Miracle-dz/UniFAR-FTUs huggingface dataset:
Intracerebral Hemorrhage: Toward Physiological Imaging of Hemorrhage Risk in Acute and Chronic Bleeding

Despite improvements in management and prevention of intracerebral hemorrhage (ICH), there has been little improvement in mortality over the last 30 years. Hematoma expansion, primarily during the first few hours is highly predictive of neurological deterioration, poor functional outcome, and mortality. For each 10% increase in ICH size, there is a 5% increase in mortality and an additional 16% chance of poorer functional outcome. As such, both the identification and prevention of hematoma expansion are attractive therapeutic targets in ICH. Previous studies suggest that contrast extravasation seen on CT Angiography (CTA), MRI, and digital subtraction angiography correlates with hematoma growth, indicating ongoing bleeding. Contrast extravasation on the arterial phase of a CTA has been coined the CTA Spot Sign. These easily identifiable foci of contrast enhancement have been identified as independent predictors of hematoma growth, mortality, and clinical outcome in primary ICH. The Spot Sign score, developed to stratify risk of hematoma expansion, has shown high inter-observer agreement. Post-contrast leakage or delayed CTA Spot Sign, on post contrast CT following CTA or delayed CTA respectively are seen in an additional ∼8% of patients and explain apparently false negative observations on early CTA imaging in patients subsequently undergoing hematoma expansion. CT perfusion provides an opportunity to acquire dynamic imaging and has been shown to quantify rates of contrast extravasation. Intravenous recombinant factor VIIa (rFVIIa) within 4 h of ICH onset has been shown to significantly reduce hematoma growth. However, clinical efficacy has yet to be proven. There is compelling evidence that cerebral amyloid angiopathy (CAA) may precede the radiographic evidence of vascular disease and as such contribute to microbleeding. The interplay between microbleeding, CAA, CTA Spot Sign and genetic composition (ApoE genotype) may be crucial in developing a risk model for ICH.
Improving lidar data evaluation for object detection and tracking using a priori knowledge and sensorfusion

This paper presents a new approach to improve lidar data evaluation on the basis of using a priori knowledge. In addition to the common I- and L-shapes, the directional IS-shape, the C-shape for pedestrians and the E-shape for bicycles are introduced. Considering the expected object shape and predicted position enables effective interpretation even of poor measurement values. Therefore a classification routine is utilized to distinguish between three classes (cars, bicycles, pedestrians). The tracking operation with Kalman filters is based on class specific dynamic models. The fusion of radar objects with the used a priori knowledge improves the quality of the lidar evaluation. Experiments with real measurement data showed good results even with a single layer lidar scanner.
Joint Opinion Relation Detection Using One-Class Deep Neural Network

Detecting opinion relation is a crucial step for fine-gained opinion summarization. A valid opinion relation has three requirements: a correct opinion word, a correct opinion target and the linking relation between them. Previous works prone to only verifying two of these requirements for opinion extraction, while leave the other requirement unverified. This could inevitably introduce noise terms. To tackle this problem, this paper proposes a joint approach, where all three requirements are simultaneously verified by a deep neural network in a classification scenario. Some seeds are provided as positive labeled data for the classifier. However, negative labeled data are hard to acquire for this task. We consequently introduce one-class classification problem and develop a One-Class Deep Neural Network. Experimental results show that the proposed joint approach significantly outperforms state-of-the-art weakly supervised methods.
The Pneumocystis carinii drug target S‐adenosyl‐L‐methionine:sterol C‐24 methyl transferase has a unique substrate preference

Pneumocystis is an opportunistic pathogen that can cause pneumonitis in immunodeficient people such as AIDS patients. Pneumocystis remains difficult to study in the absence of culture methods for luxuriant growth. Recombinant protein technology now makes it possible to avoid some major obstacles. The P. carinii expressed sequence tag (EST) database contains 11 entries of a sequence encoding a protein homologous to S‐adenosyl‐L‐methionine (SAM):C‐24 sterol methyl transferase (SMT), suggesting high activity of this enzyme in the organism. We sequenced the erg6 cDNA, identified the putative peptide motifs for the sterol and SAM binding sites in the deduced amino acid sequence and expressed the protein in Escherichia coli. Unlike SAM:SMT from other organisms, the P. carinii enzyme had higher affinities for lanosterol and 24‐methylenelanosterol than for zymosterol, the preferred substrate in other fungi. Cycloartenol was not a productive substrate. With lanosterol and 24‐methylenelanosterol as substrates, the major reaction products were 24‐methylenelanosterol and pneumocysterol respectively. Thus, the P. carinii SAM:SMT catalysed the transfer of both the first and the second methyl groups to the sterol C‐24 position, and the substrate preference was found to be a unique property of the P. carinii SAM:SMT. These observations, together with the absence of SAM:SMT among mammals, further support the identification of sterol C‐24 alkylation reactions as excellent targets for the development of drugs specifically directed against this pathogen.
Real-time compositing framework for interactive stereo fMRI displays

This research concentrates on providing high fidelity animation, only achievable with offline rendering solutions, for interactive fMRI-based experiments. Virtual characters are well established within the film, game and research worlds, yet much remains to be learned about which design, stylistic or behavioural factors combine to make a believable character. The definition of believability depends on context. When designing and implementing characters for entertainment, the concern is making believable characters that the audience will engage with. When using virtual characters in experiments, the aim is to create characters and synthetic spaces that people respond to in a similar manner to their real world counterparts. Research has shown that users show empathy for virtual characters. However, uncanny valley effects -- ie dips in user impressions -- can arise: behavioural fidelity expectations increase alongside increases in visual fidelity and vice versa. Often, characters used within virtual environments tend to be of fairly low fidelity due to technological constraints including rendering in real-time (Garau et al. 2003). This problem is addressed here by using non-linear playback and compositing of pre-rendered high fidelity sequences.
Disruption of Pheromone Communication of Choristoneura rosaceana (Lepidoptera: Tortricidae) Using Microencapsulated Sex Pheromones Formulated With Horticultural Oil

Abstract Sprayable, microencapsulated (MEC) sex pheromone formulations represent a promising tool for achieving mating disruption, yet often lack sustained effectiveness in the field, making repeated applications necessary. This study evaluated the impact of adding Purespray Green horticultural oil as an adjuvant to 3M MEC-LR, an MEC formulation of (Z)-11-tetradecenyl acetate, on disruption of mate-finding behavior in Choristoneura rosaceana (Harris) in small-plot trials in experimental apple orchards. Treatments consisting of MEC-LR in water, MEC-LR in water + 2% (vol:vol) Purespray Green, and a water control were applied to plots of apple using an airblast sprayer at a rate of 100 g of pheromone/ha. Disruption caused by foliar treatments was evaluated over a 7-wk period using mark-release recapture experiments in the field and concurrent bioassays in a flight tunnel. Disruption of orientation to 2-d-old, calling, virgin females was used as a measure of treatment effect in all experiments. Both pheromone alone and pheromone + oil treatments significantly disrupted male mate-finding behavior for a period of ≥21 d in flight tunnel assays and ≥42 d in mark-recapture field trials. The addition of oil did not significantly enhance the disruption activity nor increase the longevity of the MEC pheromone formulation. Our results show the compatibility of spraying MEC pheromone with a horticultural oil, and techniques for applying an oil-pheromone formulation to maximize the control impact of this combination are discussed.
TFEB inhibits endothelial cell inflammation and reduces atherosclerosis

TFEB suppresses oxidative stress and inflammation in endothelial cells to decrease atherosclerosis. Protected from atherosclerosis by TFEB Atherosclerosis, or the buildup of fatty plaques in blood vessels, can lead to high blood pressure and heart attacks. Lu et al. found that, in cultured endothelial cells, the transcription factor TFEB reduced oxidative stress and inflammation, two processes thought to contribute to the development of atherosclerosis. When fed a high-fat diet, mice that overexpressed TFEB in endothelial cells developed smaller atherosclerotic lesions than their control littermates on the same diet. Thus, treatments that enhance the activity of TFEB in endothelial cells could reduce the development of atherosclerosis. Furthermore, because the anti-inflammatory effect of TFEB in endothelial cells was independent of its role in autophagy, a process in which cells digest macromolecules and organelles, these results highlight new roles for this transcription factor. Transcription factor EB (TFEB) is a master regulator of autophagy and lysosome biogenesis. We investigated the function of TFEB in vascular biology and pathophysiology and demonstrated that TFEB in endothelial cells inhibited inflammation and reduced atherosclerosis development. Laminar shear stress, which protects against atherosclerosis, increased TFEB abundance in cultured primary human endothelial cells. Furthermore, TFEB overexpression in these cells was anti-inflammatory, whereas TFEB knockdown aggravated inflammation. The anti-inflammatory effect of TFEB was, at least, partially due to reduced oxidative stress because TFEB overexpression in endothelial cells decreased the concentrations of reactive oxygen species and increased the expression of the antioxidant genes HO1 (which encodes heme oxygenase 1) and SOD2 (which encodes superoxide dismutase 2). In addition, transgenic mice with endothelial cell–specific expression of TFEB exhibited reduced leukocyte recruitment to endothelial cells and decreased atherosclerosis development. Our study suggests that TFEB is a protective transcription factor against endothelial cell inflammation and a potential target for treating atherosclerosis and associated cardiovascular diseases.
An Efficient Mining Algorithm for Closed Frequent Itemsets and its Associated Data

is a repository of information. Retrieving automatic patterns from the database provide the requisite information and are in great demand in various domains of science and engineering. The effective pattern mining methods such as pattern discovery and association rule mining have been developed and find its applicability in a wide gamut ranging from science to medical to military and to engineering applications. Contemporary methods of retrieval such as pattern discovery and association rule mining algorithms are useful only for retrieving the data. The limitations of using these techniques are that they are unable to provide a complete association and relationship among the diverse patterns that is retrieved. This paper attempts a solution to the above limitation by designing a new algorithm (CFIM) which generates closed frequent patterns and its associated data concurrently. CFIM makes explicit the relationship between the patterns and its associated data. KeywordsRule Mining, Frequent Closed Itemsets and Pattern Discovery.
Auditory Gap-in-Noise Detection Behavior in Ferrets and Humans

The precise encoding of temporal features of auditory stimuli by the mammalian auditory system is critical to the perception of biologically important sounds, including vocalizations, speech, and music. In this study, auditory gap-detection behavior was evaluated in adult pigmented ferrets (Mustelid putorius furo) using bandpassed stimuli designed to widely sample the ferret’s behavioral and physiological audiogram. Animals were tested under positive operant conditioning, with psychometric functions constructed in response to gap-in-noise lengths ranging from 3 to 270 ms. Using a modified version of this gap-detection task, with the same stimulus frequency parameters, we also tested a cohort of normal-hearing human subjects. Gap-detection thresholds were computed from psychometric curves transformed according to signal detection theory, revealing that for both ferrets and humans, detection sensitivity was worse for silent gaps embedded within low-frequency noise compared with high-frequency or broadband stimuli. Additional psychometric function analysis of ferret behavior indicated effects of stimulus spectral content on aspects of behavioral performance related to decision-making processes, with animals displaying improved sensitivity for broadband gap-in-noise detection. Reaction times derived from unconditioned head-orienting data and the time from stimulus onset to reward spout activation varied with the stimulus frequency content and gap length, as well as the approach-to-target choice and reward location. The present study represents a comprehensive evaluation of gap-detection behavior in ferrets, while similarities in performance with our human subjects confirm the use of the ferret as an appropriate model of temporal processing.
The effect of aging and increasing ascorbate concentrations on respiratory chain activity in cultured human fibroblasts

The specific activities of Complexes I‐III, II‐III, and IV of the respiratory chain, and citrate synthase, were determined in mitochondrial sonicates of six control passage 5 fibroblast cultures, cultivated in growth medium containing fetal calf serum as the only source of ascorbate. The enzymes were also assayed in serially subcultured fibroblasts which were characterized as aged at passage 20 and beyond. Results indicated a significant loss of all enzyme activities in aged cells at passage 20, 25, and 30. Further studies involved maintenance of serially subcultured cells in serum free media to which increasing ascorbate concentrations (100, 200, and 300 µmol 1−1) were added. Results indicated that ascorbate at 100 µmol 1−1 was not sufficient to restore any of the enzyme activities in aged cells. An ascorbate concentration of 200 µmol 1−1 however, could totally restore Complex IV and citrate synthase activities, but had no effect on complexes I‐III and II‐III activities which required 300 µmol 1−1 ascorbate to be partially or totally restored respectively. In conclusion, this study demonstrates an age related drop in mitochondrial respiratory chain activity in cultured human fibroblasts. Enzyme activities could be completely or partially restored in the presence of double or triple normal human plasma ascorbate concentrations. Copyright © 2010 John Wiley & Sons, Ltd.
The role of income differences in explaining social inequalities in self rated health in Sweden and Britain

STUDY OBJECTIVE To analyse to what extent differences in income, using two distinct measures—as distribution across quintiles and poverty—explain social inequalities in self rated health, for men and women, in Sweden and Britain. DESIGN Series of cross sectional surveys, the Swedish Survey of Living Conditions (ULF) and the British General Household Survey (GHS), during the period 1992–95. PARTICIPANTS AND SETTING Swedish and British men and women aged 25—64 years. Approximately 4000 Swedes and 12 500 Britons are interviewed each year in the cross sectional studies used. The sample contains 15 766 people in the Swedish dataset and 49 604 people in the British dataset. MAIN RESULTS The magnitude of social inequalities in less than good self rated health was similar in Sweden and in Britain, but adjusting for income differences explained a greater part of these in Britain than in Sweden. In Britain the distribution across income quintiles explained 47% of the social inequalities in self rated health among women and 31% among men, while in Sweden it explained, for women 13% and for men 20%. Poverty explained 22% for British women and 8% for British men of the social inequalities in self rated health, while in Sweden poverty explained much less (men 2.5% and women 0%). CONCLUSIONS The magnitude of social inequalities in self rated health was similar in Sweden and in Britain. However, the distribution of income across occupational social classes explains a larger part of these inequalities in Britain than in Sweden. One reason for this may be the differential exposure to low income and poverty in the two countries.
The mouse Gene Expression Database (GXD): 2011 update

The Gene Expression Database (GXD) is a community resource of mouse developmental expression information. GXD integrates different types of expression data at the transcript and protein level and captures expression information from many different mouse strains and mutants. GXD places these data in the larger biological context through integration with other Mouse Genome Informatics (MGI) resources and interconnections with many other databases. Web-based query forms support simple or complex searches that take advantage of all these integrated data. The data in GXD are obtained from the literature, from individual laboratories, and from large-scale data providers. All data are annotated and reviewed by GXD curators. Since the last report, the GXD data content has increased significantly, the interface and data displays have been improved, new querying capabilities were implemented, and links to other expression resources were added. GXD is available through the MGI web site (www.informatics.jax.org), or directly at www.informatics. jax.org/expression.shtml.
Preliminary Evaluation of a Personal Healthcare System Prototype for Cognitive eRehabilitation in a Living Assistance Domain

The integration of rehabilitation systems in an ambient assisted living environment can provide a powerful and versatile tool for long-term stroke rehabilitation goals. This paper introduces a novel concept of a personalized cognitive rehabilitation system in a naturalistic setting. The proposed platform was developed within the CogWatch project, with the intent of fostering independence in activities of daily living in patients with apraxia and action disorganization syndrome. Technical usability was evaluated in a series of pilot experiments, which illustrate how this approach may help to retrain patients in activities of daily living. The first system prototype has been tested with 36 participants divided into three groups, providing an exploratory evaluation of the usability of this solution and its acceptability. The technical solutions used within the CogWatch project are targeted to meet both the end users' needs from the interaction and usability point of views and the clinical requirements associated with the use of such systems. The challenges behind the development of ambient assisted living systems for cognitive rehabilitation are discussed.
Location Systems: An Introduction to the Technology Behind Location Awareness

Advances in electronic location technology and the coming of age of mobile computing have opened the door for location-aware applications to permeate all aspects of everyday life. Location is at the core of a large number of high-value applications ranging from the life-and-death context of emergency response to serendipitous social meet-ups. For example, the market for GPS products and services alone is expected to grow to US$200 billion by 2015. Unfortunately, there is no single location technology that is good for every situation and exhibits high accuracy, low cost, and universal coverage. In fact, high accuracy and good coverage seldom coexist, and when they do, it comes at an extreme cost. Instead, the modern localization landscape is a kaleidoscope of location systems based on a multitude of different technologies including satellite, mobile telephony, 802.11, ultrasound, and infrared among others. This lecture introduces researchers and developers to the most popular technolog es and systems for location estimation and the challenges and opportunities that accompany their use. For each technology, we discuss the history of its development, the various systems that are based on it, and their trade-offs and their effects on cost and performance. We also describe technology-independent algorithms that are commonly used to smooth streams of location estimates and improve the accuracy of object tracking. Finally, we provide an overview of the wide variety of application domains where location plays a key role, and discuss opportunities and new technologies on the horizon. Table of Contents: Introduction / The Global Positioning System / Infrared and Ultrasonic Systems / Location Esimation with 802.11 / Cellular-Based Systems / Other Approaches / Improving Localization Accuracy / Location-Based Applications and Services / Challenges and Opportunities / References
Grey wolf optimizer: a new strategy to invert geophysical data sets

There is no meta‐heuristic approach best suited for solving all optimization problems making this field of study highly active. This results in enhancing current approaches and proposing new meta‐heuristic algorithms. Out of all meta‐heuristic algorithms, swarm intelligence is preferred as it can preserve information about the search space over the course of iterations and usually has fewer tuning parameters. Grey Wolves, considered as apex predators, motivated us to simulate Grey Wolves in the optimization of geophysical data sets. The grey wolf optimizer is a swarm‐based meta‐heuristic algorithm, inspired by mimicking the social leadership hierarchy and hunting behaviour of Grey Wolves. The leadership hierarchy is simulated by alpha, beta, delta and omega types of wolves. The three main phases of hunting, that is searching, encircling and attacking prey, is implemented to perform the optimization. To evaluate the efficacy of the grey wolf optimizer, we performed inversion on the total gradient of magnetic, gravity and self‐potential anomalies. The results have been compared with the particle swarm optimization technique. Global minimum for all the examples from grey wolf optimizer was obtained with seven wolves in a pack and 2000 iterations. Inversion was initially performed on thin dykes for noise‐free and noise‐corrupted (up to 20% random noise) synthetic data sets. The inversion on a single thin dyke was performed with a different search space. The results demonstrate that, compared with particle swarm optimization, the grey wolf optimizer is less sensitive to search space variations. Inversion of noise‐corrupted data shows that grey wolf optimizer has a better capability in handling noisy data as compared to particle swarm optimization. Practical applicability of the grey wolf optimizer has been demonstrated by adopting four profiles (i.e. surface magnetic, airborne magnetic, gravity and self‐potential) from the published literature. The grey wolf optimizer results show better data fit than the particle swarm optimizer results and match well with borehole data.