Cochannel Interference in Partially Coherent Communication

Effects of cochannel interference and synchronization error of the carrier phase on the probability of error in binary communications are considered. Several bounds on the probability of error are proposed. The bounds are easy to compute and do not require complete statistical characterization of the errors. They turn out to be simple linear combinations of error probabilities with no cochannel interferences and no phase errors. Several illustrative examples are given which show that the bounds can be tight.

Specific immunoneutralization of FSH leads to apoptotic cell death of the pachytene spermatocytes and spermatogonial cells in the rat

Although requirement for follicle stimulating hormone (FSH) in the initiation of spermatogenesis is well documented, its role in adult spermatogenesis is still debated. In the present communication, we have investigated the effect of specific immunoneutralization of FSH on apoptotic cell death in the testicular germ cells both in immature and adult rats. The germ cells of control animals showed predominantly high molecular weight DNA while the antiserum (a/s) treated group showed DNA fragmentation characteristic of apoptosis. The pattern could be detected within 24 hours of a/s treatment, and became more pronounced after 48 hours. The germ cells were purified from FSH a/s treated rats by centrifugal elutriation and vulnerability of each cell type to undergo apoptosis on FSH neutralization was investigated. The pachytene spermatocytes were found to be most sensitive to absence of FSH, even in the adult animals suggesting the involvement of FSH in spermatogenesis. The in situ analysis of DNA strand breakage following FSH a/s treatment showed fragmentation of the DNA of the pachytene spermatocytes confirming this observation. The in situ analysis also showed that the spermatogonia undergo apoptosis in addition to the pachytene spermatocytes. These data clearly demonstrate the role of FSH in the adult rat spermatogenesis.

Application of optimization methods to vibration control of stretched strings

In this paper, non-linear programming techniques are applied to the problem of controlling the vibration pattern of a stretched string. First, the problem of finding the magnitudes of two control forces applied at two points l1 and l2 on the string to reduce the energy of vibration over the interval (l1, l2) relative to the energy outside the interval (l1, l2) is considered. For this problem the relative merits of various methods of non-linear programming are compared. The more complicated problem of finding the positions and magnitudes of two control forces to obtain the desired energy pattern is then solved by using the slack unconstrained minimization technique with the Fletcher-Powell search. In the discussion of the results it is shown that the position of the control force is very important in controlling the energy pattern of the string.

Joint evaluation of multiple speech patterns for speech recognition and training

We are addressing the novel problem of jointly evaluating multiple speech patterns for automatic speech recognition and training. We propose solutions based on both the non-parametric dynamic time warping (DTW) algorithm, and the parametric hidden Markov model (HMM). We show that a hybrid approach is quite effective for the application of noisy speech recognition. We extend the concept to HMM training wherein some patterns may be noisy or distorted. Utilizing the concept of ``virtual pattern'' developed for joint evaluation, we propose selective iterative training of HMMs. Evaluating these algorithms for burst/transient noisy speech and isolated word recognition, significant improvement in recognition accuracy is obtained using the new algorithms over those which do not utilize the joint evaluation strategy.

Ligand dependent intra and inter subunit communication in human tryptophanyl tRNA synthetase as deduced from the dynamics of structure networks

Homodimeric protein tryptophanyl tRNA synthetase (TrpRS) has a Rossmann fold domain and belongs to the 1c subclass of aminoacyl tRNA synthetases. This enzyme performs the function of acylating the cognate tRNA. This process involves a number of molecules (2 protein subunits, 2 tRNAs and 2 activated Trps) and thus it is difficult to follow the complex steps in this process. Structures of human TrpRS complexed with certain ligands are available. Based on structural and biochemical data, mechanism of activation of Trp has been speculated. However, no structure has yet been solved in the presence of both the tRNA(Trp) and the activated Trp (TrpAMP). In this study, we have modeled the structure of human TrpRS bound to the activated ligand and the cognate tRNA. In addition, we have performed molecular dynamics (MD) simulations on these models as well as other complexes to capture the dynamical process of ligand induced conformational changes. We have analyzed both the local and global changes in the protein conformation from the protein structure network (PSN) of MD snapshots, by a method which was recently developed in our laboratory in the context of the functionally monomeric protein, methionyl tRNA synthetase. From these investigations, we obtain important information such as the ligand induced correlation between different residues of this protein, asymmetric binding of the ligands to the two subunits of the protein as seen in the crystal structure analysis, and the path of communication between the anticodon region and the aminoacylation site. Here we are able to elucidate the role of dimer interface at a level of detail, which has not been captured so far.

Ion-regulatory proreins in neuronal development and communication

Brain function is critically dependent on the ionic homeostasis in both the extra- and intracellular compartment. The regulation of brain extracellular ionic composition mainly relies on active transport at blood brain and at blood cerebrospinal fluid interfaces whereas intracellular ion regulation is based on plasmalemmal transporters of neurons and glia. In addition, the latter mechanisms can generate physiologically as well as pathophysiologically significant extracellular ion transients. In this work I have studied molecular mechanisms and development of ion regulation and how these factors alter neuronal excitability and affect synaptic and non-synaptic transmission with a particular emphasis on intracellular pH and chloride (Cl-) regulation. Why is the regulation of acid-base equivalents (H+ and HCO3-) and Cl- of such interest and importance? First of all, GABAA-receptors are permeable to both HCO3- and Cl-. In the adult mammalian central nervous system (CNS) fast postsynaptic inhibition relies on GABAA-receptor mediated transmission. Today, excitatory effects of GABAA-receptors, both in mature neurons and during the early development, have been recognized and the significance of the dual actions of GABA on neuronal communication has become an interesting field of research. The transmembrane gradients of Cl- and HCO3- determine the reversal potential of GABAA-receptor mediated postsynaptic potentials and hence, the function of pH and Cl- regulatory proteins have profound consequences on GABAergic signaling and neuronal excitability. Secondly, perturbations in pH can cause a variety of changes in cellular function, many of them resulting from the interaction of protons with ionizable side chains of proteins. pH-mediated alterations of protein conformation in e.g. ion channels, transporters, and enzymes can powerfully modulate neurotransmission. In the context of pH homeostasis, the enzyme carbonic anhydrase (CA) needs to be taken into account in parallel with ion transporters: for CO2/HCO3- buffering to act in a fast manner, CO2 (de)hydration must be catalyzed by this enzyme. The acid-base equivalents that serve as substrates in the CO2 dehydration-hydration reaction are also engaged in many carrier and channel mediated ion movements. In such processes, CA activity is in key position to modulate transmembrane solute fluxes and their consequences. The bicarbonate transporters (BTs; SLC4) and the electroneutral cation-chloride cotransporters (CCCs; SLC12) belong the to large gene family of solute carriers (SLCs). In my work I have studied the physiological roles of the K+-Cl- cotransporter KCC2 (Slc12a5) and the Na+-driven Cl--HCO3- exchanger NCBE (Slc4a10) and the roles of these two ion transporters in the modualtion of neuronal communication and excitability in the rodent hippocampus. I have also examined the cellular localization and molecular basis of intracellular CA that has been shown to be essential for the generation of prolonged GABAergic excitation in the mature hippocampus. The results in my Thesis provide direct evidence for the view that the postnatal up-regulation of KCC2 accounts for the developmental shift from depolarizing to hyperpolarizing postsynaptic EGABA-A responses in rat hippocampal pyramidal neurons. The results also indicate that after KCC2 expression the developmental onset of excitatory GABAergic transmission upon intense GABAA-receptor stimulation depend on the expression of intrapyramidal CA, identified as the CA isoform VII. Studies on mice with targeted Slc4a10 gene disruption revealed an important role for NCBE in neuronal pH regulation and in pH-dependent modulation of neuronal excitability. Furthermore, this ion transporter is involved in the basolateral Na+ and HCO3- uptake in choroid plexus epithelial cells, and is thus likely to contribute to cerebrospinal fluid production.

Mathematical model and rule extraction for tool wear monitoring problem using nature inspired techniques

In this paper, pattern classification problem in tool wear monitoring is solved using nature inspired techniques such as Genetic Programming(GP) and Ant-Miner (AM). The main advantage of GP and AM is their ability to learn the underlying data relationships and express them in the form of mathematical equation or simple rules. The extraction of knowledge from the training data set using GP and AM are in the form of Genetic Programming Classifier Expression (GPCE) and rules respectively. The GPCE and AM extracted rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in GP evolved GPCE and AM based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The performance of the data classification using GP and AM is as good as the classification accuracy obtained in the earlier study.

Using multi-label classification for acoustic pattern detection and assisting bird species surveys

Acoustics is a rich source of environmental information that can reflect the ecological dynamics. To deal with the escalating acoustic data, a variety of automated classification techniques have been used for acoustic patterns or scene recognition, including urban soundscapes such as streets and restaurants; and natural soundscapes such as raining and thundering. It is common to classify acoustic patterns under the assumption that a single type of soundscapes present in an audio clip. This assumption is reasonable for some carefully selected audios. However, only few experiments have been focused on classifying simultaneous acoustic patterns in long-duration recordings. This paper proposes a binary relevance based multi-label classification approach to recognise simultaneous acoustic patterns in one-minute audio clips. By utilising acoustic indices as global features and multilayer perceptron as a base classifier, we achieve good classification performance on in-the-field data. Compared with single-label classification, multi-label classification approach provides more detailed information about the distributions of various acoustic patterns in long-duration recordings. These results will merit further biodiversity investigations, such as bird species surveys.

Joint decoding of multiple speech patterns for robust speech recognition

We are addressing a new problem of improving automatic speech recognition performance, given multiple utterances of patterns from the same class. We have formulated the problem of jointly decoding K multiple patterns given a single Hidden Markov Model. It is shown that such a solution is possible by aligning the K patterns using the proposed Multi Pattern Dynamic Time Warping algorithm followed by the Constrained Multi Pattern Viterbi Algorithm The new formulation is tested in the context of speaker independent isolated word recognition for both clean and noisy patterns. When 10 percent of speech is affected by a burst noise at -5 dB Signal to Noise Ratio (local), it is shown that joint decoding using only two noisy patterns reduces the noisy speech recognition error rate to about 51 percent, when compared to the single pattern decoding using the Viterbi Algorithm. In contrast a simple maximization of individual pattern likelihoods, provides only about 7 percent reduction in error rate.

Journalism, media & communication network: Final report 2015

The JoMeC Network project had three key objectives. These were to: 1. Benchmark the pedagogical elements of journalism, media and communication (JoMeC) programs at Australian universities in order to develop a set of minimum academic standards, to be known as Threshold Learning Outcomes (TLOs), which would applicable to the disciplines of Journalism, Communication and/or Media Studies, and Public Relations; 2. Build a learning and teaching network of scholars across the JoMeC disciplines to support collaboration, develop leadership potential among educators, and progress shared priorities; 3. Create an online resources hub to support learning and teaching excellence and foster leadership in learning and teaching in the JoMeC disciplines. In order to benchmark the pedagogical elements of the JoMeC disciplines, the project started with a comprehensive review of the disciplinary settings of journalism, media and communication-related programs within Higher Education in Australia plus an analysis of capstone units (or subjects) offered in JoMeC-related degrees. This audit revealed a diversity of degree titles, disciplinary foci, projected career outcomes and pedagogical styles in the 36 universities that offered JoMeC-related degrees in 2012, highlighting the difficulties of classifying the JoMeC disciplines collectively or singularly. Instead of attempting to map all disciplines related to journalism, media and communication, the project team opted to create generalised TLOs for these fields, coupled with detailed TLOs for bachelor-level qualifications in three selected JoMeC disciplines: Journalism, Communication and/or Media Studies, and Public Relations. The initial review’s outcomes shaped the methodology that was used to develop the TLOs. Given the complexity of the JoMeC disciplines and the diversity of degrees across the network, the project team deployed an issue-framing process to create TLO statements. This involved several phases, including discussions with an issue-framing team (an advisory group of representatives from different disciplinary areas); research into accreditation requirements and industry-produced materials about employment expectations; evaluation of learning outcomes from universities across Australia; reviews of scholarly literature; as well as input from disciplinary leaders in a variety of forms. Draft TLOs were refined after further consultation with industry stakeholders and the academic community via email, telephone interviews, and meetings and public forums at conferences. This process was used to create a set of common TLOs for JoMeC disciplines in general and extended TLO statements for the specific disciplines of Journalism and Public Relations. A TLO statement for Communication and/or Media Studies remains in draft form. The Australian and New Zealand Communication Association (ANZCA) and Journalism Education and Research Association of Australian (JERAA) have agreed to host meetings to review, revise and further develop the TLOs. The aim is to support the JoMeC Network’s sustainability and the TLOs’ future development and use.

Enhancing sensor network lifetime using interactive communication

We are concerned with maximizing the lifetime of a data-gathering wireless sensor network consisting of set of nodes directly communicating with a base-station. We model this scenario as the m-message interactive communication between multiple correlated informants (sensor nodes) and a recipient (base-station). With this framework, we show that m-message interactive communication can indeed enhance network lifetime. Both worst-case and average-case performances are considered.