Miracle-dz/UniFAR-FTUs huggingface dataset:
Asymptotic Performance Analysis of Time-Frequency-Domain Spread MC DS-CDMA Systems Employing MMSE Multiuser Detection

In this contribution the asymptotic signal-to-interference-plus-noise ratio (SINR) performance of multicarrier direct-sequence code-division multiple-access systems employing time-frequency-domain spreading, i.e., of the TF/MC DS-CDMA systems, is studied, when separate minimum mean-square error multiuser detection (MMSE-MUD) is considered. The separate MMSE-MUD detects signals first in the time (T)-domain and then in the frequency (F)-domain. Based on random matrix theory, closed-form expressions for the asymptotic SINR of the TF/MC DS-CDMA systems using separate MMSE-MUD is derived, when communicating over additive white Gaussian noise (AWGN) channels. The closed-form expressions show that the asymptotic SINR performance is only depended on the T- and F-domain user load factors as well as noise variance. Hence, they are beneficial to evaluation. Furthermore, our simulation and numerical results show that in most cases the asymptotic SINR can provide a good approximation to the SINR achieved by realistic TF/MC DS-CDMA systems employing separate MMSE-MUD.
First report of the natural occurrence of the teleomorph of Leptosphaeria maculans on oilseed rape and airborne dispersal of ascospores in Hungary.

Leptosphaeria maculans (anamorph Phoma lingam) causes blackleg disease of oilseed rape. The teleomorph stage of the blackleg pathogen on oilseed rape in Hungary is reported for the first time. Airborne ascospores of the pathogen were monitored in the infected source area using a portable Hirst-type spore trap in different horizontal and vertical sampling points. Meteorological conditions influencing airborne spore dispersal of the fungus were analysed. Airborne ascospores of pathotypes A/Tox + and B/Tox 0 groups of L. maculans were identified using a modified germination test. A mixed population of L. maculans A/Tox + and B/Tox 0 groups were found in Hungary. The occurrence of the fungus on a wide range of its wild cruciferous hosts appears to be an important factor in the outbreak of the disease on oilseed rape. High relative humidity, rainfall, melting snow and moderate wind were the most important factors in the dissemination of the ascospores.
Rapid Frequency-domain Analog Fault Simulation Under Parameter Tolerances

Fault-driven analog and mixed-signal testing calls for rapid fault simulationtechniques. A problem that has not been addressed effectivelyby existing research is that circuit parameters have tolerance ranges.In this paper, we propose representing parameters under variations asintervals, and present an efficient algorithm - based on interval analysisand Householder's formula - to compute the worst-case responsebounds of good and faulty linear(ized) circuits under parameter variations.Our approach takes CPU time comparable to one nominal circuitsimulation, and always produces correct and conservative results. Thealgorithm has been implemented into SPICE3F5. Experimental resultsshow an acceptable accuracy.
Selecting theories and nonce generation for recursive protocols

Truderung's selecting theory model is one of the few models of cryptographic protocols which allows to model iterative (recursive) computations of principals and, at the same time, an automatic analysis in the following sense: there exists a procedure that checks whether in all runs of a given protocol a certain message is not revealed to an intruder. A major drawback of Truderung's model is that it allows only a finite number of constants, that is, there is no mechanism by which a principal can generate an unbounded number of fresh tokens such as nonces or session keys. We extend Truderung's model by such a mechanism and show that the extended model still allows an automatic analysis. We also demonstrate that the extended model is more appropriate to model the Recursive Authentication Protocol. It is important to know that after publication of Truderung's result it became clear that his proof only works in a restricted setting. We show that there is no hope to find a remedy to this by proving that the secrecy problem in the unrestricted setting is undecidable. In light of this, the aforementioned result about extending Truderung's model is to be read as follows. Adding anonymous constants in the restricted setting leads to a model of cryptographic protocols where insecurity is decidable.
Methylation of the hMLH1 promoter in familial gastric cancer with microsatellite instability

Microsatellite instability (MSI), which is recognized as an important mechanism in tumorigenesis, has been reported in familial gastric cancers (FGC). However, genetic defects responsible for this phenotype, that is, mutations in mismatch‐repair genes such as hMLH1 and hMSH2, have not been detected in most FGC cases. Earlier studies have shown that the promoter region of the hMLH1 gene was methylated in some sporadic colorectal and endometrial cancers. To determine how FGC acquire MSI, we examined the MSI status, hMLH1‐protein expression and methylation status of the hMLH1‐promoter region in FGC cases. Out of 9 cancers, 6 from 8 FGC kindreds showed MSI at one or more loci; no germline mutations in the hMLH1 or hMSH2 genes were detected; 4 cancers exhibiting MSI displayed aberrant hMLH1 expression: complete loss in one, decreased level in another, and partially staining pattern in the remaining 2. Methylation in the hMLH1‐promoter region was found in these 4 cases. In contrast, the cancers displaying hMLH1‐protein expression were not methylated in the hMLH1‐promoter region. Our data show a significant association between the absence of hMLH1 expression and methylation of its promoter in FGC cases with MSI. This suggests that the mechanism of inactivation of hMLH1 is epigenetic and that there are other genes responsible for FGC. Int. J. Cancer 85:50–53, 2000. © 2000 Wiley‐Liss, Inc.
Localized QoS-Aware MAC Protocol for Real-time Dynamic Sensor Networks

Sensor networks have found important applications on real-time sensing and control. In those applications, the stringent quality of service (QoS) requirements (e.g., delay, jitter) and the dynamic nature of low-power wireless communication render existing MAC protocols undesirable. In this paper, we present RoMac, a localized QoS-aware TDMA MAC protocol for real-time dynamic sensor networks. The key contributions of RoMac include: (1) it provides collision-free communication and persistent QoS guarantee such as constant packet jitter and bounded latency; (2) it is resilient to topology dynamics and truly traffic adaptive in dynamic environments. To our best knowledge, this is the first TDMA MAC protocol that can achieve the resilience to dynamic topologies; (3) its localized design eases the need of scheduling message exchange beyond the initialization phase. We present an implementation of the protocol using the TinyOS operating system running on the iMote2 sensor mote platform. Our experiment result shows that RoMac can achieve the adaptability to dynamic changes in data collection sensor networks and provide persistent QoS support in terms of timeliness, packet jitter and fairness. 1 Keywords-QoS-Aware, Media Access Control, Real-time, Dynamic Sensor Networks
Towards personalized prostate cancer therapy using delta-reachability analysis

Recent clinical studies suggest that the efficacy of hormone therapy for prostate cancer depends on the characteristics of individual patients. In this paper, we develop a computational framework for identifying patient-specific androgen ablation therapy schedules for postponing the potential cancer relapse. We model the population dynamics of heterogeneous prostate cancer cells in response to androgen suppression as a nonlinear hybrid automaton. We estimate personalized kinetic parameters to characterize patients and employ δ-reachability analysis to predict patient-specific therapeutic strategies. The results show that our methods are promising and may lead to a prognostic tool for prostate cancer therapy.
Location Management in Wireless Fourth Generation Networks

Satisfying quality of service (QoS) is one of the main goals of the wireless fourth generation (4G), which will integrate tightly a multitude of different heterogeneous networks including cellular networks (second generation, third generation, wireless local area networks, bluetooth, etc). In this paper, we develop an information-theoretic framework for optimal location updating and paging for wireless 4G network, which integrate tightly many different access networks. Then, we adopt the LZW compression algorithm as the basis of our location management schemes. Simulation results demonstrate that our proposed schemes decrease the signaling cost.
Biological response of myoblasts to three-dimensional electrically conductive fibrous scaffolds

Inter-bonded three-dimensional fibrous scaffolds were fabricated using a template-aided melt bonding method. A high-throughput bioreactor was developed for dynamic cell culture of Myoblasts. The scaffolds after surface modification with a conducting polymer, polypyrrole, showed greatly enhanced cell viability, proliferation and differentiation especially under an electrical stimulation.
Hydraulic Performance of Horticultural Substrates—2. Development of an Evaluation Framework

Sustainable, environmentally friendly and resource-saving water and nutrient management in horticulture requires knowledge of the hydraulic suitability of horticultural substrates for each specific application. The aim of this study was to develop methods and a rating framework to assess the hydraulic performance of horticultural substrates. The hydraulic criteria related to high-quality horticultural substrates were defined as the amount of easily plant-available water (EAW) in the tension range between 10 and 100 hPa, the air capacity and the height of capillary rise. Limiting factors could be water repellency effects and shrinkage. The rating framework consisted of 5 classes between non-satisfactory and very good. The assessment of the hydraulic performance was split for the cultivation into 10-, 20-, and 30-cm-high containers. It was tested on 18 commercial substrates. More than 70% of the tested substrates revealed scores between very good and good. About 30% were evaluated as medium or satisfactory. The most critical aspect was the low air capacity in shallow containers. Shrinkage and water repellency sometimes strongly diminished the score. Both the measurement methods for quantifying substrate hydraulic properties and the evaluation procedure proved applicable. The impact of different ingredients and the composition of substrates of their hydraulic performance should be statistically analysed in further studies.
APAKAH MODEL PEMBELAJARAN PROBLEM BASED LEARNING DAN PROJECT BASED LEARNING MAMPU MELATIHKAN KETERAMPILAN ABAD 21

Seiring dengan perkembangan jaman yang semakin pesat, peran pendidikan menjadi sangat penting dalam mempersiapkan peserta didik agar memiliki keterampilan abad 21. Salah satu upaya untuk menjawab tantangan ini dengan merubah peran guru dari dari penyedia dan peyampai informasi menjadi fasilitator untuk berbagi informasi dan pengetahuan serta melatihkan kemampuan memecahkan masalah kepada peserta didik. Pembelajaran konstruktivisme menjadi salah satu alternatif dalam melatihkan keterampilan abad 21. Model pembelajaran project based learning dan problem based learning menjadi model yang paling poluler pada pendekatan konstruktivisme. Namun, masih banyak para pendidik yang mengalami kebingungan dalam membedakan dan mengoperasikan kedua model pembelajaran ini. Oleh karena itu, artikel ini mengulas persamaan dan perbedaan antara project based learning dan problem based learning , serta menjawab apakah kedua model pembelajaran tersebut mampu melatihkan keterampilan abad 21.
A novel DFT-based approach for the estimation of the number of sinusoids

This paper proposes a method for the estimation of the number of sinusoidal components in a deterministic signal, based on an adaptive thresholding of the DFT The proposed method is described and compared with two common approaches present in literature, the Akaike information criterion (AIC) and the minimum description length (MDL). The proposal is also applied in the stage of the spectral estimation algorithm called IFFTc in order to detect hidden spectral components. The comparison is carried out for different signals and in terms of percentage of missed detections, percentage of false detections and elaboration times.
Multi-region competitive tractography via graph-based random walks

We propose a multi-region approach to tractography that not only allows for competition between seed regions, but also allows for the incorporation of knowledge beyond a local scale. By formulating tractography as a graph-based random walk, we are able to obtain a closed-form solution for connection probabilities. Results on synthetic data and thirty images from the MIDAS database show that the introduction of competition reduces erroneous connectivity to regions outside the seeded tracts.
Segmentation-Driven Image Registration-Application to 4D DCE-MRI Recordings of the Moving Kidneys

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) of the kidneys requires proper motion correction and segmentation to enable an estimation of glomerular filtration rate through pharmacokinetic modeling. Traditionally, co-registration, segmentation, and pharmacokinetic modeling have been applied sequentially as separate processing steps. In this paper, a combined 4D model for simultaneous registration and segmentation of the whole kidney is presented. To demonstrate the model in numerical experiments, we used normalized gradients as data term in the registration and a Mahalanobis distance from the time courses of the segmented regions to a training set for supervised segmentation. By applying this framework to an input consisting of 4D image time series, we conduct simultaneous motion correction and two-region segmentation into kidney and background. The potential of the new approach is demonstrated on real DCE-MRI data from ten healthy volunteers.
Anti-reflection coating characterization using scattered polarized light

An increase of the energy conversion efficiency of solar cells can be achieved by minimizing reflection losses. A thin film coating serves this purpose when using optimum values of its refractive index and thickness. Also, the presence of surface roughness decreases the reflection of sunlight. Consequently, advanced cell concepts combine thin films with surface texturing. Research and development of these concepts require characterization methods. Ellipsometry is a fast, nondestructive, optical measurement diagnostic which enables characterization of substrates and films with high precision. The use of ellipsometry as characterization tool requires an optical model to extract physical information from the measured data. The optical models used for thin film metrology are generally based on flat surface samples. This work explores the possibilities to extend the range of applicability of ellipsometry to rough surface samples. Polished, acid etched and alkali etched silicon samples were deposited with thin silicon nitride films using a DEPx plasma enhanced chemical vapor deposition system which makes use of the expanding thermal plasma technique. The samples were studied by means of reflectometry, scanning electron microscopy and atomic force microscopy. A single wavelength ellipsometer (λ=632.8 nm) was used to measure all samples resulting in ellipsometric layer thickness trajectories for each type of surface roughness. Comparison of the layer thickness trajectories indicated the influence of surface roughness on ellipsometry. Experiments and simulations showed that this influence can be attributed to light scattering and depolarization effects. These effects can be reduced by increasing the angle of incidence during the ellipsometry measurements. The influence of the acid etched surface roughness on the ellipsometry output showed similarities with the influence of an angle of incidence offset. A physical explanation of this behavior is given based on a feature size of the surface roughness in the so called short wavelength regime. This behavior can be exploited for relative layer characterizing measurements on deposited acid etched samples in which a film free sample is measured for reference. The accuracy of these results is acceptable for layer thickness determination, but unacceptable for the determination of the refractive index of the layer. The influence of the surface roughness of the alkali etched wafers on ellipsometry can be explained using the effective gradient medium approximation in addition to the ‘angle of incidence offset’ model. This extension of the effective medium approximation is designed for the long wavelength regime. It is shown that ellipsometry can be applied to rough surface samples. The influence of the surface roughness on ellipsometry can be explained physically. Additionally, ellipsometry can be used to characterize thin films on top of rough surface samples within the short wavelength regime.
INFORMATION-THEORETIC SENSOR MOTION CONTROL FOR DISTRIBUTED ESTIMATION

Estimate uncertainty is a clear metric for sensing problems, but is not traditionally used for optimal control of mobile sensors because it is difficult to model how it is affected by sensor motion. This work develops a multiple-step receding horizon cost for sensor motion control based on minimization of expected entropy of the estimate distribution. The structure of the cost function is analyzed and used to upper bound the degree of coupling between sensors. The contribution is a multiple step prediction of the estimate entropy incorporating probabilistic sensor and target motion models and a decomposition for its decentralized calculation. Multiple-step receding horizon control has the potential to provide better performance than single-step optimization in the cases of delayed payoff or sensor motion constraints, and has not generally been implemented for non-Gaussian models. An example is developed based on a team of unmanned air vehicles carrying vision sensors, and initial simulation results confirm the accuracy of the predictive cost calculation.Copyright © 2007 by ASME
ISIS: an adaptive, trilingual conversational system with interleaving interaction and delegation dialogs

ISIS (Intelligent Speech for Information Systems) is a trilingual spoken dialog system (SDS) for the stocks domain. It handles two dialects of Chinese (Cantonese and Putonghua) as well as English---the predominant languages in our region. The system supports spoken language queries regarding stock market information and simulated personal portfolios. The conversational interface is augmented with a screen display that can capture mouse-clicks as well as textual input by typing or stylus-writing. Real-time information is retrieved directly from a dedicated Reuters satellite feed. ISIS provides a system test-bed for our work in multilingual speech recognition and generation, speaker authentication, language understanding and dialog modeling. This article reports on our new explorations within the context of ISIS, including: (i) adaptivity to knowledge scope expansion; (ii) asynchronous human-computer interaction by task delegation to software agents; (iii) multi-threaded online interaction and offline delegation dialogs with interruptions for task switching.
Critical Modifier Role of Membrane-Cystic Fibrosis Transmembrane Conductance Regulator-Dependent Ceramide Signaling in Lung Injury and Emphysema

Ceramide accumulation mediates the pathogenesis of chronic obstructive lung diseases. Although an association between lack of cystic fibrosis transmembrane conductance regulator (CFTR) and ceramide accumulation has been described, it is unclear how membrane-CFTR may modulate ceramide signaling in lung injury and emphysema. Cftr+/+ and Cftr−/− mice and cells were used to evaluate the CFTR-dependent ceramide signaling in lung injury. Lung tissue from control and chronic obstructive pulmonary disease patients was used to verify the role of CFTR-dependent ceramide signaling in pathogenesis of chronic emphysema. Our data reveal that CFTR expression inversely correlates with severity of emphysema and ceramide accumulation in chronic obstructive pulmonary disease subjects compared with control subjects. We found that chemical inhibition of de novo ceramide synthesis controls Pseudomonas aeruginosa-LPS–induced lung injury in Cftr+/+ mice, whereas its efficacy was significantly lower in Cftr−/− mice, indicating that membrane-CFTR is required for controlling lipid-raft ceramide levels. Inhibition of membrane-ceramide release showed enhanced protective effect in controlling P. aeruginosa-LPS–induced lung injury in Cftr−/− mice compared with that in Cftr+/+ mice, confirming our observation that CFTR regulates lipid-raft ceramide levels and signaling. Our results indicate that inhibition of de novo ceramide synthesis may be effective in disease states with low CFTR expression like emphysema and chronic lung injury but not in complete absence of lipid-raft CFTR as in ΔF508-cystic fibrosis. In contrast, inhibiting membrane-ceramide release has the potential of a more effective drug candidate for ΔF508-cystic fibrosis but may not be effectual in treating lung injury and emphysema. Our data demonstrate the critical role of membrane-localized CFTR in regulating ceramide accumulation and inflammatory signaling in lung injury and emphysema.
P2DR: Privacy-Preserving Demand Response system in smart grids

Demand response programs are widely used to balance the supply and the demand in smart grids. They result in a reliable electric power system. Unfortunately, the privacy violation is a pressing challenge and increasingly affects the demand response programs because of the fact that power usage and operational data can be misused to infer personal information of customers. Without a consistent privacy preservation mechanism, adversaries can capture, model and divulge customers' behavior and activities at almost every level of society. This paper investigates a set of new privacy threat models focusing on financial rationality verse inconvenience. Furthermore, we design and implement a privacy protection protocol based on attributed-based encryptions. To demonstrate its feasibility, the protocol is adopted in several kinds of demand response programs. Real-world experiments show that our scheme merely incurs a substantially light overhead, but can address the formidable privacy challenges that customers are facing in demand response systems.
Learning Generic Features from DEH Channels for Object Proposals Generation

Depth information plays an important role in the human visual system, however it is not yet well- explored in existing proposal generation models. In this paper we propose a new geocentric embedding for depth images that encodes depth to the camera, the structural edges and height above ground-plane for each pixel named DEH channels. We demonstrate that this geocentric embedding works can be use to generate high quality object proposals with convolutional neural networks. Our experiments show significant performance improvements over existing RGB and RGB-D object proposal methods on the challenging KITTI benchmark. We also exploit Fast R- CNN \cite{girshick2015fast} on top of these proposals to perform object detection with RGB images, our approach obtains state-of-the-art results on all three KITTI object classes.