin requires the transacylase tafazzin, which is mutated in the human disorder Barth syndrome. Using Barth syndrome patient-derived cells and HeLa cells in which tafazzin was knocked down, we show that cardiolipin is required for apoptosis in the type II mitochondria-dependent response to Fas stimulation. Cardiolipin provides an anchor and activating platform for caspase-8 translocation to, and embedding in, the mitochondrial membrane, where it oligomerizes and is further activated, steps that are necessary for an efficient type II apoptotic response.
Hemifield Effects in Multiple Identity Tracking

In everyday life, we often need to attentively track moving objects. A previous study has claimed that this tracking occurs independently in the left and right visual hemifields (Alvarez & Cavanagh, 2005, Psychological Science,16, 637–647). Specifically, it was shown that observers were much more accurate at tracking objects that were spread over both visual hemifields as opposed to when all were confined to a single visual hemifield. In that study, observers were not required to remember the identities of the objects. Conversely, in real life, there is seldom any benefit to tracking an object unless you can also recall its identity. It has been predicted that when observers are required to remember the identities of the tracked objects a bilateral advantage should no longer be observed (Oksama & Hyönä, 2008, Cognitive Psychology, 56, 237–283). We tested this prediction and found that a bilateral advantage still occurred, though it was not as strong as when observers were not required to remember the identities of the targets. Even in the later case we found that tracking was not completely independent in the two visual hemifields. We present a combined model of multiple object tracking and multiple identity tracking that can explain our data.
Analysis of Vδ1 T cells in clinical grade melanoma-infiltrating lymphocytes

γδ T cells, including Vδ1 and Vδ2 T cells, can recognize tumor-associated ligands neglected by conventional αβ T cells in a MHC-independent manner. Little is known regarding the anticancer potential and the possibility to isolate and expand Vδ1 T cells to therapeutically relevant numbers. In this study, we have detected low frequencies of Vδ1 T cells among tumor-infiltrating lymphocyte (TIL) products for adoptive cell transfer generated from melanoma metastases. An increased frequency of Vδ1 T cells was found among the cell products from patients with an advanced disease stage. Vδ1 T cells displayed in vitro antitumor activities and sufficient proliferative potential to generate over 1 × 109 cells using current protocols for T cell transfer. Infusion of Vδ1 T cells together with high numbers of αβ TILs in a clinical trial was safe and well tolerated. These data suggest that Vδ1 T cells should be further scrutinized as a potentially useful tool for the treatment of patients with metastatic melanoma.
A multi-modal object attention system for a mobile robot

Robot companions are intended for operation in private homes with naive users. For this purpose, they need to be endowed with natural interaction capabilities. Additionally, such robots will need to be taught unknown objects that are present in private homes. We present a multi-modal object attention system that is able to identify objects referenced by the user with gestures and verbal instructions. The proposed system can detect known and unknown objects and stores newly acquired object information in a scene model for later retrieval. This way, the growing knowledge base of the robot companion improves the interaction quality as the robot can more easily focus its attention on objects it has been taught previously.
Repairing of N-mustard derivative BO-1055 induced DNA damage requires NER, HR, and MGMT-dependent DNA repair mechanisms

Alkylating agents are frequently used as first-line chemotherapeutics for various newly diagnosed cancers. Disruption of genome integrity by such agents can lead to cell lethality if DNA lesions are not removed. Several DNA repair mechanisms participate in the recovery of mono- or bi-functional DNA alkylation. Thus, DNA repair capacity is correlated with the therapeutic response. Here, we assessed the function of novel water-soluble N-mustard BO-1055 (ureidomustin) in DNA damage response and repair mechanisms. As expected, BO-1055 induces ATM and ATR-mediated DNA damage response cascades, including downstream Chk1/Chk2 phosphorylation, S/G2 cell-cycle arrest, and cell death. Further investigation revealed that cell survival sensitivity to BO-1055 is comparable to that of mitomycin C. Both compounds require nucleotide excision repair and homologous recombination, but not non-homologous end-joining, to repair conventional cross-linking DNA damage. Interestingly and unlike mitomycin C and melphalan, MGMT activity was also observed in BO-1055 damage repair systems, which reflects the occurrence of O-alkyl DNA lesions. Combined treatment with ATM/ATR kinase inhibitors significantly increases BO-1055 sensitivity. Our study pinpoints that BO-1055 can be used for treating tumors that with deficient NER, HR, and MGMT DNA repair genes, or for synergistic therapy in tumors that DNA damage response have been suppressed.
Experimental Measurements of Hot Electrons Generated by Ultraintense ( > 10 19 W / cm 2 ) Laser-Plasma Interactions on Solid-Density Targets

We present the first in-target measurements of the electrons produced by an ultraintense (I{gt}10{sup 19} W/cm {sup 2}) laser pulse incident on a massive solid target. Total conversion efficiency, mean electron energy, and electron cone-angle measurements are presented. A relationship between the target material and the mean electron energy is also discussed. {copyright} {ital 1998} {ital The American Physical Society}
A new statistical and Dirichlet integral framework applied to liver segmentation from volumetric CT images

Accurate liver segmentation from computed tomography (CT) images is problematic due to non-uniform density, weak boundaries and because there may be multiple liver tumors that have heterogeneous intensities in region(s) of interest (ROIs). So we propose a generalized energy framework that harnesses the statistical intensity approximation with image data on graphs. Our statistical energy term takes advantage of the mixture-of-mixtures Gaussian model to approximate the probability density distribution of the liver and background to better differentiate between the two. The probability density estimation can be combined with the spatial cohesion of the graph-based Dirichlet integral by using graph calculus. Matrix decomposition and differentiation are used to minimize our proposed energy functional. We tested our approach on 20 public high-contrast CT images with single and multiple liver tumors. Our method had an average dice similarity coefficient (DSC) of 93.75±1.29%, an average false positive (FP) rate of 9.43±3.52% and an average false negative (FN) rate of 3.48±1.48%. Our method outperformed the benchmark graph-based Random Walker algorithm (average DSC=81.97±4.09%, average FP rate 34.10±10.53%, and average FN rate 7.10±4.35%).
A Sequential Classifier for Hand Detection in the Framework of Egocentric Vision

Hand detection is one of the most explored areas in Egocentric Vision Video Analysis for wearable devices. Current methods are focused on pixel-by-pixel hand segmentation, with the implicit assumption of hand presence in almost all activities. However, this assumption is false in many applications for wearable cameras. Ignoring this fact could affect the whole performance of the device since hand measurements are usually the starting point for higher level inference, or could lead to inefficient use of computational resources and battery power. In this paper we propose a two-level sequential classifier, in which the first level, a hand-detector, deals with the possible presence of hands from a global perspective, and the second level, a hand-segmentator, delineates the hand regions at pixel level in the cases indicated by the first block. The performance of the sequential classifier is stated in probabilistic notation as a combination of both, classifiers allowing to test new hand-detectors independently of the type of segmentation and the dataset used in the training stage. Experimental results show a considerable improvement in the detection of true negatives, without compromising the performance of the true positives.