Miracle-dz/UniFAR-FTUs huggingface dataset:
Speaker verification using frame and utterance level likelihood normalization

We propose a new method, where the likelihood normalization technique is applied at both the frame and utterance levels. In this method based on Gaussian mixture models (GMM), every frame of the test utterance is inputed to the claimed and all background speaker models in parallel. In this procedure, for each frame, likelihoods from all the background models are available, hence they can be used for normalization of the claimed speaker likelihood at every frame. A special kind of likelihood normalization, called weighting models rank, is also proposed. We have evaluated our method using two databases-TIMIT and NTT. Results show that the combination of frame and utterance level likelihood normalization in some cases reduces the equal error rate (EER) more than twice.
Sensor Recycling and Reuse

The concepts of sensor recycling and re-use offer a new developmental methodology for both centralised and network-based interactive multimedia systems and multimedia art applications. This work formalises the proposed methodology, researches common issues that appear when reuse or recycling of sensing devices is introduced and discusses its application within physical interactive systems. It becomes apparent that the high system development costs typically introduced in the visual arts domain can clearly be reduced via the use of alternative recycled and reused sensing devices. A number of interactive new-media art systems case studies are presented to demonstrate its flexibility, economy and ecological advantages. This work aims to render sensor re-use a design choice that offers an alternative and inexpensive approach from the theoretical, engineering and artistic perspectives in various sensor-driven interactive multimedia systems. Keywords— interaction; sensors; recycled sensors; sensor reuse; inexpensive sensors; interactive sensor-based applications; interactive multimedia art.
Hunting organization-targeted socialbots

In this paper we perform cost-effectiveness analysis of strategies for monitoring the organizational social network in order to trap the attacker's profiles. We analyze attack strategies with different levels of knowledge on the employed monitoring strategies. The results demonstrate the efficacy in detecting the less sophisticated attackers and slowing down attackers that deliberately avoid the profiles being monitored.
Free Applicative Functors

Applicative functors ([9]) are a generalisation of monads. Both allow expressing effectful computations into an otherwise pure language, like Haskell ([8]). Applicative functors are to be preferred to monads when the structure of a computation is fixed a priori. That makes it possible to perform certain kinds of static analysis on applicative values. We define a notion of free applicative functor, prove that it satisfies the appropriate laws, and that the construction is left adjoint to a suitable forgetful functor. We show how free applicative functors can be used to implement embedded DSLs which can be statically analysed.
Increased Superoxide and Vascular Dysfunction in CuZnSOD-Deficient Mice

Abstract— Increased superoxide is thought to play a major role in vascular dysfunction in a variety of disease states. Superoxide dismutase (SOD) limits increases in superoxide; however, the functional significance of selected isoforms of SOD within the vessel wall are unknown. We tested the hypothesis that selective loss of CuZnSOD results in increased superoxide and altered vascular responsiveness in CuZnSOD-deficient (CuZnSOD−/−) mice compared with wild-type (CuZnSOD+/+) littermates. Total SOD activity was reduced (P <0.05) by approximately 60% and CuZnSOD protein was absent in aorta from CuZnSOD−/− as compared with wild-type mice. Vascular superoxide levels, measured using lucigenin (5 &mgr;mol/L)-enhanced chemiluminescence and hydroethidine (2 &mgr;mol/L)-based confocal microscopy, were increased (approximately 2-fold;P <0.05) in CuZnSOD−/− mice as compared with wild-type mice. Relaxation of the carotid artery in response to acetylcholine and authentic nitric oxide was impaired (P <0.05) in CuZnSOD−/− mice. For example, maximal relaxation to acetylcholine (100 &mgr;mol/L) was 50±6% and 69±5% in CuZnSOD−/− and wild-type mice, respectively. Contractile responses of the carotid artery were enhanced (P <0.05) in CuZnSOD−/− mice in response to phenylephrine and serotonin, but not to potassium chloride or U46619. In vivo, dilatation of cerebral arterioles (baseline diameter=31±1 &mgr;m) to acetylcholine was reduced by approximately 50% in CuZnSOD−/− mice as compared with wild-type mice (P <0.05). These findings provide the first direct insight into the functional importance of CuZnSOD in blood vessels and indicate that this specific isoform of SOD limits increases in superoxide under basal conditions. CuZnSOD-deficiency results in altered responsiveness in both large arteries and microvessels.
Removal of Pathogens by Membrane Bioreactors: A Review of the Mechanisms, Influencing Factors and Reduction in Chemical Disinfectant Dosing

The continued depletion of fresh drinking water resources throughout the world has increased the need for a variety of water treatment and recycling strategies. Conventional wastewater treatment processes rely on extensive chemical post-disinfection to comply with the stringent microbiological safety for water reuse. When well designed and operated, membrane bioreactors (MBRs) can consistently achieve efficient removals of suspended solids, protozoa and coliform bacteria. Under optimal conditions, MBR systems can also significantly remove various viruses and phages. This paper provides an in-depth overview of the mechanisms and influencing factors of pathogen removal by MBR and highlights practical issues, such as reduced chemical disinfectant dosing requirements and associated economic and environmental benefits. Special attention has been paid to the aspects, such as membrane cleaning, membrane imperfections/breach and microbial regrowth, in the distribution system on the overall pathogen removal performance of MBR.
Modelling dropouts improves feature selection in scRNASeq experiments

A key challenge of single-cell RNASeq (scRNASeq) is the many genes with zero reads in some cells, but high expression in others. Modelling zeros using the Michaelis-Menten equation provides a superior fit to existing scRNASeq datasets compared to other approaches and enables fast and accurate identification of features corresponding to differentially expressed genes without prior identification of cell subpopulations. Applying our method to mouse preimplantation embryos revealed clusters corresponding to the inner cell mass and trophectoderm of the blastocyst. Our feature selection method overcomes batch effects to cluster cells from five different datasets by developmental stage rather than experimental origin.
Decision Tree Induction: An Approach for Data Classification Using AVL-Tree

Classification is considered to be one of the important building blocks in data mining problem. The major issues concerning data mining in large databases are efficiency and scalability. This paper addresses these issues by proposing a data classification method using AVL trees, which enhances the quality and stability. Researchers from various disciplines such as statistics, machine learning, pattern recognition, and data mining considered the issue of building a decision tree from the available data. Specifically, we consider a scenario in which we apply the multi level mining method on the data set and show how the proposed approach tend to give the efficient multiple level classifications of large amounts of data. The results specify the improved performance of the proposed algorithm which acquires designing rules from the knowledge database.
The identification of multiple outliers in online monitoring data

We present a robust graphical procedure for routine detection of isolated and patchy outliers in univariate time series. This procedure is suitable for retrospective as well as for online identification of outliers. It is based on a phase space reconstruction of the time series which allows to regard the time series as a multivariate sample with identically distributed but non independent observations. Thus, multivariate outlier identifiers can be transferred into the context of time series which is done here. Some applications to online monitoring data from intensive care are given.
AIDing Chromatin and Transcription-Coupled Orchestration of Immunoglobulin Class-Switch Recombination

Secondary diversification of the antibody repertoire upon antigenic challenge, in the form of immunoglobulin heavy chain (IgH) class-switch recombination (CSR) endows mature, naïve B cells in peripheral lymphoid organs with a limitless ability to mount an optimal humoral immune response, thus expediting pathogen elimination. CSR replaces the default constant (CH) region exons (Cμ) of IgH with any of the downstream CH exons (Cγ, Cε, or Cα), thereby altering effector functions of the antibody molecule. This process depends on, and is orchestrated by, activation-induced deaminase (AID), a DNA cytidine deaminase that acts on single-stranded DNA exposed during transcription of switch (S) region sequences at the IgH locus. DNA lesions thus generated are processed by components of several general DNA repair pathways to drive CSR. Given that AID can instigate DNA lesions and genomic instability, stringent checks are imposed that constrain and restrict its mutagenic potential. In this review, we will discuss how AID expression and substrate specificity and activity is rigorously enforced at the transcriptional, post-transcriptional, post-translational, and epigenetic levels, and how the DNA-damage response is choreographed with precision to permit targeted activity while limiting bystander catastrophe.
Analysis of a system for dementia prevention based on the concept of Human-Agent Interaction

This article describes a dementia prevention system for the elderly based on a brain twister game in a tablet device. In this system, a software agent is incorporated into the tablet device, and has dialogic interactions with users (elderly people) based on the concept of Human-Agent Interaction (HAI) in order to reduce the users' psychological resistance to the system and maintain or improve their interest in the game. Several experiments and subjective evaluations for elderly people are conducted to evaluate the basic characteristics of the proposed system and investigate the impact of the system on the effect for preventive care.
Classification and evaluation of cost aggregation methods for stereo correspondence

In the last decades several cost aggregation methods aimed at improving the robustness of stereo correspondence within local and global algorithms have been proposed. Given the recent developments and the lack of an appropriate comparison, in this paper we survey, classify and compare experimentally on a standard data set the main cost aggregation approaches proposed in literature. The experimental evaluation addresses both accuracy and computational requirements, so as to outline the best performing methods under these two criteria.
Action Co-representation is Tuned to Other Humans

The present study attempts to explore the process by which knowledge of another's intentional behavior in a joint-action scenario is represented through the action observation and execution networkalso known as the common coding system. Participants (n = 18) were instructed to perform the complementary social Simon task under the implemented belief of interaction with either an unseen human (biological agent) or a computer program, where in fact, all response sequences from either partner were generated by computer. Results provide behavioral and neurophysiological evidence (P3 and S-LRP) that the believed intentionality of another person's actions is sufficient to facilitate a strong-enough agency-dependent social Simon effect to modulate action planning and anticipation. We suggest that the co-representation of human action may be an evolved biologically tuned default of the human motor system.
Climate impacts on transocean dispersal and habitat in gray whales from the Pleistocene to 2100

Arctic animals face dramatic habitat alteration due to ongoing climate change. Understanding how such species have responded to past glacial cycles can help us forecast their response to today's changing climate. Gray whales are among those marine species likely to be strongly affected by Arctic climate change, but a thorough analysis of past climate impacts on this species has been complicated by lack of information about an extinct population in the Atlantic. While little is known about the history of Atlantic gray whales or their relationship to the extant Pacific population, the extirpation of the Atlantic population during historical times has been attributed to whaling. We used a combination of ancient and modern DNA, radiocarbon dating and predictive habitat modelling to better understand the distribution of gray whales during the Pleistocene and Holocene. Our results reveal that dispersal between the Pacific and Atlantic was climate dependent and occurred both during the Pleistocene prior to the last glacial period and the early Holocene immediately following the opening of the Bering Strait. Genetic diversity in the Atlantic declined over an extended interval that predates the period of intensive commercial whaling, indicating this decline may have been precipitated by Holocene climate or other ecological causes. These first genetic data for Atlantic gray whales, particularly when combined with predictive habitat models for the year 2100, suggest that two recent sightings of gray whales in the Atlantic may represent the beginning of the expansion of this species' habitat beyond its currently realized range.
Debt and the Consumption Response to Household Income Shocks

This paper exploits a detailed new dataset with comprehensive panel financial information on millions of American households to investigate the interaction between household balance sheets, income, and consumption during the Great Recession. In particular, I test whether consumption among households with higher levels of debt is more sensitive to a given change in income. I match households to their employers and use shocks to these employers to derive persistent and unanticipated changes in household income. I find that highly-indebted households are more sensitive to these income fluctuations and that a one standard deviation increase in debt-to-asset ratios increases the elasticity of consumption by approximately 25%. I employ direct measures of asset levels, available credit, and potential credit access to show that these results are driven almost entirely by borrowing and liquidity constraints. These estimates suggest that the drop in consumption during the 2007-2009 recession was approximately 20% greater than what would have been seen with the household balance sheet positions seen during the 1980s.
Using Next-Generation Sequencing to Contrast the Diet and Explore Pest-Reduction Services of Sympatric Bird Species in Macadamia Orchards in Australia

Worldwide, avian communities inhabiting agro-ecosystems are threatened as a consequence of agricultural intensification. Unravelling their ecological role is essential to focus conservation efforts. Dietary analysis can elucidate bird-insect interactions and expose avian pest-reduction services, thus supporting avian conservation. In this study, we used next-generation sequencing to analyse the dietary arthropod contents of 11 sympatric bird species foraging in macadamia orchards in eastern Australia. Across all species and based on arthropod DNA sequence similarities ≥98% with records in the Barcode of Life Database, 257 operational taxonomy units were assigned to 8 orders, 40 families, 90 genera and 89 species. These taxa included 15 insect pests, 5 of which were macadamia pests. Among the latter group, Nezara viridula (Pentatomidae; green vegetable bug), considered a major pest, was present in 23% of all faecal samples collected. Results also showed that resource partitioning in this system is low, as most bird species shared large proportion of their diets by feeding primarily on lepidopteran, dipteran and arachnids. Dietary composition differed between some species, most likely because of differences in foraging behaviour. Overall, this study reached a level of taxonomic resolution never achieved before in the studied species, thus contributing to a significant improvement in the avian ecological knowledge. Our results showed that bird communities prey upon economically important pests in macadamia orchards. This study set a precedent by exploring avian pest-reduction services using next-generation sequencing, which could contribute to the conservation of avian communities and their natural habitats in agricultural systems.
WRENMining: Large-Scale Data Collection for Human Contact Network Research

Wireless sensor networks (WSNs) have come a long way to reach their ubiquitous state known today through scalable cost, low-power optimizations, and data management. As WSNs scale in size, the necessity for system designs - from low-level hardware implementations to data collection and management procedures - to account for handling extensive amounts of data is crucial. Several prominent papers address these issues for limited deployments of less than 200 nodes, but there are little resources available for multiple consecutive deployments of over 500 nodes. We present the engineering perspective on sensor data collection, management, and processing while collaborating with epidemiologists for the Wireless Ranging Enabled Node (WREN) network system for human contact research. The WREN and all supporting systems (base stations, software, and data procedures) sustain multiple high density, mobile deployments with fast turnovers. The WRENs completed 13 deployments over a period of 8 months to mine over 35 million contact points. We present our design considerations, challenges/experiences, and solutions to account for and correct time synchronization issues, along with our methodology for collecting, managing, and processing data.
Time Hopping for Device-To-Device Communication in LTE Cellular System

In this paper, we analyze the challenges of the interference environment in a hybrid network that consists of the device-to-device (D2D communication based ad-hoc connections and conventional cellular connections. Accordingly, time hopping (TH) based radio resource allocation schemes aiming to improve the robustness of the hybrid network are proposed. The performance improvement even with the simple random TH scheme is considerable, which is validated via extensive simulations. In addition, the simulation results also give some hints on the optimization of the practical TH operation in a hybrid network.
A Data-Driven fMRI Neuronal Activation Analysis Method Using Temporal Clustering Technique and an Adaptive Voxel Selection Criterion

Functional magnetic resonance imaging (fMRI) is one of the most widely used methods to study neuronal activity in human brain. A data-driven analysis method is proposed for studying brain responses when the information for predicting their onset or duration is unavailable. The method is suitable for experiments involving a single event or non-repetitive multiple events. It is built upon the pre-existing temporal clustering analysis techniques with additional features that make use of the signal changes of neighbouring voxels to ensure that the selected voxels for response detection are those which are most likely to have been activated by the stimuli. For method validation, eight sets of fMRI data from three different kinds of sensory experiments are applied. The results demonstrate that out method is able to detect the time bins during which the stimuli were administered and the identified voxels correspond to the brain areas, which are typically activated in this kind of experiment. Moreover, in these eight sets of data, the accuracy of stimulation response detection is 75% in comparison to 58.33% without the selection criterion.
A Model for the Adoption Process of Information System Security Innovations in Organisations: A Theoretical Perspective

In this paper, we develop a theoretical model for the adoption process of Information System Security innovations in organisations. The model stemmed from the Diffusion of Innovation theory (DOI), the Technology Acceptance Model (TAM), the Theory of Planned Behaviour (TPB) and the Technology-Organisation-Environment (TOE) framework. The model portrays Information System Security adoption process progressing in a sequence of stages. The study considers the adoption process from the initiation stage until the acquisition of innovation as an organisational level judgement while the process of innovation assimilation and integration is assessed in terms of the user behaviour within the organisation. The model also introduces several factors that influence the Information System Security innovation adoption. By merging the organisational adoption and user acceptance of innovation in a single depiction, this research contributes to IS security literature a more comprehensive model for IS security adoption in organisation, compare to any of the past representations.
Genetic variation in the fat mass and obesity-associated gene (FTO) in association with food preferences in healthy adults

Background Earlier studies have indicated that the fat mass and obesity-associated gene (FTO) is not only associated with BMI and weight but also with appetite and dietary intake. Objectives We investigated if the FTO rs9939609 associates with food preferences in healthy adults with no cancer, cardiovascular disease, or diabetes. Additionally, we challenged the question if the associations are modified by obesity status (BMI ≤25 or >25 kg/m2). Design The analyses are made with 22,799 individuals from the Swedish population-based Malmö Diet and Cancer Cohort Study, who were born between 1923 and 1945. To investigate food preference, 27 food groups conducted from a modified diet history method including a 7-day registration of cooked meals and cold beverages were used in the analyses. Bonferroni correction was used to correct for multiple testing, resulting in a cut-off value for significance level of p<0.002. Results We observed that the obesity susceptible A-allele carriers reported a higher consumption of biscuits and pastry but lower consumption of soft drinks (P for trend <0.0001 for both) as compared to TT genotype carriers. In contrast to our hypothesis, the results did not significantly differ depending on obesity status except for consumption of juice, where only the overweight individuals with A-allele had a higher consumption as compared to TT carriers (P for interaction=0.04). Conclusion Our results indicate that the FTO A-allele may associate with certain food preference and in particular with certain energy-dense foods.