Miracle-dz/UniFAR-FTUs huggingface dataset:
Current Pharmacological Management of Gastroesophageal Reflux Disease

Gastroesophageal reflux disease (GERD), a common disorder with troublesome symptoms caused by reflux of gastric contents into the esophagus, has adverse impact on quality of life. A variety of medications have been used in GERD treatment, and acid suppression therapy is the mainstay of treatment for GERD. Although proton pump inhibitor is the most potent acid suppressant and provides good efficacy in esophagitis healing and symptom relief, about one-third of patients with GERD still have persistent symptoms with poor response to standard dose PPI. Antacids, alginate, histamine type-2 receptor antagonists, and prokinetic agents are usually used as add-on therapy to PPI in clinical practice. Development of novel therapeutic agents has focused on the underlying mechanisms of GERD, such as transient lower esophageal sphincter relaxation, motility disorder, mucosal protection, and esophageal hypersensitivity. Newer formulations of PPI with faster and longer duration of action and potassium-competitive acid blocker, a newer acid suppressant, have also been investigated in clinical trials. In this review, we summarize the current and developing therapeutic agents for GERD treatment.
Building a search engine model with morphological normalization support

Searching a collection of documents can seem like an easy task, but manipulating textual data can be difficult because the data are mostly unstructured. We undertook the task of building an effective search engine for a collection of Croatian legislative documents. The developed search engine model supports multiple modules for information retrieval. To improve the effectiveness of the retrieval, we used a morphological normalization module that uses an inflectional lexicon automatically acquired from a document corpus. As we do not have a gold standard for our legislative document collection, we evaluated our search engine on three English test collections, explored the effects of stemming, and compared the results to the vector space model.
English or French? How Second Language Learners DiscriminateLanguages with a Shared Alphabet

The purpose of the study was to examine French language learners' (FLL) and English language learners' (ELL) knowledge of orthographic patterns in English and French, the relationship of orthographic knowledge to word reading, and the strategies participants used to distinguish the patterns. I hypothesized that FLL would score higher than ELL on a measure of orthographic knowledge of French and English (combined), but that orthographic knowledge would predict word reading in both groups. The analysis of strategy use was exploratory, given the lack of research in this area. Forty-eight first and second graders (31 FLL, 17 ELL) were asked to (a) complete measures of word reading; (b) classify pseudowords as French or English to assess orthographic pattern knowledge; and (c) identify their strategies for classifying pseudowords. Children's responses were then coded as phonological, orthographic, or no strategy. Their use of analogies was also examined. As expected, the FLL group scored significantly higher than the ELL group on the task of orthographic knowledge, t(46) 2.23, p < . 03. Orthographic processing predicted word reading in both languages for FLL, and in English for ELL. For strategy types (n = 48), both groups used orthographic strategies more frequently than phonological strategies, but FLL used significantly fewer phonological strategies than ELL. The results suggest that orthographic processing contributes to English and French word reading. The study also provides insight into the types of strategies L2 children use to discriminate languages with a shared alphabet.
An Optimizing Strategy Research of LDPC Decoding Based on GPGPU

As powerful error correcting codes, Low-Density Parity-Check (LDPC) codes have been adopted as a fundamental building block by dirty paper coding (DPC), which indicates that lossless precoding is theoretically possible at any signal-to-noise ratio (SNR), and is a promising strategy in future communication systems. However, to achieve this performance gain demands huge computation complexity. For its lower cost and better flexibility, the GPU-based LDPC decoder is an emerging research subject. Based on the perspective of GPU hardware architecture, a multi-stage optimizing mapping strategy (MSOMS) is proposed and implemented to accelerate LDPC decoding. The performance is boosted significantly by balancing the memory access and computation load, optimizing execution configuration and the memory access pattern, and fully utilizing the on-chip high speed resources. Proposed decoders can achieve 383-and 442-speedup compared to CPU-based decoder for LDPC and RA code (another ensemble of LDCP code), and the achieved throughput is comparable to existed GPU-based decoders, which confirm the efficiency of the MSOMS strategy.
Facial expression recognition using geometric and appearance features

A novel method using hybrid geometric and appearance features of the difference between the neutral and fully expressive facial expression images is proposed for facial expression recognition in this paper. The difference tends to emphasize the facial parts that are changed from the neutral to expressive face and eliminate in that way the identity of the facial image. The hybrid features include facial feature point displacements and local texture differences between the normalized neutral and expressive facial expression images. The proposed method achieved an average accuracy of 95% in the extended Cohn-Kanade database with a Support Vector Machine (SVM) classification method.
Albumin Therapy Improves Local Vascular Dynamics in a Rat Model of Primary Microvascular Thrombosis: A Two-Photon Laser-Scanning Microscopy Study

Background and Purpose— High-dose human albumin is robustly neuroprotective in preclinical ischemia models and is currently in phase III clinical trial for acute ischemic stroke. To explore the hypothesis that albumin’s protective effect is mediated in part by salutary intravascular mechanisms, we assessed microvascular hemodynamics in a model of laser-induced cortical arteriolar thrombosis. Methods— The cortical microcirculation of anesthetized, physiologically monitored Sprague-Dawley rats was studied in vivo via a frontoparietal cranial window (intact dura) by two-photon laser-scanning microscopy after plasma-labeling with fluorescein-dextran. Focal thrombosis was produced in 30- to 50-&mgr;m cortical arterioles by laser irradiation. Arteriolar flow velocity was measured repeatedly by line-scanning. At 30 minutes post-thrombosis, animals were treated with either human albumin, 2 g/kg, or with saline control. Results— Baseline arteriolar flow velocity averaged 3.5±1.8 mm/s and was reduced to 10% to 13% of control values by laser-induced thrombosis, which also led to focal vasodilatation (mean, 49% above baseline diameter). Saline treatment at 30 minutes post-thrombosis failed to influence arteriolar flow velocity, which remained depressed at 10% to 22% of control throughout the subsequent 60- to 90-minute observation period. By contrast, albumin treatment induced a prompt rise in median flow velocity to 38% of control by 10 minutes post-treatment, and to 61% to 67% of control by 50 to 60 minutes. Conclusions— High-dose albumin therapy induces a prompt, sustained improvement in microvascular hemodynamics distal to a cortical arteriolar thrombosis; these data support an important intravascular component to albumin’s protective effect in acute cerebral ischemia.
XMM-Newton Observations of the Perseus Cluster. I. The Temperature and Surface Brightness Structure

We present preliminary results of a XMM-Newton 50 ks observation of the Perseus Cluster that provides an unprecedented view of the central 0.5 Mpc region. The projected gas temperature declines smoothly by a factor of 2 from a maximum value of ~ 7 keV in the outer regions to just above 3 keV at the cluster center. Over this same range, the heavy-element abundance rises slowly from 0.4 to 0.5 solar as the radius decreases from 14' to 5', and then it rises to a peak of almost 0.7 solar at 1. ′25 before declining to 0.4 at the center. The global east-west asymmetry of the gas temperature and surface brightness distributions, approximately aligned with the chain of bright galaxies, suggests an ongoing merger, although the modest degree of the observed asymmetry certainly excludes a major merger interpretation. The chain of galaxies probably traces the filament along which accretion started some time ago and is continuing at the present time. A cold and dense (low-entropy) cluster core like Perseus is probably well "protected" against the penetration of the gas of infalling groups and poor clusters, whereas in noncooling core clusters such as Coma and A1367, infalling subclusters can penetrate deeply into the core region. In Perseus, gas associated with infalling groups may be stripped completely at the outskirts of the main cluster and only compression waves (shocks) may reach the central regions. We argue, and show supporting simulations, that the passage of such a wave(s) can qualitatively explain the overall horseshoe shaped appearance of the gas temperature map (the hot horseshoe surrounds the colder, low-entropy core) as well as other features of the Perseus Cluster core. These simulations also show that as compression waves traverse the cluster core, they can induce oscillatory motion of the cluster gas that can generate multiple sharp "edges" on opposite sides of the central galaxy. Gas motions induced by mergers may be a natural way to explain the high frequency of "edges" seen in clusters with cooling cores.
Investigation of alcohol-related social norms among youth aged 14–17 years in Perth, Western Australia: protocol for a respondent-driven sampling study

Introduction Alcohol use among young people is a major public health concern in Australia and internationally. Research elucidating social norms influencing alcohol use supports the desire to conform to peers. However, there is a lack of evidence on how social norms are transmitted from the community to young people and between family members and peers, as previous studies are limited to mainly school and university environments. This article describes the proposed process to investigate common alcohol-related norms held by 14-year-olds to 17-year-olds in Perth, Western Australia, and to clarify the process and pathways through which proalcohol norms are transmitted to adolescents. Methods and analysis This cross-sectional quantitative study will use respondent-driven sampling (RDS) to recruit a sample of 672 adolescents from sporting groups, youth programmes and the community in Perth. Data will be collected with a previously developed and validated multidimensional online survey instrument. A variety of strategies will be explored to aid participation including face-to-face recruitment and survey administration, web-based RDS and a ‘mature minor’ consent assessment protocol. Data analysis will include descriptive statistics of demographic characteristics, as well as social network and dyadic analyses, to explore the connections between shared understanding of norms and behaviours among individuals and how these translate into reported practices. Ethics and dissemination This research is expected to extend our understanding of normative development pathways to inform future interventions, and will be widely disseminated through conference presentations, peer-reviewed papers, media channels and community seminars. A study reference group of key health industry stakeholders will be established to encourage integration of study findings into policy and practice, and results will guide the development of community interventions. The Curtin University Human Research Ethics Committee has granted approval for this research.
Runtime adaptive allocation of dynamically mixed tasks on a heterogeneous MPSoC platform

Multiprocessor System-on-Chip platforms are typically used for co-hosting multiple tasks, which may start and stop execution independently at time instants unknown at design time. In such systems, the runtime resource manager is responsible for allocating adequate and appropriate resources to each task. We identify a key issue in existing work that the resource management algorithms consider the problem only at task-level, i.e. the optimization is performed for each individual task upon activation. However, it can be shown that such strategies are suboptimal from the system point of view. In contrast, we propose in this paper a new task allocation flow that considers the system-level resource management. Comparing with traditional techniques, significant performance improvement (up to 29.5%) is observed during evaluation using a standard benchmark set. In addition, the proposed task allocator features runtime self-adaptability with respect to changes in hardware and/or applications.
Accurate analysis of interconnect trees with distributed RLC model and moment matching

In this paper, a new method is presented for accurate analysis of interconnect trees. Based on the ABCD matrix of distributed RLC transmission lines, the new iterative method can derive the exact transfer functions of an interconnect tree with distributed RLC model. Moment matching and second-order approximation are used for fast simulation of time responses and 50% delays of interconnect trees. The new method has three advantages. First, it can calculate the exact transfer functions of an interconnect tree with any interconnect model besides distributed RLC model. Second, it can derive all leaf nodes' time-domain responses in one iterative process. Third, it runs faster than HSPICE with time complexity linearly proportional to the number of branches in an interconnect tree. Time-domain responses and 50% propagation delays of the new method are compared to the results of HSPICE, the Elmore delay for lumped RC trees, and equivalent Elmore delay for lumped RLC trees, showing that the new method is both accurate and fast.
Dense point sets have sparse Delaunay triangulations

The spread of a finite set of points is the ratio between the longest and shortest pairwise distances. We prove that the Delaunay triangulation of any set of n points in R^3 with spread D has complexity O(D^3). This bound is tight in the worst case for all D = O(sqrt{n}). In particular, the Delaunay triangulation of any dense point set has linear complexity. We also generalize this upper bound to regular triangulations of k-ply systems of balls, unions of several dense point sets, and uniform samples of smooth surfaces. On the other hand, for any n and D=O(n), we construct a regular triangulation of complexity Omega(nD) whose n vertices have spread D.
Emulation, imitation, over-imitation and the scope of culture for child and chimpanzee

We describe our recent studies of imitation and cultural transmission in chimpanzees and children, which question late twentieth-century characterizations of children as imitators, but chimpanzees as emulators. As emulation entails learning only about the results of others' actions, it has been thought to curtail any capacity to sustain cultures. Recent chimpanzee diffusion experiments have by contrast documented a significant capacity for copying local behavioural traditions. Additionally, in recent ‘ghost’ experiments with no model visible, chimpanzees failed to replicate the object movements on which emulation is supposed to focus. We conclude that chimpanzees rely more on imitation and have greater cultural capacities than previously acknowledged. However, we also find that they selectively apply a range of social learning processes that include emulation. Recent studies demonstrating surprisingly unselective ‘over-imitation’ in children suggest that children's propensity to imitate has been underestimated too. We discuss the implications of these developments for the nature of social learning and culture in the two species. Finally, our new experiments directly address cumulative cultural learning. Initial results demonstrate a relative conservatism and conformity in chimpanzees' learning, contrasting with cumulative cultural learning in young children. This difference may contribute much to the contrast in these species' capacities for cultural evolution.
Complementary substrate-selectivity of metabolic adaptive convergence in the lignocellulolytic performance by Dichomitus squalens

The lignocellulolytic platform of the wood‐decaying organism Dichomitus squalens is important for production of biodegradable elements; however, the system has not yet been fully characterized. In this study, using statistical target optimization, we analysed substrate selectivity based on a variety of D. squalens metabolic pathways using combined omics tools. As compared with the alkali‐lignin (AL) programme, the rice straw (RS) programme has the advantage of multilayered signalling to regulate cellulolytic‐related genes or to connect their pathways. The spontaneous instability of the AL programme was accelerated by harsh starvation as compared with that of the RS programme. Therefore, the AL programme converged on cellular maintenance much easier and more rapidly. However, regardless of external substrate/concentration type, the compensatory pattern of the major targets (especially peroxidases and growth regulators) was similar, functioning to maintain cellular homeostasis. Interestingly, ligninolytic‐mediated targets under non‐kaleidoscopic conditions were induced by a substrate‐input‐control, and especially this mechanism had an important effect on the early stages of the biodegradation process. This optimized target analysis could be used to understand lignocellulolytic network and to improve downstream efficiency.
Modeling interaction between individuals, social networks and public policy to support public health epidemiology

Human behavior, social networks, and civil infrastructure are closely intertwined. Understanding their co-evolution is critical for designing public policies. Human behaviors and day-to-day activities of individuals create dense social interactions that provide a perfect fabric for fast disease propagation. Conversely, people's behavior in response to public policies and their perception of the crisis can dramatically alter normally stable social interactions. Effective planning and response strategies must take these complicated interactions into account. The basic problem can be modeled as a coupled co-evolving graph dynamical system and can also be viewed as partially observable Markov decision process. As a way to overcome the computational hurdles, we describe an High Performance Computing oriented computer simulation to study this class of problems. Our method provides a novel way to study the co-evolution of human behavior and disease dynamics in very large, realistic social networks with over 100 Million nodes and 6 Billion edges.
Worm Hotspots: Explaining Non-Uniformity in Worm Targeting Behavior

Long after the Blaster, Slammer/Sapphire, and CodeRedII worms caused significant worldwide disruptions, a huge number of infected hosts from these worms continue to probe the Internet today. This paper investigates hotspots (non-uniformities) in the targeting behavior of these important Internet worms. Recent data collected over the period of a month and a half using a distributed blackhole data collection infrastructure covering 18 networks including ISPs, enterprises, and academic networks show 75K Blaster infected hosts, 180K slammer infected hosts, and 55K CodeRedII hosts. We discover through detailed analysis how critical flaws and side effects in the targeting behavior lead to a significant bias for certain destination address blocks. In particular, we demonstrate three previously unexplored biases: a severely restricted initial random seed forcing infection attempts to certain blocks; flaws in the parameters of a random number generator making certain hosts cycle through limited target addresses; and the widespread use of private address space dramatically changing the targeting distribution of certain worms. A direct consequence of these biases is that certain blocks are subjected to far more infection attempts than others. We discuss the implication of these hotspots on worm simulation and modeling, placement of blackhole sensors, worm detection and quarantine. A. Total Packets B. Unique Source IPs Figure 1: Observations of the Blaster, Witty, Slammer, Nimda, and CodeRedII worms over all monitored blocks
Survival Analysis: Objective assessment of Wait Time in HCI

Waiting for the completion of a system process is an everyday experience. While waiting, system provides feedback to the user about ongoing process through temporal metaphors (Progress bar, Busy icons, etc.). One of the key performance requirement for temporal metaphors is to retain the user till the process completes. Researchers have evaluated these metaphors through subjective means, and objective assessment has not been well explored. In this paper, we present survival analysis as objective assessment method to evaluate temporal metaphors. Through a field experiment, we demonstrate the application of survival analysis and empirically establish that auditory progress bar (temporal metaphor for audio interfaces) works for callers of a distress helpline. To the best of our knowledge, it is the first study on distress callers. The paper further discusses the applicability of survival analysis for evaluating temporal metaphors and wait time experiments for other applications, tasks, and settings.
Offender-Nightmares: Two Pilot Studies

Being the victim of an aggressor in nightmares is quite common for most persons, but there are also nightmares where the dream-self can become the offender. Two studies were conducted in two nonclinical samples of participants with frequent nightmares to investigate the so-called offender-nightmares. Study 1 served to assess the frequency of offender-nightmares in persons with frequent nightmares and the motives and actions in these dreams during a 28-day interval, whereas in Study 2, correlations to personality variables were investigated. The results indicate that the occurrence of offender-nightmares is not negligible; about 18% to 28% of the reported nightmares were classified as offender-nightmares. Most of the aggressive acts in these dreams were intentional, and killing a person was the most prominent offender’s act, with self-defense being the most common motive. Persons with offender-nightmares were also found to have been more violent in the past than persons without offender-nightmares and persons without nightmares. In addition, they scored higher in neuroticism and aggression, reported more creative achievements than persons without nightmares, and had more creative achievements than persons without offender-nightmares. The results suggest that offender-nightmares are rather common in people who frequently have nightmares and that these dreams are related to aggressiveness, creativity, and previous violent experiences.
TWO-STAGE AUTOMATIC SPEECH SUMMARIZATION BY SENTENCE EXTRACTION AND COMPACTION

This paper proposes a new automatic speech summarization method having two stages: important sentence extraction and sentence compaction. Relatively important sentences are extracted from the results of large-vocabulary continuous speech recognition (LVCSR) based on the amount of information and the confidence measures of constituent words. The set of extracted sentences is compressed by our sentence compaction method. Sentence compaction is performed by selecting a word set that maximizes a summarization score which comprises the amount of information and the confidence measure of each word, the linguistic likelihood of word strings, and the word concatenation probability. The selected words are concatenated to create a summary. Effectiveness of the proposed method was confirmed by testing summarization of spontaneous presentations. Optimal ratio of sentence extraction to sentence compaction changes according to the target summarization ratio and features of presentations.