Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting post-traumatic stress disorder following first onset acute coronary syndrome: Testing a theoretical model.

OBJECTIVES This research identified which theoretically predicted factors (Joseph, Williams, & Yule, 1997) were associated with the severity of post-traumatic stress disorder (PTSD) symptoms 1 and 6 months following onset of acute coronary syndrome (ACS). Predictor variables included event factors, peri-traumatic distress; and maintaining factors including coping strategies, social support, re-appraisal of event threat, and beliefs about the nature of ACS. Associations with alexithymia were also explored. METHOD One hundred and fifty participants completed questionnaires in hospital and at 1- and 6-month follow-up. RESULTS Hierarchical multiple regression including both baseline and contemporaneous variables explained 52 and 42% of the variance in PTSD symptoms at each follow-up. At 1-month follow-up, predictors of PTSD symptoms were as follows: peri-traumatic distress, concern over symptoms, illness comprehension, and lack of social support. At 6-month follow-up, predictors were: peri-traumatic distress, lack of social support, use of problem-focused coping, and continued symptoms. CONCLUSIONS The Joseph et al. model was generally supported. The data allow some degree of prediction of high risk individuals and suggest some possible interventions.
Using DASH Assisting Network Elements for Optimizing Video Streaming Quality

On-demand video streaming is a popular application which accounts for a large share of today's Internet traffic. Dynamic Adaptive Streaming over HTTP (DASH) is the major streaming technology used by large content providers. However, this technology suffers from performance problems when multiple clients are streaming on shared network links. Aiming at improving the viewers' Quality of Experience, this thesis studies how DASH Assisting Network Elements (DANEs) optimize bottleneck network links and improve DASH streaming performance. The DANE is aware of DASH traffic on the network link, and partitions available network resources between DASH players and other traffic. Two DANE prototypes have been proposed as part of this thesis. In experiments with DASH players in wired and wireless networks, it is shown that the DANEs increase video bitrate, reduce quality switches, and improve fairness between players. Additionally, Markov models have been developed to explore sharing policies for DANEs. The models are used to determine the effect of those policies on streaming performance and to optimize network resource sharing for DASH players. Thorough validations with real DASH players show that the Markov models are highly accurate. In the remaining last year of the PhD program, I will apply DANE technology to cellular (5G) networks and use the Markov models to obtain an optimal sharing strategy.
Fabrication of bioprobe integrated with hollow nanoneedle for cellular function analysis

In order to realize cellular function analysis in a single living cell, we have been developing a newly designed probe for atomic force microscope (AFM), named “bioprobe”, which is integrated with a hollow silicon dioxide (SiO2) nanoneedle. The probe will be capable not only of performing AFM measurements but also of introducing desired biomolecules (DNA, proteins, etc.) into living cells and extracting biomolecules expressed in the cells. In this paper, we demonstrated the ability of the fabricated bioprobe to capture AFM images of living HeLa cells under near-physiological conditions. Moreover, the sharp-tipped SiO2 nanoneedle can be inserted into the cells without significant cell damage. In order to examine the possibility of liquid delivery, water ejection tests were also carried out. As a result, an extremely small amount of water can be ejected through a nanoneedle.
An annotation-aware Java virtual machine implementation

The Java bytecode language lacks expressiveness for traditional compiler optimizations, making this portable, secure software distribution format ine cient as a program representation for high performance. This ine ciency results from the underlying stack model, as well as the fact that many bytecode operations intrinsically include sub-operations (e.g., iaload includes the address computation, array bounds checks and the actual load of the array element). The stack model, with no operand registers and limiting access to the top of the stack, prevents the reuse of values and bytecode reordering. In addition, the language has no mechanism to indicate which sub-operations in the Java bytecode stream are redundant or subsumed by previous ones. As a consequence, the Java bytecode language inhibits the expression of important compiler optimizations, including register allocation and instruction scheduling. The Java bytecode stream generated by a Java bytecode compiler is a signi cantly under-optimized program representation. The most common solution to overcome this ine ciency is the use of a Just-inTime (JIT) compiler to not only generate native code, but perform optimization as well. However, the latter is a time consuming operation in an already time-constrained translation process. In this paper we present an alternative to an optimizing JIT compiler that makes use of code annotations generated by a Java bytecode compiler. These annotations carry information concerning compiler optimizations. During the translation process, an annotation-aware Java Virtual Machine (JVM) system then uses this information to produce high performance native code without performing much of the necessary analyses or transformations. We describe the implementation of a prototype of an annotation-aware JVM consisting of an annotation-aware JIT compilation system. We conclude the paper showing performance results comparing our system with other JVMs running on SPARC architecture.
Establishing the Boundaries: The Hippocampal Contribution to Imagining Scenes

When we visualize scenes, either from our own past or invented, we impose a viewpoint for our “mind's eye” and we experience the resulting image as spatially coherent from that viewpoint. The hippocampus has been implicated in this process, but its precise contribution is unknown. We tested a specific hypothesis based on the spatial firing properties of neurons in the hippocampal formation of rats, that this region supports the construction of spatially coherent mental images by representing the locations of the environmental boundaries surrounding our viewpoint. Using functional magnetic resonance imaging, we show that hippocampal activation increases parametrically with the number of enclosing boundaries in the imagined scene. In contrast, hippocampal activity is not modulated by a nonspatial manipulation of scene complexity nor to increasing difficulty of imagining the scenes in general. Our findings identify a specific computational role for the hippocampus in mental imagery and episodic recollection.
Diffuse, Lake-like Amyloid-β Deposits in the Parvopyramidal Layer of the Presubiculum in Alzheimer Disease

A characteristic feature of the parvopyramidal layer of the presubiculum of 6 individuals with Alzheimer disease (AD) was the presence of large, evenly distributed amyloid-)β (Aβ) deposits, which in the end stage of the disease occupy 80.9 ±2.2 % of the parvopyramidal layer. The strong reaction of Ap deposits with antibodies 4G8 (17-24 amino acids, aa), 6E10 (1-17 aa), and R165 (32-42 aa), and their weak reaction with antibody R162 (32-40 aa) indicate that potentially highly fibrillogenic Aβi-42 is a major constituent of presubicular amyloid. However, AP deposits in the presubiculum are thioflavin-S- and Congo red-negative—and thus, nonflbrillar—even after 11 to 19 years of AD. The unique properties of presubicular amyloid appear to be related to their origin; amyloid-associated proteins such as apolipoproteins E, and AI, α,- antichymotrypsin, and heparan sulfate proteoglycan, which are promoters of fibrillization or stabilizers of Aβ in neuritic plaques, are absent; activated astrocytes, which are the source of these proteins, are also absent. The unchanged number and distribution and the resting appearance of microglial cells revealed with RCA-I histochemistry suggest that they do not respond to diffuse Aβ deposits. The source of nonfibrillar presubicular Aβ is probably local neurons or neuronal projections to the parvocellular layer of the presubiculum. Neuronal, lake-like Aβ deposition appears to be characteristic of AD pathology. The presubiculum is most likely the model brain structure for the study of amyloid of exclusively neuronal origin. The parvopyramidal layer of the presubiculum reveals only a small population of the neurons (2.5 ±%) affected by neurofibrillary pathology.
Social Networks and Transactive Memory in Human-Computer Interaction

This study investigates the phenomenon of transactive memory by examining trust networks and social presence in human-computer interaction. Traditional theories suggest that transactive memory can be developed by structural mechanisms that increase knowledge specialization and task coordination, but more recent research also suggests that it can be enhanced through social network mechanisms and close relationships such as trust. In this empirical study, 240 participants were randomly assigned to 3-member teams working on a businesssimulation task. The results indicate that dense trust networks had a greater impact on transactive memory than sparse trust networks. When social presence was low, team members in dense trust networks developed greater transactive memory. When social presence was high, team members in sparse trust networks developed greater transactive memory. More reciprocal exchanges were found in teams with dense trust networks, but more negotiated exchanges were found in teams with sparse trust networks.
Intractable Hiccups in a Middle-Aged Female

A previously healthy 50-year-old female was admitted with recurrent hiccups and nausea for 2 weeks. She had previously taken several consultations from physicians and gastroenterologist without getting any relief. She denied any abdominal symptoms, visual impairment, motor weakness, incoordination, gait imbalance, or abnormal sensation. General physical and neurological examinations were normal. A magnetic resonance imaging (MRI) scan of the brain showed a hyperintense signal in the region of dorsal medulla on T2-weighted and fluid-attenuated inversion recovery sequences (Figure 1A-C) without diffusion restriction or postgadolinium enhancement. Screening of the spine MRI and visual evoked potentials were normal. Serum aquaporin-4 (AQP4)/neuromyelitis optica (NMO)-IgG antibody test (by indirect immunofluorescence assay) was positive. A diagnosis of neuromyelitis optica spectrum disorder (NMOSD) with isolated medullary involvement and without optic neuritis and transverse myelitis was made. The patient was given intravenous methylprednisolone 1 g daily for 5 days and showed clinical improvement. Subsequently, azathioprine was initiated to prevent further attacks. Neuromyelitis optica or Devic disease is an immunemediated demyelinating disorder of the central nervous system that predominantly affects the optic nerves and spinal cord. The term NMOSD is used to include AQP4-IgG-seropositive patients with limited or atypical forms of NMO (eg, isolated longitudinally extensive transverse myelitis, isolated recurrent optic neuritis, or area postrema syndrome). Intractable hiccups, nausea, and vomiting (area postrema syndrome) could be the initial or isolated presence of NMOSD. Brain lesions in NMOSD are present in more than half of the patients at onset and usually seen at sites of high AQP4 expression, such as the diencephalon, the hypothalamus, and the periaqueductal region. The NMOSD, sarcoidosis, Sjogren syndrome, systemic lupus erythematosus, tumor, and Behcet disease are the main differential diagnosis for solitary brain stem white matter lesion on brain MRI. Figure 1. Axial T2 (A), FLAIR (B), and coronal T2-weighted (C) MRI sequences showing hyperintense signal in the region of dorsal medulla. FLAIR indicates fluid-attenuated inversion recovery; MRI, magnetic resonance imaging.
Toxins Produced by Valsa mali var. mali and Their Relationship with Pathogenicity

Valsa mali var. mali (Vmm), the causal agent of apple tree canker disease, produces various toxic compounds, including protocatechuic acid, p-hydroxybenzoic acid, p-hydroxyacetophenone, 3-(p-hydroxyphenyl)propanoic acid and phloroglucinol. Here, we examined the relationship between toxin production and the pathogenicity of Vmm strains and determined their bioactivities in several assays, for further elucidating the pathogenesis mechanisms of Vmm and for developing new procedures to control this disease. The toxins were quantified with the high performance liquid chromatography (HPLC) method, and the results showed that the strain with attenuated virulence produced low levels of toxins with only three to four kinds of compounds being detectable. In contrast, higher amounts of toxins were produced by the more aggressive strain, and all five compounds were detected. This indicated a significant correlation between the pathogenicity of Vmm strains and their ability to produce toxins. However, this correlation only existed in planta, but not in vitro. During the infection of Vmm, protocatechuic acid was first detected at three days post inoculation (dpi), and the others at seven or 11 dpi. In addition, all compounds produced noticeable symptoms on host plants at concentrations of 2.5 to 40 mmol/L, with protocatechuic acid being the most effective compound, whereas 3-(p-hydroxyphenyl)propanoic acid or p-hydroxybenzoic acid were the most active compounds on non-host plants.
AUC Maximization in Bayesian Hierarchical Models

Abstract. The area under the curve (AUC) measures such as the area under the receiver operating characteristics curve (AUROC) and the area under the precision-recall curve (AUPR) are known to be more appropriate than the error rate, especially, for imbalanced data sets. There are several algorithms to optimize AUC measures instead of minimizing the error rate. However, this idea has not been fully exploited in Bayesian hierarchical models owing to the difficulties in inference. Here, we formulate a general Bayesian inference framework, called Bayesian AUC Maximization (BAM), to integrate AUC maximization into Bayesian hierarchical models by borrowing the pairwise and listwise ranking ideas from the information retrieval literature. To showcase our BAM framework, we develop two Bayesian linear classifier variants for two ranking approaches and derive their variational inference procedures. We perform validation experiments on four biomedical data sets to demonstrate the better predictive performance of our framework over its error-minimizing counterpart in terms of average AUROC and AUPR values.
GRASP: A Search Algorithm for Propositional Satisfiability

This paper introduces GRASP (Generic seaRch Algorithm for the Satisfiability Problem), a new search algorithm for Propositional Satisfiability (SAT). GRASP incorporates several search-pruning techniques that proved to be quite powerful on a wide variety of SAT problems. Some of these techniques are specific to SAT, whereas others are similar in spirit to approaches in other fields of Artificial Intelligence. GRASP is premised on the inevitability of conflicts during the search and its most distinguishing feature is the augmentation of basic backtracking search with a powerful conflict analysis procedure. Analyzing conflicts to determine their causes enables GRASP to backtrack nonchronologically to earlier levels in the search tree, potentially pruning large portions of the search space. In addition, by "recording" the causes of conflicts, GRASP can recognize and preempt the occurrence of similar conflicts later on in the search. Finally, straightforward bookkeeping of the causality chains leading up to conflicts allows GRASP to identify assignments that are necessary for a solution to be found. Experimental results obtained from a large number of benchmarks indicate that application of the proposed conflict analysis techniques to SAT algorithms can be extremely effective for a large number of representative classes of SAT instances.
Synchronous I/O Scheduling of Independent Write Caches for an Array of SSDs

Solid-state drives (SSD) offer a significant performance improvement over the hard disk drives (HDD), however, it can exhibit a significant variance in latency and throughput due to internal garbage collection (GC) process on the SSD. When the SSDs are configured in a RAID, the performance variance of individual SSDs could significantly degrade the overall performance of the RAID of SSDs. The internal cache on the RAID controller can help mitigate the performance variability issues of SSDs in the array; however, the state-of-the-art cache algorithm of the RAID controller does not consider the characteristics of SSDs. In this paper, we examine the most recent write cache algorithm for the array of disks, and propose a synchronous independent write cache (SIW) algorithm. We also present a pre-parity-computation technique for the RAID of SSDs with parity computations, which calculates parities of blocks in advance before they are stored in the write cache. With this new technique, we propose a complete paradigm shift in the design of write cache. In our evaluation study, large write requests dominant workloads show up to about 50 and 20 percent improvements in average response times on RAID-0 and RAID-5 respectively as compared to the state-of-the-art write cache algorithm.
Robust identification of partial-correlation based networks with applications to cortical thickness data

Insight into brain development and organization can be gained by computing correlations between structural and functional measures in parcellated cortex. Partial correlations can often reduce ambiguity in correlation data by identifying those pairs of regions whose similarity cannot be explained by the influence of other regions with which they may both interact. Consequently a graph with edges indicating non-zero partial correlations may reveal important subnetworks obscured in the correlation data. Here we describe and investigate PC*, a graph pruning algorithm for identification of the partial correlation network in comparison to direct calculation of partial correlations from the inverse of the sample correlation matrix. We show that PC* is far more robust and illustrate its use in the study of covariation in cortical thickness in ROIs defined on a parcellated cortex.
Constructing Physics-Based Facial Models of Individuals

This paper develops a highly automated approach to constructing realistic, working models of human heads for use in animation. Th ese physics-based models are anatomically accurate and may be made to conform closely to specific individuals . We begin by scanning a person with a laser sensor which circles around th e head, acquiring detailed range and reflec tance information . Next, an automatic conformation algorithm adapts a triangulated fa ce m esh of predetermined topological structure to thes e data. Th generic mesh, which is reusable with different individuals , reduces the range data to an effi cient, polygonal approximation of the fa cial geometry and supports a high-resolution texture mapping of th e skin refl ec tivity. Th e conformed polygonal mesh forms th e epidermal layer of a new, physics-based model of facial tissu e. A n automatic algorithm constructs the multilayer synthetic skin and estimates an underlying rigid "skull" substructure with a j ointed jaw. Finally, th e algorithm inserts synthetic muscles into the deepest layer of th e fa cial tissue. Th ese co ntractile actuators, which emulate the primary muscles of fa cial expression, generate f orces that deform th e synthetic tissue into m eaningful expressions. To increase realism, we include constraints to emulate tissue incompressibility and to enable th e tissue to slide over the skull substructure without penetrating into it. The resulting animate models appear significantly more realistic than our previous physics-based fa cial m odels.
A Bulk Segregant Gene Expression Analysis of a Peach Population Reveals Components of the Underlying Mechanism of the Fruit Cold Response

Peach fruits subjected for long periods of cold storage are primed to develop chilling injury once fruits are shelf ripened at room temperature. Very little is known about the molecular changes occurring in fruits during cold exposure. To get some insight into this process a transcript profiling analyses was performed on fruits from a PopDG population segregating for chilling injury CI responses. A bulked segregant gene expression analysis based on groups of fruits showing extreme CI responses indicated that the transcriptome of peach fruits was modified already during cold storage consistently with eventual CI development. Most peach cold-responsive genes have orthologs in Arabidopsis that participate in cold acclimation and other stresses responses, while some of them showed expression patterns that differs in fruits according to their susceptibility to develop mealiness. Members of ICE1, CBF1/3 and HOS9 regulons seem to have a prominent role in differential cold responses between low and high sensitive fruits. In high sensitive fruits, an alternative cold response program is detected. This program is probably associated with dehydration/osmotic stress and regulated by ABA, auxins and ethylene. In addition, the observation that tolerant siblings showed a series of genes encoding for stress protective activities with higher expression both at harvest and during cold treatment, suggests that preprogrammed mechanisms could shape fruit ability to tolerate postharvest cold-induced stress. A number of genes differentially expressed were validated and extended to individual genotypes by medium-throughput RT-qPCR. Analyses presented here provide a global view of the responses of peach fruits to cold storage and highlights new peach genes that probably play important roles in the tolerance/sensitivity to cold storage. Our results provide a roadmap for further experiments and would help to develop new postharvest protocols and gene directed breeding strategies to better cope with chilling injury.
Accuracy and interlaboratory reliability of human papillomavirus DNA testing by hybrid capture

Epidemiologists and clinicians wishing to introduce human papillomavirus (HPV) testing into cervical cancer prevention programs need standardized, reliable, and accurate HPV DNA tests that can detect the full spectrum of pathogenic HPV types. The Hybrid Capture System assay from Digene (hybrid capture assay) is a nonradioactive kit designed to detect 14 HPV types in two groups: a mix of 9 high-risk types associated with anogenital cancer (HPV types 16, 18, 31, 33, 35, 45, 51, 52, and 56) and another group of 5 low-risk types associated with condyloma acuminatum (HPV types 6, 11, 42, 43, and 44). The assay yields quantitative data meant to reflect viral concentration. In a study of 199 cervical specimens from women with concurrent Pap smears, we assessed the reliability of the new assay by comparing the hybrid capture assay results from three laboratories. We assessed the accuracy of the hybrid capture assay in comparison with a reference standard of HPV DNA content (multiple testing by several methods in two reference laboratories). We also compared the hybrid capture assay results with the concurrent cytologic diagnoses on the basis of an independent review of each smear by five pathologists. Pairwise interlaboratory agreement rates on HPV positivity for either high-risk or low-risk types ranged from 87 to 94%, and kappa values ranged from 0.61 to 0.83. Among specimens positive for high-risk types (the most important clinical outcome), the interlaboratory correlations of the quantitative data ranged from 0.60 to 0.90. Test results from all three laboratories were strongly associated with those of the HPV DNA reference standard and with the concurrent cytopathologic diagnoses. The most common errors were sporadic, apparently false-positive results.