Miracle-dz/UniFAR-FTUs huggingface dataset:
Liquid State Machine With Dendritically Enhanced Readout for Low-Power, Neuromorphic VLSI Implementations

In this paper, we describe a new neuro-inspired, hardware-friendly readout stage for the liquid state machine (LSM), a popular model for reservoir computing. Compared to the parallel perceptron architecture trained by the p-delta algorithm, which is the state of the art in terms of performance of readout stages, our readout architecture and learning algorithm can attain better performance with significantly less synaptic resources making it attractive for VLSI implementation. Inspired by the nonlinear properties of dendrites in biological neurons, our readout stage incorporates neurons having multiple dendrites with a lumped nonlinearity (two compartment model). The number of synaptic connections on each branch is significantly lower than the total number of connections from the liquid neurons and the learning algorithm tries to find the best `combination' of input connections on each branch to reduce the error. Hence, the learning involves network rewiring (NRW) of the readout network similar to structural plasticity observed in its biological counterparts. We show that compared to a single perceptron using analog weights, this architecture for the readout can attain, even by using the same number of binary valued synapses, up to 3.3 times less error for a two-class spike train classification problem and 2.4 times less error for an input rate approximation task. Even with 60 times larger synapses, a group of 60 parallel perceptrons cannot attain the performance of the proposed dendritically enhanced readout. An additional advantage of this method for hardware implementations is that the `choice' of connectivity can be easily implemented exploiting address event representation (AER) protocols commonly used in current neuromorphic systems where the connection matrix is stored in memory. Also, due to the use of binary synapses, our proposed method is more robust against statistical variations.
When Standard RANSAC is Not Enough Cross-Media Visual Matching with Hypothesis Relevancy *

The same scene can be depicted by multiple visual-media. For example, the same event can be captured by a comic image or a movie frame; the same object can be represented by a photograph or by a 3D computer graphics model. In order to extract the visual analogies that are at the heart of cross media analysis, spatial matching is required. This matching is commonly achieved by extracting key-points, and scoring multiple, randomly generated mapping hypotheses. The more consensus a hypothesis can draw, the higher its score. In this paper we go beyond the conventional setsize measure for the quality of a match and present a more general hypothesis score that attempts to reflect how likely is each hypothesized transformation to be the correct one for the matching task at hand. This is achieved by considering additional, contextual cues for the relevance of a hypothesized transformation. This context changes from one matching task to another and reflects different properties of the match, beyond the size of a consensus set. We demonstrate that by learning how to correctly score each hypothesis based on these features we are able to deal much more robustly with T. Hassner Department of Mathematics and Computer Science, The Open University of Israel, Israel 1 University Road, P.O. B. 808, Raanana 43107, Israel Tel. : +972-9-778-1261 Fax: +972-9-778-0605 E-mail: hassner@openu.ac. il L. Assif Department of Mathematics and Computer Science, The Open University of Israel, Israel L. Wolf Blavatnik School of Computer Science at Tel Aviv University, Israel Fig. 1 Example application: matching a 3D model (left) to a photograph (right). The viewpoint of the 3D object was adjusted to match the recovered viewpoint of the photograph. the challenges required to allow cross media analysis, leading to correct matches where conventional methods fail.
A Preclinical Canine Model for Composite Tissue Transplantation

The feasibility of composite tissue allografts (CTAs) has been demonstrated by the successful transplantation of the hand, abdomen, and face. However, the survival of these transplants depends on immunosuppression. Our laboratory is interested in achieving tolerance to decrease the risks associated with the use of chronic immunosuppression. The purpose of this experiment was to develop a large-animal model for CTA. Four canine flaps were autotransplanted to examine the use of a myocutaneous rectus flap based on the deep inferior epigastric vessels. Five CTA transplants were performed between dog leukocyte antigen (DLA)-identical littermates without posttransplant immunosuppression. The allografts were followed clinically and underwent routine biopsies. The anatomic dissections and autotransplants were all successful and revealed that the flap could be divided into two separate components. Skin was perfused by the superficial epigastric artery. Rectus muscle was perfused by the deep inferior epigastric system. This allowed the allografts to be transplanted as muscle or skin or with both components based on the external iliac artery and veins. The DLA-identical littermates rejected the allografts in 15 to 30 days. This study demonstrated the versatility of the myocutaneous rectus flap for use in canines as CTA models.
Polymorphisms in GEMIN4 and AGO1 Genes Are Associated with the Risk of Lung Cancer: A Case-Control Study in Chinese Female Non-Smokers

MicroRNA biosynthesis genes can affect the regulatory effect of global microRNAs to target mRNA and hence influence the genesis and development of human cancer. Here, we selected five single nucleotide polymorphisms (SNPs) (rs7813, rs2740349, rs2291778, rs910924, rs595961) in two key microRNA biosynthesis genes (GEMIN4 and AGO1) and systematically evaluated the association between these SNPs, the gene-environment interaction and lung cancer risk. To control the impact of cigarette smoking on lung cancer, we recruited Chinese female non-smokers for the study. The total number of lung cancer cases and cancer-free controls were 473 and 395 in the case-control study. Four SNPs showed statistically significant associations with lung cancer risk. After Bonferroni correction, rs7813 and rs595961 were evidently still associated with lung cancer risk. In the stratified analysis, our results revealed that all five SNPs were associated with the risk of lung adenocarcinoma; after Bonferroni correction, significant association was maintained for rs7813, rs910924 and rs595961. Haplotype analysis showed GEMIN4 haplotype C-A-G-T was a protective haplotype for lung cancer. In the combined unfavorable genotype analysis, with the increasing number of unfavorable genotypes, a progressively increased gene-dose effect was observed in lung adenocarcinoma. We also found that individuals exposed to cooking oil fumes showed a relatively high risk of lung cancer, but no interactions were found between cooking oil fume exposure or passive smoking exposure with these SNPs, either on an additive scale or a multiplicative scale. Overall, this is the first study showing that rs7813 and rs595961 could be meaningful as genetic markers for lung cancer risk.
Large Scale Gene Expression Profiles of Regenerating Inner Ear Sensory Epithelia

Loss of inner ear sensory hair cells (HC) is a leading cause of human hearing loss and balance disorders. Unlike mammals, many lower vertebrates can regenerate these cells. We used cross-species microarrays to examine this process in the avian inner ear. Specifically, changes in expression of over 1700 transcription factor (TF) genes were investigated in hair cells of auditory and vestibular organs following treatment with two different damaging agents and regeneration in vitro. Multiple components of seven distinct known signaling pathways were clearly identifiable: TGFβ, PAX, NOTCH, WNT, NFKappaB, INSULIN/IGF1 and AP1. Numerous components of apoptotic and cell cycle control pathways were differentially expressed, including p27KIP and TFs that regulate its expression. A comparison of expression trends across tissues and treatments revealed identical patterns of expression that occurred at identical times during regenerative proliferation. Network analysis of the patterns of gene expression in this large dataset also revealed the additional presence of many components (and possible network interactions) of estrogen receptor signaling, circadian rhythm genes and parts of the polycomb complex (among others). Equal numbers of differentially expressed genes were identified that have not yet been placed into any known pathway. Specific time points and tissues also exhibited interesting differences: For example, 45 zinc finger genes were specifically up-regulated at later stages of cochlear regeneration. These results are the first of their kind and should provide the starting point for more detailed investigations of the role of these many pathways in HC recovery, and for a description of their possible interactions.
How many users are needed for non-trivial performance of random beamforming in highly-directional mm-wave MIMO downlink?

In this paper, the multi-user (MU) gain and the impact of training are investigated for random beamforming (RBF) in highly-directional millimeter-wave (mm-wave) MU multiple-input multiple-output (MIMO) downlink which is considered as one of the major technological thrusts for 5G communications. To do so, the uniform random line-of-sight (UR-LoS) channel model suitable for highly-directional mm-wave radio propagation channels is adopted. Based on the UR-LOS channel model, the performance of RBF and the MU gain in mm-wave MIMO systems are analyzed. It is shown that there exists a transition point on the number of users relative to the number of transmit antennas for non-trivial performance of the RBF scheme. Furthermore, in case of training, the number of training beams relative to the number of antennas required for asymptotically good performance of the RBF scheme is specified when the number of users relative to the number of antennas is given. The provided results in this paper yields insights into the MU gain with partial CSI and the amount of required training in highly-directional mm-wave channels.
Vehicle image mosaics technology based on improved SIFT algorithm

Aimed at the problem of large vehicle outline detect in the field of intelligent traffic, this paper proposes a vehicle stitching algorithm based on improved SIFT feature matching to reduce the requirements of the camera configuration and choose camera position easily. Firstly, the improved SIFT algorithm is used to extract and match feature point quickly. So the superior characteristics of SIFT algorithm is utilized to not only deal with the image's rotation, translation and illumination changes, the stability of visual change and affine transformation, but also ensure the processing speed of algorithm by reducing the complexity of the SIFT algorithm. In this paper, mismatched points are simply and quickly removed by limiting the matching line slope, which is proved to be a good result. After obtaining the stable matching points, we calculate the transformation matrix between two images. Finally, the image pyramid fusion is performed to perfect our stitching image and this pixel level processing has a good ability to eliminate fusion mosaic slot caused by camera position deviation, different light and other causes. Experiment results show that this algorithm reduces the rate of mismatching and improves the low efficiency in traditional image mosaic. The improved SIFT algorithm has distinct advantage in increasing speed, obtaining high resolution and completing vehicle images after mosaic.
Quest-V: A Virtualized Multikernel for High-Confidence Systems

This paper outlines the design of `Quest-V', which is implemented as a collection of separate kernels operating together as a distributed system on a chip. Quest-V uses virtualization techniques to isolate kernels and prevent local faults from affecting remote kernels. This leads to a high-confidence multikernel approach, where failures of system subcomponents do not render the entire system inoperable. A virtual machine monitor for each kernel keeps track of shadow page table mappings that control immutable memory access capabilities. This ensures a level of security and fault tolerance in situations where a service in one kernel fails, or is corrupted by a malicious attack. Communication is supported between kernels using shared memory regions for message passing. Similarly, device driver data structures are shareable between kernels to avoid the need for complex I/O virtualization, or communication with a dedicated kernel responsible for I/O. In Quest-V, device interrupts are delivered directly to a kernel, rather than via a monitor that determines the destination. Apart from bootstrapping each kernel, handling faults and managing shadow page tables, the monitors are not needed. This differs from conventional virtual machine systems in which a central monitor, or hypervisor, is responsible for scheduling and management of host resources amongst a set of guest kernels. In this paper we show how Quest-V can implement novel fault isolation and recovery techniques that are not possible with conventional systems. We also show how the costs of using virtualization for isolation of system services does not add undue overheads to the overall system performance.
Actomyosin Contractility Drives Bile Regurgitation as an Early Homeostatic Response to Increased Biliary Pressure in Obstructive Cholestasis

A wide range of liver diseases manifest as biliary obstruction, or cholestasis. However, the sequence of molecular events triggered as part of the early hepatocellular homeostatic response to abnormal elevations in biliary pressure remains poorly elucidated. Bile canaliculi are dynamic luminal structures that undergo actomyosin-mediated periodic contractions to propel secreted bile. Additionally, pericanalicular actin is accumulated during obstructive cholestasis. Therefore, we hypothesize that the pericanalicular actin cortex undergoes significant remodeling as a regulatory response against increased biliary pressure. Here, we report that, actomyosin contractility induces transient deformations along the canalicular membrane, a process we have termed inward blebbing. We show that these membrane intrusions are initiated by local ruptures in the pericanalicular actin cortex, and they typically retract following repair by actin polymerization and actomyosin contraction. However, above a certain osmotic pressure threshold, these inward blebs pinch away from the canalicular membrane into the hepatocyte cytoplasm as large vesicles (2-8 µm). Importantly, we show that these vesicles aid in the regurgitation of bile from the canalicular system. Conclusion: Actomyosin contractility induces the formation of bile-regurgitative vesicles, thus serving as an early homeostatic mechanism against increased biliary pressure during cholestasis.
Improving online gaming quality using detour paths

We study the problem of improving the user perceived quality of online games in which multiple players form a game session and exchange game-state updates over an overlay network. We propose an Indirect Relay System (IRS) to forward game-state updates over detour paths in order to reduce the round-trip time (RTT) among players. The IRS system efficiently identifies and ranks potential detour paths between any two players, and dynamically selects the most suitable one based on network and client conditions. To the best of our knowledge, this is the first system that directly reduced RTTs among players in online games, while previous works in the literature mitigate the network latency issue by either hiding it from players or preventing players with high RTTs from being in the same game session. We implement the proposed IRS system and deploy it on 500 PlanetLab nodes. The results from real experiments show that the IRS system improves the online gaming quality from several aspects, while incurring negligible network and processing overheads. We also deploy the IRS system on a number of residential computers with DSL and cable modem access links and we successfully found several detour paths among them. To evaluate the IRS system with wider ranges of system parameters we conduct extensive trace-driven simulations using a large number of real game client IPs. The experimental and simulation results show that the proposed IRS system: (i) significantly reduces RTTs among players, (ii) increases number of peers a player can connect to and maintain good gaming quality, (iii) imposes negligible network and processing overheads, and (iv) improves gaming quality and player performance.
Association between Acquired Uniparental Disomy and Homozygous Mutations and HER2/ER/PR Status in Breast Cancer

Background Genetic alterations in cellular signaling networks are a hallmark of cancer, however, effective methods to discover them are lacking. A novel form of abnormality called acquired uniparental disomy (aUPD) was recently found to pinpoint the region of mutated genes in various cancers, thereby identifying the region for next-generation sequencing. Methods/Principal Findings We retrieved large genomic data sets from the Gene Expression Omnibus database to perform genome-wide analysis of aUPD in breast tumor samples and cell lines using approaches that can reliably detect aUPD. aUPD was identified in 52.29% of the tumor samples. The most frequent aUPD regions were located at chromosomes 2q, 3p, 5q, 9p, 9q, 10q, 11q, 13q, 14q and 17q. We evaluated the data for any correlation between the most frequent aUPD regions and HER2/neu, ER, and PR status, and found a statistically significant correlation between the recurrent regions of aUPD and triple negative (TN) breast cancers. aUPD at chromosome 17q (VEZF1, WNT3), 3p (SUMF1, GRM7), 9p (MTAP, NFIB) and 11q (CASP1, CASP4, CASP5) are predictors for TN. The frequency of aUPD was found to be significantly higher in TN breast cancer cases compared to HER2/neu-positive and/or ER or PR-positive cases. Furthermore, using previously published mutation data, we found TP53 homozygously mutated in cell lines having aUPD in that locus. Conclusions/Significance We conclude that aUPD is a common and non-random molecular feature of breast cancer that is most prominent in triple negative cases. As aUPD regions are different among the main pathological subtypes, specific aUPD regions may aid the sub-classification of breast cancer. In addition, we provide statistical support using TP53 as an example that identifying aUPD regions can be an effective approach in finding aberrant genes. We thus conclude that a genome-wide scale analysis of aUPD regions for homozygous sequence alterations can provide valuable insights into breast tumorigenesis.
Second Derivatives for Optimizing Eigenvalues of Symmetric Matrices

Let $A$ denote an $n \times n$ real symmetric matrix-valued function depending on a vector of real parameters, $x \in \Re^{m}$. Assume that $A$ is a twice continuously differentiable function of $x$, with the second derivative satisfying a Lipschitz condition. Consider the following optimization problem: minimize the largest eigenvalue of $A(x)$. Let $x^*$ denote a minimum. Typically, the maximum eigenvalue of $A(x^*)$ is multiple, so the objective function is not differentiable at $x^*$, and straightforward application of Newton's method is not possible. Nonetheless, the formulation of a method with local quadratic convergence is possible. The main idea is to minimize the maximum eigenvalue subject to a constraint that this eigenvalue has a certain multiplicity. The manifold $\Omega$ of matrices with such multiple eigenvalues is parameterized using a matrix exponential representation, leading to the definition of an appropriate Lagrangian function. Consideration of the Hessian of this Lagrangian function leads to the second derivative matrix used by Newton's method. The convergence proof is nonstandard because the parameterization of $\Omega$ is explicitly known only in the limit. In the special case of multiplicity one, the maximum eigenvalue is a smooth function and the method reduces to a standard Newton iteration.
Use of the Internet for Community Practice

ABSTRACT The Internet is a relatively new community practice tool with immense potential for more effective and efficient delivery of services. The lack of research about Internet community practice is an obstacle to the effective and efficient use of Internet tools. This research used the Delphi technique to elicit the opinions of experts on how the Internet tools of email, newsgroups, text, listservs, search engines, and chat are used by the four primary models of community practice found on the Internet (information dissemination, organization building, mobilization, and community planning). Findings show that a substantial number of people use community practice sites. The most useful Internet tools for the four Internet community practice models studied were text presentation and email. The least useful tools were newsgroups and chat. Barriers to Internet community practice include quality and currency of information, bandwidth, staff time, agency support, rapid technological change, marketing, browser consistency, user skills, and the lack of Internet access by potential users. The study concluded that Internet community practice is effective and will continue to grow as society enters the information age. The findings are particularly relevant for community practice agencies interested in setting up or enhancing an agency Web site to help provide services.
Expert System for Planning Web Site Promotion Campaigns

The paper describes an approach of using an expert system for planning promotion campaigns for web sites and optimizing them for promotion. This expert system would to a certain degree substitute human-being expert in the area of web promotion. It would contain knowledge of such an expert in a certain formalized form (a knowledgebase), and a specific reasoning engine to apply that knowledge for planning web promotion campaign for a certain site. Web promotion expert system can be published on a web resource to provide remote consultation for clients through the Internet. This system also contains a plug-in to get additional real-time information from remote web resources on the Internet during the consultation, for example
A self-aware processor SoC using energy monitors integrated into power converters for self-adaptation

This paper presents a self-aware processor with energy monitoring circuits that can measure actual energy consumption of the key blocks. The monitors are embedded into on-chip DC/DC converters and generate results within 10% of accuracy with minimal power (<;0.1%) and area (<;1%) overhead. Our system, which is implemented in 0.18μm technology, is designed to be voltage scalable from 1.8V down to 0.6V. Low-voltage SRAM operation is made possible through the use of 8T bit-cells and write-assists. The d-caches are designed to be re-configurable in associativity and size to adapt to compute- versus cache-bound phases of applications. Cache configuration is performed in <; 3 clock cycles including tag invalidation. These hardware features enable a software self-aware computation engine (SEEC) to dynamically adapt the processor to meet performance and energy goals. Measurement results show that up to 8.4× energy savings can be achieved with DVFS and self-adaptation.