Miracle-dz/UniFAR-FTUs huggingface dataset:
Examination of the Wildland-Urban Interface Fire Dynamics Simulator in Modeling of Laboratory-Scale Surface-to-Crown Fire Transition

Understanding the conditions leading to the transition of fire spread from a surface fuel to an elevated (crown) fuel is critical to effective fire risk assessment and management. Surface fires that successfully transition to crown fires can be very difficult to suppress, potentially leading to damages in the natural and built environments. This is relevant to chaparral shrub lands which are common throughout parts of the Southwest U.S. and represent a significant part of the wildland urban interface. The ability of the Wildland-Urban Interface Fire Dynamic Simulator (WFDS) to model surface-to-crown fire transition was evaluated through comparison to laboratory experiments. The WFDS model is being developed by the U.S. Forest Service (USFS) and the National Institute of Standards and Technology. The experiments were conducted at the USFS Forest Fire Laboratory in Riverside, California. The experiments measured the ignition of chamise (Adenostoma fasciculatum) crown fuel held above a surface fire spreading through excelsior fuel. Cases with different crown fuel bulk densities and imposed wind speeds were considered. Cold-flow simulations with WFDS yielded wind speed profiles that closely matched the experimental measurements. Next, fire simulations with only the surface fuel were conducted to verify the rate of spread while factors such as substrate properties and fuel moisture content were varied. Finally, simulations with both a surface fuel and a crown fuel were completed. Examination of specific surface fire characteristics (rate of spread, flame angle, etc.) and the corresponding experimental surface fire behavior provided a basis for comparison of the factors most responsible for transition from a surface fire to the raised fuel ignition. The rate of spread was determined by tracking the flame in the Smokeview animations using a tool developed for tracking an actual flame in a video. WFDS simulations produced results in both surface fire spread and raised fuel bed ignition which closely matched the trends reported in the laboratory experiments.
Edinburgh Research Explorer Low-density lipoprotein (LDL) uptake demonstrates a hepatocyte phenotype in the dog but is non-specific

Low-density lipoprotein (LDL) uptake is one of a number of tests used to demonstrate hepatocyte-like function after stem cell differentiation. Use of two compounds; LDL and acetylated LDL has been described despite each having different mechanisms of uptake. Three primary hepatocyte cultures and three sets of mesenchymal stromal cell (MSCs) cultures, derived from both adipose tissue and bone marrow, were harvested from dogs. Those cells were compared to commercially available human and mouse bone marrow derived MSCs. LDL receptor expression was demonstrated by gene expression and immunofluorescence in all primary hepatocyte cultures, undifferentiated canine bone marrow mesenchymal stromal cells (MSCs) and canine adipose MSCs. Undifferentiated human and mouse bone marrow MSCs also expressed the LDL receptor. In vitro, canine hepatocytes took up labelled LDL but not acetylated LDL. All undifferentiated MSCs took up LDL but not acetylated LDL. In conclusion, LDL and not acetylated LDL is a test of canine hepatocyte-like phenotype but this is not tissue or species specific and therefore is not informative assay when testing proof of MSC to hepatocyte differentiation.
PHYTOTONIC EFFECTS OF NEONICOTINOID INSECTICIDES IN COWPEA AND GREEN GRAM

The effectiveness of neonicotinoid insecticides against a broad range of sucking insect pests like aphids, leaf hoppers, thrips and whiteflies have been reported in various crops like cotton (Vadodaria et al., 2001, Sitaramaraju et al., 2010, Kalyan et al., 2012 and Bharpoda et al., 2014), okra (Praveen, 2005), cowpea (Patel et al., 2012), green gram (Nakat et al., 2002, Khutwad et al., 2002) etc. Imidacloprid, thiamethoxam and acetamiprid are the three major neonicotinoid insecticides which are used against these pests. In addition to its effectiveness in pest management, these insecticides as seed treatment and foliar spray have been reported to exert growth promoting effects (phytotonic effects) such as increase in leaf area (Sreelatha and Divakar, 1997), plant height (Sitaramaraju et al., 2010), chlorophyll content (Preetha and Stanley, 2012), root growth (Macedo et al., 2013) and number and weight of root nodules (Singh et al., 2000) in various crops. An ideal insecticide used for seed treatment should not exert any adverse effects on seed germination and hence, the effect of neonicotinoid insecticides on seed germination needs to be investigated. Moreover, the applied insecticide must not have any deleterious effects on root nodules of legume crops.
Mixed-motion Segmentation Using Helmholtz Decomposition

Motion estimation and segmentation poses challenges in dynamic scenarios where multiple motions are mixed up and interdependent. However, existing approaches in 2D motion field usually require the mixed motions to be independent. Algorithms incorporating 3D information have proven to be superior to purely 2D approaches in many studies. Inspired by this idea, we propose a new algorithm for evolving 3D potential surfaces using Helmholtz decomposition to represent 2D motion field. Meanwhile, a surface segmentation scheme is introduced to put different motions onto different layers, so that those interdependent motions can be separated and recovered efficiently. Unlike other approaches, our method does not require the prior knowledge of the motion model. The performance is demonstrated using real data under various complex scenarios.
Pharmacovigilance from Social Media using Limited Labeled Data

Social media is becoming increasingly popular as a platform for sharing personal health-related information. This information can be utilized for public health monitoring tasks, particularly for pharmacovigilance, via the use of natural language processing (NLP) techniques. However, the language in social media is highly informal, and user-expressed medical concepts are often nontechnical, descriptive, and challenging to extract. This poses a significant challenge to the existing Natural Language Processing (NLP) and Information Retrieval (IR) methods. In this thesis, we try to address the problem of “Adverse Drug Reaction (ADR) Mention Extraction”, a specific form of pharamacovigilance, from social media. Specifically, we try to address the problem in the setting where we have a limited access to labeled data but potentially unlimited access to unlabeled data, which is often the case in the real world. We investigate the applicability of two of the popular and well-studied approaches for handling such problems: Semi-supervised learning and Multi-task learning. In the first approach, we propose a novel semi-supervised method which utilizes a novel task of “Unsupervised Drug-Name Prediction”, which is the prediction of drug-name from the tweet context where the actual drug-name is identified and masked from the tweet and the objective is to predict the drug-name from the masked tweet. Enforcing the network to predict the drug-name allows it to learn the context around the drug-name mention. Through experiments we demonstrate that pre-training the network with such task helps in improving performance on the main task. In the second work, we make use of more traditional and well-studied semi-supervised method: cotraining, for ADR extraction. To the best of our knowledge, we are the first ones to apply a co-training based methods for entity extraction using deep learning. Through experiments we demonstrate that co-training based network gives a significant improvement in the main task as compared to its fully supervised counterpart. In the third work, we propose a multi-task learning based method which can utilize a similar auxiliary task (adverse drug event detection) to enhance the performance of the main task of our interest, i.e., ADR extraction. Further, in the absence of auxiliary task dataset, we propose a novel joint multi-task learning method to automatically generate weak supervision dataset for the auxiliary task when a large pool of unlabeled tweets is available. Experiments with a large unlabeled pool of tweets, we show that the proposed approach outperforms the state-of-the-art methods for the ADR mention extraction task by ∼7.2% in terms of F1 score.
Sparsity-Promoting Methods in Remote Control Systems

In remote control systems, efficient representation of control signals is one of the crucial issues because of bandwidth limitation of the communication channel, such as a wireless communication link between the controller and the controlled object. Recently, a new method based on the technique of compressive sampling has been proposed, in which control signals are sparsely representation based on convex relaxation. There exist however so many sparsity-promoting methods for compressive sampling. In this study, we perform a comparative study of sparsity-promoting methods and reveal their advantages and disadvantages by simulation in view of remote control over rate-limited networks.
AUGMENTED REALITY AND TANGIBLE INTERFACES IN COLLABORATIVE URBAN DESIGN A user study of augmented reality in an urban design studio

This paper outlines the design, execution and analysis of a user evaluation experiment using Augmented Reality (AR) in an urban design studio. The aim of the experiment was to gauge the differences between two interfaces in regard to their impact on the design process. The two conditions of the experiment were a direct manipulating tangible user interface and a pen-like 3D manipulation interface. Findings include differences in perceived object presence, performance measures, perceived performance and variations in the communication patterns. These findings have implications for the integration of this technology in a praxis relevant design work flow.
Joint DOF Neck 2 Shoulder 3 Elbow 1 Waist 3 Hip 3 Knee 1 Ankle 2 Total 25 Stiff Joint

This paper presents a generic stabilization framework which is applicable for both compliant and stiff humanoids. The proposed control framework is applied to the passive compliant humanoid robot COMAN which is equipped with series elastic actuators. The stabilization control framework combines the compliance control and the intrinsic angular momentum modulation to achieve an agile and compliant interaction against external perturbations. The admittance based compliance control uses the force/torque sensing in both feet to regulate the active compliance for the position controlled system. The physical elasticity in the new full body COMAN is exploited for the reduction and absorption of the instantaneous impacts while the admittance control further dissipates the excessive elastic energy. The angular momentum controller reduces the overall inertia effect for providing more rapid reactions. Both the theoretical work and experimental validation were presented. The effectiveness of the control scheme is demonstrated by COMAN’s capabilities of withstanding various types of perturbations applied over the body, balancing on a moving platform and stabilizing while walking. Experimental data of the ground reaction force/torque, center of mass references and estimations, and the stored elastic energy are presented and analyzed.
Challenges to Secondary Brain Injury Prevention in Severe Traumatic Brain Injury

BACKGROUND/AIMS: Inconsistency in the use of secondary brain injury prevention guidelines among US trauma centers after severe traumatic brain injury is prevalent in many literature sources. However, this phenomenon has not been thoroughly studied. The purpose of this DNP project is to identify the key barriers and challenges in compliance to the evidencebased guidelines for secondary brain injury prevention. DESIGN: An exploratory, emergent design was used to collect descriptive qualitative data through the use of a survey. SETTING: Six Phoenix Metropolitan Level 1 trauma centers. PARTICIPANTS: All survey participants who consented to survey completion, which had greater than six months of experience and directly worked with patients suffering from a severe TBI in the clinical setting. MEASUREMENTS: Participant demographics (work experience, area of work, job title), current awareness and use of Brain Trauma Foundation guidelines, and time duration for evidence based order set implementation. Narrative responses were also used to identify barriers to current use of the BTF guidelines and factors that may promote their use in the future. RESULTS: A total of 43 participants consented to the survey study, with completion by 35 participants. RNs (n=27), Physicians (n=2), NPs or PAs (n=5), with an average work experience of 6 to 14 years (42.86%). A total of n=22 (62%) of participants were unaware of the current BTF guidelines for severe TBI and only 25% (n=9) aware that their facility has a protocol based on the BTF guidelines for severe TBI, while 51% (n=18) were unsure if their facility had a protocol. Barriers were identified in narrative form and were consistent with awareness/education, provider congruence, communication, and order set/protocol process improvement. CONCLUSION: The understanding of current patient management for severe TBI based on the BTF guidelines is
Bernoulli Asymptotic Equivalence of Fixed-size and Varying-size Determinantal Point Processes

Determinantal Point Processes (DPPs) are popular models for point processes with repulsion. They appear in numerous contexts, from physics to graph theory, and display appealing theoretical properties. On the more practical side of things, since DPPs tend to select sets of points that are some distance apart (repulsion), they have been advocated as a way of producing random subsets with high diversity. DPPs come in two variants: fixed-size and varying-size. A sample from a varying-size DPP is a subset of random cardinality, while in fixed-size “k-DPPs” the cardinality is fixed. The latter makes more sense in many applications, but unfortunately their computational properties are less attractive, since, among other things, inclusion probabilities are harder to compute. In this work we show that as the size of the ground set grows, k-DPPs and DPPs become equivalent, in the sense that fixed-order inclusion probabilities converge. As a by-product, we obtain saddlepoint formulas for inclusion probabilities in k-DPPs. These turn out to be extremely accurate, and suffer less from numerical difficulties than exact methods do. Our results also suggest that k-DPPs and DPPs also have equivalent maximum likelihood estimators. Finally, we obtain results on asymptotic approximations of elementary symmetric polynomials which may be of independent interest.
ANALYZING DETERMINANTS OF ASSETS AND LIABILITIES IN ISLAMIC BANKS : EVIDENCE FROM INDONESIA

This study attempts to analyze the factors that are important in determining the Islamic banks’ two major balance sheet items, namely deposit and financing in the case of Indonesia. By employing the vector autoregression analysis along with the associate variance decomposition analysis for all Islamic banks in Indonesia, the study examines the importance of selected financial and macroeconomic variables in determining the levels of deposit and financing in the Islamic banks. Using monthly data, the study covers the period from January 2004 to March 2011. The results highlight the influential role of rate of return on the Islamic deposit and deposit rate on the conventional bank in determining the deposit of the Islamic banks. On the asset side, the lending rate of the conventional loan is highly significant in influencing the demand for financing by the Islamic banks. Essentially, this study indicates the profit motive among the Islamic banks customers as reflected by significant effects of the financial variables on deposit and financing of the Islamic banks. The findings provide further support of the exposures of the Islamic banks to the rate of return risk, interest rate risk, and displaced commercial risk. Amid the aggressive efforts by Bank Indonesia to accelerate the growth of the Islamic banking and finance industry in the country especially to enhance the competitiveness of the industry to face the ASEAN market integration in 2015, these findings would enable the policy-makers to focus on critical issues in implementing strategies to achieve the goal of development this industry in Indonesia.
International Trade , Technical Change and Wage Inequality in the U . K . Economy

This paper examines the joint impact of international trade and technical change on U.K. wages across different skill groups. International trade is measured as changes in product prices and technical change as total factor productivity (TFP) growth. We take account of a multi-sector and multi-factor of production economy and use mandated wage methodology to offer a close theoretical-empirical relationship. We use data of the EU KLEMS database and analyse the impact of both, product price changes and TFP changes of 11 U.K. manufacturing sectors on factor rewards of high-, mediumand low-skilled workers. Results show that real wages of skill groups are driven by the sector bias of price change and TFP growth of selected sectors of production. Furthermore, for each year 1970-2005 we estimate the share of the three different skill groups on added value which indicate structural change in the U.K. economy. Empirical results show a structural change in the U.K. economy by the declined share of low-skilled workers and the increased share of medium-skilled and high-skilled workers over the years.
Ultrasound-triggered drug release from vibrating microbubbles

markdownabstract__Abstract__ Diagnostic medical ultrasound may have a slightly longer history than what you expected. Its root dates back to 1930s and 1940s, when Theodore Dussik, a psychiatrist and neurologist, and his brother Friederich used a 1.5 MHz source to record signal variations after transmitting the wave through the human brain. Although these images were later shown to measure the skull bone attenuation instead of brain ventricles as the Dussik brothers had believed, it was one of the earliest attempts to scan an in vivo organ (White 1988). The real developments of medical ultrasound imaging initiated after Second World War, since 1950s, when the “pulse echo” technique was adapted from military sonar and radar. For the practicality to position the setup for medical imaging, only a single transducer was used to measure the reflected wave from the target sample in contrast to transmission, which measures the wave transmitted through the medium by a sending transducer and a separate receiving transducer. In early 1950s, John Wild and John Reid developed the first hand-held imaging device which was applied to image breast cancer tumors (Newman and Rozycki 1998). However, it was not until 1960s and 1970s, with the development of electronics, these pioneering works truly came to fruition. The static B-mode imaging was replaced by real-time imaging modalities thanks to new techniques such as phased linear arrays (Seibert 1995). One of the major breakthroughs (which is also of special meaning to the author) is the multi-element linear arrays developed by the group headed by Professor Nicolaas Bom at Thoraxcenter, Erasmus medical center Rotterdam. The probe face consists of 20 crystals which can produce 20 scan lines in total. Figure 1.1 shows the design of the probe and the real-time cardiac image it produced. This early simple concept has later evolved into the more complicate real-time scanners that are widely available today. The later combination of real-time imaging with pulsed wave Doppler technique enabled accurate measurements of the blood flow, which greatly benefited diagnostic echocardiography.
7-1-2013 The Generative Mechanisms Of Open Government Data

The exponentially growing production of data enables global connectivity as well as increased openness and sharing, which turn into a powerful force that is changing the global economy and society. Governments around the world have become active participants in this evolution by opening up their data for access and re-use by public and private agents alike. The recent phenomenon of Open Government Data (OGD) has spread around the world, driven by the proposition that opening government data has the ability to generate both economic and social value. However, a review of the academic research and the popular press reveals only sporadic attention given to various aspects with no overarching framework that explains how OGD generates value. We apply a critical realist approach to uncover the generative mechanisms that serve to explain this relationship. First, we present a strategic framework with four archetypical generative mechanisms. The framework outlines the different pathways to value generation and highlights the current tension between the private/public and economic/social domains. Second, we offer a conceptual model that provides a systematic way of articulating and examining further the generation of value from OGD.
Toiling with the P ā li Canon

The paper describes the preparation of a Buddhist corpus in the Middle Indo-Aryan language Pāli, which is available only in a flat TEI format, for content-based analysis. This task includes transforming the file into a hierarchical TEI P5 representation, followed by tokenisation (including sandhi resolution), lemmatisation, and POS tagging.
PROBING OF POLARIZATION DYNAMICS USING FAST NANOPARTICLES

Polarization dynamics gives insight on the changes in the polarization state of partially polarized beams. We present a measurement system to follow the femtosecond scale polarization fluctuations from a point of a random light field that is based on scattering scanning near-field microscopy. To ensure the method will provide details on the instantaneous properties of an incident beam, we construct equations for the electric field scattered from a subwavelength, dipolar nanoparticle. The polarization dynamics of the scattered far field prove that apertureless SNOM can be used to follow the rapid variations of the polarization ellipse as long as the nanoprobe has a response time that is in the femtosecond range. We establish basic conditions for the polarizability and shape of the nanoparticle to guarantee that the dipole can react to the variations in the incident beam on the same timescale. The criteria indicates that the selected nanoparticles’ response times are within 2-37 femtoseconds. The most suitable nanoparticles for use with our method are silver Archimedean solids ranging from 92-136 nm in size. A limitation for this measurement approach is that no information on the instantaneous circular polarization states can be determined.
Biologic basis of orthodontics

The solution to get this book is that we don't over you the free book. But, we offer you the free information about biologic basis of orthodontics. Why should be this book to read and where is the place to get it, even the soft file forms are common questions to utter. In this website, we don't only provide this book. We have still lots of books to read. Yeah, we are on-line library that is always full of recommended books.