Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive Poisson photometric propagation for facial composite

In image composition, the inconsistent illumination of the source images is one of the major problems for seamless stitching of separated patches. The Poisson image editing is a sound technique for seamless image composition. In this paper, we have generalized and improved this technique and applied it onto solving the illumination discontinuity problem for facial image composition. Toward stitched image with patches of arbitrary shapes and number, an extended Poisson equation is proposed. To solve this equation efficiently, a layer-based Poisson solution propagation algorithm is designed. Based on above, an interactive photometric alignment system for facial compositing image is built. In the experiments, the photometric propagation effects with respect to user's selections are compared. Its time performance is also investigated. The experimental results verified the effectiveness and efficiency of the proposed method.
Improvised SVPWM Strategies for an Enhanced Performance for a Four-Level Open-End Winding Induction Motor Drive

A four-level open-end winding induction motor drive (OEWIMD) is obtained when an induction motor with open windings is fed from either side with two two-level 3-Ph voltage-source inverters (VSIs) with unequal dc-link voltages, which are in the ratio of 2:1. This drive principally suffers from two problems namely: the circulation of zero sequence current in motor phases and overcharging of the lower dc-link capacitor by its counterpart with higher dc-link voltage. It has been reported earlier, that the decoupled space vector pulse width modulation (SVPWM) control strategies avoid both of these problems. This paper proposes an improvised SVPWM scheme that achieves a better harmonic performance compared to the decoupled SVPWM scheme without altering either the power circuit configuration or the voltage ratings of the devices. The proposed PWM strategy clamps the inverter with lower dc-link voltage with an active state, while the other inverter is switched around it. It has been shown that the proposed SVPWM scheme results in an overall reduction of losses for the drive system while resulting in a considerably lower $dv/dt$ compared to the decoupled SVPWM schemes. The four-level OEWIMD employing the proposed SVPWM scheme is simulated and is validated with experimental results.
Stable Isotope Dilution Assays for Clinical Analyses of Folates and Other One-Carbon Metabolites: Application to Folate-Deficiency Studies

Folate deficiency is generally accepted as a potential direct or indirect risk factor for diseases including spina bifida, coronary heart diseases, malfunctions of the central nervous system, and cancer. The direct inclusion of folates in the methylation cycle, including the remethylation of homocysteine and regeneration of S-adenosylmethionine, underlines the importance of these vitamins and other components of one-carbon metabolism. Therefore, the aim of the present study was to develop a multiple stable isotope dilution assay (SIDA) for the respective analytes in plasma and tissue samples to allow for a closer look at the interaction between a severe folate deficiency and local folate status, as well as further interactions with circulating S-adenosylmethionine, S-adenosylhomocysteine, and homocysteine. The analytical methods were based on SIDAs coupled with liquid chromatography—tandem mass spectrometry (LC-MS/MS) analysis using the deuterated folates [2H4]-5-methyltetrahydrofolic acid, [2H4]-5-formyltetrahydrofolic acid, [2H4]-tetrahydrofolic acid, [2H4]-10-formylfolic acid, and [2H4]-folic acid and the deuterated one-carbon metabolites [2H4]-homocysteine, [2H4]-S-adenosylhomocysteine, and [2H3]-S-adenosylmethionine as internal standards. Three analytical methods have been developed for the analysis of homocysteine, S-adenosylmethionine, S-adenosylhomocysteine, and six folate vitamers. Validation data for the analysis of C1-metabolites in plasma and tissue samples or folate analysis in tissue samples revealed excellent sensitivity, precision, and recovery for all analytes studied. The miniaturized methods using sample volumes as low as 50 μL and weighed portions of 5–25 mg will allow the assessment of the status of folates and additional biomarkers of impaired one-carbon metabolism during folate deficiency.
Proteomic Signature of the Murine Intervertebral Disc

Low back pain is the most common musculoskeletal problem and the single most common cause of disability, often attributed to degeneration of the intervertebral disc. Lack of effective treatment is directly related to our limited understanding of the pathways responsible for maintaining disc health. While transcriptional analysis has permitted initial insights into the biology of the intervertebral disc, complete proteomic characterization is required. We therefore employed liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) protein/peptide separation and mass spectrometric analyses to characterize the protein content of intervertebral discs from skeletally mature wild-type mice. A total of 1360 proteins were identified and categorized using PANTHER. Identified proteins were primarily intracellular/plasma membrane (35%), organelle (30%), macromolecular complex (10%), extracellular region (9%). Molecular function categorization resulted in three distinct categories: catalytic activity (33%), binding (molecule interactions) (29%), and structural activity (13%). To validate our list, we confirmed the presence of 14 of 20 previously identified IVD-associated markers, including matrix proteins, transcriptional regulators, and secreted proteins. Immunohistochemical analysis confirmed distinct localization patterns of select protein with the intervertebral disc. Characterization of the protein composition of healthy intervertebral disc tissue is an important first step in identifying cellular processes and pathways disrupted during aging or disease progression.
Identifying domain elements from textual specifications

Analysis modeling refers to the task of identifying domain objects, their attributes and operations, and the relationships between these objects from software requirements specifications which are usually written in some natural language. There have been a few efforts to automate this task, but they seem to be largely constrained by the language related issues as well as the lack of a systematic transformation process. In this paper, we propose a systematic, automated transformation approach which first interprets the specification sentences based on the Hornby's verb patterns, and then uses semantic relationships between the words in the sentences, obtained from Type Dependencies using Stanford NL Parser, to identify the domain elements from them. With the help of a controlled experiment, we show that the analysis class diagrams generated by the proposed approach are far more correct, far more complete and less redundant than those generated by the exiting automated approaches.
Novel In Vitro Screening System Based on Differential Scanning Fluorimetry to Search for Small Molecules against the Disassembly or Assembly of HIV-1 Capsid Protein

Varieties of in vitro systems have been used to study biochemical properties of human immunodeficiency virus Gag-capsid protein (HIV Gag-CA). Recently, we have comparatively characterized HIV-1 and HIV-2 Gag-CA proteins using such technology, and have demonstrated that the NaCl-initiated CA-polymerization in vitro and the stability of CA N-terminal domain as judged by differential scanning fluorimetry (DSF) are inversely correlated. In this study, we found that ZnCl2 works as a competent initiator of the in vitro HIV-1 CA-polymerization at much lower concentrations than those of NaCl frequently used for the polymerization initiation. We also showed by DSF assays that ZnCl2 highly destabilize HIV-1 CA. Furthermore, PF74, a well-known inducer of premature HIV-1 uncoating in infected cells, was demonstrated to unusually promote the HIV-1 CA-disassembly in the presence of ZnCl2 as revealed by DSF assays. Taken together, we conclude that the DSF method may be useful as an efficient monitoring system to screen anti-HIV-1 CA molecules.
Query-Efficient Black-box Adversarial Examples

Current neural network-based image classifiers are susceptible to adversarial examples, even in the black-box setting, where the attacker is limited to query access without access to gradients. Previous methods --- substitute networks and coordinate-based finite-difference methods --- are either unreliable or query-inefficient, making these methods impractical for certain problems. We introduce a new method for reliably generating adversarial examples under more restricted, practical black-box threat models. First, we apply natural evolution strategies to perform black-box attacks using two to three orders of magnitude fewer queries than previous methods. Second, we introduce a new algorithm to perform targeted adversarial attacks in the partial-information setting, where the attacker only has access to a limited number of target classes. Using these techniques, we successfully perform the first targeted adversarial attack against a commercially deployed machine learning system, the Google Cloud Vision API, in the partial information setting.
Mining Statistically Significant Attribute Associations in Attributed Graphs

Graphs are widely used to represent many differentkinds of real world data such as social networks, protein-proteininteractions, and road networks. In many cases, each node in agraph is associated with a set of its attributes and it is criticalto not only consider the link structure of a graph but also usethe attribute information to achieve more meaningful results invarious graph mining tasks. Most previous works dealing withattributed graphs take into account attribute relationships onlybetween individually connected nodes. However, it should begreatly valuable to find out which sets of attributes are associatedwith each other and whether or not they are statistically signifi-cant over an entire graph. Mining such significant associations, we can uncover novel relationships among the sets of attributes inthe graph. We propose an algorithm that can find those attributeassociations efficiently and effectively, and show experimentalresults that confirm the high efficacy of the proposed algorithm.
Predicting Therapeutic Effects of Psychodiagnostic Assessment Among Children and Adolescents Participating in Randomized Controlled Trials

This study explored predictors of improvement after completing a psychodiagnostic screening assessment but before randomization among youth who participated in two pilot randomized controlled trials of omega-3 supplementation and Individual-Family Psychoeducational Psychotherapy (PEP). Ninety-five youth (56.8% male, 61.1% White) ages 7–14 with mood disorders completed screening and baseline assessments (including Clinical Global Impressions–Improvement [CGI-I], Children’s Depression Rating Scale–Revised, Young Mania Rating Scale), then were randomized into a 12-week trial of omega-3, PEP, their combination, or placebo. Between screening and randomization, 35.8% minimally improved (CGI-I = 3), 12.6% much improved (CGI-I < 3), totaling 48.4% improved. Caregiver postsecondary education (p = .018), absence of attention-deficit/hyperactivity disorder (p = .027), and lower screen depression severity (p = .034) were associated with CGI-I. Caregiver postsecondary education (p = .020) and absence of a disruptive behavior diagnosis (p = .038) were associated with depression severity improvement. Prerandomization improvement moderated treatment outcomes: Among youth who improved prerandomization, those who received PEP (alone or with omega-3) had more favorable placebo-controlled depression trajectories due to a lack of placebo response. This open-label trial of psychodiagnostic assessment provides suggestive evidence that psychodiagnostic assessment is beneficial, especially for those with depression and without externalizing disorders. Prerandomization improvement is associated with better placebo-controlled treatment response. Future research should test alternative hypotheses for change and determine if less intensive (shorter and/or automated) assessments would provide comparable results.
Audio keyword extraction by unsupervised word discovery

In real audio data, frequently occurring patterns often convey relevant information on the overall content of the data. The possibility to extract meaningful portions of the main content by identifying such key patterns, can be exploited for providing audio summaries and speeding up the access to relevant parts of the data. We refer to these patterns as audio motifs in analogy with the nomenclature in its counterpart task in biology. We describe a framework for the discovery of audio motifs in streams in an unsupervised fashion, as no acoustic or linguistic models are used. We define the fundamental problem by decomposing the overall task into elementary subtasks; then we propose a solution that combines a one-pass strategy that exploits the local repetitiveness of motifs and a dynamic programming technique to detect repetitions in audio streams. Results of an experiment on a radio broadcast show are shown to illustrate the effectiveness of the technique in providing audio summaries of real data.
Identifying Chemical Names in Biomedical Text: an Investigation of Substring Co-occurrence Based Approaches

We investigate various strategies for finding chemicals in biomedical text using substring co-occurrence information. The goal is to build a system from readily available data with minimal human involvement. Our models are trained from a dictionary of chemical names and general biomedical text. We investigated several strategies including Naive Bayes classifiers and several types of N-gram models. We introduced a new way of interpolating N-grams that does not require tuning any parameters. We also found the task to be similar to Language Identification.
Reduced switching-frequency voltage-balancing strategies for modular multilevel HVDC converters

Summary form only given. The modular multilevel converter (MMC) is a potential candidate for medium/high-power applications, specifically for high-voltage direct current (HVDC) transmission systems. One of the technical challenges associated with the control of an MMC is to carry out the submodule (SM) capacitor voltages balancing task without imposing any unnecessary switching transition among the SMs. This paper develops a general framework for the capacitor voltage balancing of an MMC. Based on the developed framework and with the objective of reducing the unnecessary switching transitions among the SMs, three capacitor voltage-balancing strategies are proposed and investigated: 1) a slow-rate balancing strategy based on the conventional sorting method; 2) a hybrid balancing strategy which combines a predictive method with the conventional sorting method; and 3) a fundamental-frequency balancing strategy. Performance of the proposed strategies for a point-to-point 21-level MMC-based HVDC system is evaluated based on time-domain simulation studies in the PSCAD/EMTDC software environment. The reported study results demonstrate the capability and tradeoffs of the proposed strategies to reduce the number of switching transitions and, consequently, the MMC losses, under various conditions.
Phonological short-term memory and new word learning : evidence from paired-associate and Hebb repetition paradigms

This thesis investigated the role of phonological short-term memory (PSTM) in the long-term learning of new phonological word-forms. Previous studies using the paired-associate paradigm have suggested that the learning of unfamiliar material is mediated by PSTM (e.g. Papagno & Vallar, 1992). The first'aim was. to replicate a! 1d extend this previous work. The second aim was to determine whether the Hebb repetition paradigm could provide an alternative method with which to investigate the role of PSTM in new word-form learning. Seven experiments w~re conducted to explore these aims. Experiment 1 obtained phonological similarity effects for words and nonwords in an immediate serial recall task, confirming that. the chosen manipulation of phonological similarity was adequate. Experiments 2 and' 3 . adopted the paired-associate task and replicated Papagno and Vallar' (1992), thus extending their results to English participants and materials. Phonological similarity was shown to selectively disrupt the learning of nonword pairs. In contrast, some evidence was found to suggest that phonological similarity fails to affect the learning' of word pairs. However, Experiment 3 showed that the detrimental effect of phonological similarity was restricted to an intermediate phase of learning. These findings suggest that PSTM mediates the learning of unfamiliar material, although the role of PSTM may change during the course of learning; Experiments 4 and 6 adopted the Hebb repetition task and generated patterns of results consistent with Papagno and Vallar (1992) and Experiments 2 and 3. Phonological similarity disrupted the learning of nonword s~quences, but not the learning of word sequences. These findings suggest that PSTM mediates sequence learning for unfamiliar material, thereby providing initia~ evidence that the Hebb repetition paradigm may be a possible analogue of new word-form learning. The role qf PSTM in nonword sequence learning could not be reliably assessed in Experiments 5 and 7 due to the absence of reliable Hebb Effects. Analyses of between-trial learning and forgetting rates using a Markov model revealed that phonological similarity had a negative impact on forgetting rates for nonwords in both paired-assoCiate and. Hebb repetItion paradigms, suggesting that phonological representations of nonwords are particularly fragile. Finally, it is proposed that the paired-associate paradigm represents a closer analogue of new word-form learning than the Hebb repetition paradigm as it makes use of existing lexical-semantic information.
Sequence of single neuron changes in CA1 hippocampus of rabbits during acquisition of trace eyeblink conditioned responses.

The sequence of changes in single neuron activity in the CA1 area of the rabbit hippocampus was examined during daily sessions (80 trials/session) of hippocampally dependent nonspatial trace eyeblink (i.e., nictitating membrane response) conditioning. Each trial for trace conditioned animals (n = 7) consisted of a tone conditioned stimulus (CS; 6 kHz; 90 dB, 100 ms) followed by a 500-ms silent trace period, then a corneal airpuff unconditioned stimulus (US; 3.0 psi; 150 ms). Control animals (n = 5) received unpaired CSs and USs. Most pyramidal (n = 309) and theta (n = 21) cells were recorded for a single day of training. The activity of cells for each animal were grouped according to: the day of training that CRs began to increase and the day of training that CR performance became asymptotic. Pyramidal cells from trace conditioned animals demonstrated several stages of learning-related activity: large increases in activity after both the CS and US early in conditioning on the day of training when CRs began to increase, smaller moderate increases in activity on the following days of training, and decreases in activity after the US during asymptotic CRs. Pyramidal cell-increases declined significantly across the trials of each daily session. Theta cells showed an activity pattern opposite to the pyramidal cells, consistent with the notion that theta cells have an inhibitory influence on pyramidal cells. Single pyramidal cells also were categorized into response profiles. Most pyramidal response profiles showed increases in activity specific to the day of initial CRs. Two of the pyramidal response profiles may be involved in assessing the temporal properties of the CS-US trace conditioning trial.
Towards a Semiotic Quality Framework of Software Measures

Each software entity should have as high quality as possible in the context of limited resources. A software quality measure is a kind of software entity. Existing studies about the evaluation of software measures do not pay enough attention to the quality of specifications of measures. Semiotics has been used as a basis in order to evaluate the quality of different types of software entities. In this paper, we propose a multidimensional, semiotic quality framework of software quality measures. We apply this framework in order to evaluate the syntactic and semantic quality of two sets of database design measures. The evaluation shows that these measures have some quality problems.
Adeno-associated virus (AAV) site-specific recombination does not require a Rep-dependent origin of replication within the AAV terminal repeat

Adeno-associated virus (AAV) is the only known eukaryotic virus capable of targeted integration in human cells. An AAV Rep binding element (RBE) and terminal resolution site (trs) identical to the viral terminal repeats required for AAV DNA replication are located on chromosome (ch) 19. Both ch-19 RBE and trs elements have been shown to be essential for viral targeting to this locus. To characterize the role of the AAV inverted terminal repeat (ITR) cis-acting sequences in targeted integration an AAV trs mutant incapable of supporting viral replication was tested. Wild-type and mutant substrates were assayed for targeted integration after cotransfection in the presence or absence of Rep. Our results demonstrated that, in the presence of Rep78, both ITR substrates targeted to ch-19 with similar frequency. Molecular characterization of the mutant ITR integrants confirmed the presence of the trs mutation in the majority of samples tested. Complementation analysis confirmed that the mutant targeted viral genomes were unable to rescue and replicate. In addition, Rep78 induced extensive rearrangement and amplification of ch-19 sequences independent of wild-type or mutant targeting substrate. These studies demonstrate that Rep-dependent nicking of the viral cis-acting trs sequence is not a prerequisite for site-specific recombination and suggests AAV targeting is mediated by Rep78/68-dependent replication from the ch-19 origin of replication (ori). These studies have significant impact toward the understanding of AAV site-specific recombination and the development of targeting vectors.
Global citizenship incorporated: competing responsibilities in the education of global citizens

ABSTRACT Interest in the education of young people to be ‘responsible global citizens’ has grown exponentially since the turn of the century, led by increasingly diverse networks of sectors, including government, community, business and philanthropy. These networks now have a significant influence on education policy and practice, indicative of wider changes in governance and processes of globalisation. Yet little of the academic literature on global citizenship education specifically examines the impact of these networks on the production of knowledge about young global citizens. This paper addresses this gap by analysing the discourses of global citizenship that underpin recent work by a youth organisation that works closely with a network of sectors in Australia. The paper finds that a particular kind of entrepreneurial global citizen is favoured, one that is simultaneously responsible for themselves, for the rights of others and for ensuring Australia's future economic prosperity.
Effects of pleasant and unpleasant auditory mood induction on the performance and in brain activity in cognitive tasks

Our study focuses on mood induction with pleasant and unpleasant auditory stimuli during the break. Our test includes subjective evaluation (NASA-TLX, KSS, POMS), cognitive tests and brain responses (MEG and EEG). We aim studying the effect affective state has on work-like tasks. Hypothesis: pleasantness of auditory mood induction affects cognitive performance and brain responses.