Interval Data Classification under Partial Information: A Chance-Constraint Approach

This paper presents a Chance-constraint Programming approach for constructing maximum-margin classifiers which are robust to interval-valued uncertainty in training examples. The methodology ensures that uncertain examples are classified correctly with high probability by employing chance-constraints. The main contribution of the paper is to pose the resultant optimization problem as a Second Order Cone Program by using large deviation inequalities, due to Bernstein. Apart from support and mean of the uncertain examples these Bernstein based relaxations make no further assumptions on the underlying uncertainty. Classifiers built using the proposed approach are less conservative, yield higher margins and hence are expected to generalize better than existing methods. Experimental results on synthetic and real-world datasets show that the proposed classifiers are better equipped to handle interval-valued uncertainty than state-of-the-art.

Assessing the effectiveness of High Intensity Interval Training (HIIT) for smoking cessation in women: HIIT to quit study protocol

Background: Smoking and physical inactivity are major risk factors for heart disease. Linking strategies that promote improvements in fitness and assist quitting smoking has potential to address both these risk factors simultaneously. The objective of this study is to compare the effects of two exercise interventions (high intensity interval training (HIIT) and lifestyle physical activity) on smoking cessation in female smokers. Method/design: This study will use a randomised controlled trial design. Participants: Women aged 18–55 years who smoke ≥ 5 cigarettes/day, and want to quit smoking. Intervention: all participants will receive usual care for quitting smoking. Group 1 - will complete two gym-based supervised HIIT sessions/week and one home-based HIIT session/week. At each training session participants will be asked to complete four 4-min (4 × 4 min) intervals at approximately 90 % of maximum heart rate interspersed with 3- min recovery periods. Group 2 - participants will receive a resource pack and pedometer, and will be asked to use the 10,000 steps log book to record steps and other physical activities. The aim will be to increase daily steps to 10,000 steps/day. Analysis will be intention to treat and measures will include smoking cessation, withdrawal and cravings, fitness, physical activity, and well-being. Discussion: The study builds on previous research suggesting that exercise intensity may influence the efficacy of exercise as a smoking cessation intervention. The hypothesis is that HIIT will improve fitness and assist women to quit smoking.

Huffman Binary Coding of WLN Symbols for File-Compression

Construction of Huffman binary codes for WLN symbols is described for the compression of a WLN file. Here, a parenthesized representation of the tree structure is used for computer encoding.

Deriving structural information from non-coding ribonucleic acids by mass spectrometry

The purpose of this study is to describe the development of application of mass spectrometry for the structural analyses of non-coding ribonucleic acids during past decade. Mass spectrometric methods are compared of traditional gel electrophoretic methods, the characteristics of performance of mass spectrometric, analyses are studied and the future trends of mass spectrometry of ribonucleic acids are discussed. Non-coding ribonucleic acids are short polymeric biomolecules which are not translated to proteins, but which may affect the gene expression in all organisms. Regulatory ribonucleic acids act through transient interactions with key molecules in signal transduction pathways. Interactions are mediated through specific secondary and tertiary structures. Posttranscriptional modifications in the structures of molecules may introduce new properties to the organism, such as adaptation to environmental changes or development of resistance to antibiotics. In the scope of this study, the structural studies include i) determination of the sequence of nucleobases in the polymer chain, ii) characterisation and localisation of posttranscriptional modifications in nucleobases and in the backbone structure, iii) identification of ribonucleic acid-binding molecules and iv) probing of higher order structures in the ribonucleic acid molecule. Bacteria, archaea, viruses and HeLa cancer cells have been used as target organisms. Synthesised ribonucleic acids consisting of structural regions of interest have been frequently used. Electrospray ionisation (ESI) and matrix-assisted laser desorption ionisation (MALDI) have been used for ionisation of ribonucleic analytes. Ammonium acetate and 2-propanol are common solvents for ESI. Trihydroxyacetophenone is the optimal MALDI matrix for ionisation of ribonucleic acids and peptides. Ammonium salts are used in ESI buffers and MALDI matrices as additives to remove cation adducts. Reverse phase high performance liquid chromatography has been used for desalting and fractionation of analytes either off-line of on-line, coupled with ESI source. Triethylamine and triethylammonium bicarbonate are used as ion pair reagents almost exclusively. Fourier transform ion cyclotron resonance analyser using ESI coupled with liquid chromatography is the platform of choice for all forms of structural analyses. Time-of-flight (TOF) analyser using MALDI may offer sensitive, easy-to-use and economical solution for simple sequencing of longer oligonucleotides and analyses of analyte mixtures without prior fractionation. Special analysis software is used for computer-aided interpretation of mass spectra. With mass spectrometry, sequences of 20-30 nucleotides of length may be determined unambiguously. Sequencing may be applied to quality control of short synthetic oligomers for analytical purposes. Sequencing in conjunction with other structural studies enables accurate localisation and characterisation of posttranscriptional modifications and identification of nucleobases and amino acids at the sites of interaction. High throughput screening methods for RNA-binding ligands have been developed. Probing of the higher order structures has provided supportive data for computer-generated three dimensional models of viral pseudoknots. In conclusion. mass spectrometric methods are well suited for structural analyses of small species of ribonucleic acids, such as short non-coding ribonucleic acids in the molecular size region of 20-30 nucleotides. Structural information not attainable with other methods of analyses, such as nuclear magnetic resonance and X-ray crystallography, may be obtained with the use of mass spectrometry. Sequencing may be applied to quality control of short synthetic oligomers for analytical purposes. Ligand screening may be used in the search of possible new therapeutic agents. Demanding assay design and challenging interpretation of data requires multidisclipinary knowledge. The implement of mass spectrometry to structural studies of ribonucleic acids is probably most efficiently conducted in specialist groups consisting of researchers from various fields of science.

Two Stage Transform Vector Quantization of LSFs for Wideband Speech Coding

We investigate the use of a two stage transform vector quantizer (TSTVQ) for coding of line spectral frequency (LSF) parameters in wideband speech coding. The first stage quantizer of TSTVQ, provides better matching of source distribution and the second stage quantizer provides additional coding gain through using an individual cluster specific decorrelating transform and variance normalization. Further coding gain is shown to be achieved by exploiting the slow time-varying nature of speech spectra and thus using inter-frame cluster continuity (ICC) property in the first stage of TSTVQ method. The proposed method saves 3-4 bits and reduces the computational complexity by 58-66%, compared to the traditional split vector quantizer (SVQ), but at the expense of 1.5-2.5 times of memory.

Finite field computation technique for exact solution of systems of linear equations and interval linear programming problems

An error-free computational approach is employed for finding the integer solution to a system of linear equations, using finite-field arithmetic. This approach is also extended to find the optimum solution for linear inequalities such as those arising in interval linear programming probloms.

Association of FOXE1 Polyalanine Repeat Region with Papillary Thyroid Cancer

CONTEXT: Polyalanine tract variations in transcription factors have been identified for a wide spectrum of developmental disorders. The thyroid transcription factor forkhead factor E1 (FOXE1) contains a polymorphic polyalanine tract with 12-22 alanines. Single-nucleotide polymorphisms (SNP) close to this locus are associated with papillary thyroid cancer (PTC), and a strong linkage disequilibrium block extends across this region. OBJECTIVE: The objective of the study was to assess whether the FOXE1 polyalanine repeat region was associated with PTC and to assess the effect of polyalanine repeat region variants on protein expression, DNA binding, and transcriptional function on FOXE1-responsive promoters. DESIGN: This was a case-control study. SETTING: The study was conducted at a tertiary referral hospital. PATIENTS AND METHODS: The FOXE1 polyalanine repeat region and tag SNP were genotyped in 70 PTC, with a replication in a further 92 PTC, and compared with genotypes in 5767 healthy controls (including 5667 samples from the Wellcome Trust Case Control Consortium). In vitro studies were performed to examine the protein expression, DNA binding, and transcriptional function for FOXE1 variants of different polyalanine tract lengths. RESULTS: All the genotyped SNP were in tight linkage disequilibrium, including the FOXE1 polyalanine repeat region. We confirmed the strong association of rs1867277 with PTC (overall P = 1 × 10(-7), odds ratio 1.84, confidence interval 1.31-2.57). rs1867277 was in tight linkage disequilibrium with the FOXE1 polyalanine repeat region (r(2) = 0.95). FOXE1(16Ala) was associated with PTC with an odds ratio of 2.23 (confidence interval 1.42-3.50; P = 0.0005). Functional studies in vitro showed that FOXE1(16Ala) was transcriptionally impaired compared with FOXE1(14Ala), which was not due to differences in protein expression or DNA binding. CONCLUSIONS: We have confirmed the previous association of FOXE1 with PTC. Our data suggest that the coding polyalanine expansion in FOXE1 may be responsible for the observed association between FOXE1 and PTC.

Low ML-Decoding Complexity, Large Coding Gain, Full-Rate, Full-Diversity STBCs for 2 x 2 and 4 x 2 MIMO Systems

This paper deals with low maximum-likelihood (ML)-decoding complexity, full-rate and full-diversity space-time block codes (STBCs), which also offer large coding gain, for the 2 transmit antenna, 2 receive antenna (2 x 2) and the 4 transmit antenna, 2 receive antenna (4 x 2) MIMO systems. Presently, the best known STBC for the 2 2 system is the Golden code and that for the 4 x 2 system is the DjABBA code. Following the approach by Biglieri, Hong, and Viterbo, a new STBC is presented in this paper for the 2 x 2 system. This code matches the Golden code in performance and ML-decoding complexity for square QAM constellations while it has lower ML-decoding complexity with the same performance for non-rectangular QAM constellations. This code is also shown to be information-lossless and diversity-multiplexing gain (DMG) tradeoff optimal. This design procedure is then extended to the 4 x 2 system and a code, which outperforms the DjABBA code for QAM constellations with lower ML-decoding complexity, is presented. So far, the Golden code has been reported to have an ML-decoding complexity of the order of for square QAM of size. In this paper, a scheme that reduces its ML-decoding complexity to M-2 root M is presented.

A Joint Source-Channel Coding Scheme for Transmission of Correlated Discrete Sources over a Gaussian Multiple Access Channel

We consider the problem of transmission of correlated discrete alphabet sources over a Gaussian Multiple Access Channel (GMAC). A distributed bit-to-Gaussian mapping is proposed which yields jointly Gaussian codewords. This can guarantee lossless transmission or lossy transmission with given distortions, if possible. The technique can be extended to the system with side information at the encoders and decoder.

Genotype-Phenotype Relationships in Long QT Syndrome: Role of Mental Stress, Adrenergic Activity and a Common KCNH2 Polymorphism

Long QT syndrome is a congenital or acquired arrhythmic disorder which manifests as a prolonged QT-interval on the electrocardiogram and as a tendency to develop ventricular arrhythmias which can lead to sudden death. Arrhythmias often occur during intense exercise and/or emotional stress. The two most common subtypes of LQTS are LQT1, caused by mutations in the KCNQ1 gene and LQT2, caused by mutations in the KCNH2 gene. LQT1 and LQT2 patients exhibit arrhythmias in different types of situations: in LQT1 the trigger is usually vigorous exercise whereas in LQT2 arrhythmia results from the patient being startled from rest. It is not clear why trigger factors and clinical outcome differ from each other in the different LQTS subtypes. It is possible that stress hormones such as catecholamines may show different effects depending on the exact nature of the genetic defect, or sensitivity to catecholamines varies from subject to subject. Furthermore, it is possible that subtle genetic variants of putative modifier genes, including those coding for ion channels and hormone receptors, play a role as determinants of individual sensitivity to life-threatening arrhythmias. The present study was designed to identify some of these risk modifiers. It was found that LQT1 and LQT2 patients show an abnormal QT-adaptation to both mental and physical stress. Furthermore, as studied with epinephrine infusion experiments while the heart was paced and action potentials were measured from the right ventricular septum, LQT1 patients showed repolarization abnormalities which were related to their propensity to develop arrhythmia during intense, prolonged sympathetic tone, such as exercise. In LQT2 patients, this repolarization abnormality was noted already at rest corresponding to their arrhythmic episodes as a result of intense, sudden surges in adrenergic tone, such as fright or rage. A common KCNH2 polymorphism was found to affect KCNH2 channel function as demonstrated by in vitro experiments utilizing mammalian cells transfected with the KCNH2 potassium channel as well as QT-dynamics in vivo. Finally, the present study identified a common β-1-adrenergic receptor genotype that is related a shorter QT-interval in LQT1 patients. Also, it was discovered that compound homozygosity for two common β-adrenergic polymorphisms was related to the occurrence of symptoms in the LQT1 type of long QT syndrome. The studies demonstrate important genotype-phenotype differences between different LQTS subtypes and suggest that common modifier gene polymorphisms may affect cardiac repolarization in LQTS. It will be important in the future to prospectively study whether variant gene polymorphisms will assist in clinical risk profiling of LQTS patients.

Correlation, Coding, and Cooperation in Wireless Sensor Networks

We consider a single-hop data-gathering sensor network, consisting of a set of sensor nodes that transmit data periodically to a base-station. We are interested in maximizing the lifetime of this network. With our definition of network lifetime and the assumption that the radio transmission energy consumption forms the most significant portion of the total energy consumption at a sensor node, we attempt to enhance the network lifetime by reducing the transmission energy budget of sensor nodes by exploiting three system-level opportunities. We pose the problem of maximizing lifetime as a max-min optimization problem subject to the constraint of successful data collection and limited energy supply at each node. This turns out to be an extremely difficult optimization to solve. To reduce the complexity of this problem, we allow the sensor nodes and the base-station to interactively communicate with each other and employ instantaneous decoding at the base-station. The chief contribution of the paper is to show that the computational complexity of our problem is determined by the complex interplay of various system-level opportunities and challenges.

Distributed joint source channel coding on a multiple access channel with side information

We consider the problem of transmission of several discrete sources over a multiple access channel (MAC) with side information at the sources and the decoder. Source-channel separation does not hold for this channel. Sufficient conditions are provided for transmission of sources with a given distortion. The channel could have continuous alphabets (Gaussian MAC is a special case). Various previous results are obtained as special cases.

Interactive Distributed Source Coding in Asymmetric Communication Scenarios

We provide a new unified framework, called "multiple correlated informants - single recipient" communication, to address the variations of the traditional Distributed Source Coding (DSC) problem. Different combinations of the assumptions about the communication scenarios and the objectives of communication result in different variations of the DSC problem. For each of these variations, the complexities of communication and computation of the optimal solution is determined by the combination of the underlying assumptions. In the proposed framework, we address the asymmetric, interactive, and lossless variant of the DSC problem, with various objectives of communication and provide optimal solutions for those. Also, we consider both, the worst-case and average-case scenarios.