Miracle-dz/UniFAR-FTUs huggingface dataset:
A Heuristic Checkpoint Placement Algorithm for Adaptive Application-Level Checkpointing

Checkpoint/rollback is an effective scheme for fault tolerance and has been widely used to reduce the overall execution time of long-running applications in case of faults. The locations of checkpoints in application programs are critical since the distance between two consecutive ones determines the checkpointing scheme’s sensitivity and overheads. If they are too far apart, applications might be insensitive to job failure. That is, the lost computational time between the point of failure and the end of previous checkpoint would be very large. But if they are too close, the related checkpointing overheads will slow down the normal computation. This paper proposes a heuristic checkpoint placement algorithm to improve the checkpointing schemes’ performance in terms of sensitivity and flexibility. This heuristic algorithm enables automatic and transparent insertion of checkpoints in user’s source code. Experiments on benchmark programs and real applications demonstrate this algorithm’s efficiency and sufficiency.
HYBRID APPROACH FOR ENERGY OPTIMIZATION IN CLUSTER BASED WSN USING ENERGY BALANCING CLUSTERING PROTOCOL

In recent times, the technology of wireless sensor network has a great impact on technical fields like wireless communication, information technology, electrical etc. However the major problem faced in this technology is that the sensor nodes run out of energy very quickly. Many routing protocols have been proposed to solve this problem mainly focussing on the accomplishment of minimizing the energy consumption in the sensor system. In this paper, two hierarchical protocols cluster based and chain based protocol for WSNs have been discussed. In both type of protocols some special nodes called cluster heads/chain heads acts as leader for a group of nodes. Each head collects data from its member nodes and forward it to the sink (base station). Here consider a homogeneous network where all the nodes in the network have uniform and limited resource energy. So it is essential to avoid quick depletion of head nodes. Hence every node in the network takes their turn to act as head but only for a limited period of time. Energy saving in these approaches can be obtained by cluster formation, head election and data aggregation at the head nodes. The proposed Energy Balancing Clustering Protocol (EBCP) which uses Bacterial Foraging Optimization Algorithm in electing the cluster head. The simulation results shows that the proposed protocol extends the life time of the network when compared with Energy Efficient Unequal Clustering (EEUC)and PEGASIS with Double Cluster Head technique(PDCH).
Whitespace networks for vehicular communication

We outline the design of a system to exploit the TV whitespaces for dynamically gathering video feeds from public buses in a city. The system consists of the following components: (1) A FPGA based SDR board to be fixed on buses to collect the video feed from inside the bus and transmit it to the central location, (2) An open source software (GNU-radio) to configure and control the hardware and, (3) A MAC-layer design for effective communication strategy. Our novel handoff scheme has been tested on a USRP platform.
Sonic Hedgehog Regulates Discrete Populations of Astrocytes in the Adult Mouse Forebrain

Astrocytes are an essential component of the CNS, and recent evidence points to an increasing diversity of their functions. Identifying molecular pathways that mediate distinct astrocyte functions, is key to understanding how the nervous system operates in the intact and pathological states. In this study, we demonstrate that the Hedgehog (Hh) pathway, well known for its roles in the developing CNS, is active in astrocytes of the mature mouse forebrain in vivo. Using multiple genetic approaches, we show that regionally distinct subsets of astrocytes receive Hh signaling, indicating a molecular diversity between specific astrocyte populations. Furthermore, we identified neurons as a source of Sonic hedgehog (Shh) in the adult forebrain, suggesting that Shh signaling is involved in neuron–astrocyte communication. Attenuation of Shh signaling in postnatal astrocytes by targeted removal of Smoothened, an obligate Shh coreceptor, resulted in upregulation of GFAP and cellular hypertrophy specifically in astrocyte populations regulated by Shh signaling. Collectively, our findings demonstrate a role for neuron-derived Shh in regulating specific populations of differentiated astrocytes.
Phonons as goldstone bosons

The implications of the hidden, spontaneously broken symmetry for the properties of the sound waves of a solid are analyzed. Although the discussion does not go beyond standard wisdom, it presents some of the known results from a different perspective. In particular, I argue that, as a consequence of the hidden symmetry, the equations of motion for a sound wave necessarily contain nonlinear terms, describing phonon-phonon-scattering and emphasize the analogy with the low energy theorems valid for ππ-scattering. Dedicated to Klaus Hepp and Walter Hunziker Work supported in part by Schweizerischer Nationalfonds
Survey on performance analysis of cognitive radio networks

Cognitive radio networks are being studied intensively. The major motivation for this is the heavily underutilized frequency spectrum. The development is being pushed forward by the rapid advances in software defined radio technology which enable a spectrum agile and highly configurable radio transmitter/receiver. We conduct a literature survey on recent major research advances in cognitive radio networks published recently in first-tier journals and conferences. Our viewpoint covers the problems at the MAC layer and above with a special emphasis on traffic performance in the networks.
Stereo confidence metrics using the costs of surrounding pixels

In this paper, we propose two new stereo confidence metrics which are used for estimating the reliability of a stereo matching result more accurately. Unlike the conventional metrics which exploit the cost information of the pixel being processed only, the proposed metrics utilize the cost information of the surrounding pixels as well as the pixel being processed. By checking whether the costs of the surrounding pixels at the target disparity are the local minimum or not, or calculating the ratio between costs of surrounding pixels, the proposed metrics can estimate the reliability of a stereo matching result more correctly. Experimental results show that the two proposed metrics improve the area under the curve of the error rate as a function of disparity map density by up to 0.012 and 0.025, compared to the existing methods, respectively.
Model Interpretation of Pathological Body Surface QRST Integral Maps Related to Action Potential Heterogeneity

According to theoretical and clinical considerations the risk of re-entry type malignant arrhythmia can be predicted by body surface QRST integral maps. Our aim was to understand better the intracardiac processes causing noninvasively measurable action potential (AP) heterogeneity. For this task we used a computer model of human cardiac ventricles with modifiable AP patterns to investigate the process on source level. To estimate the relevant potential maps on the body surface, we used a realistically shaped piecewise homogeneous torso model. The level of AP heterogeneity was quantified by the non-dipolarity index (NDI) of the QRST integral maps, calculated beat-to-beat. We found that the source level origin of extreme NDIs was in the apical region of the heart, due to significantly diminished or reversed transmural action potential gradients or myocardial necrosis.
Integrating Cyc and Wikipedia: Folksonomy meets rigorously defined common-sense

Integration of ontologies begins with establishing mappings between their concept entries. We map categories from the largest manually-built ontology, Cyc, onto Wikipedia articles describing corresponding concepts. Our method draws both on Wikipedia’s rich but chaotic hyperlink structure and Cyc’s carefully defined taxonomic and common-sense knowledge. On 9,333 manual alignments by one person, we achieve an F-measure of 90%; on 100 alignments by six human subjects the average agreement of the method with the subject is close to their agreement with each other. We cover 62.8% of Cyc categories relating to common-sense knowledge and discuss what further information might be added to Cyc given this substantial new alignment.
Thermal face recognition using convolutional neural network

With the rapidly development of the face recognition (FR), thermal face recognition has received increasing attention. However, the traditional methods for thermal face recognition mainly concentrate on the hand-crafted feature design, which requires more efforts from human to select and extract features and usually has relatively lower recognition rate. In this paper, we present a convolutional neural network (CNN) architecture for thermal face recognition. CNN is a new type of neural network method which can automatically learn effective features from the raw data. Experiment results on RGB-D-T face database show that our proposed CNN architecture achieves higher recognition rate compared with the traditional recognition such as LBP, HOG and moments invariant.
Harris Correlation Descriptor (HCD): A Novel Descriptor for Point Matching

In this paper, a novel descriptor for point matching, called Harris correlation descriptor (HCD), is proposed. Inspired by the Harris feature detector, we use the Harris correlation measure defined with the determinant and trace of the Harris correlation matrix to characterize the gradient distribution in a neighborhood of feature points, and then construct the HCD descriptor which is invariant to image rotation and linear change of intensity. The using of the gradient mean in the Harris correlation measure makes the HCD descriptor not sensitive to the estimated main orientation of feature points, thus robust to image rotation. Moreover, the HCD descriptor has also a good adaptability to other image transformations.
A Model-Based Approach for the Management of Electronic Invoices

The globalized market pushes companies to expand their business boundaries to a whole new level. In order to efficiently support this environment, business transactions must be executed over the Internet. However, there are several factors complicating this process, such as the current state of electronic invoices. Electronic invoice adoption is not widespread because of the current format fragmentation originated by national regulations. In this paper we present an approach based on Model-Driven Engineering techniques and abstractions for supporting the core functions of invoice management systems. We compare our solution with the traditional implementations and try to analyze the advantages MDE can bring to this specific domain.
Video Pulses: User-Based Modeling of Interesting Video Segments

We present a user-based method that detects regions of interest within a video in order to provide video skims and video summaries. Previous research in video retrieval has focused on content-based techniques, such as pattern recognition algorithms that attempt to understand the low-level features of a video. We are proposing a pulse modeling method, which makes sense of a web video by analyzing users' Replay interactions with the video player. In particular, we have modeled the user information seeking behavior as a time series and the semantic regions as a discrete pulse of fixed width. Then, we have calculated the correlation coefficient between the dynamically detected pulses at the local maximums of the user activity signal and the pulse of reference. We have found that users' Replay activity significantly matches the important segments in information-rich and visually complex videos, such as lecture, how-to, and documentary. The proposed signal processing of user activity is complementary to previous work in content-based video retrieval and provides an additional user-based dimension formodeling the semantics of a social video on the web.
Design and Realization of Medical Image Nonrigid Matching Algorithm

Although rigid matching methods are a good robust point matching (RPM), they can not meet clinic needs. Because that many deformations are non-rigid and nonlinear, so we need non-rigid registration. But at present feature-based non-rigid registration methods for frequently encounter the correspondence and robust problem (H. Chui and A. Rangarajan, 2003). In this paper, based on thin plate spline and matching matrix, a matching algorithm for non-rigid medical image is presented, this algorithm decomposes the parameters of thin plate spline (TPS) into affine part and non-affine part, and solves the matching matrix through iterative means. Comparing with the popular iterated closest point (ICP) algorithm and other non-rigid matching algorithms, the proposed algorithm can not only keep biunique constraints between image feature points, but also is more robust
Accurate Constraints Aware Mapping on Coarse-Grained Reconfigurable Architecture

The rapid diversification and evolution of wireless and multimedia standards change the flexibility of embedded processors from an option to the must. Coarse-Grained Reconfigurable Architectures (CGRAs) which make a good trade off between low power, non-programmable ASICs and high power, flexible DSPs become more and more popular. The mapping of the applications to CGRAs is the key to get high computational throughput. Because there is huge design space to explore on CGRAs, compilers must not only map the programs with high effectiveness, but also with high efficiency. However, there are many sorts of constraints exist during the mapping. Over or under estimate those constraints will lead to either low schedule quality or low efficiency. To meet this challenge, we propose an accurate constraints aware modulo scheduling approach: based on the co-analysis of the architecture and application, the compiler starts the scheduling with enough critical resources reserved and strictly make the re-try follow the correct order. The experiments on wireless base band programs show that the compilation can be speeded up by 300%.
A Routing Algorithm Based on Ant-Colony in Wireless Sensor Networks

High efficient routing is an important issue in the limited energy resource wireless sensor networks. Introducing Ant-colony algorithm, this paper proposes the wireless sensor network routing algorithm based on the LEACH. During the construction of sensor network clusters, only the nodes whose residual energy is higher than the average energy can be chosen as the cluster heads to avoid the node premature death due to the energy consumption. The method of repeated division is used to divide the clusters in sensor networks so that the numbers of the nodes in each cluster are balanced. The ant-colony algorithm is adopted to realize and maintain the routing between the cluster heads and sink. The analysis and the simulation show that the proposed routing protocol can reduce the energy consumption, balance the energy consumption between nodes, and prolong the lifetime of networks.
Business Cycle Synchronization and Vertical Trade Integration: A Case Study of the Eurozone and East Asia

Abstract Business cycle synchronization is one of the crucial conditions for a currency union to be successful. Frankel and Rose (1998) argued that increased trade after euro adoption would increase business cycle synchronization ex-ante. However, the fallout of the Eurozone forcefully demonstrated that their optimistic prediction did not turn out to be true. One thing Frankel and Rose (1998) did not examine is how different types of trade (inter vs. intra, vertical vs. horizontal, etc.) intensify/dampens business cycle synchronization. In this light, this paper empirically examines how different types of trade affect business cycle synchronization in what way. This study takes two major economic blocs that have been going under rapid economic integrations: The original Eurozone members and East Asia – integration of former mainly developing by European government initiative and the latter naturally forming by the global supply chain and associated product segmentation. Comparing these two very different economic blocs with very different factor endowment structures would give us a more convincing answer to how different types of trade can influence business cycle synchronization differently. Our key finding is that, on the contrary to Frankel and Rose (1998), the impact of increased trade intensity on business cycle co-movement is ambiguous. The impact of trade on business cycle synchronization depends on types of trade. Intra-industry trade, especially vertical intra-industry trade which is rapidly growing in East Asia, has a strong positive effect on business cycle synchronization while inter-industry trade does not.
Myth 1 : People Did not Properly “ Price ” Options Before the Black-Scholes-Merton Theory

versions of the formula of Louis Bachelier and Edward O. Thorp (that allow a broad choice of probability distributions) and removed the risk parameter by using put-call parity. The Bachelier-Thorp approach is more robust (among other things) to the high impact rare event. The paper draws on historical trading methods and 19 and early 20 century references ignored by the finance literature. It is time to stop calling the formula by the wrong name. Abstract Options traders use a pricing formula which they adapt by fudging and changing the tails and skewness by varying one parameter, the standard deviation of a Gaussian. Such formula is popularly called “Black-Scholes-Merton” owing to an attributed eponymous discovery (though changing the standard deviation parameter is in contradiction with it). However we have historical evidence that 1) Black, Scholes and Merton did not invent any formula, just found an argument to make a well known (and used) formula compatible with the economics establishment, by removing the “risk” parameter through “dynamic hedging”, 2) Option traders use (and evidently have used since 1902) heuristics and tricks more compatible with the previous
Characterization of H type 1 and type 1 N-acetyllactosamine glycan epitopes on ovarian cancer specifically recognized by the anti-glycan monoclonal antibody mAb-A4

Cancer-specific glycans of ovarian cancer are promising epitopes for targeting with monoclonal antibodies (mAb). Despite their potential, structural characterization of these glycan epitopes remains a significant challenge in mAb preclinical development. Our group generated the monoclonal antibody mAb-A4 against human embryonic stem cells (hESC), which also bound specifically to N-glycans present on 11 of 19 ovarian cancer (OC) and 8 of 14 breast cancer cell lines tested. Normal cell lines and tissue were unstained by mAb-A4. To characterize the N-linked glycan epitopes on OC cell lines targeted by mAb-A4, we used glycosidases, glycan microarray, siRNA, and advanced high sensitivity matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). The mAb-A4 epitopes were found to be Fucα1–2Galβ1–3GlcNAcβ (H type 1) and Galβ1–3GlcNAcβ (type 1 LacNAc). These structures were found to be present on multiple proteins from hESC and OC. Importantly, endo-β-galactosidase coupled with MALDI-MS allowed these two epitopes, for the first time, to be directly identified on the polylactosamines of N-glycans of SKOV3, IGROV1, OV90, and OVCA433. Furthermore, siRNA knockdown of B3GALT5 expression in SKOV3 demonstrated that mAb-A4 binding was dependent on B3GALT5, providing orthogonal evidence of the epitopes' structures. The recognition of oncofetal H type 1 and type 1 LacNAc on OC by mAb-A4 is a novel and promising way to target OC and supports the theory that cancer can acquire stem-like phenotypes. We propose that the orthogonal framework used in this work could be the basis for advancing anti-glycan mAb characterization.
AGO/RISC-mediated antiviral RNA silencing in a plant in vitro system

AGO/RISC-mediated antiviral RNA silencing, an important component of the plant’s immune response against RNA virus infections, was recapitulated in vitro. Cytoplasmic extracts of tobacco protoplasts were applied that supported Tombusvirus RNA replication, as well as the formation of RNA-induced silencing complexes (RISC) that could be functionally reconstituted with various plant ARGONAUTE (AGO) proteins. For example, when RISC containing AGO1, 2, 3 or 5 were programmed with exogenous siRNAs that specifically targeted the viral RNA, endonucleolytic cleavages occurred and viral replication was inhibited. Antiviral RNA silencing was disabled by the viral silencing suppressor p19 when this was present early during RISC formation. Notably, with replicating viral RNA, only (+)RNA molecules were accessible to RISC, whereas (−)RNA replication intermediates were not. The vulnerability of viral RNAs to RISC activity also depended on the RNA structure of the target sequence. This was most evident when we characterized viral siRNAs (vsiRNAs) that were particularly effective in silencing with AGO1- or AGO2/RISC. These vsiRNAs targeted similar sites, suggesting that accessible parts of the viral (+)RNA may be collectively attacked by different AGO/RISC. The in vitro system was, hence, established as a valuable tool to define and characterize individual molecular determinants of antiviral RNA silencing.
Lymphatics and Lymphangiogenesis in the Eye

Lymphatic is a prerequisite for the maintenance of tissue fluid balance and immunity in the body. A body of evidence also shows that lymphangiogenesis plays important roles in the pathogenesis of diseases such as tumor metastasis and inflammation. The eye was thought to lack lymphatic vessels except for the conjunctiva; however, advances in the field, including the identification of lymphatic endothelial markers (e.g., LYVE-1 or podoplanin) and lymphangiogenic factors (e.g., VEGF-C), have revealed the exsitence and possible roles of lymphatics and lymphangiogenesis in the eye. Recent studies have shown that corneal limbus, ciliary body, lacrimal gland, orbital meninges, and extraocular muscles contain lymphatic vessels and that the choroid might have a lymphatic-like system. There is no known lymphatic outflow from the eye. However, several lymphatic channels including uveolymphatic pathway might serve the ocular fluid homeostasis. Furthermore, lymphangiogenesis plays important roles in pathological conditions in the eye including corneal transplant rejection and ocular tumor progression. Yet, the role of lymphangiogenesis in most eye diseases, especially inflammatory disease or edema, remains unknown. A better understanding of lymphatic and lymphangiogenesis in the eye will open new therapeutic opportunities to prevent vision loss in ocular diseases.