Miracle-dz/UniFAR-FTUs huggingface dataset:
Power-law models of totally anisotropic scattering

The interstellar scattering responsible for pulsar parabolic arcs, and for intraday variability of compact radio quasars, is highly anisotropic in some cases. We numerically simulate these observed phenomena using totally anisotropic, power-law models for the electron density fluctuations which cause the scattering. By comparing our results to the scattered image of PSR B0834+06 and, independently, to dual-frequency light curves of the quasar PKS 1257−326, we constrain the nature of the scattering media on these lines of sight. We find that models with spectral indices slightly below β = 3, including the one-dimensional Kolmogorov model, are broadly consistent with both data sets. We confirm that a single physical model suffices for both sources, with the scattering medium simply being more distant in the case of B0834+06. This reinforces the idea that intraday variability and parabolic arcs have a common cause in a type of interstellar structure which, though obscure, is commonplace. However, the implied gas pressure fluctuations are large compared to typical interstellar pressures, and the magnetic stresses are much larger still. Thus while these scattering media may be commonplace, their underlying dynamics appear quite extraordinary.
Solar Irradiance Forecasting and Implications for Domestic Electric Water Heating

Due to increasing concerns associated with climate change and global warming there has been a renewed interest in renewable energy resources. As most of the power production in the United States stems from the use of fossil fuels, it is desirable to pursue alternative power production avenues. For example, within the home, the domestic electrical water heater accounts for approximately seventeen percent of its total energy consumption. Reducing the amount of energy required to produce hot water from this thermal system alone can have a significant effect on reducing its carbon footprint. In this work, a modeled domestic electrical water heater was supplied photovoltaic and on-grid electrical power to increase its energy efficiency. As photovoltaic energy is directly related to solar irradiation, it is important to receive accurate solar irradiance data for the area and to forecast future solar irradiance availability. As such, a solar irradiance monitoring station, with Baseline Surface Radiation Network level performance was installed locally. Based on this real-time local data, future solar irradiance data was predicted via an artificial neural network method. If solar irradiance data can be predicted accurately then so can future photovoltaic output. It was found that local irradiance data could be accurately predicted and incorporated in a model to predict photovoltaic power output. As the photovoltaic power output could be predicted, so could the energy savings of a domestic electric water heater operating both on-grid and on photovoltaic power. INDEX WORDS: Artificial Neural Network, NAR, NARX, Domestic Electric Water Heat, Solar Irradiance Forecasting, Solar Energy, Thesis, College of Graduate Studies, Georgia Southern University SOLAR IRRADIANCE FORECASTING AND IMPLICATIONS FOR DOMESTIC ELECTRIC WATER HEATING by
EFFECTS OF BILINGUALISM ON INHIBITORY CONTROL AND WORKING MEMORY: A STUDY WITH EARLY AND LATE BILINGUALS

A dense body of research shows that cognitive functions change with age. More recently, studies have provided evidence that bilingualism aids in offsetting age-related losses in executive function (Bialystok, Craik, Klein & Viswanathan, 2004; Salvatierra, 2010). The present study investigates the performances of early bilinguals (Brazilian Portuguese/Hunsruckisch), late bilinguals (Brazilian Portuguese/English), and monolinguals (Brazilian Portuguese) on executive control and working memory tasks. Participants (N = 104) performed an executive control task (Simon) and a working memory (Alpha Span) task. Statistical analyses showed significant age-related effects on executive functions: younger adults outperformed older adults in the tasks. Furthermore, early bilinguals presented more efficient inhibitory processes showing smaller Simon effect costs and higher working memory span than monolinguals. As for the late bilingual group, their performance on inhibitory control tasks was significantly faster than that of their peer monolingual group. Results suggest that bilingualism, regardless of the context and age of acquisition, has an effect on inhibitory control and working memory.
Toward a Neural Aggregated Search Model for Semi-structured Documents

One of the main issues in aggregated search for XML documents is to select the relevant elements for information need. Our objective is to gather in same aggregate relevant elements that can belong to different parts of XML document and that are semantically related. To do this, we propose a neural aggregated search model using Kohonen self-organizing maps. Kohonen self-organizing map lets classification of XML elements producing density map that form the foundations of our model.
Improving time-delay cosmography with spatially resolved kinematics

Strongly gravitational lensed quasars can be used to measure the so-called time-delay distance $D_{\Delta t}$, and thus the Hubble constant $H_0$ and other cosmological parameters. Stellar kinematics of the deflector galaxy play an essential role in this measurement by: (i) helping break the mass-sheet degeneracy; (ii) determining in principle the angular diameter distance $D_{\rm d}$ to the deflector and thus further improving the cosmological constraints. In this paper we simulate observations of lensed quasars with integral field spectrographs and show that spatially resolved kinematics of the deflector enable further progress by helping break the mass-anisotropy degeneracy. Furthermore, we use our simulations to obtain realistic error estimates with current/upcoming instruments like OSIRIS on Keck and NIRSPEC on the James Webb Space Telescope for both distances (typically $\sim6$ per cent on $D_{\Delta t}$ and $\sim10$ per cent on $D_{\rm d}$). We use the error estimates to compute cosmological forecasts for the sample of nine lenses that currently have well measured time delays and deep Hubble Space Telescope images and for a sample of 40 lenses that is projected to be available in a few years through follow-up of candidates found in ongoing wide field surveys. We find that $H_0$ can be measured with 2 per cent (1 per cent) precision from nine (40) lenses in a flat $\Lambda$cold dark matter cosmology. We study several other cosmological models beyond the flat $\Lambda$cold dark matter model and find that time-delay lenses with spatially resolved kinematics can greatly improve the precision of the cosmological parameters measured by cosmic microwave background data.
Comparative urban institutions and intertemporal externality: a revisit of the Coase conjecture

Abstract Coase originally formulated his conjecture about intertemporal price competition in an example of land monopoly, but it has been applied almost exclusively to non-spatial markets. This paper revisits the Coase conjecture and compares four institutional arrangements based on the combination of land tenure options and local governance forms: private/rental, public/rental, private/owner, and public/owner. The two-period model developed in this paper shows that homeownership may result in more land development than leasehold. Numeric examples suggest (1) public/owner is efficient for uniform distribution of consumer; (2) rentals can be desirable for ‘poor’ communities; (3) private/owner is more efficient for ‘rich’ communities; (4) restrictive zoning reduces social surplus. These results can help explain why public institutions are dominant in the urban area and why most private communities are small, located in the suburbs, and for middle-upper class.
Synthesis and characterization of copper ferrite magnetic nanoparticles by hydrothermal route

Secondary treatment of heavy metal bearing solutions requires highly expensive procedures including the application of ionic exchange resins or activated carbon packed in fixed bed reactors. The use of nanoparticles with magnetic properties as adsorbents can improve metal removal performances allowing for the achievement of high specific surface area. In addition, the simplification of the final solid-liquid separation by magnetic field can avoid the application of packed bed columns. In this study a simple synthetic pathway was optimized to produce copper nanoferrites (CuFe2O4), stable in water, magnetically active and with high specific area, to be further used as sorbent material for heavy metal removal in water solution. The hydrothermal route included surfactant-assisted coprecipitation (performed at different pH), hydrothermal treatment (1h at 120°C), washing with water and hexane, drying, and sintering (performed at 100 and 200°C for 1h). Structure and sizes of CuFe2O4 crystallites were studied as function of coprecipitation pH (8, 10, and 12.5) and sintering temperature (100-200°C). CuFe2O4 powders were characterized by field emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDX), Brunauer-EmmettTeller (BET) analysis of porosimetric data. Releasing tests of Fe and Cu at different pH were performed to define the pH range of stability in water. Potentiometric titrations were performed to determine the net charge depending on bulk solution pH. Best samples in terms of magnetic characteristics were obtained at pH 12.5 not depending on the sintering temperature. Mean size of nanoparticles obtained in such conditions was estimated by SEM images as 35-45 nm. BET analysis gave specific surface area of 147.8 ± 0.2 m2/g. CFNs have shown chemical stability in water solutions from pH 6 to 10. Zero charge point was estimated as pH 5.5. Then in the stability range of pH, CFNs present negative surface charge being able to coordinate positively charged heavy metal species.
Experimental studies of the phase transition in YbIn 12x Ag x Cu 4

We report measurements of the low-temperature specific-heat coefficientg5Cp(T)/T, cell volume V(T), Hall coefficient RH(T), and valence z521n f @where the Yb hole occupation n f (T) was determined from Yb-L3 x-ray absorption# of single crystals of YbIn12xAgxCu4. Alloying YbInCu4 with Ag increases the temperature Ts(x) of the first-order isomorphic phase transition and causes it to terminate at a critical point at xc50.195 and Tc577 K. The variation of V(T) near the critical point is well described by a mean-field equation of state. The phase transition involves a large change in the Kondo temperature, and the transition temperatures Ts(x) are of order of the Kondo temperatures TK (x) of the high-temperature state. The cell volume is found to vary proportionally to 1 2n f (T). At low temperatures, well away from the transition, the Wilson ratio of the susceptibility x~0! and specific heat coefficientg falls within 20% of the value predicted for a Kondo impurity, and 12n f (0) and x~0! are roughly proportional as predicted from the Anderson model. The temperature dependence n f (T) for temperatures away from the phase transition also fits the predictions of the Kondo model. The small volume discontinuity DV/V0 observed at Ts suggests that the phase transition is not due to a Kondo volume collapse. The large Hall coefficientsRH(T) observed for x,xc and T.Ts(x) suggest instead that a low carrier density in the high-temperature state plays a key role in the phase transition. @S0163-1829~97! 08436-1#
Hybrid control for low-regular nonlinear systems: application to an embedded control for an electric vehicle

This note presents an embedded automatic control strategy for a low consumption vehicle equipped with an " on/off " engine. The main difficulties are the hybrid nature of the dynamics, the non smoothness of the dynamics of each mode, the uncertain environment, the fast changing dynamics, and low cost/ low consumption constraints for the control device. Human drivers of such vehicles frequently use an oscillating strategy, letting the velocity evolve between fixed lower and upper bounds. We present a general justification of this very simple and efficient strategy, that happens to be optimal for autonomous dynamics, robust and easily adaptable for real-time control strategy. Effective implementation in a competition prototype involved in low-consumption races shows that automatic velocity control achieves performances comparable with the results of trained human drivers. Major advantages of automatic control are improved robustness and safety. The total average power consumption for the control device is less than 10 mW.
Optimization of Redundancy Allocation Problem with Defuzzified Fuzzy Reliabilities

Generally, in the existing literature, the reliability of each component is considered to be precise number or fixed real number in terms of probability lying in the interval [0,1]. The reliability of a system represents the probability of successful operation of the system under stated conditions upto a given period of time. However, in real life situation, we observe that all the physical phenomena are uncertain in nature and they cannot be predicted exactly and they have some uncertainty. Thus, it is well to consider the component reliability as the imprecise numbers in terms of fuzzy numbers. In this paper we have considered the redundancy allocation problem of complex system with ten subsystems connected in parallel with identical components. The reliability of each component is considered to be imprecise. This impreciseness has been represented in terms of several fuzzy numbers. After, the problem under consideration has been changed to crisp constrained optimization problem using different defuzzification methods. The transformed problem has been converted into unconstrained optimization problem with the help of Big-M penalty technique and has been solved by real coded genetic algorithm with advanced operators. Also a numerical example has been solved for different defuzzification methods and the obtained results have been compared.
Characterization of the seed oils from kiwi (Actinidia chinensis), passion fruit (Passiflora edulis) and guava (Psidium guajava)

Oils extracted from three exotic fruits, guava, kiwi and passion fruit were analyzed to evaluate the possible commercial interest for these waste materials from fruit juices industry. Results showed interesting fatty acids compositions with high amounts of essential fatty acids such as 62.3% alpha linolenic acid for kiwi seed oil, and respectively 73.4% and 77.0% for omega 6 linoleic acid in passion fruit and guava seed oils. Fatty acids regiodistribution, sterols and tocopherols contents were also analyzed to try to establish the potential nutritional interest of such oils.
Land-use and land-cover change carbon emissions between 1901 and 2012 constrained by biomass observations

Abstract. The use of dynamic global vegetation models (DGVMs) to estimate CO2 emissions from land-use and land-cover change (LULCC) offers a new window to account for spatial and temporal details of emissions and for ecosystem processes affected by LULCC. One drawback of LULCC emissions from DGVMs, however, is lack of observation constraint. Here, we propose a new method of using satellite- and inventory-based biomass observations to constrain historical cumulative LULCC emissions (ELUCc) from an ensemble of nine DGVMs based on emerging relationships between simulated vegetation biomass and ELUCc. This method is applicable on the global and regional scale. The original DGVM estimates of ELUCc range from 94 to 273 PgC during 1901–2012. After constraining by current biomass observations, we derive a best estimate of 155 ± 50 PgC (1σ Gaussian error). The constrained LULCC emissions are higher than prior DGVM values in tropical regions but significantly lower in North America. Our emergent constraint approach independently verifies the median model estimate by biomass observations, giving support to the use of this estimate in carbon budget assessments. The uncertainty in the constrained ELUCc is still relatively large because of the uncertainty in the biomass observations, and thus reduced uncertainty in addition to increased accuracy in biomass observations in the future will help improve the constraint. This constraint method can also be applied to evaluate the impact of land-based mitigation activities.
Managing disaster knowledge: identification of knowledge factors and challenges

Purpose – Knowledge management can play a vital role through ensuring the availability and accessibility of accurate and reliable disaster risk information when required and through effective lesson learning. Identification of key disaster knowledge factors will be an enabler to manage disasters successfully. The purpose of this paper is to present key knowledge factors relating to disaster management cycle, and explore a few challenges relating to identified disaster knowledge factors.Design/methodology/approach – A list of disaster knowledge factors was first identified through a comprehensive literature review and later semi‐structured interviews were conducted among few disaster management practitioners to explore the influence and challenges relating to identified knowledge factors.Findings – Technological, operational/managerial, economic, social, legal and environmental factors seem to have direct influence over the disaster management cycle, while the influence of institutional and political facto.
Golden Natural Plant Compounds Activate Apoptosis via BothMitochondrial and Death Receptor Pathways: A Review

Apoptosis (programmed cell death) is an intricate process that involves multiple signaling pathways, and failure to activate apoptosis is one of the main obstacles in cancer treatment. The apoptosis resistance of cancer cells is an inherent part of the carcinogenic process, which is also associated with chemotherapy resistance. Therefore, new drugs are required to improve cytotoxicity to cancer cells without affecting normal cells. The current knowledge of apoptosis is the theoretical source for novel and effective treatments with the selective induction of apoptosis in cancer cells and augmentation of the cytotoxicity of established chemotherapeutic agents. Based on these goals of treatment for cancer, recent attention has focused on the phytochemicals as anticancer agents. For that reason, designing new anti-tumor agents must include recognizing and developing those agents that have the ability to target various genes that regulates apoptosis. There are several natural plant compounds that demonstrate anti-tumor activity, according to various mechanisms. In view of the immense medicinal importance of natural products, this review strives to compile a brief statement on the mechanisms of apoptosis and effective natural compounds that induce apoptosis through both mitochondrial and death receptor pathways.
Amenability and geometry of semigroups

We study the connection between amenability, Folner conditions and the geometry of finitely generated semigroups. Using results of Klawe, we show that within an extremely broad class of semigroups (encompassing all groups, left cancellative semigroups, finite semigroups, compact topological semigroups, inverse semigroups, regular semigroups, commutative semigroups and semigroups with a left, right or two-sided zero element), left amenability coincides with the strong Folner condition. Within the same class, we show that a finitely generated semigroup of subexponential growth is left amenable if and only if it is left reversible. We show that the (weak) Folner condition is a left quasi-isometry invariant of finitely generated semigroups, and hence that left amenability is a left quasi-isometry invariant of left cancellative semigroups. We also give a new characterisation of the strong Folner condition in terms of the existence of weak Folner sets satisfying a local injectivity condition on the relevant translation action of the semigroup.
Towards a System Engineering Approach to Master Safety and Security

The main objectives of this article are to highlight the importance of orchestrating safety and security activities in complex projects, and to provide associated directions and exploratory elements. A first step is the definition of a common ontology as a high level conceptual harmonization of safety and security. As a second step, we illustrate how such a unified perspective can be leveraged to better coordinate and optimize risk categorization and risk treatment. Then, we explore more particularly the formal modeling approaches applied to safety and security, and illustrate them through the example of the BDMP (Boolean logic Driven Markov Processes) formalism. Finally, we explain how System Engineering approaches may facilitate the harmonization of safety and security in the context of multidisciplinary projects through a collaborative platform.
A Novel Learning Rate Decay Function of Kohonen Self-Organizing Maps Using the Exponential Decay Average Rate of Change for Image Clustering

Clustering requires efficient selection of similarities among sample vectors and true clustering capability of the algorithm. The Kohonen Self-Organizing Maps is the most preferred unsupervised Artificial Neural Network clustering algorithm for high-dimensional or multi-dimensional data. This study introduces a new way of improving the clustering capability of the algorithm by enhancing its learning rate decay function to decrease its learning rate gradually as the training goes on through the use of the Exponential Decay Average Rate of Change. The new function allows the Enhanced Kohonen Self-Organizing Maps algorithm to converge to the minimum producing a more robust clustered datasets. The enhanced algorithm and the conventional algorithm were applied for image clustering, and the EKSOM remarkably outperformed the clustering capability of the KSOM. The introduction of EDARC function paves the way to explore the clustering and classification capability of KSOM further.
Impaired renal function in a rural Ugandan population cohort

Background: Kidney disease is an important cause of morbidity and mortality globally. However, there are limited data on the prevalence of impaired kidney function in sub-Saharan Africa. We aimed to determine the prevalence of reduced kidney function and associated factors in a rural Ugandan population. Methods: We undertook a study of a representative sample of the General Population Cohort in South-western Uganda. We systematically collected data on cardiovascular disease risk factors, anthropometric measurements and blood tests including haemoglobin, HIV, HbA1c and serum creatinine. The estimated glomerular filtration rate (eGFR) was calculated using the CKD-Epi equation, without the race component of the equation. Results: A total of 5,979/6,397 (93.5%) participants had valid creatinine results. The mean age was 39 years (Range:16-103 years) and 3,627 (60.7%) were female. HIV prevalence was 9.7% and about 40% of the population were pre-hypertensive or hypertensive. The mean serum creatinine level was 0.75 mg/dl (95% CI 0.74–0.75), and the average eGFR was 109.3 ml/min/1.73 m 2 (95% CI 108.8–109.9). The overall prevalence of eGFR <60 ml/min/1.73 m 2 was 1.64% (98/5,979) (95% CI 1.34–1.99). Additionally, 4,792(80.2%) were classified as normal eGFR (≥90 ml/min/1.73 m 2), 1,089(18.2%) as low eGFR (60–89 ml/min/1.73 m 2), 91(1.52%) as moderately reduced eGFR (30–59 ml/min/1.73 m 2), 4(0.07%) as severely reduced eGFR (15-29 ml/min/1.73 m 2), and 3(0.05%) classified as having kidney failure (eGFR<15 ml/min/1.73 m 2). When age-standardised to the WHO Standard Population the prevalence of eGFR<60 ml/min/1.73 m 2 was 1.79%. Age above 35 years and the presence of hypertension (OR 2.86, 95% CI 1.15-7.08) and anaemia (OR 2.14, 95% CI 1.12-4.09) were associated with eGFR<60 ml/min/1.73 m 2. Conclusion: In a systematic survey of people in rural Uganda, we found a substantial proportion had eGFR<60 ml/min/1.73 m 2. More population based studies are needed to further characterize kidney disease in sub-Saharan Africa.