Miracle-dz/UniFAR-FTUs huggingface dataset:
Transport Infrastructure Investment and Interindustry Spillovers: The Effects on the Cost Structure of Australian Industries

This paper examines the impact of the provision of public transport infrastructure on the cost structure of the Australian economy within a context that recognises industry agglomeration externalities. The paper extends the symmetric generalised quadratic cost functionby incorporating public transportation capital as an external input and adapting the spatial econometric techniques to an industrial context to allow for industry spillovers in the cost analysis. Using industry level data over the period 1990-2010, the paper finds that while public transport has a productive effect in reducing the cost of production, neglecting interindustry spillovers has noticeably overestimates this effect.
Nuclear site remediation : first accomplishments of the Environmental Management Science Program

This is a record of the first scientific results for the coordinated environmental science program currently sponsored by the US Department of Energy. The purpose of the program is to lay the foundation for remediating the nuclear weapons production legacy in the Unived States, the most expensive environmental program ever attempted. The papers presented in this volume cover actinide, inorganic, analytical, physical, biogeochemistry, and seperative chemistry areas of this program.
Allan Gurwicz Deep Generative Models for Reservoir Data: An Application in Smart Wells

Gurwicz, Allan; Pacheco, Marco Aurélio Cavalcanti (Advisor); Abreu, Ana Carolina Alves (Co-advisor); Canchumuni, Smith Washington Arauco (Co-advisor). Deep Generative Models for Reservoir Data: An Application in Smart Wells. Rio de Janeiro, 2020. 84p. Dissertação de mestrado – Departamento de Engenharia Elétrica, Pontifícia Universidade Católica do Rio de Janeiro. Reservoir simulation, which via complex equations emulates flow in reservoir models, is paramount to the Oil & Gas industry. By estimating the behavior of the reservoir given different input conditions, it allows specialists to optimize various parameters in the oilfield project stage. Alas, the computational time needed for simulations is directly correlated to the complexity of the model, which grows exponentially with each passing day as more intricate and detailed reservoir models are needed, seeking better refinement and uncertainty reduction. As such, optimization techniques which could greatly improve the results of field developments may be made unfeasible. This work proposes the use of deep generative models for the generation of reservoir data, which may then be used for multiple purposes. Deep generative models are systems capable of modeling complex data structures, which after robust training are capable of sampling data following the same distribution of the original dataset. The present application focuses on smart wells, a technology for completions which brings about a plethora of advantages, among which the better ability for reservoir monitoring and management, although also carrying a significant increase in project investment. As such, these previously mentioned optimizations turn indispensable as to guarantee the adoption of the technology, along with its maximum possible return. As to make smart well control optimizations viable within a reasonable time frame, generative adversarial networks are here used to sample datasets after a relatively small number of simulated scenarios. These datasets are then used for the training of proxies, algorithms able to substitute the reservoir simulator and considerably speed up optimization methodologies. Case studies were done in both relatively simple and complex industry benchmark models, comparing network architectures and validating each step of the methodology. In the complex model, closest to a real-world scenario, the methodology was able to reduce the proxy error from an average of 18.93%, to 9.71%.
University of Birmingham EEG-based brain connectivity analysis of states of unawareness

—This work investigates phase synchrony as a neuro-marker for the identiﬁcation of two brain states: coma and quasi-brain-death. Scalp electroencephalography (EEG) data of 34 patients were recorded in an intensive care unit (ICU), with 17 recordings for patients in a coma state, and 17 recordings for patients in a quasi-brain-death state. Phase synchrony was used for feature extraction from EEG recording by comparing the phase value between pairs of electrodes using an entropy based measure. In particular, we performed phase synchrony analysis in ﬁve standard frequency bands and provide visualization of the phase synchronies in matrices. The effectiveness of the phase synchrony features in each of the frequency bands are evaluated with statistical analysis. Results suggest functional connectivity measured by phase synchrony for coma patients has a signiﬁcant increase in the theta / alpha band compared to quasi-brain-death patients. Hence, we propose phase synchrony as a candidate for the identiﬁcation of consciousness states between coma and quasi-brain-death.
Validation of the atherosclerotic cardiovascular disease Pooled Cohort risk equations.

IMPORTANCE The American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort risk equations were developed to estimate atherosclerotic cardiovascular disease (CVD) risk and guide statin initiation. OBJECTIVE To assess calibration and discrimination of the Pooled Cohort risk equations in a contemporary US population. DESIGN, SETTING, AND PARTICIPANTS Adults aged 45 to 79 years enrolled in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study between January 2003 and October 2007 and followed up through December 2010. We studied participants for whom atherosclerotic CVD risk may trigger a discussion of statin initiation (those without clinical atherosclerotic CVD or diabetes, low-density lipoprotein cholesterol level between 70 and 189 mg/dL, and not taking statins; n = 10,997). MAIN OUTCOMES AND MEASURES Predicted risk and observed adjudicated atherosclerotic CVD incidence (nonfatal myocardial infarction, coronary heart disease [CHD] death, nonfatal or fatal stroke) at 5 years because REGARDS participants have not been followed up for 10 years. Additional analyses, limited to Medicare beneficiaries (n = 3333), added atherosclerotic CVD events identified in Medicare claims data. RESULTS There were 338 adjudicated events (192 CHD events, 146 strokes). The observed and predicted 5-year atherosclerotic CVD incidence per 1000 person-years for participants with a 10-year predicted atherosclerotic CVD risk of less than 5% was 1.9 (95% CI, 1.3-2.7) and 1.9, respectively, risk of 5% to less than 7.5% was 4.8 (95% CI, 3.4-6.7) and 4.8, risk of 7.5% to less than 10% was 6.1 (95% CI, 4.4-8.6) and 6.9, and risk of 10% or greater was 12.0 (95% CI, 10.6-13.6) and 15.1 (Hosmer-Lemeshow χ2 = 19.9, P = .01). The C index was 0.72 (95% CI, 0.70-0.75). There were 234 atherosclerotic CVD events (120 CHD events, 114 strokes) among Medicare-linked participants and the observed and predicted 5-year atherosclerotic CVD incidence per 1000 person-years for participants with a predicted risk of less than 7.5% was 5.3 (95% CI, 2.8-10.1) and 4.0, respectively, risk of 7.5% to less than 10% was 7.9 (95% CI, 4.6-13.5) and 6.4, and risk of 10% or greater was 17.4 (95% CI, 15.3-19.8) and 16.4 (Hosmer-Lemeshow χ2 = 5.4, P = .71). The C index was 0.67 (95% CI, 0.64-0.71). CONCLUSIONS AND RELEVANCE In this cohort of US adults for whom statin initiation is considered based on the ACC/AHA Pooled Cohort risk equations, observed and predicted 5-year atherosclerotic CVD risks were similar, indicating that these risk equations were well calibrated in the population for which they were designed to be used, and demonstrated moderate to good discrimination.
A Noninvasive Method for Measuring the Blood Glucose Level Using a Narrow Band Microstrip Antenna

– In this paper, a narrowband and compact antenna resonating at 6.1 GHz with a peak realized gain of 3.3 dBi is proposed to monitor the glucose concentration in the blood without taking invasive blood samples. The proposed antenna is fabricated using a low-cost FR-4 substrate with compact dimensions of 30 mm × 30 mm × 1.6 mm. The impedance bandwidth of this antenna ranges from 5.2 to 7.1 GHz. For measuring blood glucose levels, a human ﬁnger phantom model with dimensions of 15 mm × 12 mm × 10 mm is constructed using the EM simulation (HFSS) environment. The ﬁn-ger phantom consists of different layers such as skin, fat, muscle, blood, and bone modeled at 6.1 GHz using various dielectric materials for various glucose concentrations. The ﬁnger phantom model is placed at different locations around the antenna to measure the frequency shift for monitoring glucose concentration in blood samples. The proposed ﬁnger phantom model is validated by conducting an experimental study by placing a real human ﬁnger around the fabricated antenna and measuring the frequency shift. This study shows a very good agreement with the results obtained by the simulated phantom model. The advantages and outperformance of the proposed sensor are highlighted in terms of the sensitivity obtained and compared with other techniques given in the literature.
Integrated Active Pulsed Reflector for an Indoor Local Positioning System

This paper presents an indoor localization system based on a frequency modulated continuous wave radar in the industrial-scientific-medical band at 5.8 GHz. An integrated active pulsed reflector behaves as a backscatter by regenerating the incoming phase with phase coherent startup at a constant frequency. The base station (BS) determines the distance to this reflector with a round-trip time-of-flight measurement. The active pulsed reflector is built around a switchable and tunable oscillator. The circuit has been fully integrated in a 0.18-¿m CMOS technology. Outdoor measurements revealed a positioning accuracy of 15 cm, while in a harsh multipath environment with omnidirectional antennas a positioning accuracy of 32.88 cm was measured. The localization system is capable of detecting multiple reflectors at the same time, and no synchronization between BSs is needed.
Predictive Value of Implicit and Explicit Self-Esteem for the Recurrence of Depression and Anxiety Disorders

Anxiety and depressive disorders are characterized by high rates of recurrence, substantially contributing to the high burden associated with these disorders. It is therefore crucial to identify factors related to recurrence, as they may provide viable targets for preventative intervention. Previous studies have observed a link between low self-esteem and subsequent symptoms of depression and anxiety, and low levels of self-esteem in those recovered from a depression or an anxiety disorder. Research also suggests that it is crucial to differentiate more explicit self-esteem (ESE) from more implicit self-esteem (ISE). The current study is the first to test whether ISE and ESE predict recurrence of depression and recurrence of anxiety during a 3-year follow-up as determined with clinical interviews. The sample included those with a history of a depressive disorder ( n (cid:2) 559) and/or a history of an anxiety disorder ( n (cid:2) 458) who had been depression-and anxiety-free for at least six months at baseline. During the 3-year follow-up, 119 (21%) and 104 (23%) had a depression and anxiety recurrence, respectively. ISE predicted recurrence of both depression and anxiety, even when statistically controlling for residual symptoms and neuroticism at baseline. ESE also showed predictive value, although this was not over and above residual symptoms. Explorative analyses suggest that ESE and ISE improved little, or not at all, from currently having a depression or anxiety disorder to recovery. These results therefore suggest that ISE may be an important target for interventions to prevent the recurrence of both depression and anxiety disorders.
What Are We Talking About When We Talk Study on a Definition

In Sweden, the term information-driven care has recently been put forward by healthcare organizations and researchers as a means for taking a comprehensive approach to the introduction of Artificial Intelligence (AI) in healthcare. The aim of this study is to systematically generate a consensus definition of the term information-driven care. To this end, we are conducting a Delphi study utilizing literature and experts’ opinions. The definition is needed to enable knowledge exchange on information-driven care and operationalize its introduction into healthcare practice.
Student interpreters’ strategies in dealing with unfamiliar words in sight translation

: This research investigated student interpreters’ strategies in dealing with unfamiliar words in the source texts during English-to-Mandarin (B-to-A) sight translation. The study examined and compared different strategies adopted by 10 first-year beginner student interpreters who had not yet attained NAATI Professional Interpreter accreditation and 10 advanced student interpreters who, after studying for a year and a half, had achieved a credential as NAATI Professional Interpreter in Australia. The data collection involved an English vocabulary test, three English-to-Mandarin sight translation tasks and retrospective interviews. Results showed that both groups of student interpreters tended to omit the unfamiliar English words. The advanced student interpreters made more strategic omissions of unfamiliar words in the source texts than the beginner student interpreters, whose work showed more passive involuntary omissions of unfamiliar English words than that of the advanced student interpreters. Both groups also made attempts to infer the meaning of unfamiliar words. The predominant types of inference strategies were based on participants’ experience, reading-based contextual knowledge and collocation knowledge. As there has been little research on sight translation, this small-scale empirical study attempts to bridge this gap and inspire other researchers to further explore this area by carrying out larger-scale projects.
OILS AS MOSQUITO REPELLENTS

: The mosquitoes are a serious threat to public health, since they are known vectors of many life-threatening diseases. Mosquito-borne diseases cause mi llions of deaths worldwide every year. While mosquitoes are important to maintain ecosystems, the aim is to keep them out of our personal space. People looking for alternatives to synthetic mosquito repellents may ﬁ nd that some natural repellents are eﬀ ective in protecting them from bites. Natural insect repellents use natural ingredients such essential oils and other plant-based elements. Certain essential oils are eﬀ ective and helpful in repelling mosquitoes, and are a natural alternative to the harsh chemicals in commercial bug sprays. These products are also likely to be less toxic to humans and the environment. Natural repellents and some essential oils may be eﬀ ective in keeping mosquitoes away because they block their sense of smell. Many natural scents that are appealing to humans actually repel mosquitoes. Plant - based repellents are becoming more widely used as a protecting measure against mosquito bites, but more research is needed to develop natural repellents in terms of improving their repellent eﬃ ciency as well as in terms of their safety for use. This article presents a review about the best essential oils used as green repellents against mosquito bites, their eﬃ ciency, development and testing.
Volume 37

In the literature related to choice theory an important problem which has been dealt with at length is the rationalizability of the choice function of an individual. In the literature a number of choice consistency conditions have been postulated which are proven to be necessary and sufficient for a choice function to have an ordering rationalization. In this paper a necessary and sufficient condition has been derived for the domain to be such that every possible choice function defined over the domain has an ordering rationalization
Panorama des outils de visualisation pour l'explicabilité en apprentissage profond pour le traitement automatique de la langue

The advent of Artificial Intelligence (AI), and more specifically of deep learning models, has been accompanied by impressive results in the field of Natural Language Processing (ALP). Behind the performance of neural networks lie many issues, such as interpretability. In this state of the art article, we present an overview of visualization tools specific to the explicability of deep learning methods in NLP, which aim to overcome the black box character of these approaches.
The Competition on Automatic Classification of Literary Epochs

This paper describes the shared task on Automatic Classification of Literary Epochs (CoLiE) held as a part of the 1st International Workshop on Implicit Author Characterization from Texts for Search and Retrieval (IACT’23) held at SIGIR 2023. The competition aimed to enhance the capabilities of largescale analysis and cross-comparative studies of literary texts by automating their classification into the respective epochs. We believe that the competition contributed to the field of information retrieval by exposing the first large benchmark dataset and the first study’s results with various methods applied to this dataset. This paper presents the details of the contest, the dataset used, the evaluation procedure, and an overview of participating methods.
School effectiveness for ESD: What characterizes an ESD-effective school organization?

: While research on education for sustainable development is expanding, empirical evidence on its impact and outcomes remains very limited. Moreover, the facilitating role of the school organization, while extensively documented in literature on school management and school effectiveness, is lacking. In this study we present and qualitatively validate a framework for an ESD-effective school, previously developed via a critical review of ESD and school management literature. This framework consists of eight characteristics: sustainable leadership; school resources; pluralistic communication; supportive relations; collective efficacy; adaptability; democratic decision-making; and shared vision. Via semi-structured interviews, the framework for an ESD-effective school was theoretically validated via a sample of nineteen teachers and school leaders with expertise on education for sustainable development. The findings from the interviews show that the participants largely confirm the framework and the individual characteristics are recognized by the sample. There were relevant differences between the respondents in terms of positioning the different characteristics within the framework. Specifically, views on pluralistic communication differed from the initial conceptual framework.
Relating evaporative fraction to remotely sensed data at the FIFE site

Evaporative fractions at surface flux stations on the Konza Prairie are investigated by means of heat-flux estimation, evaporative fractions, and other remotely sensed parameters. Radiometric surface-temperature measurements are used to calculate sensible heat, and evaporative fraction is characterized by comparing systematic differences and consistencies at 21 stations. The evaporative fractions are related to soil and vegetation data collected concurrently with attention given to specific correlations. Little variation is found in the evaporative fraction during the day for the four periods studied, although the most significant change corresponded with the lowest values of soil moisture, leaf-area indices, and simple ratio. Uncertainties in air/surface temperature differences and in small wind speeds affect the reliability of estimates of the surface fluxes.
Consumers ’ inflation expectations and monetary policy in Europe

Outline This paper analyses the effects of monetary policy decisions on inflation expectations of European consumers. Using a novel approach that does not assume unbiasedness of expectations, which makes use of survey data on expected future as well as perceived past price developments and allows for non-normal peakedness and asymmetry, we convert qualitative survey responses of consumers in various European countries into quantitative time series of inflation expectations. After checking the rationality of the constructed expectations measures, we investigate the effects of unanticipated movements in interest rates and inflation on inflation expectations across European countries. We inter alia seek to explore whether the reaction of consumers in countries with more credible central banks differs from the reaction of consumers in less credible countries. the European System of Central Banks (ESCB) is the rapid acquisition and maintenance of credibility for achieving price stability. Indeed, the credibility of the central bank is probably the single most important factor determining whether the pursuit of an anti-inflation policy is associated with significant output and employment losses. ' When the central bank lacks credibility, when the public does not believe that the central bank is going to do what it says it is going to do, expected inflation in the private sector will exceed the central bank's objective for inflation. These expectations will feed into the wage and price decisions of households and firms, causing some workers and businesses to price their goods and services too high. The attendant decline in employment and real activity complicates the environment for monetary policy, making the central bank's job more difficult. Thus the public's expectations of inflation need to be taken into account by the central bank when determining the stance of monetary policy, in order to Moreover, central banks need to assess the credibility of their monetary policy on an ongoing basis, and a key to this assessment is knowing how the inflation expectations of the general public compare with the price stability objective pursued by the central bank. However, measures of expected inflation are also of interest by themselves, as forecasting inflation is a major task of any central bank. Measures of expected inflation will play an important role in any such exercise, given that what firms and households expect inflation to be over various horizons influences their wage and price decisions, thereby feeding into the measured inflation rate. Broadly speaking, there are two approaches to gauging …