Miracle-dz/UniFAR-FTUs huggingface dataset:
Posttraumatic Growth in Non-Hispanic White and Hispanic Women with Cervical Cancer

ABSTRACT This study examined posttraumatic growth (PTG) in Non-Hispanic White (NHW; n = 132) and Hispanic (HISP; n = 51) women who had been diagnosed with cervical cancer. Participants completed measures of PTG, spirituality, optimism, stage of cancer, and demographics variables. The results showed that women with cervical cancer reported PTG but at lower levels than in studies of women with breast cancer. Greater spirituality and more advanced cancer stage predicted more PTG, but optimism did not predict PTG. HISP women reported higher levels of PTG than NHW women, and greater spirituality in the HISP women partially accounted for the difference.
Performance Modeling of Distributed Deep Neural Networks

During the past decade, machine learning has become extremely popular and can be found in many aspects of our every day life. Nowayadays with explosion of data while rapid growth of computation capacity, Distributed Deep Neural Networks (DDNNs) which can improve their performance linearly with more computation resources, have become hot and trending. However, there has not been an in depth study of the performance of these systems, and how well they scale. In this paper we analyze CNTK, one of the most commonly used DDNNs, by first building a performance model and then evaluating the system two settings: a small cluster with all nodes in a single rack connected to a top of rack switch, and in large scale using Blue Waters with arbitary placement of nodes. Our main focus was the scalability of the system with respect to adding more nodes. Based on our results, this system has an excessive initialization overhead because of poor I/O utilization which dominates the whole execution time. Because of this, the system does not scale beyond a few nodes (4 in Blue Waters). Additionally, due to a single server-multiple worker design the server becomes a bottleneck after 16 nodes limiting the scalability of the CNTK.
Effect of Exposure to Atmospheric Ultrafine Particles on Production of Free Fatty Acids and Lipid Metabolites in the Mouse Small Intestine

Background: Exposure to ambient ultrafine particulate matter (UFP) is a well-recognized risk factor for cardiovascular and respiratory diseases. However, little is known about the effects of air pollution on gastrointestinal disorders. Objective: We sought to assess whether exposure to ambient UFP (diameter < 180 nm) increased free fatty acids and lipid metabolites in the mouse small intestine. Methods: Ldlr-null mice were exposed to filtered air (FA) or UFP collected at an urban Los Angeles, California, site that was heavily affected by vehicular emissions; the exposure was carried out for 10 weeks in the presence or absence of D-4F, an apolipoprotein A-I mimetic peptide with antioxidant and anti-inflammation properties on a high-fat or normal chow diet. Results: Compared with FA, exposure to UFP significantly increased intestinal hydroxyeicosatetraenoic acids (HETEs), including 15-HETE, 12-HETE, 5-HETE, as well as hydroxyoctadecadienoic acids (HODEs), including 13-HODE and 9-HODE. Arachidonic acid (AA) and prostaglandin D2 (PGD2) as well as some of the lysophosphatidic acids (LPA) in the small intestine were also increased in response to UFP exposure. Administration of D-4F significantly reduced UFP-mediated increase in HETEs, HODEs, AA, PGD2, and LPA. Although exposure to UFP further led to shortened villus length accompanied by prominent macrophage and neutrophil infiltration into the intestinal villi, administration of D-4F mitigated macrophage infiltration. Conclusions: Exposure to UFP promotes lipid metabolism, villus shortening, and inflammatory responses in mouse small intestine, whereas administration of D-4F attenuated these effects. Our findings provide a basis to further assess the mechanisms underlying UFP-mediated lipid metabolism in the digestive system with clinical relevance to gut homeostasis and diseases. Citation: Li R, Navab K, Hough G, Daher N, Zhang M, Mittelstein D, Lee K, Pakbin P, Saffari A, Bhetraratana M, Sulaiman D, Beebe T, Wu L, Jen N, Wine E, Tseng CH, Araujo JA, Fogelman A, Sioutas C, Navab M, Hsiai TK. 2015. Effect of exposure to atmospheric ultrafine particles on production of free fatty acids and lipid metabolites in the mouse small intestine. Environ Health Perspect 123:34–41; http://dx.doi. org/10.1289/ehp.1307036
BEAM-BASED FEEDBACK FOR THE NLC LINAC *

The NLC linac train-by-train feedback system is designed to stabilize the beam trajectory, but is also a valuable element in the strategy for emittance preservation. New simulations employ improved strategies [1], allowing beam steering to be performed significantly less often than without the feedback system. Additional simulations indicate that the linac feedback can contribute towards successful operation at noisier sites.
Factors affecting transfer of training in Thailand

To begin the validation process for the Learning Transfer System Inventory (LTSI) in Thailand, research replicating Holton, Bates, and Ruona's study (2000) was conducted in Thailand. The LTSI was administered to 1,029 employees. Exploratory factor analysis and MANOVA were used to identify factors. A factor structure almost identical to that of Holton and colleagues was identified. Perceived content validity of the training was identified as the most important factor. Organization type created the greatest number of differences among variables tested.
Whole‐genome array‐CGH identifies novel contiguous gene deletions and duplications associated with developmental delay, mental retardation, and dysmorphic features

Cytogenetic imbalances are the most frequently identified cause of developmental delay or mental retardation, which affect 1–3% of children and are often seen in conjunction with growth retardation, dysmorphic features, and various congenital anomalies. A substantial number of patients with developmental delay or mental retardation are predicted to have cytogenetic imbalances, but conventional methods for identifying these imbalances yield positive results in only a small fraction of these patients. We used microarray‐based comparative genomic hybridization (aCGH) to study a panel of 20 patients predicted to have chromosomal aberrations based on clinical presentation of developmental delay or mental retardation, growth delay, dysmorphic features, and/or congenital anomalies. Previous G‐banded karyotypes and fluorescence in situ hybridization results were normal for all of these patients. Using both oligonucleotide‐based and bacterial artificial chromosome (BAC)‐based arrays on the same panel of patients, we identified 10 unique deletions and duplications ranging in size from 280 kb to 8.3 Mb. The whole‐genome oligonucleotide arrays identified nearly twice as many imbalances as did the lower‐resolution whole‐genome BAC arrays. This has implications for using aCGH in a clinical setting. Analysis of parental DNA samples indicated that most of the imbalances had occurred de novo. Moreover, seven of the 10 imbalances represented novel disorders, adding to an increasing number of conditions caused by large‐scale deletions or duplications. These results underscore the strength of high‐resolution genomic arrays in diagnosing cases of unknown genetic etiology and suggest that contiguous genomic alterations are the underlying pathogenic cause of a significant number of cases of developmental delay. © 2007 Wiley‐Liss, Inc.
Recurrent neural control for rollover prevention on heavy vehicles

An active control system is developed to prevent rollover in heavy vehicles. A high order recurrent neural network is used to model the unknown tractor semitrailer system; a learning law is obtained using the Lyapunov methodology. Then a control law, which stabilizes the reference tracking error dynamics, is developed using control Lyapunov functions. The control scheme is applied to the speed and speed-yaw rate trajectory tracking in a tractor-semitrailer during a cornering situation.
Evaluating I/O Scheduler in Virtual Machines for Mapreduce Application

This paper explores the relationship between I/O scheduling in a virtual machine monitor (VMM) and performance of Map Reduce applications running on the virtual machines (VMs). Traditionally, Map Reduce applications running on the virtual machines perform worse than on the physical machines due to competing for I/O. In this paper, we discuss the effect of I/O scheduling on performance of Map Reduce running on VMs. We present two strategies to improve the I/O scheduling and evaluate the performance through experiments. The results show that the strategies could reduce the percentage of I/O waiting and time consuming of Map Reduce applications effectively.
Hazardous drinking in elite New Zealand sportspeople.

AIMS To examine the link between hazardous drinking and level of sport participation in New Zealand. METHODS Sports science and general university students (n = 427) completed a sporting profile questionnaire that included the Alcohol Use Disorders Identification Test (AUDIT). RESULTS Elite sportspeople (both provincial and international/country level) reported higher rates of hazardous drinking than non-sportspeople and non-elite sportspeople. Similar differences were observed in AUDIT subscale scores, with international/country level sportspeople reporting greater symptoms of dependence than other groups.
ENERGY EFFICIENT DYNAMIC ADAPTIVE SELF-CONFIGURABLE NETWORK PROCESSOR 1

In the current generation of network technology, the performance penalties are very severe due to poor resource allocation, especially when the traffic mix is non-uniform. Network processors, one of the recent popular network devices, inspite of their immense computing power and abundant resources, are being underutilized, especially in common applications. This paper explores the concept of self-configurable environment for the Intel IXP 2400 Network Processor (NP), which would dynamically reconfigure its resources/services based on the traffic flow. The objective of this paper is to transform the IXP2400 NP into a self-configurable environment. Microengines (MEs) are the more power hungry components of NP and IXP2400 NP consists of eight micro-engines (MEs) for packet processing. Our method involved the optimization of the usage of MEs based on network fluctuations and reduction of energy consumption by NP. The control plane constantly monitored the traffic arrival rate in the system and based on the workload, the MEs were switched on/off without any packet loss. We employed enhanced NePSim2.0 (e-NePSim) to estimate the power consumption of IXP2400 NP. Finally, our method could bring about an overall power consumption of up to 25-28% without affecting the performance of the system.
Non-rigid 3D shape retrieval using Multidimensional Scaling and Bag-of-Features

Matching non-rigid shapes is a challenging research field in content-based 3D object retrieval. In this paper, we present an image-based method to effectively address this problem. Multidimensional Scaling (MDS) and Principal Component Analysis (PCA) are first applied to each object to calculate its canonical form, which is afterward represented by 66 depth-buffer images captured on the vertices of an unit geodesic sphere. Then, each image is described as a word histogram obtained by the vector quantization of the image's salient local features. Finally, a multi-view shape matching scheme is carried out to measure the dissimilarity between two models. Experimental results on the McGill Articulated Shape Benchmark database demonstrate that, our method obtains better retrieval performance compared to the state-of-the-art.
Anomaly Detection and Characterization in Spatial Time Series Data: A Cluster-Centric Approach

Anomaly detection in spatial time series (spatiotemporal data) is a challenging problem with numerous potential applications. A comprehensive anomaly detection approach not only should be able to detect and identify the emerging anomalies but has to characterize the essence of these anomalies by visualizing the structures revealed within data in a way that is understandable to the end-user as well. In this paper, we consider fuzzy c-means (FCM) as a conceptual and algorithmic setting to deal with the problem of anomaly detection. Using a sliding window, the time series are divided into a number of subsequences, and the available spatiotemporal structure within each time window is discovered using the FCM method. In the sequel, an anomaly score is assigned to each cluster, and using a fuzzy relation formed between revealed structures, a propagation of anomalies occurring in consecutive time intervals is visualized. To illustrate the proposed method, several datasets (synthetic data, a simulated disease outbreak scenario, and Alberta temperature data) have been investigated.
The Effects of Metabolic Syndrome on TpTe Interval and TpTe/QT Ratio in Patients with Normal Coronary Arteries.

OBJECTIVE T wave peak to T wave end (TpTe) interval and TpTe/QT have been accepted as predictors of ventricular arrythmia. In this study our aim is to investigate the effect of metabolic syndome on these parameters in patients with angiographically normal coronary arteries. MATERIALS AND METHODS Thirty patients with metabolic syndrome (4 male, mean age 52±7.8 years) and twenty patients without metabolic syndrome as control group (8 male, mean age 54±9.3 years) were included. TpTe interval and TpTe/QT ratio were measured from the 12-lead electrocardiogram. These parameters were compared between the groups. RESULTS When compared with to the control group the systolic and diastolic blood pressure, pulse pressure, waist circumference, triglyceride and fasting plasma glucose levels were higher and HDL cholesterol level was lower in the metabolic syndrome group. In the analysis of electrocardiography, QT dispersion (QTd) and corrected QTd were significantly increased in metabolic syndrome group as compared to the controls group (44±14 versus 30±12 ms and 433±10 versus 405±4 ms, all p value p=0.01). TpTe interval and TpTe/QT ratio were also significantly higher in patient with metabolic syndrome (112±10 versus 91±10 ms and 0.25±0.02 versus 0.22±0.01, all p value p=0.01). CONCLUSION According to these results, we supposed that TpTe/QT ratio and TpTe interval is prolonged and those patients with metabolic syndrome may be at greater risk of ventricular arrhythmias.
Characterization of multijoint finger stiffness: dependence on finger posture and force direction

The two-dimensional static stiffness of the index finger was measured with the interphalangeal joints in flexed and extended postures. The stiffness of the relaxed finger was compared with the stiffness when voluntary force was exerted in different directions. The finger stiffness was found to be anisotropic, with the direction of greatest stiffness being approximately parallel to the proximal phalange of the finger. This direction was relatively unaffected by finger posture or direction of finger force. Finger stiffness was more anisotropic when the interphalangeal joints were extended than flexed. The stiffness was most anisotropic when the interphalangeal joints were extended and force was being exerted in the direction of pointing, while it was least anisotropic when the interphalangeal joints were flexed and force was being exerted in directions normally associated with pinching and tapping actions. The stiffness of the individual finger joints was computed and the relation between stiffness and joint torque was examined. Previous studies, which examined single finger joints in isolation, had found that joint stiffness varied in a linear fashion with net joint torque. In contrast, the authors did not find a monotonic relation between joint stiffness and net joint torque, which they attributed to the need to vary the amount of cocontraction of antagonistic muscles when controlling the direction of finger force.
Hydrodynamics in a Liquid Solid Circulating Fluidized Bed–A Review

Liquid solid circulating fluidised bed and its performance at various operating conditions have been critically reviewed and reported. Hydrodynamic includes pressure drop across the bed, phase hold up distribution, flow regime, flow structure of each phase and solid circulation rate. Detailed analysis of axial and radial solid distributions, average solid holdup, solid circulation rate, critical transitional velocity for solid at different densities and fluids at varying viscosities was reported. The effect of the increase in liquid viscosity during heat and mass transfer phenomena in LSCFB has to be studied extensively as the industrial processing fluids are highly viscous.
Stress-Induced Changes in Executive Control Are Associated With Depression Symptoms

Deficits in executive control may underlie an inability to effectively respond to stressors, which has been linked to depression symptoms. Previous studies, however, have almost exclusively focused on trait executive control and have not assessed individual differences in changes in executive control when facing acute stressors. The current study examined whether changes in executive control when under stress are related to depression symptoms and whether this relation is moderated by brooding, a subtype of rumination. Ninety-two undergraduate students completed an n-back task before and immediately following a stress induction. As predicted, changes in n-back performance following the stress induction were related to depression symptoms and this relation was moderated by trait brooding. These results suggest that future studies examining the role of executive control in depression should measure executive control under conditions of stress as this may tap into a construct that is distinct from trait measures of executive control.
Unified Real-Time Tracking and Recognition with Rotation-Invariant Fast Features

We present a method that unifies tracking and video content recognition with applications to Mobile Augmented Reality (MAR). We introduce the Radial Gradient Transform (RGT) and an approximate RGT, yielding the Rotation-Invariant, Fast Feature (RIFF) descriptor. We demonstrate that RIFF is fast enough for real-time tracking, while robust enough for large scale retrieval tasks. At 26× the speed, our tracking-scheme obtains a more accurate global affine motionmodel than the Kanade Lucas Tomasi (KLT) tracker. The same descriptors can achieve 94% retrieval accuracy from a database of 104 images.
Tools and methodologies for annotating syntax and named entities in the National Corpus of Polish

The on-going project aiming at the creation of the National Corpus of Polish assumes several levels of linguistic annotation. We present the technical environment and methodological background developed for the three upper annotation levels: the level of syntactic words and groups, and the level of named entities. We show how knowledge-based platforms Spejd and Sprout are used for the automatic pre-annotation of the corpus, and we discuss some particular problems faced during the elaboration of the syntactic grammar, which contains over 800 rules and is one of the largest chunking grammars for Polish. We also show how the tree editor TrEd has been customized for manual post-editing of annotations, and for further revision of discrepancies. Our XML format converters and customized archiving repository ensure the automatic data flow and efficient corpus file management. We believe that this environment or substantial parts of it can be reused in or adapted for other corpus annotation tasks.
MegaMol—A Prototyping Framework for Particle-Based Visualization

Visualization applications nowadays not only face increasingly larger datasets, but have to solve increasingly complex research questions. They often require more than a single algorithm and consequently a software solution will exceed the possibilities of simple research prototypes. Well-established systems intended for such complex visual analysis purposes have usually been designed for classical, mesh-based graphics approaches. For particle-based data, however, existing visualization frameworks are too generic - e.g. lacking possibilities for consistent low-level GPU optimization for high-performance graphics - and at the same time are too limited - e.g. by enforcing the use of structures suboptimal for some computations. Thus, we developed the system softwareMegaMol for visualization research on particle-based data. On the one hand, flexible data structures and functional module design allow for easy adaption to changing research questions, e.g. studying vapors in thermodynamics, solid material in physics, or complex functional macromolecules like proteins in biochemistry. Therefore, MegaMol is designed as a development framework. On the other hand, common functionality for data handling and advanced rendering implementations are available and beneficial for all applications. We present several case studies of work implemented using our system as well as a comparison to other freely available or open source systems.
Achieving long-term operation with a capacitor-driven energy storage and sharing network

Energy is the most precious resource in sensor networks. The ability to move energy around makes it feasible to build distributed energy storage systems that can robustly extend the lifetime of networked sensor systems. eShare supports the concept of energy sharing among multiple embedded sensor devices by providing designs for energy routers (i.e., energy storage and routing devices) and related energy access and network protocols. In a nutshell, energy routers exchange energy sharing control information using their data network while sharing energy freely among connected embedded sensor devices using their energy network. To improve sharing efficiency subject to energy leakage, we develop an effective energy charging and discharging mechanism using an array of ultra-capacitors as the main component of an energy router. We extensively evaluate our system under seven real-world settings. Results indicate our charging and discharging control can effectively minimize the energy leaked away. Moreover, the energy sharing protocol can quantitatively share 113J energy with 96.82% accuracy in less than 2 seconds.
Hotel stay scenarios based on emotional design research

This paper elaborates on an emotion-oriented qualitative research project that aims at discovering design opportunities for enhancing hotel stay experiences of female business travelers. Photo elicitation and in-depth interviews are used as the key methods in studying emotions during hotel stays. To generate insights relevant to emotional design and experience design for hotels, data analysis methods based on appraisal theory in psychology and systematic coding are used. Research findings are presented by three main categories: emotions, triggers, and guest concerns. Two scenarios of optimal hotel stay experiences are also presented. These scenarios are character-rich storylines developed based on the research findings and depict hotel features that evoke pleasant emotions during four stages of hotel stay experiences: (1) Arrival, (2) room entry, (3) settling down and (4) return in the evening.
Active Perception at the Architecture Level

BDI agents rely on a set of beliefs, while looping in an action-perception cycle. The set of beliefs contains, among other things, the agent's beliefs about the world. These are the end result of a perception process which uses sensors and computation power in order to receive, fuse, filter and process information about the environment, to acquire new beliefs, and revise existing ones. Ketenci et al. [4] and So et al. [9] describe two principled types of perception generating these beliefs. A top-down process, known also as active perception, is ideally controlled by the goal-oriented reasoning process, enables the agent to turn its perception|by taking actions|to the most relevant aspects of the environment according to its task. A bottom-up process known also as passive perception ideally originates from the sensors, allowing goal-independent, and opportunistic perception.