Miracle-dz/UniFAR-FTUs huggingface dataset:
Ensemble neural network rule extraction using Re-RX algorithm

In this paper, we propose a feed-forward ensemble neural network for data sets having both discrete and continuous attributes. The ensemble provides results that are more accurate than those of conventional neural networks and expresses more comprehensible rules. Through the separation of data in compliance with primary rules, it enables the generation of secondary rules that apply solely to instances of non-compliance with the primary rules and maintain higher accuracy than is conventionally attainable. We demonstrate the high performance of the ensemble neural network with rules extracted by Re-RX, and verify that it can reduce the complexity of handling multiple neural networks.
Good Guys vs. Bad Guys: Countering Cheating in Peer-to-Peer Authority Computations over Social Networks

Eigenvector computations are an important building block for computing authority, trust, and reputation scores in social networks and other graphs. In peer-to-peer networks or other forms of decentralized settings (such as multi-agent platforms), this kind of analysis needs to be performed in a distributed manner and requires bilateral data exchanges between peers. This gives rise to the problem that dishonest peers may cheat in order to manipulate the computation’s outcome. This paper presents a distributed algorithm for countering the eects of such misbehavior, under the assumption that the fraction of dishonest peers is bounded and that there is an unforgeable mechanism for peer identities, which can be implemented using security tools available. The algorithm is based on general principles of replication and randomization and thus widely applicable to social network analysis, web link analysis, and other problems of this kind. Our algorithm converges to the correct result that the honest peers alone would compute. Experiments, on a realworld dataset from a large social-tagging platform, demonstrate the practical viability and performance properties of our algorithm.
Application of adaptive sliding mode control with integral/exponential adaptation law to mechanical manipulators

In this paper, we discuss the application of a recently proposed adaptive sliding mode control (ASMC) design with a novel switching gain dynamics, called integral/exponential adaptation law, to a five-link robot manipulator with uncertain dynamics. The proposed design does not require a priori knowledge of the upper bounds of perturbations. Robust stability with finite time convergence (FTC) is obtained with low chatter on control action and fast transient performance. The simulation results demonstrate the effectiveness of the proposed design.
Antiangiogenesis Mediates Cisplatin-Induced Peripheral Neuropathy: Attenuation or Reversal by Local Vascular Endothelial Growth Factor Gene Therapy Without Augmenting Tumor Growth

Background—Toxic neuropathies induced by cisplatin and other chemotherapeutic agents are important clinical problems because of their high incidence, their lack of effective treatment, and the fact that neuropathy represents a dose-limiting factor for these therapies. The pathogenic basis for toxic neuropathies induced by chemotherapeutic agents has not been completely elucidated. Methods and Results—We investigated the hypothesis that experimental toxic neuropathy results from an antiangiogenic effect of these drugs, resulting in destruction of the vasa nervorum, and accordingly that the neuropathy could be prevented or reversed by locally administered VEGF gene transfer without augmenting tumor growth. In an animal model of cisplatin-induced neuropathy, nerve blood flow was markedly attenuated, and there was a profound reduction in the number of vasa nervorum associated with marked endothelial cell apoptosis, resulting in a severe peripheral neuropathy with focal axonal degeneration characteristic of ischemic neuropathy. After intramuscular gene transfer of naked plasmid DNA encoding VEGF-1 in animals with an established neuropathy, vascularity and blood flow returned to levels similar to those of control rats, peripheral nerve function was restored, and histological nerve architecture was normalized. Gene therapy administered in parallel with cisplatin chemotherapy completely attenuated endothelial cell apoptosis and inhibited destruction of nerve vasculature, deterioration of nerve function, and axonal degeneration. In a rat tumor model, VEGF gene transfer administered locally did not alter tumor growth or vascularity. Conclusions—These findings implicate microvascular damage as the basis for toxic neuropathy induced by cisplatin and suggest that local angiogenic gene therapy may constitute a novel prevention or treatment for this disorder without augmenting tumor growth or vascularization.
Photo Tagging by Collection-Aware People Recognition

Some mature ﬁndings in person recognition research restrict their use cases for dealing with near frontal face poses under controlled environments conditions. Such special pose and environment conditions can be accepted if imposed as a requirement for security applications, but they are not reasonable constraints when dealing with personal collections. In this paper a person recognition approach is proposed designed for aiding the task of personal collections tagging under non-controlled conditions. It can be generally described as a collection-aware clustering approach, that evaluates people appearance across the photo set. A classiﬁcatory procedure working over a trained Ko-honen network is proposed. The network is responsible for learning people appearance, working over a dynamically reduced feature space.
Potential Applications of a CONUS Sounding Climatology Developed at the Storm Prediction Center

The Storm Prediction Center (SPC) maintains an internal database of observational soundings from the contiguous United States (CONUS), dating back to the 1940s and 1950s for many sites. This database has been the source of extensive development in both research and operational forecasting over the past several decades. Previous studies utilizing this database have primarily focused on individual severe phenomena using proximity soundings (e.g., Evans and Doswell 2001; Thompson et al. 2003).
Conflict characterization and Analysis of Non Functional Requirements: An experimental approach

Prior studies reveal that conflicts among Non Functional Requirements (NFRs) are not always absolute. They can also be relative depending on the context of the system being developed. Given that existing techniques to manage the NFRs conflicts are mainly focused on cataloguing the interrelationships among various types of NFRs, hence a technique to manage the NFRs conflicts with respect to NFRs relative characteristic is needed. This paper presents a novel framework to manage the conflicts among NFRs with respect to NFRs relative characteristic. By applying an experimental approach, the quantitative evidence of NFRs conflicts will be obtained and modeled. NFRs metrics and measures will be used in the experiments as parameters to generate the quantitative evidence. This evidence can then allow developers to identify and reason about the NFRs conflicts. We also provide an example of how this framework could be applied.
Characterizing Large-Scale HPC Applications through Trace extrapolation

The analysis and understanding of large-scale application behavior is critical for effectively utilizing existing HPC resources and making design decisions for upcoming systems. In this work we utilize the information about the behavior of an MPI application at a series of smaller core counts to characterize its behavior at a much larger core count. Our methodology first captures the application's behavior via a set of features that are important for both performance and energy (cache hit rates, floating point intensity, ILP, etc.). We then find the best statistical fit from among a set of canonical functions in terms of how these features change across a series of small core counts. The models for a given feature can then be utilized to generate an extrapolated trace of the application at scale. The accuracy of the extrapolated traces is evaluated by calculating the error of the extrapolated trace relative to an actual trace for two large-scale applications, UH3D and SPECFEM3D. The accuracy of the fully extrapolated traces is further evaluated by comparing the results of building performance models using both the extrapolated trace along with an actual trace in order to predict application performance. For these two full-scale HPC applications, performance models built using the extrapolated traces predicted the runtime with absolute relative errors of less than 5%.
Mutation of SENP1/SuPr-2 Reveals an Essential Role for Desumoylation in Mouse Development

ABSTRACT The covalent modification of proteins by the small ubiquitin-like protein SUMO has been implicated in the regulation of numerous biological processes, including nucleocytoplasmic transport, genomic stability, and gene transcription. Sumoylation occurs by a multienzyme process similar to ubiquitination and, in Saccharomyces cerevisiae, is reversed by desumoylating enzymes encoded by the Ulp1 and Smt4/Ulp2 genes. The physiological importance of desumoylation has been revealed by mutations in either gene, which lead to nonoverlapping defects in cell cycle transition and meiosis. Several mammalian Ulp homologues have been identified, but, to date, nothing is known of the phenotypic effects of their loss of function. Here, we describe a random retroviral insertional mutation of one homolog, mouse SENP1/SuPr-2. The mutation causes increased steady-state levels of the sumoylated forms of a number of proteins and results in placental abnormalities incompatible with embryonic development. Our findings provide the first insight into the critical importance of regulating sumoylation in mammals.
A description length approach to determining the number of k-means clusters

We present an asymptotic criterion to determine the optimal number of clusters in k-means. We consider k-means as data compression, and propose to adopt the number of clusters that minimizes the estimated description length after compression. Here we report two types of compression ratio based on two ways to quantify the description length of data after compression. This approach further offers a way to evaluate whether clusters obtained with k-means have a hierarchical structure by examining whether multi-stage compression can further reduce the description length. We applied our criteria to determine the number of clusters to synthetic data and empirical neuroimaging data to observe the behavior of the criteria across different types of data set and suitability of the two types of criteria for different datasets. We found that our method can offer reasonable clustering results that are useful for dimension reduction. While our numerical results revealed dependency of our criteria on the various aspects of dataset such as the dimensionality, the description length approach proposed here provides a useful guidance to determine the number of clusters in a principled manner when underlying properties of the data are unknown and only inferred from observation of data.
A Query-Focused Multi-Document Summarizer Based on Lexical Chains

This paper presents our work on queryfocused multi-document summarization with the enhanced IS_SUM system. We focus on improving its lexical chain algorithm for efficiency enhancement, applying the WordNet for similarity calculation and adapting it to query-focused multi-document summarization. We present its performance in terms of its official DUC2007 evaluation results together with some other improvements.
Nocturnal awakenings and pediatric injury risk.

OBJECTIVE This study was designed to examine relations between nocturnal awakenings and unintentional injury risk among toddlers. METHODS A nationally representative sample of 799 children was followed longitudinally from birth through 36 months. Patterns of nocturnal awakening were assessed by parent-report at ages 6, 15, 24 and 36 months, and injury events were reported at quarterly intervals over the same time period. A range of external covariates, including positive and negative affect and externalizing behavior; maternal stress, maternal depression, and parenting style; and family socioeconomic status were measured. RESULTS A persistent pattern of very mild nocturnal awakening was related to increased risk of injury during the toddler years, and that relation held after controlling for a range of potential covariates. CONCLUSIONS A pattern of persistent nocturnal awakening appears to be related to unintentional injury risk in toddlers.
A high-efficiency fully digital synchronous buck converter power delivery system based on a finite-state machine

A fully digital, self-adjusting, and high-efficiency power supply system has been developed based on a finite-state machine (FSM) control scheme. The system dynamically monitors circuit performance with a delay line and provides a substantially constant minimum supply voltage for digital processors to properly operate at a given frequency. In addition, the system adjusts the supply voltage to the required minimum under different process, voltage, and temperature and load conditions. The design issues of the fully digital power delivery system are discussed and addressed. This digital FSM scheme significantly reduces the complexity of control-loop implementation (<1800 gates) and power consumption (< 100 /spl mu/W at 1.2 V) compared to other approaches based on proportional-integral-differential control. The power delivery control system is fabricated in a 0.13-/spl mu/m CMOS process and its core die size is 160 /spl times/ 110 /spl mu/m/sup 2/.
ODE Constrained Mixture Modelling: A Method for Unraveling Subpopulation Structures and Dynamics

Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity.
Declining volatility, a general property of disparate systems: from fossils, to stocks, to the stars

Abstract: There may be structural principles pertaining to the general behaviour of systems that lead to similarities in a variety of different contexts. Classic examples include the descriptive power of fractals, the importance of surface area to volume constraints, the universality of entropy in systems, and mathematical rules of growth and form. Documenting such overarching principles may represent a rejoinder to the Neodarwinian synthesis that emphasizes adaptation and competition. Instead, these principles could indicate the importance of constraint and structure on form and evolution. Here, we document a potential example of a phenomenon suggesting congruent behaviour of very different systems. We focus on the notion that universally there has been a tendency for more volatile entities to disappear from systems such that the net volatility in these systems tends to decline. We specifically focus on origination and extinction rates in the marine animal fossil record, the performance of stocks in the stock market, and the characters of stars and stellar systems. We consider the evidence that each is experiencing declining volatility, and also consider the broader significance of this.
A Micro-Computed Tomography Technique to Study the Quality of Fibre Optics Embedded in Composite Materials

Quality of embedment of optical fibre sensors in carbon fibre-reinforced polymers plays an important role in the resultant properties of the composite, as well as for the correct monitoring of the structure. Therefore, availability of a tool able to check the optical fibre sensor-composite interaction becomes essential. High-resolution 3D X-ray Micro-Computed Tomography, or Micro-CT, is a relatively new non-destructive inspection technique which enables investigations of the internal structure of a sample without actually compromising its integrity. In this work the feasibility of inspecting the position, the orientation and, more generally, the quality of the embedment of an optical fibre sensor in a carbon fibre reinforced laminate at unit cell level have been proven.
Content-based image retrieval with hierarchical Gaussian Process bandits with self-organizing maps

A content-based image retrieval system based on relevance feedback is proposed. The system relies on an interactive search paradigm where at each round a user is presented with k images and selects the one closest to her target. The approach based on hierarchical Gaussian Process (GP) bandits is used to trade exploration and exploitation in presenting the images in each round. Experimental results show that the new approach compares favorably with previous work.
Improving aggregate utility and fairness in multi-lane vehicle-to-infrastructure networks

In IEEE 802.11p based vehicle-to-infrastructure networks, there exists an access unfairness problem which results due to the existence of multi-velocity vehicles in the network. A high speed vehicle has less opportunity to communicate with the road side unit (RSU), when competed with a low speed vehicle, owing to their reduced time in which the vehicle resides within the scope of RSU. Accordingly, the data transferred by high speed vehicle is in reduced amount as compared to that of vehicle with lower speed. In this paper, we focus on resolving the unfairness problem by altering the transmission opportunity (TXOP) limit of vehicles in accordance to their average velocities. Further, to improve the aggregate data transferred, a novel scheme called block Acknowledgement (BA) scheme is introduced in V2I networks. BA scheme reduces the overhead of ACK transmission by integrating multiple ACKs of data frames in a TXOP limit into a block ACK frame. Considering a single-rate, multi-lane, V2I network, we prove that, fairness (equal chance of communicating with RSU) can be attained; simultaneously, aggregate data transferred can be improved when BA scheme is implemented along with TXOP differentiation. Analytical results are provided and validated using simulation studies. Unfairness, Fairness, IEEE 802.11p, TXOP differentiation, Block ACK, V2I Networks
An assessment of methods for computing radiative forcing in climate models

Because the radiative forcing is rarely computed separately when performing climate model simulations, several alternative methods have been developed to estimate both the instantaneous (or direct) forcing and the adjusted forcing. The adjusted forcing accounts for the radiative impact arising from the adjustment of climate variables to the instantaneous forcing, independent of any surface warming. Using climate model experiments performed for CMIP5, we find the adjusted forcing for 4 × CO2 ranges from roughly 5.5–9 W m−2 in current models. This range is shown to be consistent between different methods of estimating the adjusted forcing. Decomposition using radiative kernels and offline double-call radiative transfer calculations indicates that the spread receives a substantial contribution (roughly 50%) from intermodel differences in the instantaneous component of the radiative forcing. Moreover, nearly all of the spread in adjusted forcing can be accounted for by differences in the instantaneous forcing and stratospheric adjustment, implying that tropospheric adjustments to CO2 play only a secondary role. This suggests that differences in modeling radiative transfer are responsible for substantial differences in the projected climate response and underscores the need to archive double-call radiative transfer calculations of the instantaneous forcing as a routine diagnostic.
Combinatorics of the Breakage-Fusion-Bridge Mechanism

The breakage-fusion-bridge (BFB) mechanism was proposed over seven decades ago and is a source of genomic variability and gene amplification in cancer. Here we formally model and analyze the BFB mechanism, to our knowledge the first time this has been undertaken. We show that BFB can be modeled as successive inverted prefix duplications of a string. Using this model, we show that BFB can achieve a surprisingly broad range of amplification patterns. We find that a sequence of BFB operations can be found that nearly fits most patterns of copy number increases along a chromosome. We conclude that this limits the usefulness of methods like array CGH for detecting BFB.
A dual spinal cord lesion paradigm to study spinal locomotor plasticity in the cat

After a complete spinal cord injury (SCI) at the lowest thoracic level (T13), adult cats trained to walk on a treadmill can recover hindlimb locomotion within 2–3 weeks, resulting from the activity of a spinal circuitry termed the central pattern generator (CPG). The role of this spinal circuitry in the recovery of locomotion after partial SCIs, when part of descending pathways can still access the CPG, is not yet fully understood. Using a dual spinal lesion paradigm (first hemisection at T10 followed three weeks after by a complete spinalization at T13), we showed that major changes occurred in this locomotor spinal circuitry. These plastic changes at the spinal cord level could participate in the recovery of locomotion after partial SCI. This short review describes the main findings of this paradigm in adult cats.
A measurement driven, 802.11 anti-jamming system

Dense, unmanaged 802.11 deployments tempt saboteurs into launching jamming attacks by injecting malicious interference. Nowadays, jammers can be portable devices that transmit intermittently at low power in order to conserve energy. In this paper, we first conduct extensive experiments on an indoor 802.11 network to assess the ability of two physical layer functions, rate adaptation and power control, in mitigating jamming. In the presence of a jammer we find that: (a) the use of popular rate adaptation algorithms can significantly degrade network performance and, (b) appropriate tuning of the carrier sensing threshold allows a transmitter to send packets even when being jammed and enables a receiver capture the desired signal. Based on our findings, we build ARES, an Anti-jamming REinforcement System, which tunes the parameters of rate adaptation and power control to improve the performance in the presence of jammers. ARES ensures that operations under benign conditions are unaffected. To demonstrate the effectiveness and generality of ARES, we evaluate it in three wireless testbeds: (a) an 802.11n WLAN with MIMO nodes, (b) an 802.11a/g mesh network with mobile jammers and (c) an 802.11a WLAN. We observe that ARES improves the network throughput across all testbeds by up to 150%.