Miracle-dz/UniFAR-FTUs huggingface dataset:
The emergence of the global workplace : opportunities and barriers for building surveyors in Oceania

The Royal Institution of Chartered Surveyors (RICS) the professional body representing surveyors in the UK, has implemented a policy to globalise in order to meet the challenges and opportunities the global marketplace was creating for its members as well as protecting and serving its interests (RICS, 1999). Quantity surveyors had a presence and history of employment outside the UK, particularly in the Middle and Far East. Real estate surveyors found the transition to working in European Union (EU) countries relatively straightforward and numerous UK real estate organisations have European, Asian, North American and Oceanic offices. Additionally UK based firms establishing partnerships with overseas real estate firms expanded significantly over the previous decade. Building Surveying is different. Small numbers worked in commonwealth countries but in most countries their professional and academic qualifications were not recognised. With the changes implemented by the RICS, this paper examines the barriers and opportunities facing RICS Chartered Building Surveyors (CBS) in Oceania (taken as Australia, New Zealand, Papua New Guinea and Fiji). A desk top study reviewed the political, economic and sociological variables affecting employment opportunities and professional services which were put to the RICS Oceania Building Surveying Faculty. No previous study had been undertaken to identify the specific barriers and opportunities in Oceania for the BS and this research adopted a census survey of RICS practitioners currently employed in the region and the results form the most comprehensive picture of the current position. The findings are that some of the opportunities and barriers will change in significance over time. The main barriers to growth were perceived as lack of support from a Euro focussed RICS and the difficulties associated with being perceived as outsiders. Opportunities were perceived as emerging in new areas of professional services such as sustainability and energy efficiency.
Towards Seamless Mobile Learning with Mixed Reality on Head-Mounted Displays

This paper discusses the opportunities and challenges of utilizing optical (head-mounted) displays for mixed reality in the context of seamless mobile learning. Recent technological developments have significantly improved the capabilities and the mobility of head-mounted displays. Future displays, frequently referred to as data glasses, will be even more lightweight, have a larger naturally sized field of view, and will redefine the standing of mixed reality in economy and society. We envision that these immersive displays will introduce a new world of didactical opportunities and novel context-aware designs for seamless mobile learning, particularly in outdoor learning environments. Our discussion is based on an extensive literature review and first-hand experience with applying this type of novel technology in learning scenarios. Our considerations comprise new ways of collaborative learning and communication between peers, the role of human-computer interaction, the visualization of learning content, and exemplary learning scenarios with mixed reality. We further provide an overview of potential research directions to be pursued in the near future.
Title Ligand binding and activation of the Ah receptor Permalink

The Ah receptor (AhR) is a ligand-dependent transcription factor that can be activated by structurally diverse synthetic and naturally-occurring chemicals. Although a significant amount of information is available with respect to the planar aromatic hydrocarbon AhR ligands, the actual spectrum of chemicals that can bind to and activate the AhR is only now being elucidated. In addition, the lack of information regarding the actual three-dimensional structure of the AhR ligand binding domain (LBD) has hindered detailed analysis of the molecular mechanisms by which these ligands bind to an active AhR signal transduction. In this review we describe the current state of knowledge with respect to naturally occurring AhR ligands and present and discuss the first theoretical model of the AhR LBD based on crystal structures of homologous PAS family members. # 2002 Elsevier Science Ireland Ltd. All rights reserved.
and abandonment as a precursor of built-up development at the prawling periphery of former socialist cities imona

In former socialist countries, as cities expanded they permeated into nearby agricultural areas. The periphery then became a mosaic of built-up and agricultural patches. Due to small sizes, inconvenient shapes and scattered locations, the parcels often became unprofitable for agricultural use, and were later abandoned and frequently transformed into built-up areas. Our paper aims to assess whether agricultural land abandonment can be considered a valid precursor of built-up development. The periphery of Bucharest was chosen as the study area, and analyzed over a period of 11 years (2002–2013) based on data sets derived from aerial images. Logistic regression models were used to test whether land abandonment was a significant explanatory variable of built-up development along with other socio-economic, land use, and urban planning variables. The results showed that land abandonment has the potential to be considered a precursor of built-up development. It acts within a cause and effect framework, being influenced by ongoing economic transformations, and changes in urban regulations. Its addition as an explanatory variable in a built-up prediction model significantly increased the prediction power, which makes it a useful variable in urban land use change scenarios. The type of observed abandonment at the periphery of urban areas follows a different pathway compared to land abandonment observed in remote or rural areas. Here, land abandonment is the result of anticipated higher profits through new economic opportunities and urbanization. Monitoring of abandoned land and urban sprawl could enable local authorities to evaluate the outcomes of planning policies and economic incentives.
Cyclotron maser emission: stars, planets, and laboratory

This paper is a review of results by the group over the past decade on auroral kilometric radiation and similar cyclotron emissions from stars and planets. These emissions are often attributed to a horseshoe or crescent shaped momentum distribution of energetic electrons moving into the convergent magnetic field which exists around polar regions of dipole-type stars and planets. We have established a laboratory-based facility that has verified many of the details of our original theoretical description and agrees well with numerical simulations. The experiment has demonstrated that the horseshoe distribution does indeed produce cyclotron emission at a frequency just below the local cyclotron frequency, with polarization close to X-mode and propagating nearly perpendicularly to the beam motion. We discuss recent developments in the theory and simulation of the instability including addressing a radiation escape problem and the effect of competing instabilities, relating these to the laboratory, space, and astrophysical observations.
Revista Electrónica Nova Scientia Detection scheme for linear dispersion space- time block codes using modified SQRD decomposition Esquema de detección para códigos espacio- temporales de bloque basados en códigos de dispersión lineal utilizando la descomposición Sorted QR

In this work, a novel architecture for detection of Hybrid MIMO Systems over Rayleigh fading channels is presented. The Hybrid MIMO scheme consists of one Alamouti space-time block code unit, plus S n antennas operating as layers of V-BLAST in the transmitter. The proposed receiver is based on the algorithm Sorted QR decomposition (SQRD) presented in (Wubben et al., 2001). This proposal reduces significantly the complexity while maintaining the advantages of the SQRD scheme, obtaining a considerable gain in performance in terms of bit error rate (BER) at the expense of decreasing data rate.
An Improved Arbitrary-Radius-Wire Representation for FDTD Electromagnetic and Surge Calculations

In this paper, it is shown that finite-difference time- domain (FDTD) electromagnetic computations for a conductor system having a radius smaller than 0. 15Δr or larger than 0. 65Δr (Δr is the lateral side length of cells employed), which is modeled using arbitrary-radius-wire representations proposed so far with a time increment determined from the upper limit of Courant's stability condition, result in numerical instability. A primary factor causing this numerical instability is that the speed of waves propagating in the radial direction from the wire in the immediate vicinity of the wire exceeds the speed of light, and therefore, Courant's condition is not satisfied there. Further, it is shown that the arbitrary-radius-wire representation can be improved by modifying the material parameters as follows. In representing a wire whose radius is smaller than the equivalent radius (a0 =0.230Δr or 0.208Δr) using the improved technique, the permeability for calculating the axial magnetic field components closest to the wire and for calculating the circulating magnetic field components closest to and half cell away from the tip of the wire is modified in addition to the permeability and the permittivity for calculating the circulating magnetic field components and the radial electric field components, closest to the wire, respectively. In representing a wire whose radius is larger than a0 using the technique, the permittivity for calculating the axial electric field components closest to the wire is modified in addition to the permittivity and the permeability for calculating the radial electric field components and the circulating magnetic field components, respectively. The improved wire representation is effective in representing a wire whose radius ranges from 0. 0001Δr to 0. 9Δr.
Using Compression / Decompression Technique for FPGA Targeted Matrix-Oriented SAT Solvers

The paper shows that the data exchange between a host computer and FPGA-based matrix-oriented accelerators might influence the total time of computations significantly. Two methods based on data compression have been examined. The first one provides matrix compression in a host computer and decompression in an FPGA. The second method makes possible to execute operations required for solving combinatorial problem over compressed matrices. The proposed architecture for FPGA-based SAT accelerator attains high performance and it makes possible very complex SAT problem instances to be solved.
Construction of Evaluation Index System of supply logistics collaboration based on Supply-Hub

At present, theoretical studies on collaboration evaluation of supply logistics based on Supply-Chain were very few, while almost no researches were on its index system. The paper took supply logistics system based on Supply-Hub as research object, built up a framework of performance evaluation system, analyzed connotation of supply logistics collaboration based on Supply-Hub, adopted literature research as reference for indicators selection and Q-Sort method to test indicators to improve reliability and validity of this evaluation index system, and to provide support for subsequent research on supply logistics collaboration based on Supply-Hub.
Volatility Forecasting and Volatility Risk Premium

Volatility is an important variable in the financial market. We propose a model-free implied volatility method to measure the volatility and test the volatility risk premium. The model-free implied volatility does not depend on the option pricing model, and extracts information from all the option contracts. We provide empirical evidence from the S & P 500 index option that model-free implied volatility is more accurate to forecast the future volatility and the volatility risk premium does not exist.
A Novel Network Based on Densely Connected Fully Convolutional Networks for Segmentation of Lung Tumors on Multi-Modal MR Images

Lung cancer has become the most common malignant tumor in recent years. Tumor segmentation from medical images is substantial for the benign and malignant classification of tumors and the choice of subsequent therapy plans. Current diagnostic methods of standard lung images in clinic mainly depend on computed tomography (CT). Magnetic Resonance Imaging (MRI) has advantages of no radiation to human body and higher sensitivity to soft tissue lesions compared with CT. Multi-modality imaging is the attribute of MRI, which can give more information for tumor delineation. In this paper, we proposed a novel approach for the segmentation of lung tumors from multi-modal MR images which combines fully convolutional network (FCN) based semantic network (U-Net) and hyper-densely connected CNN model (Hyper-DenseNet) for multi-modality fusion. Our proposed method has two aspects of architecture: multi-modality feature fusion architecture and encoder-decoder based semantic segmentation architecture. The combination of these two architectures overcomes the deficiency of single modality U-Net and Hyper-DenseNet. The effectiveness of our proposed method has been demonstrated by comparative experiments on 564 scan slices of 89 lung cancer patients. Our method yields better experiment results by Dice Similarity Coefficient (DSC) to evaluation than single-modal U-Net and Hyper-DenseNet without encoder-decoder. The more encouraging result, especially, is that the segmentation results of the tumors adjacent to normal tissues and organs or the inflammatory tissues has a more remarkable improvement.
Feature Collection and Selection in Malware Classification

In order to make up for the shortcomings of signature-based traditional classification methods, the supervised learning algorithms of machine learning and deep learning are gradually applied to malware detection and classification. Based on the Windows malware classification problem, we firstly introduce the collection techniques of different features. Then we discuss the impact of the different features from malware behavior selected on classification results. The results show that the fine-grained features are usually better than coarse-grained features, multi-features are better than single features under certain circumstances. Besides, the collection and training costs of static features are smaller than dynamic features. Finally, considering the factors of training time, complexity of feature collection and classification accuracy, we present our own views on the features that should be applied to malware classification issues in different situations.
Classifying points of interest with minimum metadata

In this paper, we present an approach for effectively classifying Points of Interest (POIs) that are represented only by their name and location (coordinates). Most existing approaches make the assumption that the handled POIs carry a wealth of metadata (e.g. reviews, ratings, working hours, price ranges). Consequently, such methods rely on semantically rich POI profiles and exploit them to develop correspondingly rich, and thus more accurate, POI classification models. However, in several real world scenarios, assuming the existence of such rich POI profiles is unrealistic. Contrary to existing works, we propose a method that can produce accurate category recommendations based only on the minimum amount of initially available POI metadata (name, coordinates) combined with open and straightforwardly accessible metadata drawn from OpenStreetMap. To this end, we propose a set of textual and neighbourhood-based training features, capturing POI properties as well as their relations with their spatial neighborhoods. These features are fed into several classification algorithms and are evaluated on a proprietary POI dataset of a geo-marketing company and the Yelp POI dataset.
Quantitative GITT analysis of a model system with applications to lithium-sulfur batteries

Galvanostatic Intermittent Titration Technique (GITT) is a powerful characterization tool for batteries that provides key thermodynamic and kinetic information about battery performance. However, the quantitative analysis of GITT measurements of lithiumsulfur batteries has so far been limited to the evaluation of the internal resistance of the cell and the equilibrium voltage profiles. In this work, we provide the mathematical framework to characterize the mass transport kinetics in lithium-sulfur batteries from GITT data and we demonstrate the validity of the approach via the application to a model and well-behaved system, ethyl viologen, whose diffusion coefficient is corroborated by cyclic voltammetry. The present approach is also advantageous for the analysis of ion-insertion electrodes, where non-linearity of concentration and voltage changes would produce unrealistic evaluations of the diffusion coefficient by the classical analysis of GITT data.
Resource Allocation Scheme for Hadoop in Campus Networks

On most campus networks, outdated computational resources are not used. This paper proposes a Hadoop-based resource allocation scheme for leveraging these outdated resources. The proposed scheme splits a computational job into tasks using appropriate splitting ratios based on computer processing performance and network resource availability. We compare our resource allocation scheme with a conventional scheme, which divides a job equally without consideration of computer processing performance and network resource availability. Both experiments and simulations are used to compare our proposed scheme and the conventional scheme. Simulation results show that the proposed scheme outperforms the conventional scheme in terms of job execution time.
Adoption of social media for scientific communication by PhD students: The case of the PhD in Education in the Knowledge Society

There is currently a consensus about the importance that social communication of science has in order to reach all audiences and add value to the researcher's work. PhD students that join the profession have a growing number of opportunities to form themselves in transversal communication and media competencies, including technologies such as social media, which strengthen their profile. The use of the most popular social media, such as Facebook, Twitter, Instagram or YouTube is already common in this new context. Previous studies have proven the existence of a relationship between the perception of obtaining future rewards with a technology (performance Expectancy), the difficulty its use implies (effort Expectancy) and the opinion of the social environment (social influence), and the real use of said technology. Based on the theoretical model of UTAUT (Unified Theory of Adoption and Use of Technologies), our hypothesis is that existence of an indirect conditional effect of the performance Expectancy, the effort Expectancy and the social influence over the real use of social media for science communication by PhD student, and that this effect is mediated by the intention of use and moderated by gender and age. Our goal is to analyze the mechanisms that cause said effect in doctoral students of the PhD in Education in the Knowledge Society of the University of Salamanca. We surveyed the 180 students of the program, so that we could know the level of adoption of social media for science dissemination and the variables that influence the intention of use and the real use of them. The UTAUT model is partially confirmed and the results of the moderated mediation prove that the performance Expectancy, the effort Expectancy and the social influence in the students affect the real use of these media.
WideSee: towards wide-area contactless wireless sensing

Contactless wireless sensing without attaching a device to the target has achieved promising progress in recent years. However, one severe limitation is the small sensing range. This paper presents WideSee to realize wide-area sensing with only one transceiver pair. WideSee utilizes the LoRa signal to achieve a larger range of sensing and further incorporates drone's mobility to broaden the sensing area. WideSee presents solutions across software and hardware to overcome two aspects of challenges for wide-range contactless sensing: (i) the interference brought by the device mobility and LoRa's high sensitivity; and (ii) the ambiguous target information such as location when employing just a single pair of transceivers. We have developed a working prototype of WideSee for human target detection and localization that are especially useful in emergency scenarios such as rescue search, and evaluated WideSee with both controlled experiments and the field study in a high-rise building. Extensive experiments demonstrate the great potential of WideSee for wide-area contactless sensing with a single LoRa transceiver pair hosted on a drone.
rban ragweed populations in vacant lots : An ecological perspective n management aniel

Ragweed (Ambrosia artemisiifolia L.) is one of the most prolific producers of allergenic pollen in North America, and negatively impacts tens of millions of people each year. Recent work shows that local plant populations can be the most important source of allergenic pollen in the urban environment. This research emphasizes that management choices that influence species abundance can determine the burden of allergenic pollen for people living near these plant populations. In Detroit, MI, USA, ragweed populations are predominantly found in vacant lots; the management of these lots could therefore have large impacts on allergenic pollen burdens. The main form of management in these vacant lots is mowing, which occurs at frequencies ranging from monthly mowing to no mowing. We hypothesized that annual or biennial mowing would result in conditions where ragweed populations could thrive. To test this, we conducted a vegetation survey of vacant lots in Detroit, in which we quantified the mowing regime, characteristics of the vegetation, and ragweed presence and stem density. We found that ragweed was significantly more likely to be present in lots that were mowed annually or biennially; unfortunately these are the most common management types, accounting for 51% of vacant lots in Detroit. Ragweed’s association with this disturbance regime fits with its early successional status, as it is most competitive in recently disturbed soils where there is reduced competition for resources such as light. We therefore recommend one of two alternative management regimes for reducing ragweed in vacant lots: either mow them frequently (multiple times a growing season) or do not mow them at all. Both approaches will reduce ragweed prevalence in vacant lots and reduce allergenic pollen exposure for people who live near vacant lots. © 2014 Elsevier GmbH. All rights reserved.
Breaking vs. solving: analysis and routing of real-time networks with cyclic dependencies using network calculus

Distributed real-time systems in the aerospace domain require worst-case end-to-end latency analysis methods to provide certification evidence of the correct temporal behavior of critical traffic classes. One such analysis method is the Network Calculus framework. While the Network Calculus analysis is mature enough to be allowed in certification artefacts, it is only applied in networks where there are no cyclic dependencies between communication flows (so-called feed-forward networks). In general topologies, flows can form cyclic dependencies, making it difficult to prove the determinism of a network. There are two approaches to solve this problem: 1) breaking the dependencies in the routing algorithm to study a feed-forward network; 2) solving, i.e., computing the bounds, in the dependency. In this paper, we review the recent improvements of both methods and do a performance analysis of AFDX and TTEthernet networks to compare their impact on the worst-case delay and backlog bounds. Results show that the best method depends on a number of parameters, such as load and dependency length. Using these results, we propose a new routing methodology resulting in the lowest bounds for networks with cyclic dependencies.