Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of Radiation Therapy in Modulation of the Tumor Stroma and Microenvironment

In recent decades, there has been substantial growth in our understanding of the immune system and its role in tumor growth and overall survival. A central finding has been the cross-talk between tumor cells and the surrounding environment or stroma. This tumor stroma, comprised of various cells, and extracellular matrix (ECM), has been shown to aid in suppressing host immune responses against tumor cells. Through immunosuppressive cytokine secretion, metabolic alterations, and other mechanisms, the tumor stroma provides a complex network of safeguards for tumor proliferation. With recent advances in more effective, localized treatment, radiation therapy (XRT) has allowed for strategies that can effectively alter and ablate tumor stromal tissue. This includes promoting immunogenic cell death through tumor antigen release to increasing immune cell trafficking, XRT has a unique advantage against the tumoral immune evasion mechanisms that are orchestrated by stromal cells. Current studies are underway to elucidate pathways within the tumor stroma as potential targets for immunotherapy and chemoradiation. This review summarizes the effects of tumor stroma in tumor immune evasion, explains how XRT may help overcome these effects, with potential combinatorial approaches for future treatment modalities.
Development of a MEMS microwave switch and application to adaptive integrated antennas

Adaptive integrated antennas are serious candidates for achieving the performance requirements of next-generation, broadband, wireless systems. This paper reports on the development of a microelectromechanical system (MEMS) shunt switch and its application to reconfigurable patch antennas. The micromachining procedure employs hexa-methyldisilizane (HMDS) as an anti-stiction surface treatment, significantly increasing the process yield. A MEMS shunt switch was designed for 10-20 GHz operation in a coplanar waveguide (CPW) regime. At 20 GHz, the insertion loss of the switch in the on-state was measured to be 0.25 dB, while an isolation of 10 dB was obtained in the off-state. Further improvement in the off-state isolation appears possible. The MEMS switch is applied to a novel co-planar patch antenna configuration in order to achieve adaptive radiation characteristics. A 30 GHz patch design shows in simulation a phase shift of 70 degrees between the two operating states.
Initial Evaluation of Pain Intensity Among Depressed Patients as a Possible Mediator Between Depression and Pain Complaints

Pain complaints are frequently described by depressed patients, and are mostly attributed to abnormal pain perception and modulation. The present study aimed to assess whether a unique pain processing profile differentiates depressed patients from healthy controls. Participants were 25 patients suffering from a moderate-severe unipolar depressive episode and 25 age and sex-matched healthy controls. Thermal stimuli were used to assess sensory threshold and pain threshold. Pain-60 temperature (temperature that induces pain ratings of 60 out of 100) was the first noxious stimuli to be administered during the experimental session. Central pain inhibition was assessed via conditioned pain modulation (CPM) and the degree of central nervous system excitability was assessed via mechanical temporal summation. Depressed patients reported higher levels of pain compared with healthy controls, and a significantly higher perceived pain during the last month. Additionally, they displayed significantly lower pain-60 temperature values compared with healthy controls (p = 0.01). Otherwise, no significant group differences were found in measures of pain perception and modulation. Our results suggest that the initial evaluation of pain intensity among depressed patients, as validated by pain-60 temperature values, is increased compared with healthy controls, and might be the mediator between depression and pain complaints. Possibly, depressed patients' negative bias in the processing of pain is similar to their processing pattern of facial expression or future events. Further studies are necessary in order to establish the mechanisms underlying the excessive pain complaints reported by patients with unipolar depression.
Performance evaluation of stored geocast

This paper presents a definition, the design space, three reasonable implementations, and an ns-2 simulation study of a new type of geocast protocol, called stored geocast. A stored geocast is a time stable geocast, which is delivered to all nodes that are inside a destination region within a certain period of time. When used in a mobile ad hoc network (MANET) it allows to realize a persistent message valid for a certain geographic region, possibly combined with a time limit. Stored geocast is of particular interest in the automotive domain, since it allows realizing virtual traffic signs or for location-based services in general. The simulation results investigate the delivery success ratio and the resulting message overhead in several scenarios with random waypoint movement and in realistic vehicular traffic scenarios gathered from a driver behavior simulator.
Transformation of speaker characteristics for voice conversion

The paper presents a voice conversion method based on analysis and transformation of the characteristics that define a speaker's voice. Voice characteristic features are grouped into three main categories: (a) the spectral features at formants; (b) the pitch and intonation pattern; (c) the glottal pulse shape. Modelling and transformation methods for each group of voice features are outlined. The spectral features at formants are modelled using a two-dimensional phoneme-dependent HMM. Subband frequency warping is used for spectrum transformation where the subbands are centred on estimates of formant trajectories. The F0 contour, extracted from autocorrelation-based pitchmarks, is used for modelling the pitch and intonation patterns of speech. A PSOLA based method is used for transformation of pitch, intonation patterns and speaking rate. Finally a method based on deconvolution of the vocal tract is used for modelling and mapping of the glottal pulse. The experimental results present illustrations of transformations of the various characteristics and perceptual evaluations.
MIPMANET-mobile IP for mobile ad hoc networks

Mobile ad hoc networking allows nodes to form temporary networks and communicate beyond the transmitter range by supporting multihop communication through IP routing. Routing in such networks is often reactive, i.e., performed on-demand, as opposed to Internet routing that is proactive. As ad hoc networks are formed on a temporary basis, any IP address should be allowed to appear in an ad hoc network. This paper presents MIPMANET, a solution for connecting an ad hoc network, in which on-demand routing is used, to the Internet. MIPMANET provides Internet access by using mobile IP with foreign agent care-of addresses and reverse tunneling. This allows nodes to enjoy the mobility services of mobile IP while at the same time the requirements on the ad hoc routing protocol are kept to a minimum. Simulations of MIPMANET have been performed in the Network Simulator 2. The ad hoc on-demand distance vector (AODV) routing protocol has been used for routing within the ad hoc network. These simulations show that the ability to choose the closest access point to the Internet is worth extra work, as less traffic is generated in the network resulting in lower delays and fewer dropped packets.
Dynamic Load Balance in Parallel Merge Sorting over Homogeneous Clusters

Sorting is one of the most usual and important operations carried out in a computer. The time required by the sequential sorting algorithms is an important problem when working with large sized sequences. As solution, we can consider parallelization and attaining a near optimal performance achieving a balance in the work to be done by processors. Notice that the work does not depend only on the amount of data but also on the sequence disordering, and on the relative computer power of processors. This paper develops a technique of redistributing dynamically the data load from the prediction of work to be carried out by each processor, balancing the load among the different processes. The method is proved to reach the theoretical optimum for the parallel algorithm performance.
Adapted iterative decoding of product codes

This paper deals with iterative decoding of product codes for high spectral efficiency transmissions. A solution is proposed to adapt the decoding algorithm to the characteristics of the encoder, the modulation and the number of decoding steps. A coding gain of up to 2 dB is then obtained for short codes. For long codes, the number of decoding steps to achieve a specified bit error rate (BER) can be reduced by 1 or 2, which is interesting in terms of decoding latency and power consumption.
The development of computer science research in the People’s Republic of China 2000–2009: a bibliometric study

This paper reports a bibliometric study of the development of computer science research in the People’s Republic of China in the 21st century, using data from the Web of Science, Journal Citation Reports and CORE databases. Focusing on the areas of data mining, operating systems and web design, it is shown that whilst the productivity of Chinese research has risen dramatically over the period under review, its impact is still low when compared with established scientific nations such as the USA, the UK and Japan. The publication and citation data for China are compared with corresponding data for the other three BRIC nations (Brazil, Russian and India). It is shown that China dominates the BRIC nations in terms of both publications and citations, but that Indian publications often have a greater individual impact.
Hybrid Scene Reconstruction by Integrating Scan Data and Stereo Image Pairs

3D geometric models obtained by using laser scanners are often incomplete due to the equipment limitations. In this paper, we propose a novel hybrid reconstruction algorithm, which integrates stereo image pairs to overcome these limitations. This work focuses on a category of scenes that can be approximated by planes (such as manmade scenes). The scan data are first segmented into planar patches, many of which may be incomplete. Stereo image pairs are then incorporated to retrieve the missing data. Specifically, we decide each plane's extension in the image domain via segment-based stereo matching with disparity layers extracted from scan data. Then, points in the missing area are interpolated by calculating ray-plane intersections. All procedures are automatic except for the range to image registration. The validity of our approach is demonstrated by experiments on real data.
An evolutionary node architecture and performance optimization

The boom of Internet applications has resulted in ever increasing demands for new network services support. Different applications require different QoS, protocols and security mechanisms to be deployed in the network. These demand the network to evolve to keep pace with the change of application requirements. As the current Internet's functions are very hard to expand and cope with the changing environment. A new evolutionary node architecture is proposed in this paper. New network services, protocols, control and management functions can be dynamically deployed on the ENN node so that the network can exhibit a flexible and application sensitive behavior. Major technical issues related to ENN are discussed.A prototyping evolutionary network called FAN is designed and implemented. The performance of the mobile agent execution environment was analyzed, evaluated and optimized. Experiments on FAN show that the ENN architecture is effective in promoting the evolution of the network.
An evolutionary method of training topography-preserving maps

In this paper, we introduce an evolutionary training method that can be used either to replace standard self-organizing map (SOM) training or to post-process a trained SOM. The approach is motivated by a desire to improve the way a map preserves relationships in the data beyond the presentation of continuity. There are two stages in the algorithm, prompted by the observation that there is conflict in standard SOM training between the goal of representing the probability distribution of the data and the goal of preserving topology between input and output (a conflict between competition and cooperation). By pursuing these two goals in two separate stages of training, we are able to focus on each goal individually and prevent each from impeding the other. The use of a genetic algorithm in the second stage determines the adjacencies of neurons in the output map grid and allows greater control over the way relationships between output neurons preserve the relationships found in the input data. This is important because it enhances the ability of the map to more accurately represent the structure of the input data. It may prove especially valuable when dealing with high-dimensional data, when one cannot visually inspect the map plotted in the data space to verify the quality of the mapping.
Detection of small man-made objects in sector scan imagery using neural networks

This paper presents a neural network based system to detect small man-made objects in sequences of sector scan sonar images. The detection of such objects is considered out to ranges of 150 metres using a forward-looking sonar system mounted on a vessel. After an initial cleaning operation performed by compensating for the motion of the vessel, the imagery was segmented to extract objects for analysis. A set of 31 features extracted from each object was examined. These features consisted of basic object size and contrast features, shape moment-based features, moment invariants, and features extracted from the second-order histogram of each object. The best set of 15 features was then selected using sequential forward selection and sequential backward selection. These features were then used to train a neural network to detect man-made objects in the image sequences. The detector achieved a 97% accuracy at a mean false positive rate of 9 per frame.
Interaction effects in the transport of particles in nanowire quantum dots

Interactions between physical bodies constantly affect their properties. This thesis presents a theoretical study on the effects of interaction in few-body nanowire quantum dots. The focus is to a large extent on a phenomenon called Wigner localization, and how this, as well as other interaction effects, can be identified in an experiment by transport spectroscopy and by thermopower measurements. The physical systems considered are electrons in semiconductor nanowires and an ultracold gas of dipolar particles in magneto-optical traps. The full many-body description of the nanowire quantum dot is obtained by exact diagonalization (also known as the configuration interaction method) while the transport simulations are based on a Pauli master equation approach. The thesis is based on three papers: In Paper I we examine Wigner localization in an InSb nanowire quantum dot and identify the onset of Wigner localization in an experiment. In Paper II we study how different interaction regimes can be accessed in an ultracold dipolar gas by tuning the dipole-dipole interaction externally, providing Wigner localization for strong repulsion and total current blockade for attraction. The effect of excited states on the thermopower lineshape is investigated in Paper III, asserting the possibility to detect the onset of Wigner localization by thermopower measurements. (Less)
Instance-based learning by searching

Instance based learning (IBL) methods fascinate with their conceptual simplicity. Usually, IBL systems center on (a subset of) given "training" instances. Restricting the acquisition of instances to given training instances is known to cause difficulties and limitations. We propose to overcome these limitations by searching for suitable instances. We employ a genetic algorithm to conduct such an intricate search. We demonstrate the viability of this approach in connection with instance based concept learning.
Flickr: Who is Looking?

This article presents a characterization of user behavior on Flickr, a popular on-line photo sharing service that allows users to store, search, sort and share their photos. Based on a sub-set of photos being uploaded during a 10 day window, we track the interest of users in those photos over a period of 50 days. In particular we investigate the user behavior on temporal, social, and spatial dimensions. Results show that the users are able to discover new photos within hours after being uploaded and that 50% of the photo views are generated within the first two days. The social networking behavior of users, and photo pooling are identified as the two major indicators related to a photo's popularity. Finally we show that the geographic distribution is more focussed around a geographic location for the infrequently viewed photos, than for the photos that attract a large number of views.
XploRe Package for the Popular Parametric and the Semiparametric Single Index Models

This study introduces and shows the applicability of the XploRe commands of the parametric and the semiparametric single index models, which are two most popular alternatives of each other. The commands required for the estimation in all stages of the semiparametric estimation and the parametric logistic, probit and complementary log log regression models are introduced in detail. An artificial data set is used to demonstrate the applicability of the commands in practice. The major contribution of this study is that it enables researchers to obtain additional outputs in easier way that are not so easy to have in the standard statistical packages especially for the semiparametric models. Additionally, users could extend and adapt these commands in conjunction with the new developments in this area. Key Words : Single index model, Semiparametric approach, Binary response modelling, XploRe.
Hierarchical Junction Trees as the Secondary Structure for Inference in Bayesian Networks

The paper investigates some important transport layer algorithms for wireless sensor networks. On the basis of the single-path-based distributed TCP caching, which work badly when some node on the path be down, adopt multi-path routing on the network layer and distributed TCP caching on the transport layer to enhance transport reliability. From the simulation results, it improves overall performance in term of end-to-end transport delay comparing with the original DTC algorithm and loads are distributed among the intermediate nodes. And then address some open issues as the research prospects.
OWL 2 Web Ontology Language

The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information written in RDF, and OWL 2 ontologies themselves are primarily exchanged as RDF documents. The OWL 2 Document Overview describes the overall state of OWL 2, and should be read before other OWL 2 documents. The Manchester syntax is a user-friendly compact syntax for OWL 2 ontologies; it is frame-based, as opposed to the axiom-based other syntaxes for OWL 2. The Manchester Syntax is used in the OWL 2 Primer, and this document provides the language used there. It is expected that tools will extend the Manchester Syntax for their own purposes, and tool builders may collaboratively extend the common language.
Finite word length effects on the performance of MMSE receiver for DS-CDMA systems

The minimum mean square error (MMSE) receiver for a DS-CDMA system is capable of suppressing multiple access interference (MAI), unlike the conventional digital matched filter (DMF) receiver. Moreover, this type of receiver offers implementation advantages over optimum receivers for DS-CDMA systems. However, the performance of the MMSE receiver is affected by the quantization of the adaptive filter coefficients and the analog-to-digital converter (ADC) output. In this paper, the performance degradation of the MMSE receiver due to finite precision arithmetic of a digital signal processor is simulated for both non-fading and fading channels. The performance comparison between the MMSE receiver and the DMF receiver, for a given number of bits per sample, is also evaluated.
An approach to regression testing using slicing

The authors present a novel approach to data-flow-based regression testing that uses slicing type algorithms to explicitly detect definition-use pairs that are affected by a program change. An important benefit of the slicing technique is that, unlike previous techniques, no data flow history is needed nor is the recomputation of data flow for the entire program required to detect affected definition-use pairs. The program changes drive the recomputation of the required partial data flow through slicing. Another advantage is that the proposed technique achieves the same testing coverage as a complete retest of the program without the need for maintaining and updating a test suite. <<ETX>>
On the Application of Discrete Marginal Graphical Models

Graphical models are defined by general and possibly complex conditional independence assumptions and are well suited to model direct and indirect associations and effects that are of central importance in many problems of sociology. Such relevance is apparent in research on social mobility. This article provides a unified view of many of the graphical models discussed in a largely scattered literature. The marginal modeling framework proposed here relies on parameters that capture aspects of associations among the variables that are relevant for the graph and, depending on the substantive problem at hand, may lead to deeper insight than other approaches. In this context, model search, which uses a sequence of nested models, means the restriction of increasing subsets of parameters. As a special case, general path models for categorical data are introduced. These models are applied to the social status attainment process, generating substantive results and gaining new insights into the difference between liberal and conservative welfare systems. To help others use these models, all details of the analyses are posted on the Web site for this article at http://nemethr.web. elte.hu/discrete-graphical-models/. Researchers can thus easily modify the analyses to their own data and models.
LIRAD Analysis of TWP Cirrus at Nauru

The purpose of this work is to implement algorithms for retrieval of high-cloud emittance and optical depth using lidar-radiometer (LIRAD) analysis based on available continuous data streams from the Atmospheric Radiation Measurement (ARM) Program’s Cloud and Radiation Testbed (CART) sites. Routine, continuous operation of the micropulse lidar (MPL), infrared thermometer (IRT), microwave radiometer (MWR), and frequent sonde soundings should allow for near-continuous retrieval of LIRAD products, subject to time and accuracy limitations described later in this paper. Initial development of these techniques has focused on the Tropical Western Pacific (TWP) sites, where cirrus clouds are common and temperatures remain inside the range of the IRT. We present preliminary results based on measurements at Nauru over a three-month period in 1999. These results utilize a recently released higher-level MPL data stream. Algorithms used in this analysis are being refined for use in a LIRAD Value-Added Procedure (VAP) for automated retrieval of cirrus optical properties.