Miracle-dz/UniFAR-FTUs huggingface dataset:
QoS–aware Mesh-based Multicast Routing Protocols in Edge Ad Hoc Networks: Concepts and Challenges

Multicast communication plays a pivotal role in Edge based Mobile Ad hoc Networks (MANETs). MANETs can provide low-cost self-configuring devices for multimedia data communication that can be used in military battlefield, disaster management, connected living, and public safety networks. A Multicast communication should increase the network performance by decreasing the bandwidth consumption, battery power, and routing overhead. In recent years, a number of multicast routing protocols (MRPs) have been proposed to resolve above listed challenges. Some of them are used for dynamic establishment of reliable route for multimedia data communication. This article provides a detailed survey of the merits and demerits of the recently developed techniques. An ample study of various Quality of Service (QoS) techniques and enhancement is also presented. Later, mesh topology-based MRPs are classified according to enhancement in routing mechanism and QoS modification. This article covers the most recent, robust, and reliable QoS-aware mesh based MRPs, classified on the basis of their operational features, and pros and cons. Finally, a comparative study has been presented on the basis of their performance parameters on the proposed protocols.
Is it hard to retrieve an error-correcting pair?

Code-based cryptography is an interesting alternative to classic number-theory Public-Key Cryptosystems (PKC) since it is conjectured to be secure against quantum computer attacks. Many families of codes have been proposed for these cryp-tosystems. One of the main requirements is having high performance t-bounded decoding algorithms which is achieved in the case the code has a terror correcting pair (ECP). The class of codes with a t-ECP is proposed for the McEliece cryp-tosystem. The hardness of retrieving the t-ECP for a given code is considered. To this end we have to solve a large system of bilinear equations. Two possible induction procedures are considered, one for sub/super ECP's and one by punctur-ing/shortening. In both procedures in every step only a few bilinear equations need to be solved.
Automatic construction of probabilistic dynamic bidirectional reflectance distribution functions from reflection screen images

The reflections of high energy laser off surfaces can present hazards to persons and instruments at significant distances. The heating from these lasers cause changes in the reflection characteristics of surfaces they impact. As such, the reflections from these surfaces cannot be properly modeled with static bidirectional reflectance distribution functions (BRDFs), but require time-dynamic BRDFs. Moreover, the time-evolution of the surface reflections is not deterministic, but can vary even when the materials and irradiance conditions are nearly identical, such that only probabilistic characterization is realistic. Due to the swiftly changing nature of the reflections, traditional BRDF measurements with goniometric instruments is impossible, and BRDFs must be deduced from images of the reflected light incident on a screen which intercepts a portion of the reflection solid angle. A model has been constructed to describe these complex probabilistic dynamic BRDFs with only a moderate number of intuitive parameters, where these parameters have central values and statistical variances. These simple parametric representations are appropriate for use in predictive modeling codes and are also easily adjustable to allow facile exploration of the sensitivity of hazards to laser, material, and model uncertainties. An automated procedure has been created for determining appropriate parameter values and variances from captured screen images, without the need for case-by-case human judgment. Examples of the parameter determination procedure are presented.
The Lottery Ticket Hypothesis : Training Pruned Neural Network Architectures

Recent work on neural network pruning indicates that, at training time, neural networks need to be significantly larger in size than is necessary to represent the eventual functions that they learn. This paper articulates a new hypothesis to explain this phenomenon. This conjecture, which we term the lottery ticket hypothesis, proposes that successful training depends on lucky random initialization of a smaller subcomponent of the network. Larger networks have more of these “lottery tickets,” meaning they are more likely to luck out with a subcomponent initialized in a configuration amenable to successful optimization. This paper conducts a series of experiments with XOR, MNIST (for fully-connected networks), and CIFAR10 (for convolutional networks) that support the lottery ticket hypothesis. In particular, we identify these fortuitously-initialized subcomponents by pruning low-magnitude weights from trained networks. We then demonstrate that these subcomponents can be successfully retrained in isolation so long as the subnetworks are given the same initializations as they had at the beginning of the training process. Initialized as such, these small networks reliably converge successfully, often faster than the original network at the same level of accuracy. However, when these subcomponents are randomly reinitialized or rearranged, they perform worse than the original network. In other words, large networks that train successfully contain small subnetworks with initializations conducive to optimization. The lottery ticket hypothesis and its connection to pruning are a step toward developing architectures, initializations, and training strategies that make it possible to solve the same problems with much smaller networks.
Population Dynamics in Active Galactic Nuclei

The goal of this thesis is to present an approach to understanding the dynamics that govern the evolution of active galactic nuclei (AGN) in general, and those associated with spiral galaxies in particular. This approach starts with the continuity equation governing the mass function for a population of supermassive black holes (SMBHs). This approach is then extended to the luminosity function for AGN. Where the dynamical parameters that govern accretion are fairly well known, those values are adopted. The values that are not as well known are constrained by comparing evolved luminosity functions with observed luminosity functions. Boundary conditions for this model are typically taken to be locally observed mass functions unless otherwise speci ed. It can be concluded that the Eddington ratio is likely a function of time and possibly a function of mass. The duty cycle is likely a function of both time and mass. The qualitative evolution of the Eddington ratio and duty cycle can be inferred from the luminosity evolution and density evolution of observed luminosity functions respectively. Additionally, models with a break in the duty cycle agree well with observations. This may be an indication of feedback within the host galaxy. The e ect of mergers is also examined brie y, and the results imply lower Eddington ratios than models without mergers.
Why is it so Difficult to Find An Effect of Exchange Rate Risk on Trade?

The question whether exchange rate risk a⁄ects trade has received considerable attention in the literature. However, the conclusions are still mixed. This paper analyzes why it is so di¢cult to obtain a clear answer from time series analyses. We use data on bilateral aggregate US exports to the other G7 countries. The results show that export decisions are mostly a⁄ected by the exchange rate about one year later. The riskiness of the exchange rate at such a long horizon appears fairly constant over time with only short-term (cid:135)uctuations. This makes it di¢cult to discover the true e⁄ect of exchange risk on trade from the limited time series data that are typically available
Why Is It so Di¢cult to Find an E¤ect of Exchange Rate Risk on Trade?

The question whether exchange rate risk a¤ects trade has received considerable attention in the literature. However, the conclusions are still mixed. This paper analyzes why it is so di¢cult to obtain a clear answer from time series analyses. We use data on bilateral aggregate US exports to the other G7 countries. The results show that export decisions are mostly a¤ected by the exchange rate about one year later. The riskiness of the exchange rate at such a long horizon appears fairly constant over time with only short-term ‡uctuations. This makes it di¢cult to discover the true e¤ect of exchange risk on trade from the limited time series data that are typically available.
A structural reliability-based sensitivity analysis method using particles swarm optimization: relative convergence rate

This paper proposes a novel reliability-based sensitivity analysis (SA) method, namely relative convergence rate of random variables using particles swarm optimization (PSO). The convergence rate of a random variable during the optimum evolution process reflects the sensitivity of the objective function with respect to the random variables. An optimized group strategy is proposed to consider the fluctuation of the convergence rate of a variable during the optimum process. The coefficient of variation (COV) for candidate particles and the relative convergence rate of a random variable can be calculated using the particles in the optimized group. The smaller the COV for candidate particles, i.e., the larger the relative convergence rate, the more sensitive the objective function with respect to the variable. Three examples are available for the application of this method, and the results indicate that the sensitivity of the reliability index with respect to the variable obtained using the PSO technique and gradient of limit-state function is the same in the quantitative sense. 概 要目 的采用粒子群优化算法(PSO)提高可靠指标计算效率, 探讨PSO 求解过程中粒子群在不同维上统计特性及其收敛速率表征的物理含义, 研究优化过程中粒子收敛速率与随机变量敏感性的关系, 提出可靠度敏感性分析新方法。 创新点1. 根据PSO 寻优过程中粒子在不同维上收敛速率不同, 提出采用收敛速率表征随机变量的敏感性; 2. 建立最优化策略组避免粒子群收敛过程中产生波动, 保证最优化策略组内粒子在不同维上连续收敛, 定义相对收敛率表征随机变量敏感性。 方 法1. 根据Hasofer-Lind 可靠指标的几何意义, 建立可靠指标的优化模型, 提出采用改进的PSO 求解可靠指标与验算点, 采用可行策略方法处理约束条件; 2. 通过理论推导, 构造PSO 迭代过程的最优评价函数集(公式(18)), 建立最优化策略组保证粒子在不同维上连续收敛, 提出表征随机变量敏感性的相对收敛率计算公式(公式(19)); 3. 通过数值模拟并与传统基于梯度的敏感性分析计算结果比较, 验证本文所提方法的可行性和有效性。 结 论1. 相对收敛率可以表征随机变量的敏感性; 2. 最优化策略组避免相对收敛率的波动, 保证候选粒子变异系数曲线在解空间内连续收敛; 3. 最优化策略组内随机变量候选解的变异系数越小则其表征的随机变量越敏感; 4. 基于PSO的可靠度及敏感性分析对复杂问题更有效。
PAC-BAYESIAN MARGIN BOUNDS FOR CONVOLUTIONAL NEURAL NETWORKS

Deep neural networks generalize well despite having more parameters than the number of training samples. This runs contrary to traditional learning theory intuition, and generalization error bounds obtained using traditional techniques for these classification architectures are vacuous. There have been a number of recent works using Margin and PAC-Bayes analyses trying to address this problem. We start from a recent bound based on PAC-Bayes theory for fully connected networks and extend it to the convolutional setting. Our bound is orders of magnitude better than the previous estimate, and is a step towards analysing the generalization behaviour of more realistic deep convolutional architectures.
Compatibility of the Enskog kinetic theory with thermodynamics. I

It is proved that the solutions to the Enskog equation for an $N$-component gas enjoy the nice properties that are known in the context of the Boltzmann equation, to indicate its compatibility with thermodynamics, provided some restrictions are imposed on the functions $\ensuremath{\chi}$. The functions $\ensuremath{\chi}$ are introduced in the Enskog equation in order to account for correlations among particles.
Design and Implementation of the International Genetics and Translational Research in Transplantation Network

Citation for published version (APA): Keating, B. J., van Setten, J., Jacobson, P. A. , Holmes, M. V. , Verma, S. S. , Chandrupatla, H. R. , Nair, N. , Gao, H. , Li, Y. R. , Chang, B-L. , Wong, C. , Phillips, R. , Cole, B. S. , Mukhtar, E. , Zhang, W. , Cao, H. , Mohebnasab, M. , Hou, C. , Lee, T. , . Int Genetics & Translational Res T (2015). Design and Implementation of the International Genetics and Translational Research in Transplantation Network. Transplantation, 99(11), 2401-2412. https://doi.org/10.1097/TP.0000000000000913
Existence theorems for measures on continous posets, with applications to random set theory.

We state conditions on a partially ordered set L and a mapping λ, defined on a class of filters on L, under which λ extends to a measure on the minimal σ-field over this class. By applying this result to the case when L is a continuous lattice, all locally finite measures on L are identified as well as all Levy-Khinchin measures. We then characterize these kinds of measures on continuous semilattices and continuous posets. The correspondence between probability measures on the line and distribution function is a particular case of this result. We give a simple proof of the Daniell-Kolmogorov existence theorem for probability measures on products of continuous lattices
Supplementary File 2: FORESEE Data Overview and Preparation

One of the major accommodations provided by FORESEE in facilitating a rapid drug prediction model development is its rich curated data sets. More than three gigabytes of cell line, xenograft and patient data sets are downloaded, curated and structured in objects, which are designed for more convenient model development. In this text we describe the FORESEE data objects ForeseeCell and ForeseePatient. We also provide information about data sets added to FORESEE in the structure of the aforementioned objects.
Preview Estimation and Control for (Semi-) Active Suspensions

SUMMARY An active suspension with preview is tested for rounded pulses and a stochastic road surface, and is compared to a passive suspension. The spectacular performance improvement obtained for a step function as road surface is not achieved but the improvement is still significant. The frequency response of the active suspension is determined for comparison with some suspension systems found in literature An observer to reconstruct the preview information is presented. No model of the road surface is needed. From simulations, it appears that the observer reconstructs both deterministic and stochastic road surfaces satisfactory. However, the influence of measurement noise is not reduced sufficiently.
Highlights from the ANTARES neutrino telescope

ANTARES is the largest neutrino telescope currently in operation in the Northern hemisphere. Its location and the excellent optical properties of the sea water make it an excellent tool to search for potential emission from the Galactic Centre and the Galactic Plane. The ANTARES physics program includes, among others, the direct search for TeV-PeV neutrinos, indirect searches of dark matter and the detection of signals in coincidence with other cosmic messengers. This document reports a short overview of the most recent and relevant results on this topics, obtained from the analysis of the data recorded by the experiment since 2007.
Center for Policy Research Working Paper No . 45 CONTRACTING WITH LIMITED COMMITMENT : EVIDENCE FROM EMPLOYMENT-BASED HEALTH INSURANCE CONTRACTS *

When an individual’s health status is observable, but evolving over time, the key to maintaining a successful health insurance arrangement is to have the healthier members of the group cross-subsidize those who experience adverse health outcomes. We argue that impediments to worker mobility may serve to mitigate the attrition of healthy individuals from employer-sponsored insurance pools, thereby creating a de facto commitment mechanism that allows for more complete insurance of health risks than would be possible in the absence of such frictions. Using data on health insurance contracts obtained from the 1987 National Medical Expenditure Survey, we find that the quantity of insurance provided, as measured by lifetime limits on benefits and annual stop-loss amounts, is positively related to the degree of worker commitment. These results illustrate the importance of commitment in the design of long-term contracts, and provide an additional rationale for the practice of bundling health insurance with
Segmentation of the Gastrointestinal Tract MRI Using Deep Learning

This paper proposes a deep learning-based model to segment gastrointestinal tract (GI) magnetic resonance images (MRI). The application of this model will be useful in potentially accelerating treatment times and possibly improve the quality of the treatments for the patients who must undergo radiation treatments in cancer centers. The proposed model employs the U-net architecture, which provides outstanding overall performance in medical image segmentation tasks. The model that was developed through this project has a score of 81.86% using a combination of the dice coefficient and the Hausdorff distance measures, rendering it highly accurate in segmenting and contouring organs in the gastrointestinal system.
Chapter 1 MULTISENSOR FUSION UNDER UNKNOWN DISTRIBUTIONS Finite-Sample Performance Guarantees

We consider a multiple sensor system such that for each senso r the utputs are related to the actual feature values according to a certain p robability distribution. We present an overview of informational and computational a spects of a fuser that is required to combine the sensor outputs to more accura tely predict the feature, when the sensor distributions are unknown but iid m easurements are given. Our focus is on methods to compute a fuser with probabi listic guarantees in terms of distribution-free performance bounds based on a finite sample. We first discuss a number of methods based on the empirical risk minim ization approach. These methods yield a fuser which is guaranteed, with a high p robability, to be close to an optimal fuser (computable only under a complet e knowledge of sensor distributions). Then we describe the isolation fuse rs that are guaranteed to perform at least as good as the best sensor, and the project ive fusers that are guaranteed to perform at least as good as the best subset of se ns r . Then we consider physical systems wherein the training data consis ti g of actual physical values is not available. We discuss methods that utilize the physical laws to obtain a suitable fuser under these conditions.
TITAN’S UPPER ATMOSPHERE FROM CASSINI/UVIS SOLAR OCCULTATIONS

Titan’s atmosphere is composed mainly of molecular nitrogen, methane being the principal trace gas. From the analysis of 8 solar occultations measured by the Extreme Ultraviolet channel of the Ultraviolet Imaging Spectrograph (UVIS) on board Cassini, we derived vertical profiles of N2 in the range 1100–1600 km and vertical profiles of CH4 in the range 850–1300 km. The correction of instrument effects and observational effects applied to the data are described. We present CH4 mole fractions, and average temperatures for the upper atmosphere obtained from the N2 profiles. The occultations correspond to different times and locations, and an analysis of variability of density and temperature is presented. The temperatures were analyzed as a function of geographical and temporal variables, without finding a clear correlation with any of them, although a trend of decreasing temperature toward the north pole was observed. The globally averaged temperature obtained is (150 ± 1) K. We compared our results from solar occultations with those derived from other UVIS observations, as well as studies performed with other instruments. The observational data we present confirm the atmospheric variability previously observed, add new information to the global picture of Titan’s upper atmosphere composition, variability, and dynamics, and provide new constraints to photochemical models.
Physiological and anatomical evidence for an inhibitory trigemino‐oculomotor pathway in the cat

During blink down‐phase, the levator palpebrae superioris (levator) muscle is inactivated, allowing the orbicularis oculi muscle to act. For trigeminal reflex blinks, the excitatory connections from trigeminal sensory nuclei to the facial nucleus have been described, but the pathway whereby the levator is turned off have not. We examined this question by use of both physiological and anatomical approaches in the cat. Intracellular records from antidromically activated levator motoneurons revealed that periorbital electrical stimulation produced bilateral, long latency inhibitory postsynaptic potentials (IPSPs). Central electrical stimulation of the principal trigeminal nucleus produced shorter latency IPSPs. Intracellular staining revealed that these motoneurons reside in the caudal central subdivision and have 10 or more poorly branched dendrites, which extend bilaterally into the surrounding supraoculomotor area. Axons penetrated in this region could be activated from periorbital and central electrodes. Neurons labeled from tracer injections into the caudal oculomotor complex were distributed in a crescent‐shaped band that lined the ventral and rostral aspects of the pontine trigeminal sensory nucleus. Double‐label immunohistochemical procedures demonstrated that these cells were not tyrosine hydroxylase‐positive cells in the Kölliker‐Fuse area. Instead, supraorbital nerve afferents displayed a similar crescent‐shaped distribution, suggesting they drive these trigemino‐oculomotor neurons. Anterograde labeling of the trigemino‐oculomotor projection indicates that it terminates bilaterally, in and above the caudal central subdivision. These results characterize a trigemino‐oculomotor pathway that inhibits levator palpebrae motoneurons in response to blink‐producing periorbital stimuli. The bilateral distributions of trigemino‐oculomotor afferents, levator motoneurons, and their dendrites supply a morphological basis for conjugate lid movements. J. Comp. Neurol. 520:2218–2240, 2012. © 2012 Wiley Periodicals, Inc.
The Role of Ventromedial Prefrontal Cortex in Mental Time Travel and Mind Wandering

Recent research showed that a network of brain regions known as the Default Mode Network (DMN), including the ventromedial prefrontal cortex (vmPFC), is active when individuals remember the past, imagine the future, take the perspective of others, as well as during spontaneous cognition (mind wandering). The goal of this dissertation is to investigate whether the vmPFC plays a crucial role during DMN-related cognitive processes, such as MTT and mind wandering. Experiment 1 revealed that a damage to the vmPFC provokes the disruption of past and future MTT and a decreased ability to imagine future other-related episodes. vmPFC role extends to imagining events that are not self-relevant indicating that vmPFC is crucial for the imagination of complex experiences alternative to the current reality. In experiment 2, findings showed that a lesion to vmPFC disrupts the ability to construct complex atemporal scenarios. However, unlike the control groups, vmPFC patients had more difficulties in imagining future compared to fictitious experiences, suggesting that vmPFC is more critical for the simulation of future episodes. Experiment 3 revealed that these results are not explained by the disruption of non-episodic capabilities, such as narrative and working memory abilities. Furthermore, experiment 4 explored the effect of a lesion to vmPFC on the occurrence of mind wandering. A damage to the vmPFC provokes a decreased propensity to mind-wander, showing that vmPFC supports spontaneous cognition. Experiment 5 confirmed the involvement of the medial prefrontal cortex (mPFC) in supporting mind wandering. Using the transcranial direct current stimulation to inhibit the mPFC we could decrease the intensity of mind wandering in males. Together, these results point out the fundamental role of vmPFC in allowing human beings to escape the here and now, whether it occurs deliberately or spontaneously.