Miracle-dz/UniFAR-FTUs huggingface dataset:
Localization of Optic Disk Using Independent Component Analysis and Modified Structural Similarity Measure

Localization and segmentation of Optic Disk (OD) is an important prerequisite for automatic detection of Diabetic Retinopathy (DR) from digital retinal fundus images. Considerable research has been done to isolate OD with varying degrees of success but on a limited number of images. In this paper we propose a novel algorithm based on Independent Component Analysis (ICA) coupled with a modified Structural Similarity Index Measure (m-SSIM) for localization of OD. We have tested our method on 100 normal retinal images (achieving 100 % success) and 232 diseased retinal images (achieving 75% success), thereby demonstrating a significant improvement over two other existing methods.
Anonymous identification with cancelable biometrics

Cancelable biometrics were introduced by Ratha et al. in 2001 to obtain templates which are renewable and do not let come back to the original biometric trait. We extend this technique to achieve the property of untraceability among different identifications across time. To this end, we need time-dependent templates. We here describe a system relying on time-dependent cancelable biometrics and analyse its security.
Heterogeneous reasoning in learning to model

Conceptual learning in mathematics and science involves learning to coordinate multiple representation systems into smoothly functioning heterogeneous reasoning systems composed of sub-languages, graphics, mathematical representations, etc. In these heterogeneous systems information can be transformed from one representation to another by inference rules, and learning coordination is learning how and when to apply these rules. The study of heterogeneous representations in learning has had the benefit of focusing attention on the reality of representation in the ‘wild’. We propose that the concept of heterogeneity of representation should be extended from multimodal (e.g. diagrammatic plus language) systems to multiply interpreted systems, even when those systems are apparently homogeneously linguistic. We proceed by analysing, from the perspective of the heterogeneity of reasoning, three learning incidents which happened in groups of students engaged in learning the mathematics and biology involved in modelling biological populations. We observe both learning successes and failures that cannot be understood without understanding the integrations of heterogeneous systems of representation involved and the inference rules and operations required to get from one to another. The purpose of presenting real incidents in some of their undomesticated detail is that they show what phenomena a homogeneous theory of reasoning would really have to account for. We argue that this type of rich naturalistic data makes implausible the instrumentality of any reconstruction in terms of a pre-existing fully interpreted homogeneous interlingua.
Software protection for dynamically-generated code

Process-level Virtual machines (PVMs) often play a crucial role in program protection. In particular, virtualization-based tools like VMProtect and CodeVirtualizer have been shown to provide desirable obfuscation properties (i.e., resistance to disassembly and code analysis). To be efficient, many tools cache frequently-executed code in a code cache. This code is run directly on hardware and consequently may be susceptible to unintended, malicious modification after it has been generated. To thwart such modifications, this work presents a novel methodology that imparts tamper detection at run time to PVM-protected applications. Our scheme centers around the run-time creation of a network of software knots (an instruction sequence that checksums portions of the code) to detect tamper. These knots are used to check the integrity of cached code, although our techniques could be applied to check any software-protection properties. Used in conjunction with established static techniques, our solution provides a mechanism for protecting PVM-generated code from modification. We have implemented a PVM system that automatically inserts code into an application to dynamically generate polymorphic software knots. Our experiments show that PVMs do indeed provide a suitable platform for extending guard protection, without the addition of high overheads to run-time performance and memory. Our evaluations demonstrate that these knots add less than 10% overhead while providing frequent integrity checks.
Discrete spatial organization of TGFβ receptors couples receptor multimerization and signaling to cellular tension

Cell surface receptors are central to the cell's ability to generate coordinated responses to the multitude of biochemical and physical cues in the microenvironment. However, the mechanisms by which receptors enable this concerted cellular response remain unclear. To investigate the effect of cellular tension on cell surface receptors, we combined novel high-resolution imaging and single particle tracking with established biochemical assays to examine TGFβ signaling. We find that TGFβ receptors are discretely organized to segregated spatial domains at the cell surface. Integrin-rich focal adhesions organize TβRII around TβRI, limiting the integration of TβRII while sequestering TβRI at these sites. Disruption of cellular tension leads to a collapse of this spatial organization and drives formation of heteromeric TβRI/TβRII complexes and Smad activation. This work details a novel mechanism by which cellular tension regulates TGFβ receptor organization, multimerization, and function, providing new insight into the mechanisms that integrate biochemical and physical cues. DOI: http://dx.doi. org/10.7554/eLife.09300. 001
Dynamical Equations, Invariants and Spectrum Generating Algebras of Mechanical Systems with Position-Dependent Mass

We analyze the dynamical equations obeyed by a classical system with position- dependent mass. It is shown that there is a non-conservative force quadratic in the velocity associated to the variable mass. We construct the Lagrangian and the Hamiltonian for this system and find the modifications required in the Euler{Lagrange and Hamilton's equations to reproduce the appropriate Newton's dynamical law. Since the Hamiltonian is not time invariant, we get a constant of motion suited to write the dynamical equations in the form of the Hamilton's ones. The time-dependent first integrals of motion are then obtained from the factorization of such a constant. A canonical transformation is found to map the variable mass equations to those of a constant mass. As particular cases, we recover some recent results for which the dependence of the mass on the position was already unnoticed, and find new solvable potentials of the Poschl{Teller form which seem to be new. The latter are associated to either the su(1;1) or the su(2) Lie algebras depending on the sign of the Hamiltonian.
Commentator's Speech Extraction in Audio Stream of Sports Games

This paper proposes a method to deal with the problem of extracting commentator’s speech in audio stream of live sports games. First, a two-pass metric-based audio segmentation module is developed to segment the audio stream into short ones with homogeneous acoustic features. Then a model-based classification module is adopted to extract the speech segments. For robust audio classification, various audio features have been used in this paper. Finally, a music scene analysis (Music-CASA) method is adopted to remove the speech in the advertisements with minimum loss of commentator’s speech. By integrating all the techniques, an average F value of 94.79% is achieved in the commentator’s speech extraction task evaluated on eleven games of six kinds of sports.
Execution Time Compensation for Cloud Applications by Subtracting Steal Time based on Host-Level Sampling

Accurate measurement of program execution time is indispensable to time-based charge systems and performance debugging in all computer systems. However, cloud application execution time cannot be measured properly because measurement in a virtual machine (VM) includes additional time called steal time. The steal time of each program in a VM is unrecognizable by existing standard operating system (OS) tools. Therefore, it is quite difficult for performance engineers to grasp the accurate execution time of each program in a VM. In this ongoing work, we show the novel point of steal in the broad sense and describe how to compensate for function-level execution time in each program in a VM. Our novel approach works by subtracting steal time, which is based on the time-series data of host-level sampling in each function. We implement our approach as a host-level kernel module based on hardware performance counters and some user-level analysis programs. Therefore, our method requires no modification of user applications, guest OSes, a virtual machine monitor (VMM) or a host OS. Finally, our results demonstrate accurate execution time of a function-level guest program, with an overhead lower than 1% for practical use.
Constrained Ramsey numbers of graphs

Given two graphs G and H, let f(G,H) denote the minimum integer n such that in every coloring of the edges of Kn, there is either a copy of G with all edges having the same color or a copy of H with all edges having different colors. We show that f(G,H) is finite iff G is a star or H is acyclic. If S and T are trees with s and t edges, respectively, we show that 1+s(t−2)/2≤f(S,T)≤(s−1)(t2+3t). Using constructions from design theory, we establish the exact values, lying near (s−1)(t−1), for f(S,T) when S and T are certain paths or star‐like trees. © 2002 Wiley Periodicals, Inc. J Graph Theory 42: 1–16, 2003
Analgesic and Anti-Inflammatory Activities of the Methanolic Stem Bark Extract of Nyctanthes arbor-tristis Linn.

Stem bark of Nyctanthes arbor-tristis Linn. was extracted in methanol to evaluate their analgesic and anti-inflammatory activities. The analgesic activity was determined on Wistar albino rats by hot plate method, tail flick assay, and tail immersion method using Morphine sulphate as standard drug at a dose of 5 mg/kg of body weight and the results were expressed as mean increase in latency after drug administration ± SEM. The anti-inflammatory activity was assessed by Carrageenan-induced rat paw oedema using diclofenac sodium as standard drug at a dose of 100 mg/kg of body weight and expressed in terms of mean increase in paw volume ± SEM. Stem bark extract was given at a dose of 250 mg/kg and 500 mg/kg of body weight. Both standard drugs and extract were administered orally to the animals. Control received distilled water orally. Results showed that Nyctanthes arbor-tristis Linn. had potent analgesic and anti-inflammatory activities.
Late-Successional and Old-Growth Forests in the Northeastern United States: Structure, Dynamics, and Prospects for Restoration

Restoration of old-growth forest structure is an emerging silvicultural goal, especially in those regions where old-growth abundance falls below the historic range of variability. However, longitudinal studies of old-growth dynamics that can inform silvicultural and policy options are few. We analyzed the change in structure, including stand density, diameter distribution, and the abundance of large live, standing dead, and downed dead trees on 58 late-successional and old-growth plots in Maine, USA, and compared these to regional data from the U.S. Forest Inventory and Analysis program. Structural dynamics on the late-successional plots reflected orderly change associated with density-dependent growth and mortality, but dynamics on the old-growth plots were more variable. Some plots experienced heavy mortality associated with beech bark disease. Diameter distributions conformed poorly to a classic exponential distribution, and did not converge toward such a distribution at the plot scale. Although large live trees showed a broad trend of increasing density in regional forests, recent harvesting patterns offset a considerable fraction of those gains, while mean diameter was static and the number of large dead trees was weakly declining. Even though forests of the northeast are aging,
Security Issues in BitTorrent like P 2 P Streaming Systems

We present a streaming protocol that addresses the security issues pertaining to BitTorrent like P2P systems. Any efficient streaming system would not be effective if it cannot withstand security threats. We focus on free rider's, whitewasher's and malicious payload insertion attacks which implicitly affect Quality of Service like important metrics for the streaming system. We propose a novel idea of alliance formation, wherein the nodes collaborate with their preferred participating peers for a symbiotic association. The protocol enforces a strict policy that dissuades free riders and whitewashers from their selfish behavior. We propose a lightweight integrity checking algorithm for malicious garbled payload insertion to guard against security threats to the swarm. We present an evaluative comparison of the system performance in a cheating node free environment versus system with prevalent threats. Our simulation results show that cheating and malicious node problem can be significantly reduced by our proposed protocol. We explore the security vulnerabilities in the contemporary p2p file sharing systems and make security recommendations for the same.
Model checking UML Statechart diagrams using JACK

Statechart diagrams provide a graphical notation for describing dynamic aspects of system behaviour within the Unified Modelling Language (UML). In this paper, we present a branching-time model-checking approach to the automatic verification of the formal correctness of UML Statechart diagram specifications. We use a formal operational semantics for building a labelled transition system (automaton) which is then used as a model to be checked against correctness requirements expressed in Action-Based Temporal Logic (ACTL). Our reference verification environment is JACK, where automata are represented in a standard format, which facilitates the use of different tools for automatic verification.
A Range-Based Distributed Localization Algorithm for Wireless Sensor Networks

Aiming at the problem of the localization error and localization coverage rate of wireless sensor network nodes, a range-based distributed localization algorithm is proposed in this paper. The algorithm can reduce the localization error by introducing the confidence factor that makes the credibility as weights adding to the coordinate calculation of the unknown nodes. Simulation results show that this algorithm can effectively improve the positioning accuracy and promote localization coverage rate compared to classic Euclidean localization algorithm.
Adaptive estimation for Hawkes processes; application to genome analysis

The aim of this paper is to provide a new method for the detection of either favored or avoided distances between genomic events along DNA sequences. These events are modeled by a Hawkes’ process. The biological problem is actually complex enough to need a non asymptotic penalized model selection approach. We provide a theoretical penalty that satisfies an oracle inequality even for quite complex families of models. The consecutive theoretical estimator is
Jackknife Empirical Likelihood-Based Confidence Intervals for Low Income Proportions with Missing Data

The estimation of low income proportions plays an important role in comparisons of poverty in different countries. In most countries, the stability of the society and the development of economics depend on the estimation of low income proportions. An accurate estimation of a low income proportion has a crucial role for the development of the natural economy and the improvement of people’s living standards. In this thesis, the Jackknife empirical likelihood method is employed to construct confidence intervals for a low income proportion when the observed data had missing values. Comprehensive simulation studies are conducted to compare the relative performances of two Jackknife empirical likelihoodbased confidence intervals for low income proportions in terms of coverage probability. A real data example is used to illustrate the application of the proposed methods. INDEX WORDS: Jackknife, Empirical Likelihood, Missing data, Auxiliary information, Coverage Probability, Low Income Proportion, Income distribution JACKKNIFE EMPIRICAL LIKELIHOOD-BASED INFERENCES FOR A LOW INCOME PROPORTION WITH MISSING DATA
Incarcerated Mothers of Minor Children: Physical Health, Substance Use, and Mental Health Needs

Mothers of minor children serving sentences in a large Midwestern jail were screened for potential substance use problems and asked to report their physical and mental health status and treatment experiences. Of mothers screened for substance use problems, 72.1% had positive findings on the AUDIT-12, 56.7% reported at least one serious physical health problem, and 67.1% had received mental health treatment. More than two-thirds (68.8%) of the 240 mothers reported a co-occurring condition, and a third (33.8%) reported problems in all three spheres (substance use, mental health, and physical health). The relationship among the three health-related problems is examined as well as the characteristics of mothers related to having co-occurring health conditions. Given that the overwhelming majority of mothers reported more than one health-related problem, the changes to policy and practice need to avoid simplistic solutions.
Genome-Wide Association Analysis of Meat Quality Traits in a Porcine Large White × Minzhu Intercross Population

Pork quality is an economically important trait and one of the main selection criteria for breeding in the swine industry. In this genome-wide association study (GWAS), 455 pigs from a porcine Large White × Minzhu intercross population were genotyped using the Illumina PorcineSNP60K Beadchip, and phenotyped for intramuscular fat content (IMF), marbling, moisture, color L*, color a*, color b* and color score in the longissimus muscle (LM). Association tests between each trait and the SNPs were performed via the Genome Wide Rapid Association using the Mixed Model and Regression-Genomic Control (GRAMMAR-GC) approach. From the Ensembl porcine database, SNP annotation was implemented using Sus scrofa Build 9. A total of 45 SNPs showed significant association with one or multiple meat quality traits. Of the 45 SNPs, 36 were located on SSC12. These significantly associated SNPs aligned to or were in close approximation to previously reported quantitative trait loci (QTL) and some were located within introns of previously reported candidate genes. Two haplotype blocks ASGA0100525-ASGA0055225-ALGA0067099-MARC0004712-DIAS0000861, and ASGA0085522-H3GA0056170 were detected in the significant region. The first block contained the genes MYH1, MYH2 and MYH4. A SNP (ASGA0094812) within an intron of the USP43 gene was significantly associated with five meat quality traits. The present results effectively narrowed down the associated regions compared to previous QTL studies and revealed haplotypes and candidate genes on SSC12 for meat quality traits in pigs.
Transient detection of spin-labeled myosin subfragment 1 conformational states during ATP hydrolysis.

We have used time-resolved electron paramagnetic resonance spectroscopy and caged ATP to detect nucleotide-induced changes in the conformational state of spin-labeled myosin heads (IASL-S1). Changes in the internal rotational dynamics of IASL-S1 were monitored with millisecond time resolution during the pre-steady-state phase of ATP hydrolysis. The changes in the internal protein dynamics were rigorously correlated with specific biochemical kinetic transitions, allowing us to observe directly the dynamic sequence of structural changes in IASL-S1 during the binding and hydrolysis of ATP. When caged ATP was photolyzed (producing 500 microM ATP) in the presence of 100 microM IASL-S1, the EPR signal intensity rose transiently to the steady-state ATPase level, indicating increased rotational motion about the SH1 region of the myosin head. Kinetic and spectral analyses have resolved two phases of this transient, one representing the population of the M*. ATP state and the other representing the population of the M**. ADP.Pi state. We conclude that two motionally distinct states of the myosin head are present during ATP hydrolysis and that these states represent distinct conformational states that can be correlated with specific biochemical intermediates. Since specific labeling of myosin heads with IASL has been achieved in skinned muscle fibers, this study establishes the feasibility for the first direct detection and resolution of myosin's conformational transients during muscle contraction.
A framework for applying the principles of depth perception to information visualization

During the visualization of 3D content, using the depth cues selectively to support the design goals and enabling a user to perceive the spatial relationships between the objects are important concerns. In this novel solution, we automate this process by proposing a framework that determines important depth cues for the input scene and the rendering methods to provide these cues. While determining the importance of the cues, we consider the user's tasks and the scene's spatial layout. The importance of each depth cue is calculated using a fuzzy logic--based decision system. Then, suitable rendering methods that provide the important cues are selected by performing a cost-profit analysis on the rendering costs of the methods and their contribution to depth perception. Possible cue conflicts are considered and handled in the system. We also provide formal experimental studies designed for several visualization tasks. A statistical analysis of the experiments verifies the success of our framework.
Visualization Regularizers for Neural Network based Image Recognition

The success of deep neural networks is mostly due their ability to learn meaningful features from the data. Features learned in the hidden layers of deep neural networks trained in computer vision tasks have been shown to be similar to mid-level vision features. We leverage this fact in this work and propose the visualization regularizer for image tasks. The proposed regularization technique enforces smoothness of the features learned by hidden nodes and turns out to be a special case of Tikhonov regularization. We achieve higher classification accuracy as compared to existing regularizers such as the L2 norm regularizer and dropout, on benchmark datasets without changing the training computational complexity.
Neuronal pentraxins mediate silent synapse conversion in the developing visual system

Neuronal pentraxins (NPs) are hypothesized to play important roles in the recruitment of AMPA receptors (AMPARs) to immature synapses, yet a physiological role for NPs at nascent synapses in vivo has remained elusive. Here we report that the loss of NP1 and NP2 (NP1/2) leads to a dramatic and specific reduction in AMPAR-mediated transmission at developing visual system synapses. In thalamic slices taken from early postnatal mice (<P10) NP1/2 knock-out (KO) neurons displayed severely reduced AMPAR-mediated retinogeniculate transmission. The reduced currents reflected an increased number of silent synapses with no change in quantal amplitude or presynaptic release. These are the first data to demonstrate that NP1/2 are required in vivo for the normal development of AMPAR-mediated transmission. In addition, they suggest a novel role for NP1/2 in silent synapse conversion during a discrete developmental period when visual circuit connections are undergoing eye-specific refinement. After this period, retinogeniculate transmission not only recovered in the knock-outs but became excessive. The enhanced currents were attributable, at least in part, to a deficit in the characteristic elimination of functional inputs that occurs in the developing dLGN. These data indicate that the loss of NP1/2 disrupts several aspects of retinogeniculate development including the initial establishment of AMPAR transmission and the subsequent elimination of inappropriate circuit connections.