Miracle-dz/UniFAR-FTUs huggingface dataset:
PRINCIPLES OF INNER WORK: PSYCHOLOGICAL AND SPIRITUAL*

As a psychotherapist and a practitioner of a spiritual path, I am continually faced with questions about the interface between psychological work and spiritual work in my own experience, as well as with clients, students, and friends. So I would like to share with you some questions and some directions that have come to me in exploring what is involved in inner work, the process of growing beyond limited views of self toward a greater vision and realization of what it is to be human.
An Object-driven Online Segmentation System for Mobile Robots

In this paper we propose an object-driven online segmentation system for mobile robots. Among existing tracking and segmentation methods, the methods themselves are highly emphasized while properties of objects are usually not exploited enough. We propose an adaptive selection mechanism based on the properties of the objects to automatically choose an optimal tracking algorithm. For textured objects, a tracking algorithm which combines Lucas-Kanade tracker and model based detector using Random Forests classifier is adopted; for uniform objects, a color based tracker with a smooth constraint enforcement is used to ensure a robust performance. Moreover, a two-step object segmentation using Gaussian Mixture Models and graph cuts is applied to obtain detailed shape information. The experimental results on a variety of objects show the effectiveness of the adaptive tracking selection mechanism. The system also yields very promising performance in very challenging conditions with occlusions, illumination changes as well as cluttered background.
Users Know Better: A QoE Based Adaptive Control System for VoD in the Cloud

As VoD systems migrate to the Cloud, new challenges emerge in managing user Quality-of- Experience (QoE). The complexity of the cloud system due to virtualization and resource sharing complicates the QoE management. Operational failures in the Cloud could be challenging for QoE as well. We believe that end users have the best perception of system performance in terms of their QoE. We propose a QoE based adaptive control system for VoD in the Cloud. The system learns server performance from the user QoE and then adaptively selects servers for users accordingly. We deploy our proposed system in Google Cloud and evaluate it with hundreds of clients deployed all over the world. Results show that given the same amount of resources, our system provides 9% to 30% more users with QoE above the Mean Opinion Score (MOS) "good" level than the existing measurement based server selection systems. The system guarantees a better QoE (above 6% better) for 90% users. Additionally, our system discovers operational failures by monitoring QoE and prevents streaming session crashes. A computational overhead analysis shows that our system can easily scale to large VoD systems containing thousands of servers.
Adjunctive therapies to reduce thrombotic events in patients with a history of myocardial infarction: role of vorapaxar

Acute myocardial infarction (AMI) is generally attributed to coronary atherothrombotic disease. Platelet activation is essential for thrombus formation and is thus an important target for pharmacological intervention to prevent and treat AMI. Despite contemporary treatment with dual antiplatelet therapy, including acetylsalicylic acid and adenosine diphosphate receptor antagonists, patients with prior AMI remain at increased risk of future thrombotic events. This has stimulated the search for more potent antithrombotic agents. Among these is the oral protease-activated receptor-1 antagonist vorapaxar, which represents a new oral antiplatelet agent to reduce thrombotic risk in patients with atherothrombotic disease. The TRACER and the TRA 2°P-TIMI 50 trials concluded that vorapaxar in addition to standard therapy reduced ischemic adverse cardiac events. A remarkable benefit was observed in patients with stable atherosclerotic disease, particularly those with a previous history of AMI. Although favorable effects were seen in reduction of adverse cardiac events, this was associated with excess major and intracranial bleeding, particularly in patients at high risk of bleeding and those with a history of stroke or transient ischemic attack. Currently, the lack of a reliable individualized risk stratification tool to assess patients for thrombotic and bleeding tendencies in order to identify those who might gain most net clinical benefit has led to limited use of vorapaxar in clinical practice. Vorapaxar may find a niche as an adjunct to standard care in patients at high risk of thrombotic events and who are at low risk of bleeding.
Predicting microarchitectural power using Interval Based Hierarchical Support Vector Machine

Microarchitectural design involves exploring an exponentially large design space in order to determine an optimal configuration for a number of hardware parameters. Determining a particular combination of these parameters which lead to low power consumption can be daunting. New configurations must be tested on software simulators using benchmark programs which typically take a considerable amount of time to run. In this paper we present Interval Based Hierarchical Support Vector Machine (IBH-SVM) for identifying optimal power aware combinations of microarchitectural parameters from this exponentially large design space. The advantage of this formulation is twofold in that it accurately and efficiently finds power aware configurations while considerably decreasing the number of software benchmark simulations needed to select the most appropriate configurations. The reduction in power is not only in terms of the savings on future applications run on these processors, but also on the testing time required during the design phase since suboptimal configurations are ignored early on.
Thigh strength and activation as predictors of knee biomechanics during a drop jump task.

PURPOSE To examine whether normalized quadriceps and hamstring strength would predict quadriceps and hamstring muscle activation amplitudes and whether these neuromuscular factors would predict knee kinematics and kinetics during a drop jump task. METHODS Thirty-nine females and 39 males were measured for isometric quadriceps and hamstring strength and were instrumented to obtain surface electromyography, kinematic, and kinetic measures during the initial landing of a drop jump. Multiple linear regressions first examined the relationship between thigh strength and activation then examined whether these neuromuscular variables were predictive of hip and knee flexion excursions, knee extensor moments (KEM), and anterior knee shear forces during the deceleration phase of the drop jump. RESULTS Females versus males produced lower normalized thigh strength and demonstrated greater quadriceps and hamstring activation amplitudes during the drop jump. Lower thigh muscle strength was a weak (males) to moderate (females) predictor of greater quadriceps activation amplitudes. However, thigh strength and activation were poor predictors of hip and knee joint excursions and KEM. Regardless of sex and thigh strength, anterior shear forces were greater in individuals who demonstrated less hip flexion and greater knee flexion excursions and greater peak quadriceps activation and internal KEM during the landing. CONCLUSIONS Although thigh muscle strength explained some of the variance in quadriceps and hamstring activation levels as measured with surface electromyography, we failed to support the hypothesis that these neuromuscular factors are strong predictors of sagittal plane hip and knee flexion excursions or KEM. Although greater quadriceps activation amplitude was a significant predictor of greater anterior tibial shear forces, its contribution was relatively small compared with kinematic and kinetic variables.
Quantization effects on Compressed Sensing Video

Compressed Video Sensing (CVS) is the application of the theory and principles of Compressed Sensing to video coding. Previous research has largely ignored the effects of quantization on the random measurements. In this paper, we showed that Gaussian quantization of the CVS coefficients produce higher quality reconstructed videos compared to using MPEG and uniform quantization. Furthermore, the quantization matrix is robust against variations in the mean and standard deviations of the CS measurements among frames. Our work shows how quantization can be implemented for a practical CVS codec.
Semiconductor Laser Diode Model Implementation Including Optical Back-Reflection

Fabry Perot (FP) and distributed feedback (DFB) laser diode rate equations were augmented to model optical back-reflections. The proposed laser model was implemented and used in simulations to determine the effect of reflected optical power on the performance of directly modulated FP and DFB laser diodes for modulation frequencies spanning near-DC to 10 GHz. The relationship between optical feedback and the laser threshold current and the laser linearity are examined and presented with supporting measurements
Information Extraction across Linguistic Barriers

Information extraction (IE) systems have been tailored to extract fixed target information from documents in a fixed language. In order to be truly useful for information analysts, the target information must be user-definable and the source documents should cover multiple languages. We will map out the path toward such open-target multilingual IE systems, identifying necessary technological breakthroughs along the path. We also discuss a Japanese-English named entity extraction system under development, which represents a case of the next step along the path.
A note on ENDOG: a computer program for analysing pedigree information.

The aim of this note is to describe the program ENDOG (v.3.0). The program handles pedigree information to conduct several demographic and genetic analyses including: (a) the individual inbreeding and average relatedness coefficients; (b) effective population size; (c) parameters characterizing the concentration of both gene and individuals origin such as the effective number of founders and ancestors, the effective number of founder herds; (d) F statistics and paired genetic distances for each subpopulation under study; (e) descriptors of the genetic importance of the herds in a population and (f) generation intervals. The program will help breeders and researchers to monitor the changes in genetic variability and population structure with limited costs of preparing datasets. The program, user's guide and example file can be down-loaded free of charge from the World Wide Web at http://www.ucm. es/ info/prodanim/Endog30.zip.
An overview of the mesa processor architecture

This paper provides an overview of the architecture of the Mesa processor, an architecture which was designed to support the Mesa programming system [4]. Mesa is a high level systems programming language and associated tools designed to support the development of large information processing applications (on the order of one million source lines). Since the start of development in 1971, the processor architecture, the programming language, and the operating system have been designed as a unit, so that proper tradeoffs among these components could be made.
Isolation and characterization of a myo-inositol-1-phosphate synthase gene from yellow passion fruit (Passiflora edulis f. flavicarpa) expressed during seed development and environmental stress.

BACKGROUND AND AIMS Myo-inositol-1l-phosphate synthase (MIPS) catalyses the conversion of d-glucose 6-phosphate to 1-l-myo-inositol-1-phosphate, the first and rate-limiting step in the biosynthesis of all inositol-containing compounds. Inositol phospholipids play a vital role in membrane trafficking and signalling pathways, auxin storage and transport, phytic acid biosynthesis, cell wall biosynthesis and production of stress-related molecules. In the present study, an MIPS cDNA from developing Passiflora edulis f. flavicarpa seeds was characterized and an investigation made into its spatial and differential expression, as well as changes in its transcription during exposure of growing plants to cold and heat stresses. METHODS The MIPS-encoding gene was isolated by polymerase chain reaction (PCR) methods, and transcript levels were examined using semi-quantitative reverse transcription-PCR (RT-PCR) during seed development and in response to heat and cold stress. In addition, the copy number of the cloned PeMIPS1 gene in the genome of Passiflora edulis, P. eichleriana, P. caerulea, P. nitida and P. coccinea was determined by Southern blot analyses. KEY RESULTS A full-length cDNA clone of the PeMIPS1 from P. edulis was isolated and characterized. Southern blot analyses indicated that the genomic DNA might have diverse sequences of MIPS-encoding genes and one copy of the cloned PeMIPS1 gene in the genomes of P. edulis, P. eichleriana, P. caerulea, P. nitida and P. coccinea. RT-PCR expression analyses revealed the presence of PeMIPS1 transcripts in ovules, pollen grains and leaves, and during the seed developmental stages, where it peaked at 9 d after pollination. The PeMIPS1 gene is differentially regulated under cold and heat stress, presenting a light-responsive transcription. CONCLUSIONS Experimental data suggest that PeMIPS1 transcription plays an important role in the establishment of developmental programmes and during the response of plants to environmental changes. The PeMIPS1 is differentially transcribed during cold and heat stress, presenting a light response pattern, suggesting that it is important for environmental stress response.
Reduction Method of Regression Testing Requirements Based on Relation Mode

The variations in testing requirements often result in the problem of numerous test cases and low efficiency in regression testing. To solve this problem, a reduction method of testing requirements is proposed based on the relation mode in this paper. This method analyzes the relationship between the modules and testing requirements, then determines the varied regression testing requirements, and gets the final testing requirement set by reduction of the varied regression testing requirement set and the original testing requirement set in three times. If test cases are generated and reduced on the basis of the testing requirement reduction set, the efficiency of the regression testing will be improved.
Investigation of CO, C2H6 and aerosols in a boreal fire plume over eastern Canada during BORTAS 2011 using ground- and satellite-based observations, and model simulations

We present the results of total column measurements of CO, C2H6 and fine-mode aerosol optical depth (AOD) during the “Quantifying the impact of BOReal forest fires onTropospheric oxidants over the Atlantic using Aircraft andSatellites” (BORTAS-B) campaign over eastern Canada. Ground-based observations, using Fourier transform spectrometers (FTSs) and sun photometers, were carried out in July and August 2011. These measurements were taken in Halifax, Nova Scotia, which is an ideal location to monitor the outflow of boreal fires from North America, and also in Toronto, Ontario. Measurements of fine-mode AOD enhancements were highly correlated with enhancements in coincident trace gas (CO and C 2H6) observations between 19 and 21 July 2011, which is typical for a smoke plume event. In this paper, we focus on the identification of the origin and the transport of this smoke plume. We use back trajectories calculated by the Canadian Meteorological Centre as well as FLEXPART forward trajectories to demonstrate that the enhanced CO, C 2H6 and fine-mode AOD seen near Halifax and Toronto originated from forest fires in northwestern Ontario that occurred between 17 and 19 July 2011. In addition, total column measurements of CO from the satelliteborne Infrared Atmospheric Sounding Interferometer (IASI) have been used to trace the smoke plume and to confirm the origin of the CO enhancement. Furthermore, the enhancement ratio – that is, in this case equivalent to the emission ratio (ERC2H6/CO) – was estimated from these groundbased observations. These C 2H6 emission results from boreal fires in northwestern Ontario agree well with C 2H6 emission measurements from other boreal regions, and are relatively high compared to fires from other geographical regions. The ground-based CO and C 2H6 observations were compared with outputs from the 3-D global chemical transport model GEOS-Chem, using the Fire Locating And Modeling of Burning Emissions (FLAMBE) inventory. Agreement within the stated measurement uncertainty ( ∼ 3% for Published by Copernicus Publications on behalf of the European Geosciences Union. 10228 D. Griffin et al.: Boreal fire plume over eastern Canada CO and∼ 8% for C2H6) was found for the magnitude of the enhancement of the CO and C 2H6 total columns between the measured and modelled results. However, there is a small shift in time (of approximately 6 h) of arrival of the plume over Halifax between the results.
Real-Time Traffic Sign Recognition System based on Colour Image Segmentation

The traffic symbol system has been studies for many years. The system mainly has two phases, 1) Sign detection, 2) Recognition. It is one of the most important research area for enabling vehicle driving assistances. The automatic driving system should be simple in order to detect symbol with high responses. The challenge gets more difficult in order to make system simple while avoiding complex image processing techniques to detect symbol. The propose system consist of three main phases, 1) Frame selection, 2) Symbol detection, 3) Symbol Recognition. In frame selection phase the best frame possibly consisting of traffic symbol is selected from number of frames. In detection phase color image segmentation is perform on given frame in order detect the symbol. In recognition phase the detected traffic symbol is recognized using joint tranceform correlation (JTC) technique which is generally use for pattern matching.
Gender and emotion: Social psychological perspectives

Part I. Cultural, Gender and Emotional Beliefs: 1. Thinking about gender, thinking about theory Stephanie A. Shields 2. The socialisation of gender differences in emotional expression Leslie R. Brody 3. Men's and women's lay theories of emotion Vanda L. Zammuner 4.The relationship between gender and emotions in different cultures Agneta H. Fischer and Anton S. R. Manstead Part II. Emotion Expression and Communication: 5. Gender differences in nonverbal communication of emotion Judy A. Hall, Jason D. Carter and Terrence G. Horgan 6. Gender and smiling: a meta-analysis Marianne LaFrance and Marvin Hecht 7. Sex differences in crying Ad Vingerhoets and Jan Scheirs 8. Masculine identity and restrictive emotionality Jeroen Jansz Part III. Distinct Emotions: 9. Women, men and positive emotions Michele G. Alexander and Wendy Wood 10. Gender and anger Ann Kring 11. Gender, sadness and depression Robyn Fivush and Janine P. Buckner 12. Engendering gender differences in shame and guilt Tamara J. Ferguson and Heidi L. Eyre 13. Sex differences in anxiety and depression Tracey E. Madden, Lisa Feldman Barrett and Paula R. Pietromonaco Part IV. Epilogue: Gender and emotion: notes from a grateful tourist Kay Deaux.
Efficient Link Scheduling and Channel Hopping for Convergecast in WirelessHART Networks

Fast convergecast is a critical functionality for data collection in wireless networks deployed for industrial monitoring and control. We address the joint link scheduling and channel hopping problem for convergecast in networks operating according to the recent WirelessHART standard. We first demonstrate that the minimum time to complete convergecast in networks with multi-line/tree routing topology is max{2n1 − 1, N} time-slots where N is the number of field devices in the network and n1 is the maximum number of field devices in a line/subtree. Then we present time-optimal scheduling policies which complete convergecast using at most h(the maximum hopcount from a field device to the gateway) channels and require each device to buffer at most one packet at any time slot. We also establish lower bounds on the number of channels for time-optimal convergecast with single-packet buffering capability, and present a heuristic algorithm which can generate near-optimal schedule for timeand channel-optimal convergecast. We further demonstrate that, with our heuristic algorithm, the success rate that both the lower bound on convergecast time and the lower bound on the number of channels can be achieved goes up to 99.8%. Simulation and experimental results show that our scheme can provide very fast convergecast in WirelessHART networks.
Learning Probabilistic Relational Models in the context of reverse engineering genetic networks

This thesis places itself in the general direction of a probabilistic approach to systems biology. In specific we are concerned with applying the framework of Probabilistic Relational Models to the task of inferring clusters of transcriptionally coregulated genes on the basis of two distinct types of data: gene expression data and promoter sequence data. Such clustering is likely to reveal groups of interdependent genes that effectively form functional units. Identifying coregulation can therefore act as the first step enabling the smaller scale analysis required for the reverse engineering of genetic networks. In particular, we have focused on the model of transcriptional coregulation suggested in Segal et al. (2003) and have thoroughly explored the issues of generalisation performance and interpretability of the model, finding them interlinked in several ways. Finally, we have constructed a biologically interpretable regularising scheme, which performed very successfully against synthetic data.
Commercial adoption of open source software: an empirical study

There has been a dramatic increase in commercial interest in the potential of open source software (OSS) over the past few years. However, given the many complex and novel issues that surround the use of OSS, the process of OSS adoption is not well-understood. We investigated this issue using a framework derived from innovation adoption theory which was then validated in an organisation which had embarked on a large-scale of adoption of OSS. The framework comprised four macro-factors - external environment, organisational context, technological context and individual factors. We then investigated these factors in a large-scale survey. Overall, the findings suggest a significant penetration of OSS with general deployment in two industry sectors - consultancy/software house and service/communication - and more limited deployment in government/public sector. However, the existence of a coherent and planned IT infrastructure based on proprietary software served to impede adoption of OSS. Finally, individual-relevant factors such as support for the general OSS ideology and committed personal championship of OSS were found to be significant.
Residential Electrical Load Model Based on Mixture Model Clustering and Markov Models

Detailed large-scale simulations require a lot of data. Residential electrical load profiles are well protected by privacy laws. Representative residential electrical load generators get around the privacy problem and allow for Monte Carlo simulations. A top-down model of the residential electrical load, based on a dataset of over 1300 load profiles, is presented in this paper. The load profiles are clustered by a Mixed Model to group similar ones. Within the group, a behavior model is constructed with a Markov model. The states of the Markov models are based on the probability distribution of the electrical power. A second Markov model is created to randomize the behavior. A load profile is created by first performing a random-walking of the Markov models to get a sequence of states. The inverse of the probability distribution of the electrical power is used to translate the resulting states into electrical power.