Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk Stratification of ICU Patients Using Topic Models Inferred from Unstructured Progress Notes

We propose a novel approach for ICU patient risk stratification by combining the learned "topic" structure of clinical concepts (represented by UMLS codes) extracted from the unstructured nursing notes with physiologic data (from SAPS-I) for hospital mortality prediction. We used Hierarchical Dirichlet Processes (HDP), a non-parametric topic modeling technique, to automatically discover "topics" as shared groups of co-occurring UMLS clinical concepts. We evaluated the potential utility of the inferred topic structure in predicting hospital mortality using the nursing notes of 14,739 adult ICU patients (mortality 14.6%) from the MIMIC II database. Our results indicate that learned topic structure from the first 24-hour ICU nursing notes significantly improved the performance of the SAPS-I algorithm for hospital mortality prediction. The AUC for predicting hospital mortality from the first 24 hours of physiologic data and nursing text notes was 0.82. Using the physiologic data alone with the SAPS-I algorithm, an AUC of 0.72 was achieved. Thus, the clinical topics that were extracted and used to augment the SAPS-I algorithm significantly improved the performance of the baseline algorithm.
Shape-based defect classification for non destructive testing

The aim of this work is to classify the aerospace structure defects detected by eddy current non-destructive testing. The proposed method is based on the assumption that the defect is bound to the reaction of the probe coil impedance during the test. Impedance plane analysis is used to extract a feature vector from the shape of the coil impedance in the complex plane, through the use of some geometric parameters. Shape recognition is tested with three different machine-learning based classifiers: decision trees, neural networks and Naive Bayes. The performance of the proposed detection system are measured in terms of accuracy, sensitivity, specificity, precision and Matthews correlation coefficient. Several experiments are performed on dataset of eddy current signal samples for aircraft structures. The obtained results demonstrate the usefulness of our approach and the competiveness against existing descriptors.
Adiponectin/(FBG × FIns) as a predictor of insulin sensitivity and metabolic syndrome in patients with polycystic ovary syndrome

Abstract The euglycemic–hyperinsulinemic clamp is not available in most clinical settings. An accessible and inexpensive measurement for identifying insulin resistance (IR) is necessary. Our aim is to assess whether the adiponectin (ADI) index (ADI/[FBG × FIns]) is a better surrogate index for the assessment of IR or metabolic syndrome (MetS). A population-based cross-sectional study was conducted including 100 healthy women and 99 polycystic ovary syndrome patients. The euglycemic–hyperinsulinemic clamp was performed. Circulating ADI levels were determined by ELISA. Polycystic ovary syndrome and polycystic ovary syndrome plus MetS subjects had higher products of fasting triglycerides and glucose (TyG), Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), increased ratios of the area under the curve for insulin/the area under the curve for glucose (AUCi/AUCg), but lower ADI index as compared with healthy subjects. Partial correlation analysis in all populations showed that the M-value was significantly negatively correlated with HOMA-IR, TyG, TG/HDL, and AUCi/AUCg, and correlated positively with the ADI index. The r value of Pearson correlation between the ADI index and M-value was greater than that of the correlation between HOMA-IR, TyG, TG/HDL-C, and AUCi/AUCg. The optimal cut-off value of the ADI index for detection of IR was 0.67, with a sensitivity of 89.4% and a specificity of 88.1%, whereas for detection of MetS, it was 0.32, with a sensitivity of 88.7% and a specificity of 71.0%. The ADI index may be a surrogate marker in detecting IR and MetS.
Multisensory interaction metaphors with haptics and proprioception in virtual environments

For several years, virtual environments (VEs) are promising applications to explore and manipulate 3D data and 3D worlds. Those environments are designed to be intuitive and easy to use, however, in practice no ideal solution has been proposed yet. Designers and researchers always have to make compromises due to the complexity of the human senses and technical and financial restrictions. It is widely accepted that multisensory metaphors dramatically can improve the user's performance when interaction in a VE. In this paper, we present a modelling application, for research purposes, called nVRment, which uses and combines several interaction metaphors. The aim of this application is to test in practice our newly proposed metaphors: the "Object In Hand" metaphor, which uses proprioception together with force feedback for manipulations and the "Small Scene Manipulation" which is suitable for manipulation of an object in its local context.
Computing Dynamic Slices of Object-Oriented Programs using Dependency Information

a days, object-oriented programs are becoming very popular amongst the developers and hence almost all software are designed using the object-oriented paradigm. Advanced features of object-oriented programming has made it complicated to understand, test, debug and maintain. To better manage these software, slicing techniques have been proved to be quite efficient. This paper proposed an algorithm for dynamic slicing of object-oriented software. It uses SDG(System Dependence Graph) and DG(Dynamic Graph) as the intermediate program representation while computing the dynamic slices. In this paper dynamic slicing algorithm is based on traversing through the outgoing control dependence edges and incoming data dependence edges of Dynamic Graph. The major advantage of the proposed algorithm is that the time required to compute the dynamic slice of the object- oriented programs is directly proportional to the number of dependencies (control and/or data) arising during the run time. Also the proposed algorithm depends on the numbers of nodes present in the intermediate program representation.
A Parallel Procedure for Dynamic Multi-objective TSP

This paper proposes a new parallel search procedure for dynamic multi-objective traveling salesman problem. We design a multi-objective TSP in a stochastic dynamic environment. The proposed procedure first uses parallel processors to identify the extreme solutions of the search space for each of k objectives individually at the same time. These solutions are merged into a matrix E. The solutions in E are then searched by parallel processors and evaluated for dominance relationship. The proposed procedure was implemented in two different ways: a master-worker architecture and a pipeline architecture.
Weighting of Mel Sub-bands Based on SNR/Entropy for Robust ASR

Mel-frequency cepstral coefficients (MFCC) are the most widely used features for speech recognition. However, MFCC-based speech recognition performance degrades in presence of additive noise. In this paper, we propose a set of noise-robust features based on conventional MFCC feature extraction method. Our proposed method consists of two steps. In the first step, mel sub-band Wiener filtering is carried out. The second step consists of estimating SNR in each sub-band and calculating the sub-band entropy by defining a weight parameter based on sub-band SNR to entropy ratio. The weighting has been carried out in a way that gives more important roles, in cepstrum parameter formation, to sub-bands that are less affected by noise. Experimental results indicate that this method leads to improved ASR performance in noisy environments. Furthermore, due to the simplicity of the implementation of our method, its computational overhead in comparison to MFCC is quite small.
The effect of overlying tissue on the spatial sensitivity profile of near-infrared spectroscopy.

The exact volume of brain tissue interrogated in near-infrared spectroscopy (NIRS) studies of cerebral oxygenation in unknown, the inhomogeneity of the head and resulting variation in optical paths making determination of the interrogated volume difficult. In this study, the spatial sensitivity profiles in simple two-component inhomogeneous cylindrical models are predicted by Monte Carlo simulation in order to reveal the effects of the overlying tissue on the volume of tissue interrogated by NIRS. The predictions are validated by experimental measurements on solid "tissue equivalent' cylindrical phantoms. The phantom diameter is 30 mm and the thickness of the outer layer is 2 mm. The optical properties of the inner cylinder match those of adult brain white matter (mu' s1 = 6.4 mm-1 and mu' a1 = 0.02 mm-1), but those of the outer layer are changed (mu' s0 from 1.7 to 8.3 mm-1 and mu' a0 from 0.002 to 0.1 mm-1). Results show that the spatial sensitivity profile is largely confined to the outer layer at small optode spacing (< 15 degrees) and to the inner layer at large spacing (> 120 degrees). At intermediate angles, the sensitivity profiles are sensitive to the optical properties of the outer layer. A low mu' s0 or mu' a0 moves the profile toward the surface, at high mu' a0 it moves in towards the inner layer and at high mu' a0 it is similar to the homogeneous case.
Amifostine alleviates radiation-induced lethal small bowel damage via promotion of 14-3-3σ-mediated nuclear p53 accumulation

Amifostine (AM) is a radioprotector that scavenges free radicals and is used in patients undergoing radiotherapy. p53 has long been implicated in cell cycle arrest for cellular repair after radiation exposure. We therefore investigated the protective p53-dependent mechanism of AM on small bowel damage after lethal whole-abdominal irradiation (WAI). AM increased both the survival rate of rats and crypt survival following lethal 18 Gy WAI. The p53 inhibitor PFT-α compromised AM-mediated effects when administered prior to AM administration. AM significantly increased clonogenic survival in IEC-6 cells expressing wild type p53 but not in p53 knockdown cells. AM significantly increased p53 nuclear accumulation and p53 tetramer expression before irradiation through the inhibition of p53 degradation. AM inhibited p53 interactions with MDM2 but enhanced p53 interactions with 14-3-3σ. Knockdown of 14-3-3σ also compromised the effect of AM on clonogenic survival and p53 nuclear accumulation in IEC-6 cells. For the first time, our data reveal that AM alleviates lethal small bowel damage through the induction of 14-3-3σ and subsequent accumulation of p53. Enhancement of the p53/14-3-3σ interaction results in p53 tetramerization in the nucleus that rescues lethal small bowel damage.
An Energy-Efficient Power Control Approach for IEEE 802.11n Wireless LANs

With large amount of energy consumed in wireless LAN (WLAN) system, it becomes an important and meaningful issue to reduce the energy consumption of wireless communication devices nowadays. Although different kinds of energy-saving strategies have been proposed to achieve this goal, few of them take the new features of the IEEE 802.11n standard into account. In this paper, we analyze the energy-saving problem from two relevant aspects: the energy-saving measurement criteria and the effect of the new features of the IEEE 802.11n standard. Based on the analysis, we propose an adaptive transmission power control mechanism (A-TPCM) to reduce the power consumption and improve the energy efficiency of 802.11n WLAN devices. We evaluate the performance of the A-TPCM in terms of multi-factors. Particularly, simulation results show that the A-TPCM can significantly decrease energy consumption of 802.11n WLAN devices in different conditions.
Enabling private and non-intrusive smartphone calls with LipTalk

The typical usage for phones is making calls. However, under certain scenarios, phone calls are inappropriate or intrusive when people are having a meeting, impractical when background noise level is too high or insecure under monitoring of other personals/parties. Typical solution to these problems is to send text-based messages. Yet, we argue that the most natural, efficient way for human-beings to communicate is via speech. In this work, we provide envision for our project, a non-intrusive, convenient and secure communication system. We utilize the front camera of smart phones, efficiency of cloud computing environment and state-of-the-art text-to-speech methods to create a robust visual speech recognition system to enable people to chat with lip movements. We present the current challenges, system architecture, initial findings and planned approaches to our problem.
Context-enhanced Adaptive Entity Linking

More and more knowledge bases are publicly available as linked data. Since these knowledge bases contain structured descriptions of real-world entities, they can be exploited by entity linking systems that anchor entity mentions from text to the most relevant resources describing those entities. In this paper, we investigate adaptation of the entity linking task using contextual knowledge. The key intuition is that entity linking can be customized depending on the textual content, as well as on the application that would make use of the extracted information. We present an adaptive approach that relies on contextual knowledge from text to enhance the performance of ADEL, a hybrid linguistic and graph-based entity linking system. We evaluate our approach on a domain-specific corpus consisting of annotated WikiNews articles.
ROSAT X–Ray Observations of the Radio Galaxy NGC 1316 (Fornax A)

We have observed NGC 1316 (Fornax A) with the ROSAT HRI. In this paper, we present the results of these observations and complement them with the spectral analysis of the archival PSPC data. The spectral properties suggest the presence of a significant component of thermal X-ray emission (greater than 60%), amounting to ~109 M☉ of hot interstellar matter (ISM). Within 3' from the nucleus of NGC 1316, the HRI X-ray surface brightness falls as r-2. In the inner ~40'', the X-ray surface brightness is significantly elongated (ϵ ~ 0.3). This flattened X-ray feature is confirmed by a straightforward statistics test as well as moment analysis. By comparing the morphology of the X-ray emission with the distribution of optical dust patches, we find that the X-ray emission is significantly reduced at the locations where the dust patches are more pronounced, indicating that at least some of the X-ray photons are absorbed by the cold ISM. We also compare the distribution of the hot and cold ISM with that of the ionized gas, using recently obtained Hα CCD data. We find that the ionized gas is distributed roughly along the dust patches and follows the large-scale X-ray distribution at r > 1' from the nucleus. However, there is no one-to-one correspondence between ionized gas and hot gas. Both morphological relations and kinematics suggest different origins for hot and cold ISM. The radio jets in projection appear to pass perpendicularly through the central X-ray ellipsoid. Comparison of thermal and radio pressures suggests that the radio jets are confined by the surrounding hot gaseous medium.
Structural Features in XML Retrieval

The structure of documents provides a new source of information that retrieval systems may exploit to improve their search effectiveness. This seminar summarizes the main ideas and results of our research, which investigates the use of several structural features -markup and (derived) metadata -for effective XML retrieval. Our retrieval framework is based on the principle of polyrepresentation (Ingwersen,1994) and makes use of the available evidence collected from documents, queries, and contextual features to rank components of XML documents. We will present our approaches on three main topics: (1) new retrieval strategies that use structural information, (2) the use of relevance feedback techniques to refine the structural information given a user need, and (3) the study of the relationships between user search tasks and contextual factors and the structural characteristics of the relevant information. We evaluate these approaches using the INEX benchmark and show that structural information can be further exploited to improve retrieval effectiveness.
New types of faults detection and diagnosis using a mixed soft & hard clustering framework

In general, one limitation in current diagnosis approaches is that they could only detect the existing types of faults, while not be able to detect new types of faults. It is difficult to know in advance all fault types and new types of faults may occur in industry. As such, effective detection and diagnosis on new types of faults are important. In this paper, a novel mixed soft&hard assignment clustering framework will be proposed to detect and diagnose new types of faults based on the feature signals. As a popular soft assignment strategy, Gaussian mixture model targets to diagnose existing types from training and detect new category. Next, the hard assignment strategy based on the Euclidean distance of K-means is used to further classify the fault details if the new category is detected. Effectiveness of the proposed framework is testified on a partial discharge measurement dataset of different high voltage electronic and power equipment in industry. It is able to achieve as good performance as benchmark approaches for conventional diagnosis without new fault category, while it also effectively detects and classifies new types of faults with average accuracy of 75.0%.
The Interchange of ( Meta ) Models between MetaEdit + and Eclipse EMF Using M 3-Level-Based Bridges

Nowadays there are powerful tools for Domain-Specific Modeling. An ongoing problem is the insufficient tool interoperability which complicates the development of complete tool chains or the re-use of existing metamodels, models, and model operations. In this paper we present the approach of M3-Level-Based Bridges and apply this approach to enable the interoperability between two selected tools. The first tool is MetaEdit+ with strengths in (meta)modeling and the second tool is the Eclipse Modeling Framework with advantages in model processing by transformation and generation tools. General Terms Model-Driven Engineering, Metametamodel, Domain-Specific Language, Interoperability
Parsing Strategies for the Integration of Two Stochastic Context-Free Grammars

Integration of two stochastic context-free grammars can be useful in two pass approaches used, for example, in speech recognition and understanding. Based on an algorithm proposed by [Nederhof and Satta, 2002] for the non-probabilistic case, left-to-right strategies for the search for the best solution based on CKY and Earley parsers are discussed. The restriction that one of the two grammars must be non recursive does not represent a problem in the considered applications.
The effects of vardenafil and pentoxifylline administration in an animal model of ischemic colitis

OBJECTIVES: Vardenafil enhances dilatation of vascular smooth muscle and inhibits platelet aggregation. The purpose of this study was to evaluate the clinical effects of vardenafil and pentoxifylline administration in an experimental model of ischemic colitis. METHODS: Forty female Wistar albino rats weighing 250–300 g were randomized into five experimental groups (each with n = 8) as follows:1) a sham group subjected to a sham surgical procedure and administered only tap water; 2) a control group subjected to a standardized surgical procedure to induce ischemic colitis and administered only tap water; 3) and 4) treatment groups subjected to surgical induction of ischemic colitis followed by the postoperative administration of 5 mg/kg or 10 mg/kg vardenafil, respectively; and 5) a treatment group subjected to surgical induction of ischemic colitis followed by postoperative administration of pentoxifylline at 50 mg/kg/day per day as a single dose for a 3-day period. All animals were sacrificed at 72 h post-surgery and subjected to relaparotomy. We scored the macroscopically visible damage, measured the ischemic area and scored histopathology to determine the severity of ischemia. Tissue malondialdehyde levels were also quantified. RESULTS: The mean Gomella ischemic areas were 63.3 mm2 in the control group; 3.4 and 9.6 mm2 in the vardenafil 5 and vardenafil 10 groups, respectively; and 3.4 mm2 in the pentoxifylline group (p = 0.0001). The mean malondialdehyde values were 63.7 nmol/g in the control group; 25.3 and 25.6 nmol/g in the vardenafil 5 and vardenafil 10 groups, respectively; and 22.8 nmol/g in the pentoxifylline group (p = 0.0001). CONCLUSION: Our findings indicate that vardenafil and pentoxifylline are effective treatment options in an animal model of ischemic colitis. The positive clinical effects produced by these drugs are likely due to their influence on the hemodynamics associated with vascular smooth muscle and platelet functions.
Brain Neurotransmitters, Cognitive Control, and Resting Heart Rate Variability (rHRV) in the MRI Environment

Determining reliable measures that show how the brain can regulate the body and its physiological states could offer insight into how mental health and wellbeing is related to physiology and self-regulation. This study investigates how heart rate variability (HRV) at rest (rHRV), a measure of autonomic nervous system activity according to several studies (Thayer 2009, Colzato 2017, Shaffer & Ginsberg, 2017), relates to neurotransmitter levels in the prefrontal cortex (PFC), cognitive control over emotional material, and individual traits involved in psychopathology. Across two time points, the study in which this project is embedded takes a multi-perspective approach including brain neurotransmitters, Gamma Aminobutyric Acid (GABA), the main inhibitory neurotransmitter in the central nervous system (CNS), and glutamate, the main excitatory neurotransmitter in the CNS, to neurocircuits and anatomy, to behavior, to self-report about mental states and daily functioning. Resting heart rate (HR) measures were taken via pulse rate measurements in an MRI scanner, and processed into rHRV. Prior research has suggested that increased heart rate variability is associated with a) better emotional regulation and b) individual differences in GABAergic function. We investigated these relationships in a novel manner by examining whether GABAergic function of the prefrontal cortex, which is known to be involved in emotion regulation, is associated with rHRV. To do so rHRV of 21 adult subjects was correlated to levels of GABA in dorsolateral PFC (DLPFC) and ventrolateral PFC (VLPFC) taken from 20 to 24 months prior to the rHRV measurement. In addition, rHRV of adults and children was also associated with their scores on the Emotional Regulation Questionnaire (ERQ) which measures cognitive control of emotional states (Gross, J.J., & John, O.P. 2003). rHRV was additionally associated with psychopathology factors processed from the Mood and Anxiety Symptom Questionnaire (MASQ) and Brain Neurotransmitters, Cognitive Control, and rHRV in the MRI Environment 2 Pennsylvania State Worry Questionnaire (PSWQ), of Anxious Apprehension, Low Positive Affect, Worry and Common Internalizing factors (Watson et al., 1995, Zhong et al., 2009). Data was then analyzed to examine relationships between neurotransmitters, rHRV, cognitive emotional control, and psychopathology. No significant correlations were found between rHRV and any of the main measures: prefrontal GABA concentration, emotional regulation or measures related to psychopathology. Potential reasons for these null findings include a) that the GABA concentrations were obtained 20-24 months earlier, b) that the method used to assess rHRV is not as robust as standard measures which are difficult to implement in the magnet, c) the size of our current sample is small and hence may be underpowered to detect such relationships.