Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Multi-target Localization Method for Distributed MIMO Radar

This paper studies a multi-target localization method for distributed Multiple-input Multiple-output (MIMO) radar. We assume that the sets of time delays have already been estimated by a pre-processing algorithm. Based on the assumption, we propose a search pairing method based on ellipse model to locate the multi-target. Simulation results demonstrate that the proposed method effectively accomplishes multi-target localization with the distributed MIMO radar across scattering cross-section (RCS). Comparisons are given to present that the proposed method outperforms the existing method both at the search time and the localization accuracy.
Cross-lingual Adaptation as a Baseline: Adapting Maximum Entropy Models to Bulgarian

We describe our efforts in adapting five basic natural language processing components to Bulgar-ian: sentence splitter, tokenizer, part-of-speech tagger, chunker, and syntactic parser. The components were originally developed for English within OpenNLP, an open source maximum entropy based machine learning toolkit, and were retrained based on manually annotated training data from the BulTreeBank. The evaluation results show an F1 score of 92.54% for the sentence splitter, 98.49% for the tokenizer, 94.43% for the part-of-speech tagger, 84.60% for the chunker, and 77.56% for the syntactic parser, which should be interpreted as baseline for Bulgarian.
New bit loading algorithms for DMT systems based on the greedy approach

The performance of a DMT system, which transmits information over channels with varying characteristics through the frequency zones, is improved when the subchannels of the system are loaded with variable data rate. In this study, we meet the bit loading problem of the subcarriers of a DMT system. We propose two new optimum-loading algorithms with low computational complexity. These algorithms assign integer number of bits successively until a target bit rate is fulfilled. We compare them with several existing algorithms in terms of transmitting energy versus data rate and complexity versus system's characteristics i.e. number of subcarriers and target data rate. Simulations prove that without sacrificing optimality both our proposals present a lower complexity level. Copyright © 2006 John Wiley & Sons, Ltd.
Isolation and Speciation of Candida in Type II Diabetic Patients using CHROM Agar: A Microbial Study.

INTRODUCTION Newer Candida species are now becoming increasingly predominant commensal in the oral cavity. AIM Aim of the study was to identify and compare different Candida species in the oral cavity of Type II diabetic individuals. MATERIALS AND METHODS The present microbial study was carried out for the duration of three months. Sixty participants were included in the study and divided into two groups of 30 individual each. Group I consisted of patients with Type II diabetes while Group II consisted of healthy individuals without diabetes or any other systemic disease. A total of 3 ml of unstimulated whole saliva was collected from them and centrifuged at 5000 rpm for fives minutes. This pellet was plated onto CHROM agar medium plates and incubated at 37°C for at least 3-4 days. CHROM agar plates were visualized daily at 24 hours, 72 hours and followed up to seven days to check for growth. Candida speciation was done by counting the different coloured creamy colonies. Comparison of Candida spp. between two groups was done by applying the Student's t-test. A p-value<0.05 was considered as statistically significant. RESULTS All the species of Candida, namely, Candida albicans, Candida glabrata, Candida dubliniensis, Candida krusei, Candida parapsilosis except for Candida tropicalis showed a significantly higher (p<0.001) occurrence in the diabetic group compared to the healthy group. The highest identified species is C. parapsilosis, second being C. albicans in both the groups. CONCLUSION C. parapsilosis is now considered as one of the significant causes of Candida infection in the oral cavity. This increased virulence will affect the global burden of Candidiasis as few treatment options are available for this new pathogen.
Climate change and the socioeconomics of global food production: a quantitative analysis of how socioeconomic factors influence the vulnerability of grain crops to drought

in 2008 to advance public and private action on climate change through innovative, rigorous research. The Centre is funded by the UK Economic and Social Research Council and has five inter-linked research programmes: 1. Developing climate science and economics 2. Climate change governance for a new global deal 3. Adaptation to climate change and human development 4. Governments, markets and climate change mitigation 5. The Munich Re Programme-Evaluating the economics of climate risks and opportunities in the insurance sector More information about the Centre for Climate Change Economics and Policy can be found This working paper is intended to stimulate discussion within the research community and among users of research, and its content may have been submitted for publication in academic journals. It has been reviewed by at least one internal referee before publication. The views expressed in this paper represent those of the author(s) and do not necessarily represent those of the host institutions or funders. Acknowledgements We would like to thank Jami Dixon for collecting data, and Esben Almquist and Alexander Walther for their Matlab scripts. Abstract The impact of climate change on agriculture depends on the environmental and socioeconomic contexts in which the changes occur. However, current tools to anticipate climate change impacts focus almost entirely on biological and environmental processes. For example, most large-scale crop models can identify where yields are sensitive to new temperatures and CO 2 concentrations but do not include any socioeconomic factors that may enable (or inhibit) farmers' abilities to adapt. To address this gap, this paper uses national scale socioeconomic , meteorological and agricultural data to identify socioeconomic factors that have made rice, maize and wheat production resilient and sensitive to past droughts. Results suggest that cereal harvests in countries undergoing economic and political transition are most vulnerable to droughts and that factors related to investments in the agriculture sector (such as the amount of fertilizer used by farmers or the amount of Gross Domestic Product produced by a nation's agricultural sector) help reduce vulnerability. While results are limited by data quality and availability, this study provides preliminary quantitative insights that highlight important areas for further research on the socioeconomic factors that create vulnerability to climate change.
Analysing IT Investments in the Public Sector: A Project Portfolio Approach

Since the first electronic computers hit the market in the 1950's, governments have been amongst the biggest users of Information Technology (IT) worldwide. Therefore, it is in the general public's best interests that government officials are provided with concepts, methods and tools that help them to optimise the results yielded by IT investments. This paper presents a method that identifies the best implementation order for a portfolio of IT projects that has been broken down into a large number of subprojects. The method builds on previous proposals by providing a framework that properly considers the intangible benefits that are a matter of common concern in the public sector.
SATCOM link adaptive configuration design in radio frequency interference environment

Radio frequency interference (RFI) is ubiquitous in wireless communications which could greatly degrade communication system performances in an open environment. For satellite communications (SATCOM), the system performances degradation could be even worse considering the large round trip time (RTT) delay. To mitigate RFI effects, cognitive radio with adaptive waveform configurations could be effective. To quantify the cognitive radio system performance, spectral efficiency and energy efficiency are two metrics. Spectral efficiency (SE), defined as the average data rate per unit bandwidth, quantifies how efficiently the available spectrum is utilized. Energy efficiency (EE), defined as the successful transmitted information bits per unit energy from transmitter to receiver, quantifies how efficiently the energy is utilized. However, the two metrics construct a fundamental trade-off in communication system design. Basically, with higher average energy per bit to noise power spectral density ratio at the receiver, the packet can be more successfully detected, thus utilizing the spectrum more efficiently, giving higher SE; which however requires more energy, lowering EE, and vice versa. In this paper, we design adaptive configuration of SATCOM link operating in the RFI environment, and study the system trade-off between SE and EE, by greatly exploiting cognitive radio configurability for SATCOM interference mitigation capability. A general metric SEE (Spectral/Energy Efficiency), which quantifies the preference of SE or EE, has been formulated with practical system parameters, including information bit length, overhead bits, modulation and channel coding schemes, frequency hopping, wireless channel conditions, frame retransmissions, etc, to facilitate the system analysis. A closed-form solution for information bits rate control is obtained in various RFI environments. An iteration algorithm is presented for cognitive radio joint transmission power control, information bits rate control, and modulation and channel coding adaptation, to optimize the system performances in the RFI environment.
A Hybrid Relative Distance Based Cluster Scheme for Energy Efficiency in Wireless Sensor Networks

Energy efficiency is of great importance for the wireless sensor network (WSN). A popular way to save energy is to construct clusters for data aggregation and forwarding. This paper studies the distributed cluster algorithm to improve the energy consumption efficiency. We observe that the cluster head has to lie within the transmission range of the base station (sink node) and the distance between cluster head and base station is critical for the energy consumption performance, we propose a hybrid relative distance based clustering scheme (HRDCS), which considers the relative distance to the base station and the residual energy level during the cluster head selection stage. Consequently we could better balance the chance of being cluster head for all nodes. Simulation results show that our scheme is able to result in longer network lifetime than the well-known protocol LEACH [2].
Learning Techniques in Verification and Model Checking

A minimally adequate teacher is one that can answer two types of questions: should the point x ∈ D be classified positively or negatively (eval), and given a conjecture conj : D → {true, false}, is this the correct concept the teacher has in mind (equiv). Starting with Angluin’s seminal work [5] on regular languages, learning with minimally adequate teachers is now well-understood in computational learning theory. Recently, there have been several applications of these techniques to problems in verification and model-checking. We describe three of these: on synthesizing interfaces for APIs [3], on automatically inferring invariants for imperative programs [23], and in compositional assume-guarantee reasoning [30]. We argue that the appropriate learning problem can be seen as the computational content of the verification problem being solved.
Unraveling Firms: Demand, Productivity and Markups Heterogeneity

We develop a novel framework that simultaneously allows recovering heterogeneity in demand, quantity TFP and markups across firms while leaving the correlation between the three dimensions unrestricted. We accomplish this by explicitly introducing demand heterogeneity and systematically exploiting assumptions used in previous productivity estimation approaches. In doing so, we provide an exact decomposition of revenue productivity in terms of the underlying heterogeneities, thus bridging the gap between quantity and revenue productivity estimations. We use Belgian firms production data to quantify TFP, demand and markups and show how they are correlated with each other, across time and with measures obtained from other approaches. In doing so, we find quantity TFP and demand to be strongly negatively correlated with each other so suggesting a trade-off between the quality of a firm’s products and their production cost. We also show how our framework provides deeper and sharper insights on the response of firms to increasing import competition from China. In particular, we find that changes in revenue productivity materialise as the outcome of complex, and sometimes offsetting, changes in quantity TFP, demand, markups and production scale.
Modeling the Etiology of p53-mutated Cancer Cells*

p53 gene mutations are among the most common alterations in cancer. In most cases, missense mutations in one TP53 allele are followed by loss-of-heterozygosity (LOH), so tumors express only mutant p53. TP53 mutations and LOH have been linked, in many cases, with poor therapy response and worse outcome. Despite this, remarkably little is known about how TP53 point mutations are acquired, how LOH occurs, or the cells involved. Nutlin-3a occupies the p53-binding site in MDM2 and blocks p53-MDM2 interaction, resulting in the stabilization and activation of p53 and subsequent growth arrest or apoptosis. We leveraged the powerful growth inhibitory activity of Nutlin-3a to select p53-mutated cells and examined how TP53 mutations arise and how the remaining wild-type allele is lost or inactivated. Mismatch repair (MMR)-deficient colorectal cancer cells formed heterozygote (p53 wild-type/mutant) colonies when cultured in low doses of Nutlin-3a, whereas MMR-corrected counterparts did not. Placing these heterozygotes in higher Nutlin-3a doses selected clones in which the remaining wild-type TP53 was silenced. Our data suggest silencing occurred through a novel mechanism that does not involve DNA methylation, histone methylation, or histone deacetylation. These data indicate MMR deficiency in colorectal cancer can give rise to initiating TP53 mutations and that TP53 silencing occurs via a copy-neutral mechanism. Moreover, the data highlight the use of MDM2 antagonists as tools to study mechanisms of TP53 mutation acquisition and wild-type allele loss or silencing in cells with defined genetic backgrounds.
Transaction management for object-oriented databases: performance advantages of using multiple versions

Many applications of object-oriented database systems demand high performance and require longer duration transactions. These requirements are contrary to one another. Two trends in modern systems can help improve the situation. Firstly, multiprocessors are becoming commonplace, and secondly, object-oriented database systems supporting multiple versions are becoming popular. Consequently, database protocols that are less prone to extensive blocking (as can be the case with the popular two-phase locking protocol) are needed in future systems. The authors' simulation studies have shown substantial performance improvements can be obtained by using multiversion protocols for database transaction management. These protocols provide higher throughput at higher levels of concurrency (which are achievable with multiprocessors) than their traditional single version equivalents. <<ETX>>
Confidence-Weighted Linear Classification for Text Categorization

Confidence-weighted online learning is a generalization of margin-based learning of linear classifiers in which the margin constraint is replaced by a probabilistic constraint based on a distribution over classifier weights that is updated online as examples are observed. The distribution captures a notion of confidence on classifier weights, and in some cases it can also be interpreted as replacing a single learning rate by adaptive per-weight rates. Confidence-weighted learning was motivated by the statistical properties of natural-language classification tasks, where most of the informative features are relatively rare. We investigate several versions of confidence-weighted learning that use a Gaussian distribution over weight vectors, updated at each observed example to achieve high probability of correct classification for the example. Empirical evaluation on a range of text-categorization tasks show that our algorithms improve over other state-of-the-art online and batch methods, learn faster in the online setting, and lead to better classifier combination for a type of distributed training commonly used in cloud computing.
Infective pyomyositis and myositis in children in the era of community-acquired, methicillin-resistant Staphylococcus aureus infection.

BACKGROUND Cases of pyomyositis and myositis have been increasing in frequency at Texas Children's Hospital (Houston) since 2000. The increase appears to correlate with the emergence of community-acquired methicillin-resistant Staphylococcus aureus (MRSA). METHODS The medical records of patients with pyomyositis and myositis hospitalized at Texas Children's Hospital during the period from January 2000 through December 2005 were reviewed. Available S. aureus isolates were obtained for susceptibility testing, to determine the presence of pvl (lukS-PV and lukF-PV), and for pulsed-field gel electrophoresis analysis. RESULTS Forty-five previously healthy children with bacterial pyomyositis or myositis were analyzed. The causes were S. aureus (in 57.8% of children) and Streptococcus pyogenes (in 2.2%); 40.0% of children had negative culture results. The number of cases increased between 2000 and 2005, primarily as a result of an increase in the prevalence of community-acquired MRSA. The mean patient age was 5.5 years (range, 0.06-15 years). The thigh (40.0% of children) and pelvis (28.9%) were the most commonly affected sites. The mean abscess diameter was 3.5 cm. Eighteen children required at least 1 muscle drainage procedure. Of the 24 available S. aureus isolates (15 community-acquired MRSA isolates and 9 community-acquired, methicillin-susceptible S. aureus [MSSA] isolates), 16 were found to be USA300 by pulsed-field gel electrophoresis, and 17 carried pvl. Patients with community-acquired MRSA, USA300, and/or pvl-positive strains required more drainage procedures than did those with community-acquired MSSA, non-USA300, and/or pvl-negative strains (81% vs. 40% [P=.05], 82% vs. 29% [P=.02], and 81% vs. 38% [P=.07], respectively). CONCLUSIONS Community-acquired MRSA is an increasing cause of pyomyositis and myositis in children. Community-acquired MRSA, USA300, pvl-positive S. aureus isolates caused more severe disease than did community-acquired MSSA, non-USA300, and pvl-negative isolates, respectively.
Full body interaction for serious games in motor rehabilitation

Serious games and especially their use in healthcare applications are an active and rapidly growing area of research. A key aspect of games in rehabilitation is 3D input. In this paper we present our implementation of a full body motion capture (MoCap) system, which, together with a biosignal acquisition device, has been integrated in a game engine. Furthermore, a workflow has been established that enables the use of acquired skeletal data for serious games in a medical environment. Finally, a serious game has been implemented, targeting rehabilitation of patients with chronic pain of the lower back and neck, a group that has previously been neglected by serious games. The focus of this work is on the full body MoCap system and its integration with biosignal devices and the game engine. A short overview of the application and prelimiary results are provided.
Manifestations of Deviation in the Adolescent Subculture

In this article we will only look at questions relating to school students’ attitudes toward types of deviation such as smoking and the use of alcohol and narcotics. The empirical material is divided into the following topics: how widespread these forms of behavior are; motives that cause adolescents to start smoking, using alcohol, and taking narcotics; and the reactions of people who are most closely associated with them (parents, classmates, and teachers) to such manifestations. As we analyze the material, it is important not only to determine the role that deviation plays in getting through the crisis of adolescence but also to show specific gender differences in the adolescent subculture’s deviant forms of behavior. The article is based on the materials of a questionnaire survey of 2,983 students in the seventh, ninth, and eleventh grades of general education schools in Moscow. The survey was carried out in 2002, and was generally designed for the study of the characteristics of the different types of deviant behavior (smoking, using alcohol and narcotics, fighting, becoming sexually active, and so on) and orientations toward maintaining a healthy way of life. The research program within which the project was carried out is a
Medical Image Encryption: An Application for Improved Padding Based GGH Encryption Algorithm

Medical images are regarded as important and sensitive data in the medical informatics systems. For transferring medical images over an insecure network, developing a secure encryption algorithm is necessary. Among the three main properties of security services (i.e., confidentiality, integrity, and availability), the confidentiality is the most essential feature for exchanging medical images among physicians. The Goldreich Goldwasser Halevi (GGH) algorithm can be a good choice for encrypting medical images as both the algorithm and sensitive data are represented by numeric matrices. Additionally, the GGH algorithm does not increase the size of the image and hence, its complexity will remain as simple as O(n2). However, one of the disadvantages of using the GGH algorithm is the Chosen Cipher Text attack. In our strategy, this shortcoming of GGH algorithm has been taken in to consideration and has been improved by applying the padding (i.e., snail tour XORing), before the GGH encryption process. For evaluating their performances, three measurement criteria are considered including (i) Number of Pixels Change Rate (NPCR), (ii) Unified Average Changing Intensity (UACI), and (iii) Avalanche effect. The results on three different sizes of images showed that padding GGH approach has improved UACI, NPCR, and Avalanche by almost 100%, 35%, and 45%, respectively, in comparison to the standard GGH algorithm. Also, the outcomes will make the padding GGH resist against the cipher text, the chosen cipher text, and the statistical attacks. Furthermore, increasing the avalanche effect of more than 50% is a promising achievement in comparison to the increased complexities of the proposed method in terms of encryption and decryption processes.
Strongly Stabilizing Controller Synthesis for a Class of MIMO Plants

Abstract The strong stabilization problem (i.e., stabilization by a stable feedback controller) is studied for unstable MIMO plants with arbitrary number of finitely many poles but no more than two blocking zeros in the extended right half plane. Simple strongly stabilizing controllers, of order not exceeding that of the plant, are obtained for such plants satisfying the parity interlacing property. Connections with earlier design methods are illustrated: for this particular class of plants, it is shown that a sufficient condition appearing in earlier publications is equivalent to the parity interlacing property and hence it is also necessary for the existence of strongly stabilizing controllers. The results are illustrated with numerical examples.