Miracle-dz/UniFAR-FTUs huggingface dataset:
Looking for Rural Idyll 'Down Under': International Immigrants in Rural Australia

This article outlines the empirical findings of the first national longitudinal study of almost 1,000 recent immigrants who decided to move to non-metropolitan Australia. The national survey (2008-2010) identified that new international immigrants tend to move to rural areas because of the natural beauty, lifestyle and community spirit to be found there, as well as the idyllic image of peacefulness and a relaxing environment associated with these areas. Natural attractors, such as rurality and climate, were important features of the places which, according to the survey, were particularly liked. However, there is tension between the imagined Australian rural ideal and reality, with remoteness, isolation and parochialism being the key features in how the countryside may be misrepresented. The retention of new immigrants in rural places is very strongly related to constructed attractors – the availability and quality of infrastructure, as well as recreational, entertainment and cultural activities.
An Efficient ID-KEM Based On The Sakai-Kasahara Key Construction

This work presented an identity-based key encapsulation mechanism (ID-KEM). It is possible to use this ID-KEM to build a secure identity based encryption scheme using the techniques of Bentahar et al. The resulting encryption scheme has a number of performance advantages over existing methods. The proposed algorithm has been used in the industry (for example by Identum Ltd.) and is included in the IEEE P1363.3 standard draft.
Online configuration identification of a composable aerial vehicle

This work focuses on the design of estimation algorithms able to identify the interconnection topology of a class of modular aerial vehicles obtained by rigidly interconnecting a number of actuator and payload modules. The idea is to obtain a composable aerial vehicle that can be easily assembled and then deployed on the selected application scenario without a priori knowledge of the exact final geometric structure. Two different scenarios are then addressed. In the first one, it is assumed that the modules can be interconnected only following a pre-defined scheme, namely the admissible geometric configurations constitute a discrete set. In the second one, no restrictions on the admissible geometric configuration are taken into account. The effectiveness of the proposed identification algorithms is finally shown by means of numerical simulations comprehensive of noises affecting the sensors' output.
A Hybrid Algorithm for Removal of Eye Blinking Artifacts from Electroencephalograms

A robust method for removal of artifacts such as eye blinks and electrocardiogram (ECG) from the electroencephalograms (EEGs) has been developed in this paper. The proposed hybrid method fuses support vector machines (SVMs) based classification and blind source separation (BSS) based on independent component analysis (ICA). The carefully chosen features for the classifier mainly represent the data higher order statistics. We use the second order blind identification (SOBI) algorithm to separate the EEG into statistically independent sources and SVMs to identify the artifact components and thereby to remove such signals. The remaining independent components are remixed to reproduce the artifact free EEGs. Objective and subjective results from the simulation studies show that the algorithm outperforms previously proposed algorithms
A stress-dependent hysteresis model for PZT-based transducers

A ferroelastic switching model for single crystal piezoceramic compounds is developed. The model is based on a phenomenological Landau-Devonshire type thermodynamic theory for the materials. The model incorporates externally applied electric fields and compressive stress inputs to the crystals and models the 90° and 180° ferroelastic and ferroelectric switching induced by the inputs. Properties of the ferroelastic model are qualitatively similar to experimental PLZT data.
Comparison of Fine-Scale Recombination Rates in Humans and Chimpanzees

We compared fine-scale recombination rates at orthologous loci in humans and chimpanzees by analyzing polymorphism data in both species. Strong statistical evidence for hotspots of recombination was obtained in both species. Despite ∼99% identity at the level of DNA sequence, however, recombination hotspots were found rarely (if at all) at the same positions in the two species, and no correlation was observed in estimates of fine-scale recombination rates. Thus, local patterns of recombination rate have evolved rapidly, in a manner disproportionate to the change in DNA sequence.
Distribution network topology detection with time-series measurements

This paper proposes a novel approach to detecting the topology of distribution networks based on the analysis of time series measurements. The analysis approach draws on data from high-precision phasor measurement units (PMUs or synchrophasors) for distribution systems. A key fact is that time-series data taken from a dynamic system show specific patterns regarding state transitions such as opening or closing switches, as a kind of signature from each topology change. The algorithm proposed here is based on the comparison of the actual signature of a recent state transition against a library of signatures derived from topology simulations. The IEEE 33-bus model is used for initial algorithm validation.
Plants Bioclimatic Affinity Groups in China: Observed vs. Simulated Ranges

Predicting future ecosystems changes is necessary for better managing human resources. Such forecasting requires robust vegetation models which have been tested versus observed field data. Nowadays, it is very common that a simulation model is firstly validated using modern observed data and then tested versus palaeodata. In a sense, ecological data represent the natural laboratory for modelers. Thus, palaeo and actuo-ecological data are key points when dealing with predicting future changes. The present work represents the first step in such data-model comparison approach. Here, we use only modern plants distributions to test the robustness of our ecosystems definitions and use these definitions for testing a dynamic vegetation model. We have defined twenty-nine Bioclimatic affinity groups (BAGs) for 196 dominant plant species including trees, shrubs and herbs in China. These BAGs are characterized by the phenology and the climatic tolerances of the species they include. They are detailed enough to describe all vegetation types in China including the tropical, the subtropical, the temperate and the high altitude (Tibet Plateau) ecosystems. The climatic thresholds of these 29 BAGs were then used to test and validate a global dynamic vegetation model (CARAIB). The simulated BAGs are in good agreement with those observed in China, especially in the Tibetan Plateau and in the subtropical ecosystems. Broadly, all simulated BAGs fit quite well with the modern distribution. However, they all cover larger areas than the observed distributions, especially in the temperate region and in some areas in the northwest and the tropical zone. These discrepancies between simulated and observed distributions are related to the fact that the vegetation models simulate potential distributions. In China during recent decades natural ecosystems, mostly in the temperate zone, have been strongly altered in their species composition and geographical extent by different human activities such as the intense cultivation, deforestation, introduction of fast growing species and grazing.
Optimal predictive resource allocation: Exploiting mobility patterns and radio maps

Resource Allocation (RA) in cellular networks is a challenging problem due to the demanding user requirements and limited network resources. Moreover, mobility results in channel gains that vary significantly with time. However, since location and received signal strength are correlated, user mobility patterns can be exploited to predict the data rates they will experience in the future. In this paper, we show that with such predictions, long-term RA plans that span multiple cells can be made. We formulate an optimal Predictive Resource Allocation (PRA) framework for a network of cells as a linear programming problem for three different objectives. Presented numerical results provide a benchmark of the PRA performance in realistic and random user mobility scenarios. Significant network and user satisfaction gains are observed compared to RA schemes that do not utilize any predictions.
Reliable Location-Routing Design Under Probabilistic Facility Disruptions

This paper presents an integer program formulation of a reliable location-routing problem where built facilities are subject to the risk of probabilistic disruptions. The objective is to determine facility locations, outbound delivery routing, and backup plans under disruptions, so as to minimize the total cost including the facility set-up cost, the expected routing cost, and the customer penalty (if no delivery is possible). A variety of solution approaches (i.e., Lagrangian relaxation with embedded column generation, ring sweep heuristics, and local search) are proposed to solve the problem. The authors also present an alternative continuum approximation model for large-scale instances of this problem. This model not only provides analytical formulas to predict the optimal system cost but also can be used to generate high quality feasible solutions. A series of numerical case studies are conducted to test the performance of the proposed models and solution algorithms. Managerial insights are also drawn on how various system parameters impact the optimal solution.
How Mindfulness Training May Help to Reduce Vulnerability for Recurrent Depression

This review investigates how recent neuroimaging findings on vulnerability for depression and the mechanisms of mindfulness may serve to inform and enhance the understanding that is guiding the use of mindfulness training in the prevention and treatment of recurrent and chronic depression. In particular, we review evidence suggesting that alterations in default-mode-network activity and connectivity represent a fundamental deficit underlying cognitive vulnerability for depression and explore the ways in which mindfulness meditation may reverse such alterations. Furthermore, we discuss findings from studies that have investigated the effects of mindfulness on emotion-regulatory capacities. These findings suggest mindful emotion regulation has a characteristic neural signature that is particularly conducive to therapeutic learning. We conclude that training in mindfulness has unique strengths for addressing neural mechanisms associated with cognitive vulnerabilities for recurrent and chronic depression and propose future lines of research to more effectively harness this potential.
TEMPERATURE RESPONSE OF A RAIL-CASK-SIZE PIPE CALORIMETER IN LARGE-SCALE POOL FIRES

The Container Analysis Fire Environment (CAFE) computer code is being developed at Sandia National Laboratories (SNL) to predict the response of massive spent nuclear fuel transport casks to a range of severe fire environments. It is designed for use in transportation risk and design studies. CAFE employs physics-based reaction chemistry and radiation heat transfer models that are appropriate for fuel-rich and highly sooty pool fires. These models allow CAFE to produce accurate fire heat transfer results even when relatively coarse (and fast running) computational grids are employed. Parameters for these models must be determined from large-scale fire test data. Three fire tests were performed at the SNL outdoor fire test facility to benchmark CAFE. In these tests, the interior surface of a 2.4 m diameter, 4.6 m long, and 2.5 cm thick pipe calorimeter was instrumented with 70 Type-K thermocouples. It was suspended above a 7.2 m diameter water pool with enough JP8 jet fuel on top to burn for up to 40 minutes. Heat flux gages, directional flow probes, thermocouples, and anemometers were used to characterize the environment in the vicinity of the calorimeter during and after the fire. Transient wind conditions and calorimeter temperatures were recorded during and after the fires. The average wind speed was roughly 0.8 m/s during the first test, 1.1 m/s during the second, and 2.6 m/s during the third. CAFE simulations were performed using the measured wind conditions as boundary conditions and a range of model parameters. The resulting calculated calorimeter temperatures are compared to the experimental measurements.
The DLR MIRO: a versatile lightweight robot for surgical applications

Purpose – Surgical robotics can be divided into two groups: specialized and versatile systems. Versatile systems can be used in different surgical applications, control architectures and operating room set‐ups, but often still based on the adaptation of industrial robots. Space consumption, safety and adequacy of industrial robots in the unstructured and crowded environment of an operating room and in close human robot interaction are at least questionable. The purpose of this paper is to describe the DLR MIRO, a new versatile lightweight robot for surgical applications.Design/methodology/approach – The design approach of the DLR MIRO robot focuses on compact, slim and lightweight design to assist the surgeon directly at the operating table without interference. Significantly reduced accelerated masses (total weight 10 kg) enhance the safety of the system during close interaction with patient and user. Additionally, MIRO integrates torque‐sensing capabilities to enable close interaction with human beings .
Prediction of individual finger movements for motor execution and imagery: An EEG study

In the study of brain computer interface using electroencephalogram (EEG), the area of motor imagery of individual finger movement has been extensively examined. The objective of this study is to predict which finger is moving or being imaged through the use of EEG. We measured EEG activity while subjects performed either motor execution or motor imagery of individual finger movements with their right hand. Event related spectral perturbation was used as indicator of brain activity, which represents frequency power fluctuation from the baseline interval. The frequency bands α, β, and γ (8–15, 16–31, and 32–128 Hz, respectively) were used for analysis. Additionally, a feature consisting of a combination of those three bands was also explored using principal component analysis. These four kinds of features were classified by a linear discriminant analysis using ten-fold cross validation. Result indicated that the combined feature of the three frequency bands could classify most combinations of finger in both motor execution and motor imagery. The results suggest that EEG during the performance of motor imagery of individual finger movement is discriminable depending on the subject.
Effective Born radii in the generalized Born approximation: The importance of being perfect

Generalized Born (GB) models provide, for many applications, an accurate and computationally facile estimate of the electrostatic contribution to aqueous solvation. The GB models involve two main types of approximations relative to the Poisson equation (PE) theory on which they are based. First, the self‐energy contributions of individual atoms are estimated and expressed as “effective Born radii. ” Next, the atom‐pair contributions are estimated by an analytical function fGB that depends upon the effective Born radii and interatomic distance of the atom pairs. Here, the relative impacts of these approximations are investigated by calculating “perfect” effective Born radii from PE theory, and enquiring as to how well the atom‐pairwise energy terms from a GB model using these perfect radii in the standard fGB function duplicate the equivalent terms from PE theory. In tests on several biological macromolecules, the use of these perfect radii greatly increases the accuracy of the atom‐pair terms; that is, the standard form of fGB performs quite well. The remaining small error has a systematic and a random component. The latter cannot be removed without significantly increasing the complexity of the GB model, but an alternative choice of fGB can reduce the systematic part. A molecular dynamics simulation using a perfect‐radii GB model compares favorably with simulations using conventional GB, even though the radii remain fixed in the former. These results quantify, for the GB field, the importance of getting the effective Born radii right; indeed, with perfect radii, the GB model gives a very good approximation to the underlying PE theory for a variety of biomacromolecular types and conformations. © 2002 Wiley Periodicals, Inc. J Comput Chem 23: 1297–1304, 2002
Identification of Carbon Black in Military Textiles Using Infrared Imaging Techniques

The carbon black has been used in military fabrics to comply with the color requirements and infrared radiation lessening criteria. Currently, military industries don’t distinguish between fabrics with carbon black fibers or with carbon black into dyes or prints. The latter initially allows us to comply with the color specifications in the visible and infrared, but fabrics are degraded with use losing that initial capacity. The inclusion of carbon black in the fiber gets that the fabric doesn’t degrade with the wear, washed and dried, ensuring the accomplishment of the specifications all the time. The use of infrared imaging will allow us to define a method to discriminate those textiles with carbon black in their fibers from those which are dyed or printed.
Exploiting fine-grain thread level parallelism on the MIT multi-ALU processor

Much of the improvement in computer performance over the last twenty years has come from faster transistors and architectural advances that increase parallelism. Historically, parallelism has been exploited either at the instruction level with a grain-size of a single instruction or by partitioning applications into coarse threads with grain-sizes of thousands of instructions. Fine-grain threads fill the parallelism gap between these extremes by enabling tasks with run lengths as small as 20 cycles. As this fine-grain parallelism is orthogonal to ILP and coarse threads, it complements both methods and provides an opportunity for greater speedup. This paper describes the efficient communication and synchronization mechanisms implemented in the Multi-ALU Processor (MAP) chip, including a thread creation instruction, register communication, and a hardware barrier. These register-based mechanisms provide 10 times faster communication and 60 times faster synchronization than mechanisms that operate via a shared on-chip cache. With a three-processor implementation of the MAP: fine-grain speedups of 1.2-2.1 are demonstrated on a suite of applications.
Serum Stem Cell Factor Assay in Elderly Poor Responder Patients Undergoing IVF

In humans, stem cell factor (SCF), produced during follicular phase, may reflect a successful stimulation and oocyte maturation and so it may be a predictor of in vitro fertilization (IVF) outcome. An observational cohort study was conducted on 37 poor responders scheduled for fresh nondonor IVF/intracytoplasmic sperm injection treatment with standard controlled ovarian stimulation (COS) using recombinant follicle-stimulating hormone (rFSH; S-COS group). A total of 35 women received a second treatment using both rFSH and recombinant luteinizing hormone (rLH; LH-COS group). From 144 samples collected at pickup day, serum concentration of SCF (s-SCF) and follicular levels of SCF (f-SCF) were measured by enzyme-linked immunosorbent assay (ELISA) kit. No differences were observed between the 2 protocols in terms of both f-SCF and s-SCF levels. The comparison between f-SCF and s-SCF levels showed a strong linear correlation. The comparison between s-SCF levels and clinical outcomes showed a statistically significant correlation between both the number of metaphase II (MII) oocytes retrieved and the embryos obtained after fertilization. Cases with at least 3 MII oocytes showed s-SCF values >800 pg/mL, 2 MII oocytes >600 pg/mL, and 1 MII oocytes >400 pg/mL. In 100% of cases with s-SCF <400 pg/mL, no MII oocytes were recovered. All 5 pregnancies occurred in patients with s-SCF values >1000 pg/mL. The introduction of s-SCF assay in the management of poor-responder patients may contribute to solving the dilemma of whether to cancel or proceed with the stimulation cycle.
Characterizing Ambiguous Visual information in the Brain through intracranial EEG

In order to guide our actions, the human brain relies most on the information that is received from the visual sense. However, the visual input the brain receives through the eyes is often subject to noise and ambiguity. Consider for example a person driving a car throughthe fog. In this situation, the visual information that the brain receives is severely degraded. It is obvious that the brain needs a way to resolve such ambiguities in order to be able to provide the reliable visual information necessary to guide our actions. The neuralmechanisms that are involved in resolving ambiguity in the visual input have been the subject of many studies for over a century. In recent years, many studies have used psychophysics and neuroimaging toinvestigate how and where the brain processes and resolves ambiguous visual information. In this study we used a structure-from-motionstimulus to investigate the neural responses during the viewing of an ambiguous stimulus. To investigate these neural responses underlying ambiguous visual perception we used a novel approach. Intracranial electroencephalography is a relatively new method that provides several advantages over more commonly used methods such as scalp EEGor magnetic resonance imaging. The electrodes that are used to record the electrical activity of the brain are implanted directly on thesurface of the brain. This allows for more accurate measurements ofbrain activity becausethere is no interference from the skull and skin which cause problems in scalp EEG.Using intracranial EEG, we identified two separate locations in the left hemisphere of one partici-pant that showed a significant difference in alpha band power during a switch in perception when viewing an unambiguous stimulus compared to viewing an ambiguous stimulus. This difference could indicatethat the neuronal populations at theselocations respond preferentially to bottom-up visual information and not to top-down visual information. A subsequent analysis of the time-frequency spectrum revealedno significant differences but clearly showed a decrease in power in the lower frequencies before the participant responded to a changein the stimulus. This decrease in power is likely related to the preparation of the motor response. The results of this study show thatintracranial EEG is useful new method that can provide an improvement over both scalp EEG and MRI.