Miracle-dz/UniFAR-FTUs huggingface dataset:
Earthquake-Induced Subsidence and Burial of Late Holocene Archaeological Sites, Northern Oregon Coast

Fire hearths associated with prehistoric Native American occupation lie within the youngest buried lowland soil of the estuaries along the Salmon and Nehalem rivers on the northern Oregon coast. This buried soil is the result of sudden subsidence induced by a great earthquake about 300 years ago along the Cascadia subduction zone, which extends offshore along the North Pacific Coast from Vancouver Island to northern California. The earthquake 300 years ago was the latest in a series of subsidence events along the Cascadia subduction zone over the last several thousand years. Over the long term, subsidence and burial of prehistoric settlements as a result of Cascadia subduction zone earthquakes have almost certainly been an important factor contributing to the limited time depth of the archaeological record along this section of the North Pacific Coast.
Outlier detection for wireless sensor networks using density-based clustering approach

Outlier detection (OD) constitutes an important issue for many research areas namely data mining, medicines, and sensor networks. It is helpful mainly in identifying intrusion, fraud, errors, defects, noise and so on. In fact, outlier measurements are essential improvements to quality of information, as they are not conforming to expected normal behaviour. Due to the importance of sensed measurements is collected via wireless sensor networks, a novel OD process dubbed density-based spatial clustering of applications with noise (DBSCAN)-OD has been developed based on the algorithm DBSCAN, as a background for OD. With respect to the classic DBSCAN approach, two processes have been jointly combined, the first of computing parameters, while the second concerns class identification in spatial temporal databases. Through both of these modules, one is able to consider real-time application cases as centralised in the base station for the purpose of separating outliers from normal sensors. For the sake of evaluating the authors proposed solution, a diversity of synthetic databases has been applied as generated from real measurements of Intel Berkeley lab. The reached simulation findings indicate well that their devised method can prove to help effectively in detecting outliers with an accuracy rate of 99%.
Geopot: a Cloud-based geolocation data service for mobile applications

We propose a novel Cloud-based geolocation data service system, termed ‘Geopot’, for location-based mobile applications. The exponentially growing number of users of location-based mobile applications demand a data service that can easily be deployed and is scalable against a large volume of accesses from mobile devices across the world. The purpose of our work is to construct a scalable spatial data service that leverages the powerful benefits of a Cloud-based storage. We focus on highly scalable check-in and nearby search service, which is a common focus of location-based mobile applications. Our system comprises two parts: a local data service for indexing and storing geolocation data of check-ins to achieve a compact spatial index database. This is based on an in-memory R-tree and a local hash table, and it utilizes a Cloud storage that enables global accesses. The local data service maintains a compact spatial index, with tempo-spatial clustering, in which check-ins are grouped by their distance through a time window. A centroid of a cluster is used as a spatial index of R-tree, and members of the cluster are stored in the local networked hash table temporarily. This insures that R-tree remains in a compact size that can fit into the system memory. The data stored in the local hash table will be published into the Cloud storage to allow users to access it remotely with the same quality of service. Publishing the local data to a Cloud not only insures staying within the specified storage size limits of the local data service, but also promotes scalable access to the Cloud from mobile clients. Our contribution lies in the design of a new scale-out data service architecture and in implementing this for mobile applications. We encourage the building of a mobile application with our proposed system as well as a low-cost Cloud data service for linking to a large-scale spatial database.
Fruit Consumption by Youth in the United States

OBJECTIVES: To describe the contribution of whole fruit, including discrete types of fruit, to total fruit consumption and to investigate differences in consumption by sociodemographic characteristics. METHODS: We analyzed data from 3129 youth aged 2 to 19 years from the National Health and Nutrition Examination Survey, 2011 to 2012. Using the Food Patterns Equivalents Database and the What We Eat in America 150 food groups, we calculated the contribution of whole fruit, 100% fruit juices, mixed fruit dishes, and 12 discrete fruit and fruit juices to total fruit consumption. We examined differences by age, gender, race and Hispanic origin, and poverty status. RESULTS: Nearly 90% of total fruit intake came from whole fruits (53%) and 100% fruit juices (34%) among youth aged 2 to 19 years. Apples, apple juice, citrus juice, and bananas were responsible for almost half of total fruit consumption. Apples accounted for 18.9% of fruit intake. Differences by age were predominately between youth aged 2 to 5 years and 6 to 11 years. For example, apples contributed a larger percentage of total fruit intake among youth 6 to 11 years old (22.4%) than among youth 2 to 5 years old (14.6%), but apple juice contributed a smaller percentage (8.8% vs 16.8%), P < . 05. There were differences by race and Hispanic origin in intake of citrus fruits, berries, melons, dried fruit, and citrus juices and other fruit juices. CONCLUSIONS: These findings provide insight into what fruits US youth are consuming and sociodemographic factors that may influence consumption.
Encuesta Longitudinal Colombiana de la Universidad de los Andes- ELCA 2013

La Encuesta Longitudinal Colombiana de la Universidad de los Andes tiene por objetivo seguir a lo largo de una decada a mas de 10 mil hogares en zonas urbanas y rurales en Colombia. Es la primera encuesta longitudinal de esta magnitud en Colombia que permitira conocer las dinamicas de los hogares, la evolucion en el mercado laboral, en el desarrollo de los ninos, la vulnerabilidad frente a choques y los mecanismos que los hogares tienen para reaccionar ante ellos, el acceso a los servicios financieros, las dinamicas en la propiedad de la vivienda y la tenencia de tierras y produccion en la zona rural, entre otros temas. En 2010 se realizo la primera ronda de la ELCA donde se encuesto a 5,446 hogares urbanos, representativos nacional de la zona urbana y a nivel regional y 4,720 hogares rurales representativos de cuatro microrregiones regiones de Colombia. La segunda ronda se recogio en el primer semestre del 2013 alcanzando una cobertura del 94% de los hogares de seguimiento. Este documento describe la ELCA y provee informacion sobre la muestra, los instrumentos, el diseno de los contenidos, el operativo de campo y los resultados de cobertura del primer seguimiento.
A robust PI current controller for grid-connected renewable energy systems

This paper presents a robust PI current controller for three-phase grid-connected converters with LCL-filter for renewable energy systems. The controller is designed in synchronous reference frame and the grid impedance uncertainty is considered in the design. The controller consists of a PI current controller and state-feedback, where the gains of the PI controller and the gains of the state-feedback are designed together in a one-step procedure. The robustness of the current controller is ensured by an LMI approach, which guarantees closed-loop stability in the whole range for the considered grid impedance uncertainty.
Regularized tracking of shear-wave in ultrasound elastography

Ultrasound elastography involves imaging tissue while it undergoes deformation and inferring its mechanical properties from the deformation pattern. The initial deformation in the tissue is typically induced through an external mechanical force, for example, by exerting a slight pressure using an ultrasound probe or by applying an acoustic radiation force (ARF) against the tissue. The ARF excites the tissue locally, which leads to the propagation of a shear-wave. The goal of the shear-wave elastography is to estimate the speed of the shear-wave that is explicitly related to the elasticity of tissue. We formulate tissue displacement estimation as an optimization problem and propose a computationally efficient approach to estimate the displacement field. A novel algorithm based on the minimization of a regularized cost function using higher-order analytical minimization (HAM) coupled with the second-order Taylor series approximation is proposed. Our algorithm first computes an integer displacement field based on dynamic programming (DP) that provides the global optima, which is then refined iteratively to obtain the subpixel displacement estimate. We test the proposed algorithm on real experimental data obtained from a tissue-mimicking phantom and illustrate the superiority of our approach over some commonly used elastography techniques using signal to noise ratio (SNR) comparisons.
Climbing up the leaderboard: an empirical study of applying Gamification techniques to a computer programming class

Conventional taught learning practices often experience difficulties in keeping students motivated and engaged. Video games, however, are very successful at sustaining high levels of motivation and engagement through a set of tasks for hours without apparent loss of focus. In addition, gamers solve complex problems within a gaming environment without feeling fatigue or frustration, as they would typically do with a comparable learning task. Based on this notion, the academic community is keen on exploring methods that can deliver deep learner engagement and has shown increased interest in adopting gamification – the integration of gaming elements, mechanics, and frameworks into non-game situations and scenarios – as a means to increase student engagement and improve information retention. Its effectiveness when applied to education has been debatable though, as attempts have generally been restricted to one-dimensional approaches such as transposing a trivial reward system onto existing teaching materials and/or assessments. Nevertheless, a gamified, multi-dimensional, problem-based learning approach can yield improved results even when applied to a very complex and traditionally dry task like the teaching of computer programming, as shown in this paper. The presented quasi-experimental study used a combination of instructor feedback, real time sequence of scored quizzes, and live coding to deliver a fully interactive learning experience. More specifically, the “Kahoot! ” Classroom Response System (CRS), the classroom version of the TV game show “Who Wants To Be A Millionaire? ”, and Codecademy’s interactive platform formed the basis for a learning model which was applied to an entry-level Python programming course. Students were thus allowed to experience multiple interlocking methods similar to those commonly found in a top quality game experience. To assess gamification’s impact on learning, empirical data from the gamified group were compared to those from a control group who was taught through a traditional learning approach, similar to the one which had been used during previous cohorts. Despite this being a relatively small-scale study, the results and findings for a number of key metrics, including attendance, downloading of course material, and final grades, were encouraging and proved that the gamified approach was motivating and enriching for both students and instructors.
A new correctness criterion for the proof nets of non-commutative multiplicative linear logics

Abstract. This paper presents a new correctness criterion for marked Danos-Reginer graphs (D-R graphs, for short) of Multiplicative Cyclic Linear Logic MCLL and Abrusci's non-commutative Linear Logic MNLL. As a corollary we obtain an affirmative answer to the open question whether a known quadratic-time algorithm for the correctness checking of proof nets for MCLL and MNLL can be improved to linear-time.
Correlation of the Emergency Medicine Resident In-Service Examination with the American Osteopathic Board of Emergency Medicine Part I

Introduction: Eligible residents during their fourth postgraduate year (PGY-4) of emergency medicine (EM) residency training who seek specialty board certification in emergency medicine may take the American Osteopathic Board of Emergency Medicine (AOBEM) Part 1 Board Certifying Examination (AOBEM Part 1). All residents enrolled in an osteopathic EM residency training program are required to take the EM Resident In-service Examination (RISE) annually. Our aim was to correlate resident performance on the RISE with performance on the AOBEM Part 1. The study group consisted of osteopathic EM residents in their PGY-4 year of training who took both examinations during that same year. Methods: We examined data from 2009 to 2012 from the National Board of Osteopathic Medical Examiners (NBOME). The NBOME grades and performs statistical analyses on both the RISE and the AOBEM Part 1. We used the RISE exam scores, as reported by percentile rank, and compared them to both the score on the AOBEM Part 1 and the dichotomous outcome of passing or failing. A receiver operating characteristic (ROC) curve was generated to depict the relationship. Results: We studied a total of 409 residents over the 4-year period. The RISE percentile score correlated strongly with the AOBEM Part 1 score for residents who took both exams in the same year (r=0.61, 95% confidence interval [CI] 0.54 to 0.66). Pass percentage on the AOBEM Part 1 increased by resident percent decile on the RISE from 0% in the bottom decile to 100% in the top decile. ROC analysis also showed that the best cutoff for determining pass or fail on the AOBEM Part 1 was a 65th percentile score on the RISE. Conclusion: We have shown there is a strong correlation between a resident's percentile score on the RISE during their PGY-4 year of residency training and first-time success on the AOBEM Part 1 taken during the same year. This information may be useful for osteopathic EM residents as an indicator as to how well prepared they are for the AOBEM Part 1 Board Certifying Examination.
Heat and acid resistance depend on growth pH in the food-borne pathogen Bacillus cereus ATCC 14579

Bacillus cereus is a toxin producing bacterium responsible for food-borne toxi-infections. To monitor the ability of the food-borne opportunistic pathogen Bacillus cereus to survive during minimal processing of food products conditions were established which allowed the cells to adapt to heat and acid stresses. Cells were grown in chemostat at different pH (7.0 and 5.5) and at a growth rate of 0,2 h-1 . Cells were submitted during 40 minutes to an acid shock at pH 4 or to a heat shock at 50°C. The effect of preadaptation at a subletal temperature (42°C -15 min) was studied. Cells grown at low pH (pH 5.5) shown an acid stress adaptation with induction of an Acid Tolerance Response (ATR). Cross-adaptations was observed between thermotolerance and acidotolerance which suggested that a common mechanism was involved in the acid and heat stress responses in B. cereus ATCC 14579. Adaptive levels of stressor were found to induce the over expression of different genes encoding classical heat shock proteins such as dnaK, dnaJ sigB and GroEL and gene involved in internal pH homeostasis encoding ATPase, arginine decarboxylase or deiminase and lysine decarboxylase activities. These data shown that during mild processing, a cross-protection between acid and heat was occurred in B. cereus. These common mechanisms between acid and heat stress response may result in increasing survival of B. cereus cells in foods and can rising the pathogenicity of this bacteria. The virulence of this bacterium poses a major problem in public health in food poisoning.
Resource Sharing Cloud for University Clusters

There is a phenomena digital divide as regard to available delivery of lecture between the urban and the rural area colleges. This is also true as against lesser developed countries and developed countries. Today's education need to be innovative and thrusting to take care of the various distractions and attractions available for the students. Teaching methods should include practical, intellectual, and graphics as never before. Rural areas do not lure the best resources. How this can be made available and delivered for rural classrooms. This is possible if a system is provided by forming university clusters (UC). The University clusters share the resources available around the globe digitally. The UC will facilitate live digital lectures and allow the students to be taught from remote areas. This paper tries to present a modus of operandi, in providing a better live digital classroom educational system by bringing together leading universities and institutes. This is different from pod casting a lecture or distance learning and Learning. The digital live lectures can be streamed through IP and digital equipments. The rural students can interact with the urban students, face critiques, be evaluated, share their individuality and gather different techniques. This method will benefit rural students and teachers and bring about a socio economic development. A concept of 'Train the Trainee' will be a added advantage. An educational Teaching resource cloud for each cluster could be built to augment better logistics to share the resources. The colleges may be informed, about the lecture schedules, through the cloud service. The educational cloud can be set by the Institutes and universities under one cluster. This paper talks a little more about improved teaching and learning methodology which can be adopted for extended features like, tutorial rooms, library at the laptop, remote laboratory access, research and development.
Adaptive Single-Antenna Transmit Selection with Interference Suppression

This paper studies the performance of adaptive transmit selection with co-channel interference suppression in multipath fading channels. The adaptive selection algorithms are configured for single-antenna bandwidth-efficient or power-efficient transmission with as low transmit channel estimations as possible. Due to the fact that the number of active co-channel interfering signals and their corresponding powers experience random behavior, the adaptation to channels conditions, assuming uniform buffer and traffic loading, is proposed to be jointly based on the transmit channels instantaneous signal-to-noise ratios (SNRs) and signal-to-interference-plus-noise ratios (SINRs). Two interference cancelation algorithms are considered. The first algorithm assumes that the receiver eliminates the impact of the strongest subset of interferers, whereas the second algorithm suggests random cancelation of interferers to further reduce processing complexity. The impact of outdated ordering of interferers powers on the efficiency of interference cancelation, and the effect of imperfect prediction of transmit channels for desired user adaptation are investigated. Analytical formulations for various performance measures and comparisons between the performance and processing complexity of different adaptation schemes are presented.
Novel Noise-Robust Optoacoustic Sensors to Identify Insects Through Wingbeats

For certain countries, the production of olive oil and fruits is a significant percentage of the total gross income. Fruit flies affect a yearly crop loss calculated in billions of dollars worldwide. At the top of the hazard scale, certain mosquitoes and flies transmit harmful organisms that cause serious illnesses and even death to humans, pets, and livestock. In this paper, we develop a novel, noise-robust optoacoustic sensors to record insects' wingbeats. Our experiments with various insects of economic and social importance demonstrate that the sensors deliver high SNR recordings of the wing-flap. This paper emphasizes the development of the sensors and successfully analyzes the wingbeats of many insects of economic importance. Accurate analysis of insects' wing-flaps will allow the embedding of the sensors in common traps. The goal is to achieve species classification and remote monitoring of crops, which is currently carried out manually, and to develop reliable decision making regarding the initiation of large-scale spraying.
Implementing a Space-Aware Stochastic Simulator on Low-Power Architectures: A Systems Biology Case Study

In the last decade, different computing paradigms and modelling frameworks for the description and simulation of biochemical systems based on stochastic modelling have been proposed. From a computational point of view, many simulations of the model are necessary to identify the behaviour of the system. The execution of thousands of simulations can require huge amount of time, therefore the parallelization of these algorithms is highly desirable. In particular, models that consider the size of volumes and objects involved in the reaction are very time-consuming, since many rules should be considered to take into account the position of the different molecules. In this work we present an implementation of a stochastic space-aware simulator which exploits the benefit and features of hybrid low-power computing architectures. This work shows that the simulator dynamic probabilistic approach to select possible chemical reactions can be applied and implemented in hybrid low-power low-cost architectures as well as current industry high-end servers.
A codebook design approach for massive MIMO with planar antenna array

In this paper codebook for massive MIMO system with planar array is studied. To separate spatially correlated and spatially uncorrelated parts of the channel, antennas are divided into a number of blocks according to their position in the array. Antennas in a block are spatially correlated and antennas across blocks tend to be spatially uncorrelated. A codebook design approach is proposed based on such antenna block division. After analyzing the correlation property, the codebook is proposed to be constructed from two component codebooks by Kronecker product. One component codebook is used to quantize spatially correlated part within a block, and the other codebook is designed to match channel across blocks which are spatially uncorrelated. The effectiveness of proposed codebook design approach is demonstrated by evaluation results.