Miracle-dz/UniFAR-FTUs huggingface dataset:
Suprabasin Is Hypomethylated and Associated with Metastasis in Salivary Adenoid Cystic Carcinoma

Background Salivary gland adenoid cystic carcinoma (ACC) is a rare cancer, accounting for only 1% of all head and neck malignancies. ACC is well known for perineural invasion and distant metastasis, but its underlying molecular mechanisms of carcinogenesis are still unclear. Principal Findings Here, we show that a novel oncogenic candidate, suprabasin (SBSN), plays important roles in maintaining the anchorage-independent and anchorage-dependent cell proliferation in ACC by using SBSN shRNA stably transfected ACC cell line clones. SBSN is also important in maintaining the invasive/metastatic capability in ACC by Matrigel invasion assay. More interestingly, SBSN transcription is significantly upregulated by DNA demethylation induced by 5-aza-2′-deoxycytidine plus trichostatin A treatment and the DNA methylation levels of the SBSN CpG island located in the second intron were validated to be significantly hypomethylated in primary ACC samples versus normal salivary gland tissues. Conclusions/Significance Taken together, these results support SBSN as novel oncogene candidate in ACC, and the methylation changes could be a promising biomarker for ACC.
Situation Assessment for Automatic Lane-Change Maneuvers

Current research on advanced driver-assistance systems (ADASs) addresses the concept of highly automated driving to further increase traffic safety and comfort. In such systems, different maneuvers can automatically be executed that are still under the control of the driver. To achieve this aim, the task of assessing a traffic situation and automatically taking maneuvering decisions becomes significantly important. Thus, this paper presents a system that can perceive the vehicle's environment, assess the traffic situation, and give recommendations about lane-change maneuvers to the driver. In particular, the algorithmic background for this system is described, including image processing for lane and vehicle detection, unscented Kalman filtering for estimation and tracking, and an approach that is based on Bayesian networks for taking maneuver decisions under uncertainty. Furthermore, the results of a first prototypical implementation using the concept vehicle Carai are presented and discussed.
Particle localization and the Notion of Einstein Causality

The notion of Einstein causality, i.e. the limiting role of the velocity of light in the transmission of signals, is discussed. It is pointed out that Nimtz and coworkers use the notion of signal velocity in a different sense from Einstein and that their experimental results are in full agreement with Einstein causality in its ordinary sense. We also show that under quite general assumptions instantaneous spreading of particle localization occurs in quantum theory, relativistic or not, with fields or without. We discuss if this affects Einstein causality.
Scene Flow Estimation: A Survey

This paper is the first to review the scene flow estimation field, which analyzes and compares methods, technical challenges, evaluation methodologies and performance of scene flow estimation. Existing algorithms are categorized in terms of scene representation, data source, and calculation scheme, and the pros and cons in each category are compared briefly. The datasets and evaluation protocols are enumerated, and the performance of the most representative methods is presented. A future vision is illustrated with few questions arisen for discussion. This survey presents a general introduction and analysis of scene flow estimation.
A Simple Multicloud Parameterization for Convectively Coupled Tropical Waves. Part I: Linear Analysis

Abstract Recent observational analysis reveals the central role of three multicloud types, congestus, stratiform, and deep convective cumulus clouds, in the dynamics of large-scale convectively coupled Kelvin waves, westward-propagating two-day waves, and the Madden–Julian oscillation. A systematic model convective parameterization highlighting the dynamic role of the three cloud types is developed here through two baroclinic modes of vertical structure: a deep convective heating mode and a second mode with low-level heating and cooling corresponding respectively to congestus and stratiform clouds. A systematic moisture equation is developed where the lower troposphere moisture increases through detrainment of shallow cumulus clouds, evaporation of stratiform rain, and moisture convergence and decreases through deep convective precipitation. A nonlinear switch is developed that favors either deep or congestus convection depending on the relative dryness of the troposphere; in particular, a dry troposphere.
Cox Regression Model Model Definition

The Cox or proportional hazards regression model [21] is used to analyze survival or failure time data. It is now perhaps the most widely used statistical model in medical research. Whenever the outcome of a clinical trial is the time to an event, the Cox model is the first method considered by most researchers. The model has also inspired an enormous statistical literature, ranging from the mathematical study of estimating the model parameters , to applied techniques for validating the model assumptions. This article is divided into sections touching on some of the vast literature that has developed around the model: 1. model definition 2. history 3. using the Cox model–the basics 4. estimators and algorithms 5. asymptotic properties (see Large-sample Theory) 6. time-dependent explanatory variables 7. model checking 8. alternatives and extensions. Several books have now been published on survival analysis that devote major sections to the Cox model. The first of these appeared in the early 1980s [23, 50]. Of the more recent books some are mathematically rigorous [6, 29], while others are more applied [20, 53, 60]. The book by Andersen et al. [6] is the most comprehensive. Cox's essential novelty was to model the hazard function (see Hazard Rate) rather than the mean or some other measure of location. Let X denote a random failure time and Z a vector of explanatory variables. The conditional hazard of X given Z = z at time t is defined as λ(t|z) = lim ∆t↓0 Pr(X ≤ t + ∆t|X > t, z) ∆t. (1) The hazard function is sometimes called the intensity function or the force of mortality. Roughly, the hazard function is the probability that someone who is alive now will die in the next small unit of time. Cox proposed that the conditional hazard be modeled as the product of an arbitrary baseline hazard λ 0 (t) and an exponential form that is linear in z: λ(t|z) = λ 0 (t) exp(β z). (2) Here β is a vector of regression parameters and the infinite-dimensional parameter λ 0 (·) is the hazard function for an individual with Z = 0. The model in (2) forces the hazard ratio between two individuals to be constant over time: λ(t|z 2) λ(t|z 1) = exp[β (z 2 − z 1)]. The exponential form of the relative risk function has become standard and is the most stable compu-tationally, but it …
Second-Order Analysis of Formation of Holes in Spatial Point Patterns: Applications in Wireless Sensor Networks

Dense deployment of wireless sensors can be used for environmental monitoring applications. Natural and artificial disasters, such as floods and fires, are significant events that need to be continuously monitored and contained as fast as possible. However, such disasters may destroy sensors deployed to monitor environmental conditions and prevent reporting of critical measurements that may indicate an occurring hazard. In this paper, we present how spatial point pattern analysis techniques, which have traditionally been used to analyze clustering, randomness, or regularity, can also be employed to analyze formation of a "hole" in a point pattern, which is also of significant interest in randomly deployed sensor networks since formation of a hole might be considered as an indication of a hazard. We first outline a methodology based on an information theoretic approach that can be used in decision support systems for detecting holes wherein visual inspection of destroyed sensors on a sensor map at a central station is hard, if not impossible. We show, by means of a second-order spatial point pattern analysis, that manifestation of such holes can be detected at small spatial scales. Furthermore, second-order analysis might provide an insight into the spatial scale of the hole in the pattern. Results presented validate our observations that failure of sensors due to a systematic destruction may be inferred by decision support systems when only a small portion of the monitored area is affected.
Image-based transformation of viewpoint and scene appearance

This thesis addresses the problem of synthesizing images of real scenes under threedimensional transformations in viewpoint and appearance. Solving this problem enables interactive viewing of remote scenes on a computer, in which a user can move a virtual camera through the environment and virtually paint or sculpt objects in the scene. It is demonstrated that a variety of three-dimensional scene transformations can be rendered on a video display device by applying simple transformations to a set of basis images of the scene. The virtue of these transformations is that they operate directly on images and recover only the scene information that is required in order to accomplish the desired e ect. Consequently, they are applicable in situations where accurate three-dimensional models are di cult or impossible to obtain. A central topic is the problem of view synthesis, i.e., rendering images of a real scene from di erent camera viewpoints by processing a set of basis images. Towards this end, two algorithms are described that warp and resample pixels in a set of basis images to produce new images that are physically-valid, i.e., they correspond to what a real camera would see from the speci ed viewpoints. Techniques for synthesizing other types of transformations, e.g., non-rigid shape and color transformations, are also discussed. The techniques are found to perform well on a wide variety of real and synthetic images. A basic question is uniqueness, i.e., for which views is the appearance of the scene uniquely determined from the information present in the basis views. An important contribution is a uniqueness result for the no-occlusion case, which proves that all views on the line segment between the two camera centers are uniquely determined from two uncalibrated views of a scene. Importantly, neither dense pixel correspondence nor camera information is needed. From this result, a view morphing algorithm is derived that produces high quality viewpoint and shape transformations from two uncalibrated images.
Review of pulse generators for gated ring oscillator based Time-to-Digital converters

Pulse generator serves an important role in gated ring oscillator (GRO) based Time-to-Digital converters (TDC) to enable the ring oscillator for the input time difference between two reference timing events. As the resolution of TDC advances to a few picoseconds, the linearity of the pulse generator becomes increasingly important. This paper reviews and compare between pulse generators implemented using a XOR gate, SR latch, phase frequency detector (PFD) and time difference generator (TDG). Simulation results in standard 40nm CMOS technology shows that the TDG is the most suitable pulse generator since it has the best linearity. In terms of power and area, the dynamic PFD is a good alternative.
EU-BRIDGE MT: Combined Machine Translation

This paper describes one of the collaborative efforts within EU-BRIDGE to further advance the state of the art in machine translation between two European language pairs, German→English and English→German. Three research institutes involved in the EU-BRIDGE project combined their individual machine translation systems and participated with a joint setup in the shared translation task of the evaluation campaign at the ACL 2014 Eighth Workshop on Statistical Machine Translation (WMT 2014). We combined up to nine different machine translation engines via system combination. RWTH Aachen University, the University of Edinburgh, and Karlsruhe Institute of Technology developed several individual systems which serve as system combination input. We devoted special attention to building syntax-based systems and combining them with the phrasebased ones. The joint setups yield empirical gains of up to 1.6 points in BLEU and 1.0 points in TER on the WMT newstest2013 test set compared to the best single systems.
04 10 03 2 v 1 4 O ct 2 00 4 SOLITON RESONANCES FOR MKP-II

Using the second flow the Derivative Reaction-Diffusion system, and the third one of the dissipative SL(2,R) Kaup-Newell hierarchy, we show that the product of two functions, satisfying those systems is a solution of the modified Kadomtsev-Petviashvili equation in 2+1 dimension with negative dispersion (MKP-II). We construct Hirota’s bilinear representation for both flows and combine them together as the bilinear system for MKP-II. Using this bilinear form we find one and two soliton solutions for the MKP-II. For special values of parameters our solution shows resonance behaviour with creation of four virtual solitons. Our approach allows one to interpret the resonance soliton as a composite object of two dissipative solitons in 1+1 dimensions.
Performance Analysis of MIMO Based Multi-User Cooperation Diversity Over Various Fading Channels

—In this paper, hybrid FDMA-TDMA access technique in a cooperative distributive fashion introducing and implementing a modiﬁed protocol introduced in [1] is analyzed termed as Power and Cooperation Diversity Gain Protocol (PCDGP). A wireless network consists of two users terminal , two relays and a destination terminal equipped with two antennas. The relays are operating in amplify-and-forward (AF) mode with a ﬁxed gain. Two operating modes: cooperation-gain mode and power-gain mode are exploited from source terminals to relays, as it is working in a best channel selection scheme. Vertical BLAST (Bell Laboratories Layered Space Time) or V-BLAST with minimum mean square error (MMSE) nulling is used at the relays to perfectly detect the joint signals from multiple source terminals. The performance is analyzed using binary phase shift keying (BPSK) modulation scheme and investigated over independent and identical ( i.i.d ) Rayleigh, Ricean-K and Nakagami-m fading environments. Subsequently, simulation results show that the proposed scheme can provide better signal quality of uplink users in a cooperative communication system using hybrid FDMA-TDMA technique.
Relational Contracts and Inequity Aversion

We study the effects of envy on the feasibility of relational contracts in a standard moral hazard setup with two agents. Performance is evaluated via an observable, but non-contractible signal which reflects the agent´s individual contribution to firm value. Both agents exhibit disadvantageous inequity aversion. In contrast to the literature, we find that inequity aversion may be beneficial: In the presence of envy, for a certain range of interest rates relational contracts may be more profitable. Furthermore, for some interest rates reputational equilibria exist only with inequity averse agents.
Privacy Preserving in K-Anonymization Databases Using AES Technique

— Data mining is the process of searching a different pattern from the existing datasets. The main purpose is to gain the knowledge in human understandable form from dataset and also allows sharing the private crucial data for analysis. So due to this reason the data mining becomes increasingly popular and highly demanding process. A number of methods and techniques have been proposed for privacy preserving data mining. The area of privacy preserving has seen developed very increasingly and becomes necessary for every data collector. Because everyone collects his data at very much amount so it becomes necessary to provide the Data confidentiality and to prevent individual’s security. Another issue is that for knowledge-and information-based decision taking is requires exchange and publish data in various parties and it requires data is in its actual form obviously it’s very risky for everyone. In this paper, we will observe and presents Suppression and Generalization based techniques to Privacy preserving and proposing system “privacy preserving of K-Anonymization Using AES Technique” that are more strong to preserve the privacy.
Dorsal and ventral myotome motoneurons and their input during fictive locomotion in lamprey

Motoneurons supplying the dorsal and ventral parts of the myotome in the lamprey are shown to have different morphological characteristics; furthermore, their pattern of activation during fictive locomotion may differ considerably. Intracellular recordings from motoneurons were performed in an in vitro spinal cord-myotome preparation from segments rostral to the fins. The location of the contracting muscle fibers in the myotome could be observed directly in the dissection microscope during intracellular stimulation of the motoneuron. The motoneurons were injected with Lucifer Yellow, an intracellular dye, and were subsequently reconstructed, sometimes in both a horizontal and a transverse plane. Motoneurons supplying the ventral third of the myotome had a dense, fan-like, dendritic tree and ramifications near the midline. In contrast, motoneurons supplying the dorsal third of the myotome had a more widespread and less dense dendritic tree, with few ramifications near the midline. Some motoneurons supplying the most ventral or dorsal part of the myotome had contralateral dendrites crossing in the ventral commissure and ramifying near contralateral large, reticulospinal Muller fibers. The differences in morphology may indicate that these motoneurons receive different descending inputs. This may be related to the need for an effective control in the dorsoventral plane during righting and steering responses. During fictive locomotion elicited in the isolated spinal cord by bath-applied N-methyl-aspartate, pairs of motoneurons were recorded which subsequently were identified and characterized by intracellular injections of Lucifer Yellow. (ABSTRACT TRUNCATED AT 250 WORDS)
Modelling Macroeconomic Time Series

Two traditionally separate approaches to economic time series modelling, namely the methods of univariate statistical analysis known as Box-Jenkins methods and the multivariate methods of econometrics, are compared, contrasted and, through the notion of the final equation, related to one another. Empirical comparisons are based on an existing econometric model of aggregate demand in the U.K. A detailed account of the univariate analyses of the key variables of the system is presented, and problems of seasonality and model selection are discussed. In terms of residual variance, the econometric model provides a better fit.
Optimal Reinsurance and Dividend Strategies with Capital Injections in Cramér-Lundberg Approximation Model

In this paper, we consider a diffusion approximation to a classical risk process with the possibility of quota-share and excess-of-loss reinsurance, while in addition the company controls the amount of dividends paid out to the shareholders as well as the capital injections. The objective is to maximize the cumulative expected discounted dividends minus the penalized discounted capital injections until the time of bankruptcy. We show that the optimal combinational reinsurance strategy must be pure excess-of-loss reinsurance. The control problem is solved by constructing some suboptimal model which allows no bankruptcy by capital injection. Then we obtain the analytical expressions for the value function and the optimal strategies and it is concluded that they are the same as those in the case of no bankruptcy. 2010 Mathematics Subject Classification: 62P05, 91B30
Determining Successful Negotiation Strategies: The Evolution of Intelligent Agents

Due to the desire of almost all departments of business organizations to be interconnected and to make data accessible at any time and any place, more and more multi-agent systems are applied to business management. As numerous agents are roaming through the Internet, they compete for the limited resource to achieve their goal. In the end, some of them will succeed, while the others will fail. However, when agents are initially created, they have little knowledge and experience with relatively lower capability. They should also strive to adapt themselves to the changing environment. It is advantageous if they have the ability to learn and evolve. This paper addresses evolution of intelligent agents in virtual enterprises. Agent fitness and fuzzy multi-criteria decision-making approach are proposed as evolution mechanisms, and fuzzy soft goal is introduced to facilitate the evolution process. Genetic programming operators are employed to restructure agents in the proposed multi-agent evolution cycle. We conduct a series of experiments to determine the most successful strategies and to see how and when these strategies evolve depending on the context and negotiation stance of the agent’s opponent.
Association Rule Mining Approach in Strategy Planning for Team India in ICC World Cup 2015

Performance analysis in every sport is essential to find out the weaknesses and strengths of the players. In a team game like cricket, analysis of career-data is indispensable to get the insight of the players' performance, which helps the selectors to do their job flawlessly and also helps the players' themselves to identify their weaknesses and their strengths. And, when the time comes for world cup cricket, every team looks for their best team-combination to be available on the ground to achieve the desired result in their favour. Association rule mining techniques reveal the unknown information from a huge set of data, and this technique can be used in extracting the information from the performance-data of the players. In this paper, we have applied association rule mining technique on individual Indian players' career-record to obtain the underlying unknown relations of several factors impacting the players' performances. This analysis could help in selecting the best-suited team-combination in a given match condition. The relation among various intrinsic factors such as venue of the match, batting first or second, batting position (of batsmen), strike-rate and runs (of batsmen), economy-rate and wickets taken (of bowlers) is analyzed. The result of this study could be useful for Indian team-captain and team-manager in decision making and strategy planning and could also boost the chances of success for team India for the world cup 2015.
A COMBINED APPROACH TO SEARCH FOR EVASION TECHNIQUES IN NETWORK INTRUSION DETECTION SYSTEM

Network Intrusion Detection Systems (NIDS) whose base is signature, works on the signature of attacks. They must be updated quickly in order to prevent the system from new attacks. The attacker finds out new evasion techniques so that he should remain undetected. As the new evasion techniques are being developed it becomes difficult for NIDS to give accurate results and NIDS may fail. The key aspect of our paper is to develop a network intrusion detection system using C4.5 algorithm where Adaboost algorithm is used to classify the packet as normal packet or attack packet and also to further classify different types of attack. Apriori algorithm is used to find real time evasion and to generate rules to find intrusion These rules are further given as input to Snort intrusion detection system for detecting different attacks.