Miracle-dz/UniFAR-FTUs huggingface dataset:
Supersymmetry versus Gauge Symmetry on the Heterotic Landscape

One of the goals of the landscape program in string theory is to extract information about the space of string vacua in the form of statistical correlations between phenomenological features that are otherwise uncorrelated in field theory. Such correlations would thus represent predictions of string theory that hold independently of a vacuum-selection principle. In this paper, we study statistical correlations between two features which are likely to be central to any potential description of nature at high-energy scales: gauge symmetries and spacetime supersymmetry. We analyze correlations between these two kinds of symmetry within the context of perturbative heterotic string vacua, and find a number of striking features. We find, for example, that the degree of spacetime supersymmetry is strongly correlated with the probabilities of realizing certain gauge groups, with unbroken supersymmetry at the string scale tending to favor gauge-group factors with larger rank. We also find that nearly half of the heterotic landscape is nonsupersymmetric and yet tachyon-free at tree level; indeed, less than a quarter of the tree-level heterotic landscape exhibits any supersymmetry at all at the string scale.
An Online EM Algorithm Using Component Reduction

The EM algorithm has been widely used in many learning or statistical tasks. However, since it requires multiple database scans, applying the EM algorithm to data streams is not straight forward. In this paper we propose an online EM algorithm which can deal with data streams. The algorithm utilizes a component reduction technique which reduces the number of components in a mixture model. A notable advantage of our algorithm over existing online variants of the EM algorithm lies in its simplicity. Our algorithm almost preserves the theoretical clearness of the EM algorithm.
Proton-Binding Sites of Acid-Sensing Ion Channel 1

Acid-sensing ion channels (ASICs) are proton-gated cation channels that exist throughout the mammalian central and peripheral nervous systems. ASIC1 is the most abundant of all the ASICs and is likely to modulate synaptic transmission. Identifying the proton-binding sites of ASCI1 is required to elucidate its pH-sensing mechanism. By using the crystal structure of ASIC1, the protonation states of each titratable site of ASIC1 were calculated by solving the Poisson-Boltzmann equation under conditions wherein the protonation states of all these sites are simultaneously in equilibrium. Four acidic-acidic residue pairs—Asp238-Asp350, Glu220-Asp408, Glu239-Asp346, and Glu80-Glu417—were found to be highly protonated. In particular, the Glu80-Glu417 pair in the inner pore was completely protonated and possessed 2 H+, implying its possible importance as a proton-binding site. The pK a of Glu239, which forms a pair with a possible pH-sensing site Asp346, differs among each homo-trimer subunit due to the different H-bond pattern of Thr237 in the different protein conformations of the subunits. His74 possessed a pK a of ≈6–7. Conservation of His74 in the proton-sensitive ASIC3 that lacks a residue corresponding to Asp346 may suggest its possible pH-sensing role in proton-sensitive ASICs.
Quantitative Analysis of Community Detection Methods for Longitudinal Mobile Data

Mobile phones are now equipped with increasingly large number of built-in sensors that can be utilized to collect long-term socio-temporal data of social interactions. Moreover, the data from different built-in sensors can be combined to predict social interactions. In this paper, we perform quantitative analysis of 6 community detection algorithms to uncover the community structure from the mobile data. We use Bluetooth, WLAN, GPS, and contact data for analysis, where each modality is modelled as an undirected weighted graph. We evaluate community detection algorithms across 6 inter-modality pairs, and use well know partition evaluation features to measure clustering similarity between the pairs. We compare the performance of different methods based on the delivered partitions, and analyse the graphs at different times to find out the community stability.
Study of differences on heart rate in patients with apnea and insomnia syndromes

A high percentage of patients with obstructive sleep apnea-hypopnea syndrome (OSAHS) also have chronic insomnia, particularly elderly people. Additionally, these patients usually show high levels of depression, stress and other sleep disorders. In order to quantify the potential negative impact that insomnia produces in patients with OSAHS, some studies have analyzed the usual parameters in the polysomnographic reports, although the results are inconclusive.
A New Insect-Specific Flavivirus from Northern Australia Suppresses Replication of West Nile Virus and Murray Valley Encephalitis Virus in Co-infected Mosquito Cells

Recent reports of a novel group of flaviviruses that replicate only in mosquitoes and appear to spread through insect populations via vertical transmission have emerged from around the globe. To date, there is no information on the presence or prevalence of these insect-specific flaviviruses (ISFs) in Australian mosquito species. To assess whether such viruses occur locally, we used reverse transcription-polymerase chain reaction (RT-PCR) and flavivirus universal primers that are specific to the NS5 gene to detect these viruses in mosquito pools collected from the Northern Territory. Of 94 pools of mosquitoes, 13 were RT-PCR positive, and of these, 6 flavivirus isolates were obtained by inoculation of mosquito cell culture. Sequence analysis of the NS5 gene revealed that these isolates are genetically and phylogenetically similar to ISFs reported from other parts of the world. The entire coding region of one isolate (designated 56) was sequenced and shown to have approximately 63.7% nucleotide identity and 66.6% amino acid identity with its closest known relative (Nakiwogo virus) indicating that the prototype Australian ISF represents a new species. All isolates were obtained from Coquillettidia xanthogaster mosquitoes. The new virus is tentatively named Palm Creek virus (PCV) after its place of isolation. We also demonstrated that prior infection of cultured mosquito cells with PCV suppressed subsequent replication of the medically significant West Nile and Murray Valley encephalitis viruses by 10–43 fold (1 to 1.63 log) at 48 hr post-infection, suggesting that superinfection exclusion can occur between ISFs and vertebrate-infecting flaviviruses despite their high level of genetic diversity. We also generated several monoclonal antibodies (mAbs) that are specific to the NS1 protein of PCV, and these represent the first ISF-specific mAbs reported to date.
The Australian fruit Illawarra plum (Podocarpus elatus Endl., Podocarpaceae) inhibits telomerase, increases histone deacetylase activity and decreases proliferation of colon cancer cells

Fruit antioxidants have many health benefits including prevention of cancer development. The native Australian bush fruit Illawarra plum (Podocarpus elatus Endl., Podocarpaceae) has a high content of anthocyanin-rich phenolics, with an antioxidant capacity at levels higher than most fruits. In the present study the molecular mechanisms of the anti-proliferative activity of Illawarra plum on colorectal cancer cells were investigated. Non-tumorigenic young adult mouse colonic (YAMC) cells and tumorigenic human colonic (HT-29) cells were treated with a polyphenolic-rich Illawarra plum extract (0–1000 μg/ml). Illawarra plum had anti-proliferative properties in only the cancer cells, with growth suppressed in a dose- and time-dependent manner. Treatment of HT-29 cells with Illawarra plum extract (500 μg/ml; 24 h) was also associated with a 2-fold increase in apoptosis, and a cell cycle delay in the S phase (P< 0·01). Assessment of biomarkers for DNA damage revealed that plum treatment caused a 93 % down-regulation of telomerase activity (P< 0·001) and a decrease in telomere length (up to 75 %; P< 0·01). Treatment with Illawarra plum extract also induced morphological alterations to HT-29 cells that were suggestive of induction of autophagy, as the formation of cytoplasmic vacuoles was observed in many cells. This could be induced by the increased (6-fold) histone deacetylase (HDAC) activity (P< 0·001) and the trend for increased expression of the class III HDAC sirtuin 1. The present study has shown that Illawarra plum extract is able to reduce the proliferation of colon cancer cells by altering the cell cycle, increasing apoptosis and possibly inducing autophagy. The active ingredients in Illawarra plum may provide an alternative chemoprevention strategy to conventional chemotherapy.
An Analog VLSI Integrate-and-Fire Neural Network for Sound Segmentation

This paper presents a cascadable aVLSI integrate-and-re neural network chip (SPIKE I) capable of realistic biological time constants incorporated into a real time software based sound segmentation system with results. The sound segmentation system is based on an engineering abstraction of the functionality of the cochlea and auditory nerve. A comparison of the software simulation and soft-ware/hardware combination results indicates that clustering does occur. Furthermore the patterns of onsets and oosets generated are broadly similar. Analysis of the results indicates area's for improvement. These have been included in a second integrate-and-re neural network chip (SPIKE II) presently being fabricated.
Hybrid Systems to Select Variables for Time Series Forecasting Using MLP and Search Algorithms

Research on time series forecasting has been an area of considerable interest in recent decades. Several techniques have been researched for time series forecasting. There is a fundamental task in any area of knowledge of time series: use past values to predict future values from the available historical series. Thus, a very important step is to define which of these past values will be considered in the prediction process. In this paper it is proposed two hybrid systems to select variables: Harmony Search and Neural Networks (HS + MLP) and Temporal Memory Search and Neural Networks (TMS + MLP). The variables selections improves the performance of learning models by eliminating redundant or irrelevant attributes. To perform a comparative study between the techniques, ten real-world time series were used.
Research on the method of combining period extraction with eigenvalue entropy

The echo of target with micro-motion contains the electromagnetic scattering characteristics and movement characteristics, which plays important roles in the target identification. Precession period is one of the important characteristics on the analysis of the micro-motion characteristics. Aimed at the phenomenon of extracting the cycle of no precession target, in the thesis a method is proposed by combing period extraction with eigenvalue entropy. The original echo is constructed by establishing autocorrelation matrix and the eigenvalues are obtained through eigenvalue decomposition. Then the period is extracted after calculating the eigenvalue entropy. The method can eliminate some targets with no obvious precession and minish the error of period extraction.
The Basis for Evolution of DNA-Binding Specificity of the Aft1 Transcription Factor in Yeasts

The Saccharomyces cerevisiae Aft1 and Kluyveromyces lactis KlAft are orthologous yeast transcription activators that regulate the expression of the same group of iron-uptake genes but bind to the different DNA sites: TGCACCC for Aft1 and PuCACCC for KlAft. To establish whether the DNA-binding mechanisms of Aft1 and KlAft have diverged during the evolution of the Aft-type transcription factor, we examined the function of a nonconserved region in their DNA-binding domains. A large part of this region is composed of a sequence predicted to be disordered in structure and potentially phosphorylated. We show with deletion mutant analyses that this sequence is essential for the binding of Aft1 to its DNA site and for the iron uptake and growth of S. cerevisiae under iron-limited conditions. We constructed hybrid proteins by exchanging the nonconserved regions of Aft1 and KlAft. We show that the Aft1 region is necessary and sufficient for KlAft to bind efficiently to the Aft1 DNA site in S. cerevisiae and to complement the iron-dependent phenotype of the aft1Δaft2Δ mutant. This demonstrates that the changes in the nonconserved region of the Aft-type DNA-binding domain have led to changes in the DNA-binding specificity and have major consequences for the regulation of iron homeostasis. The combination of bioinformatic and experimental analyses indicates that the sequence TGCACCC is the most probable ancestral Aft-type element. Our findings suggest that the changes in the nonconserved region of the DNA-binding domain are responsible for the evolution of the TGCACCC sequence toward PuCACCC in the K. lactis species.
Solving QoS multicast routing with genetic algorithms

Proliferation of group-based real-time applications, such as online games and video conferencing motivates research into QoS multicast routing. This type of applications requires consideration of both end-to-end delay (i.e., packet delay from the source to all destinations is bounded) and group synchronisation (i.e., the difference in packet delay from the source to different destinations is bounded) constraints. In this paper, we describe the combined problem of multicast routing and delay partitioning with end-to-end delay and group synchronization constraints in a QoS framework where a delay dependent cost function is associated with each network link [H.T. Tran and R. J. Harris, 2003]. Due to NP-completeness of this problem, a genetic algorithm (GA) based algorithm, that computes a source-based multicast tree that meet both requirements with near-optimal cost, is developed. In our GA, we compare two different tree encoding techniques: link weight and link bias encoding, and by the means of simulation, find that link weight encoding is less effective than link bias coding. The simulation result also shows that our GA consistently performs better than two other simple heuristics.
A Virtual Object Generation Method Based on Image Vector Recognition

A new virtual object generation method for AR applications based on image vector recognition is introduced in this paper. During the whole process, data acquiring and virtual object generation are completed automatically, including image smoothing, image edge detection, target silhouette tracking, vector curve compression and real-time rendering. This method improved the degree of automation of virtual object generation in AR applications rather than using pre-built models with digital content creation software. The key steps of the approach are described in detail and a practical application is also given.
The practices of local governance : a Tasmanian case study

In this thesis I examine how local government and community actors are managing change in local governing processes. I describe how governing is practised and document the effects of such practices for the rural township of Geeveston in the Huon Valley Council, Tasmania, Australia. The aim of the research is to apprehend the materiality of governing at the local level under neoliberal governmental regimes in order to comprehend what happens and what is at stake when people govern and are governed in particular ways . This project is underpinned by an interest in everyday practices and the particular experiences of individuals in communities of place and interest and grounded in a case study of township revitalisation. The implementation of neoliberal governmental technologies has changed profoundly governing practices at all levels of government. The term governance is being used as a general reference for these changing conditions of governing. Of concern here are the effects of those changes on local government that occurred in Tasmania, Australia during the 1990s. This period of local government modernisation emphasised managerial and structural changes designed to increase local government efficiency and effectiveness and were accompanied by legislative requirements to enhance citizen participation in local government processes. Determining how to integrate these twin goals has generated significant challenges for local government and community actors as they negotiate what it means to govern and be governed in the new governance environment. The design for the research is based on a case study approach and draws on qualitative research methods. It assumes great value in working from the particularities of people’s experiences; a position central to the practice of cultural geography. The theoretical framework draws on concepts of government developed in literature on governmentality; a perspective that highlights the regimes of practices of government used in attempts to shape rationally human conduct for particular ends. In its detailed examination of the practices of government, this project addresses a gap identified in the literature calling for more empirical research to explicate theorizations of governmental practices. This research builds knowledge about local governance with attention to its constitution through the discursive and material practices of identity, community, representation, citizenship and politics in place. The work links the empirical findings of this research with concepts of the representative claim, agonistic pluralism and governing through community to problematise, respectively, meanings and practices of representation, the role of conflict in democracy and practices of community empowerment.
Gene Finding for Microbial Metagenomics

Metagenomics is the study of genomes directly sequenced from an environment. The goal of metagenomics is to understand the ecosystems by identifying the community members and the genes in the environment, and microbial organisms are a main target of the research [2] [3]. Microbial metagenomics enables to access uncultured microbial organisms, thus obtained sequences are composed of various species. Metagenomic sequences cannot be assembled, and almost all of them are one-pass sequences (about 700bp). Gene finding is a fundamental goal in all metagenomics projects. However, conventional gene finding methods cannot be applied to metagenomic sequences because they are anonymous and short fragments, thus we cannot estimate their appropriate codon usage [1]. A realistic alternative method is a similarity search against the sequence database or the metagenomic sequences themselves, but about 30% of metagenomic data have no significant similarity [1]. In this study, we proposed a method for predicting genes in a mixture of anonymous and short fragment sequences of bacteria, archea, and fungi.
Eﬀective Techniques for Static Race Detection in Java Parallel Loops

Despite signiﬁcant progress in recent years, the important problem of static race detection remains open. Previous techniques took a general approach and looked for races by analyzing the eﬀects induced by low-level concurrency constructs (e.g., java.lang.Thread). But constructs and libraries for expressing parallelism at a higher level (e.g., fork-join, futures, parallel loops) are becoming available in all major programming languages. We claim that specializing an analysis to take advantage of the extra semantic information provided by the use of these constructs and libraries improves precision and scalability. We present IteRace , a set of techniques that are specialized to use the intrinsic thread, safety, and data-ﬂow structure of collections and of the new loop-parallelism mechanism introduced in Java 8. Our evaluation shows that IteRace is fast and precise enough to be practical. It scales to programs of hundreds of thousands of lines of code and it reports very few race warnings, thus avoiding a common pitfall of static analyses. In ﬁve out of the seven case studies IteRace reported no false warnings. Also, it revealed six bugs in real-world applications. We reported four of them, one had already been ﬁxed, and three were new and the developers conﬁrmed and ﬁxed them. Furthermore, we evaluate the eﬀect of each specialization technique on the running time and precision of the analysis. For each application, we run the analysis under 32 diﬀerent conﬁgurations. This allows us to analyze each technique’s eﬀect both alone and in all possible combinations with other techniques. Categories and Subject Descriptors: D
A New Adaptive Switching Median Filter

A new Adaptive Switching Median (ASWM) filter for removing impulse noise from corrupted images is presented. The originality of ASWM is that no a priori Threshold is needed as in the case of a classical Switching Median filter. Instead, Threshold is computed locally from image pixels intensity values in a sliding window. Results show that ASWM provides better performance in terms of PSNR and MAE than many other median filter variants for random-valued impulse noise. In addition it can preserve more image details in a high noise environment.
UFOme: A User Friendly Ontology Mapping Environment

Recently the Ontology Mapping Problem (OMP) has been identified as a key factor towards the success of the Semantic Web and related applications. This problem arises since it is possible for different people to give, through ontologies, different conceptualizations of the same (or overlapping) knowledge domain. In order to tackle the OMP several algorithms have been designed. They aim at discovering correspondences (aka mappings) between ontology entities. However, these algorithms mostly suffer from the following shortcomings: (i) do not allow to quickly combine and/or compare different mapping strategies; (ii) do not offer support for evaluating mapping strategies in terms of quality of results and performance. In this paper we present a pluginbased system called UFOme along with its current implementation. We illustrate how it can be exploited to graphically design mapping tasks by connecting different types of modules. UFOme provides three categories of modules. The first one (i.e., visualization) allows to explore the ontologies to be mapped. The second one (i.e., matching) provides different types of individual matchers, exploited to discover mappings between ontologies, and a module for combining them. The third one (i.e., evaluation) enables to evaluate each module of the mapping task, a sub mapping task, or the mapping task in the whole w.r. t performance and quality of results.
Difference equations for correlation functions of Belavin's ℤn-symmetric model with boundary reflection

Belavin's n-symmetric elliptic model with boundary reflection is considered on the basis of the boundary CTM bootstrap. We find non-diagonal K-matrices for n>2 that satisfy the reflection equation (boundary Yang-Baxter equation), and also find non-diagonal Boltzmann weights for the A(1)n-1-face model even for n≥2. We derive difference equations of the quantum Knizhnik-Zamolodchikov type for correlation functions of the boundary model. The boundary spontaneous polarization is obtained by solving the simplest difference equations in the case of the free boundary condition. The resulting quantity is the square of the spontaneous polarization for the bulk n-symmetric model, up to a phase factor.
Statistical timing analysis in sequential circuit for on-chip global interconnect pipelining

With deep-sub-micron (DSM) technology, statistical timing analysis becomes increasingly crucial to characterize signal transmission over global interconnect wires. In this paper, a novel statistical timing analysis approach has been developed to analyze the behavior of two important pipelined architectures for multiple clock-cycle global interconnect, namely, the flip-flop inserted global wire and the latch inserted global wire. We present analytical formula that is based on parameters obtained using Monte Carlo simulation. These results enable a global interconnect designer to explore design trade-offs between clock frequency and probability of bit-error during data transmission.