Miracle-dz/UniFAR-FTUs huggingface dataset:
RADIATION IN ARCHAEOMETRY APPLIED TO TAQUARY VALLEY

In the present work, soil and archaeological ceramic samples from one archaeological site located in Taquari Valley, (Lajeado, RS), were investigated. Ceramics pottery fragments were dated using thermoluminescence method and analyzed by mass spectrometry. The samples were grounded, sieved, and then divided in two: a) the fraction with lower grain size diameters was used in the chemical analysis, b). the portion with intermediate size grain diameter was chemically leached, submitted to different doses and then finally the thermoluminescence was measured. The ages obtained varied from 385 up to 926 years BP. The chemical analysis of soil and ceramics was made using ICP-MS (Plasma Mass Spectrometry) analytical technique. The ICP-MS determination was performed in the solubilized samples. For solubilization of each sample it was used a microwave-assisted digestion technique. Mn ,Fe, Al, Ca, K, Ti, Mg, Na, Cr, V, Ni, Zn, Pb, Li, Cu, La, Ce, Th, U, Sr and Ba have been determined in the studied samples. To guarantee the analytical performance a series of certified reference materials were used (IAEA-Soil 7, and GSJ- JG1a, JA-3, JB2 and JB-3). The ICP-MS data treatment using hierarchical cluster analysis with the squared Euclidean distances was used to calculate dissimilarities between samples. In the resulting dendrogram, the distinct groups of samples were evidenced.
Microseismicity and 3-D Mapping of an Active Geothermal Field, Kilauea Lower East Rift Zone, Puna, Hawaii

The local fault and dike structures in Puna, southeastern Hawaii, are of interest both in terms of electricity production and volcanic hazard monitoring. The geothermal power plant at Puna has a 30 MW capacity and is built on a section of the Kilauea Lower East Rift Zone that was resurfaced by lava flows as recently as 1955 and 1960. The Puna Borehole Network was established in 2006 in order to provide detailed seismic data about the Puna geothermal field. The array consists of eight 3-component borehole seismometers. The instrument depths range from 24 to 210 m (80 to 690 ft); five stations with 2 Hz geophones and three with 4.5 Hz geophones. The large majority of events were < M0.5 and occurred at depths between 2 and 3 km. The size, location, and depth of the microearthquakes suggest that power plant activity affects local seismicity. Earthquake depths increase from NE to SW, trending up the rift zone towards the Kilauea summit. Depths also increase from the study area to the SE, consistent with active normal faulting along Kilauea’s south flank. Shear wave polarization indicates that the active, fluid-filled fracture system trends SW-NE, consistent with the orientation of the LERZ. Double difference relocation suggests an intersecting network of fractures with both NE and approximately NW trends. 3-D tomographic analyses of P-wave velocity, S-wave velocity, and the Vp/Vs ratio are also presented. An area of anomalously fast P-wave velocity at the relatively shallow depth of 2.5 km may be evidence for a dense, gabbroic intrusion. This intrusion may underlie and be the parent of a body of dacitic melt that was discovered under the geothermal field during drilling.
Systematic Evaluation of Kriging and Inverse Distance Weighting Methods for Spatial Analysis of Soil Bulk Density.

Spatial interpolation methods are frequently used to characterize spatial phenomena in soil properties over various spatial scales; however, it is very difficult to select the best interpolation method. No specific standards or tests are available to determine the “appropriateness” of an interpolation model. This study focused on evaluation of the performance of two widely used interpolators: kriging and inverse distance weighting (IDW) for the spatial analysis of soil bulk density. Predicted values by both interpolation models were compared with the observed data and analyzed using various indices. Results indicated that both interpolation methods do not reflect true variation of bulk density. Both models, however, performed equally well for spatial analysis with almost the same accuracy, precision and consistency with a difference of less than 1.0%, 0.5% and 2.0%, respectively. Inverse distance weighting method, simpler than kriging method, gives competitive and somewhat superior results when an optimal power value is used. No relation was found among coefficient of variation, skewness and kurtosis in selecting an appropriate interpolation method for spatial description or selecting a power value for IDW method or a semivariogram model for the kriging method. This study has provided an example of an approach to systematically evaluate the performance of one or more spatial interpolation methods. By employing the validation indices used in this study, any interpolation method can be assessed to accurately describe any spatial data set from the field.
Wind-Driven Subinertial Circulation inside a Semienclosed Bay in the Gulf of California

AbstractMoored current and pressure observations were obtained at Bahia Concepcion, a semienclosed bay located on the eastern side of the Baja California peninsula in Mexico, to describe the wind-driven subinertial circulation. In winter and early spring, the bay is well mixed and forced by persistent winds toward the southeast, aligned with the central axis. The authors’ observations show that the sea surface rises downwind in response to wind stress and that there exists a crosswind drift at the surface that is consistent with Ekman dynamics. This feature is typical of a bay that is deeper than one Ekman depth and hence affected by the rotation of the earth. There is a persistent along-bay circulation toward the end of the bay along its western side with return flow on the opposite side. Drifters released near the surface across a transect move westward and downwind toward the closed end, where they recirculate cyclonically. Wind-driven linear theoretical models successfully predict the observed cross-b.
Prediction of wind farm energy yield using NWP considering within-cell wake losses

yield for a typical range of operating conditions to assess sensitivity of yield to within cell losses. Annual yield is evaluated for the Horns Rev wind farm during the year 2007 using the ERA-Interim dataset and for intervals of one week duration simulated using WRF for resource only, using the Fitch 1 scheme with a standard turbine power and thrust curve and a modified power and thrust curve representing wake losses across a sub-group of turbines. Numerical Weather Prediction (NWP) models such as Weather Research and Forecasting 5 (WRF) are widely used for predicting the wind resource at potential wind farm deployment sites and, increasingly, for energy yield prediction. Sub-grid models have previously been developed 1 to represent wind farms by modification of momentum sink and turbulence kinetic energy source terms within cells containing wind turbines. In this study, a sub-group of turbines are parameterized by thrust and power curves determined using semi-empirical wake models to assess influence of within-cell wake losses on net yield. Variation of thrust and power with wind speed and direction was obtained for groups of turbines using the modified PARK and Eddy Viscosity methods in Openwind 4 . Sensitivity to turbine number and spacing relative to the cell were determined. The influence of such wake-losses on yield was evaluated by comparison of energy yield from a power curve and predicted wind speed, from use of a standard turbine representation within WRF and from a modified parameterization to represent wake losses. The case study is based on the Horns Rev farm for time intervals selected to represent the annual wind speed distribution. The parameterization developed provided an energy yield that is within 0.5% of the annual, when scaled for a year, compared to predictions within range 2-4% of measured by standard methods. Abstract
Rapid Quantification of Telomerase Activity Employing an Improved Real-time Telomeric Repeat Amplification Protocol in Clinical Tissue Samples Eliminates Interference by PCR Inhibitors

Telomerase, a ribonucleoprotein with reverse transcriptase activity, plays a pivotal role in maintaining telomere length and chromosomal stability in proliferating mammalian cells. In cells without telomerase activity, replication-associated telomere attrition limits the replicative lifespan [1]. Therefore, telomere maintenance, mostly through telomerase activation, has been described as prerequisite for cancer [2]. As activation of telomerase is considered to be a crucial step in carcinogenesis [3,4], telomerase has been proposed as tumor marker for various malignancies [5], including hepatocellular carcinoma (HCC) and liver metastases [6]. Thus, a highly sensitive and reliable test to precisely quantify telomerase activity in biopsy samples would be useful to evaluate suspicious lesions. Telomerase activity can be detected by the sensitive telomeric repeat amplification protocol (TRAP) introduced by Kim et al. [7]. However, this technique is timeconsuming and susceptible to carry-over contamination because it requires post-PCR polyacrylamide gel analysis and cannot be performed as closed-tube assay. Even more importantly, reliable quantification of telomerase activity by conventional TRAP assays requires the use of radioactive nucleotides restraining its application in high-throughput clinical analyses. To circumvent the need for post-PCR analysis and to obtain quantitative data without the use of radioactivity, the standard TRAP assay was modified by various groups. For example, Uehara et al. [8] employed energy transfer primers that emit fluorescence upon incorporation into PCR products, which allows telomerase detection in a closed-tube system without post-PCR analysis. Furthermore, to measure telomerase activity in cultured cells some investigators have developed real-time TRAP assays using fluorescent dyes or probes to monitor product generation during amplification [9,10]. To further promote clinical application of the TRAP assay, Jakupciak et al. [11] reported an automated high-throughput system for the measurement of telomerase activity in cultured cells and body fluids.
The Impact of Transformational Leadership on Organizational Performance via the Mediating Role of Corporate Social Responsibility: A Structural Equation Modeling Approach

This study aims to examine the associated relationships between transformational leadership, corporate social responsibility, and organizational performance. A total of 217 questionnaires were gathered from employees operating the various pharmaceutical companies in Jordan and then were analysed using structural equation modelling (SEM). The results of the data were threefold. First, transformational leadership did not have a positive influence on organizational performance. Second, transformational leadership did have a positive influence on corporate social responsibility. Third, corporate social responsibility did have a positive influence on organizational performance. These findings may aid future researchers in their quest in understanding the inherent relationships that lie between the variables in question and may provide a platform for managers in their efforts to improve organizational performance.
Geochemical and Petrogenetic Study of Proterozoic Sewariya and Govindgarh Granitoids from South Delhi Fold Belt

The present study reports the geochemical composition of Sewariya two-mica granites (SG) and Govindgarh granites (GG) intruding rocks of Delhi Supergroup along the western margin of South Delhi Fold Belt in Rajasthan, India. Both granite varieties are highly evolved possessing high SiO 2 , Al 2 O 3 , low MgO, CaO, Fe 2 O 3 , Ni, Cr and V and are calc-alkaline in nature. In chondrite normalized REE diagrams, SG are characterized by highly fractionated REE patterns (avg La N / Yb N = 21.45) and sharp negative Eu* anomaly (Eu/Eu* = 0.25), whereas GG do not show significant REE fractionated patterns (avg La N /Yb N = 3.31) and have variable Eu anomalies. From primitive mantle normalized multi-element diagrams, crustal signatures (low Nb, Ti and high Pb, U, Th) can be inferred for both the granitoid varieties. Also, strong peraluminous nature, high A/CNK, normative corundum and abundant mica content point towards a (meta)sedimentary protolith for them. An arc setting is indicated by their calc-alkaline nature; volcanic arc or syncollisional affinities in tectonic discriminant diagrams (Nb versus Y; Rb versus Nb + Y). They are peraluminous leucogranites derived from crustal melts with little mantle contribution as is evident from their mineralogy and geochemical characteristics. The anatectic conditions prevalent during the formation of these granites differed with SG being formed under dehydration conditions, while the formation of GG involved fluid-present melting reactions.
Causes of the Multidecadal-Scale Warming of the Intermediate Water in the Okhotsk Sea and Western Subarctic North Pacific

AbstractCauses of the multidecadal-scale warming of the intermediate water in the Okhotsk Sea and the western subarctic North Pacific during 1980–2008 are investigated using an ice–ocean coupled model with interannually varying atmospheric forcing. A hindcast experiment qualitatively reproduces the warming and decadal fluctuations of the intermediate water that are similar to those of observations: the warming is significant along the western part of the Okhotsk Sea and subarctic frontal region. The effects of the thermohaline- and wind-driven ocean circulation on the warming are evaluated from perturbation experiments on thermohaline (turbulent heat and freshwater fluxes) and wind causes, respectively. The thermohaline causes are shown to contribute positively to warming in the Okhotsk Sea Intermediate Water (OSIW). The heat budget analysis for the OSIW indicates that the warming is related to a decrease in cold and dense shelf water (DSW) flux, which is caused by a decrease in sea ice and surface water .
Regulation mechanism of exogenous ALA on growth and physiology of Leymus chinensis (Trin.) under salt stress

Salt stress is one of major problem hampering plant growth and development to a significant level. In present study, 5-aminolevulinic acid (ALA) was exogenously applied to Leymus chinensis (Trin.) Tzvel. plants at various concentrations (10, 50, and 100 mg L -1 ) to assess its effects on morphology, physiology, and biochemistry under salt stress conditions (150 mmol NaCl L -1 ) as compared with control. The results indicated that salt stress substantially impaired growth, physiology and biochemistry of L. chinensis plants; nonetheless, ALA application alleviated the adverse effects of salt stress. Application of ALA improved the leaf length, leaf area, leaf conductance, plant dry biomass, water contents, and root activity of L. chinensis under stress and no stress conditions. Additionally, biosynthesis of chlorophyll, carotenoids, free proline, soluble sugars and proteins of L. chinensis plants was also increased following ALA application as compared to control, under salt stress conditions. Moreover, we also observed an enhanced activity of antioxidant defense system in L. chinensis in response to ALA application. ALA elevated the activity of enzymatic antioxidants viz. ascorbate peroxidase (APX), glutathione reductase (GR), superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD) significantly scavenged reactive oxygen species thus reduced the accumulation of malondialdehyde (MDA) under salt stress as compared to control under both normal and stressed conditions. The effect of ALA on all growth and biochemical attributes was concentration dependent and application of 50 as well as 100 mg L -1 ALA proved better. The results concluded that salt stress tolerance in L. chinensis plants can be increased by exogenously applied ALA at appropriate concentration. It was suggested that L. chinensis plants were treated with ALA application of 50-100 mg L -1 was more beneficial under both normal and saline conditions. enzymes, growth, Leymus chinensis , salt stress.
Cross‐Country Rankings in Intergenerational Mobility: A Comparison of Approaches from Economics and Sociology

Abstract This paper summarizes research on the relative level of intergenerational mobility – whether classified by income, education or social class. The literatures on education and income mobility reveal a similar ranking with South America, other developing nations, southern European countries and France tending to have rather limited mobility although the Nordic countries exhibit strong mobility. Estimates of mobility based on social class point to rather different patterns, and we demonstrate that these differences are most likely generated by intergenerational earnings persistence within social classes. The second part of the paper looks for explanations for the differences in earnings and education persistence and finds that mobility is negatively correlated with inequality and the return to education but positively correlated with a nation's education spending.
Constructing Demand Curves from Purchase Probability Data: An Application of the Juster Scale

Two studies examined the effect, on estimates of purchase rates and purchase level, of diff erent procedures for obtaining Juster purchase probabilities ratings. The results of the two studies reported here indicate that, while it is certainly possible to obtain data for constructing demand curves using the Juster Scale, great care needs to be taken if this approach is used. The most important finding from the two studies reported was the strong effect associated with the order of presentation of the different price-points. Higher estimates were obtained for all price-points when the highest price-point was presented first. Since there is some evidence that all estimates are likely to be over-estimates, presenting the lowest price-point first would appear to be the better approach. However, this has yet to be confirmed. Unfortunately, it was not possible to determine just how accurate the estimates were, since the product was never put on the market. Also, there was some indication in the research reported of a possible context effect, since higher estimates were achieved when respondents had been required to answer preliminary questions related to the product in question.
Overview of textual anti-spam filtering techniques

Elecronic mail (E-mail) is an essential communication tool that has been greatly abused by spammers to disseminate unwanted information (messages) and spread malicious contents to Internet users. Current Internet technologies further accelerated the distribution of spam. Effective controls need to be deployed to countermeasure the ever growing spam problem. Machine learning provides better protective mechanisms that are able to control spam. This paper summarizes most common techniques used for anti-spam filtering by analyzing the e-mail content and also looks into machine learning algorithms such as Naive Bayesian, support vector machine and neural network that have been adopted to detect and control spam. Each machine learning has its own strengths and limitations as such appropriate preprocessing need to be carefully considered to increase the effectiveness of any given machine learning. Key words: Anti-spam filters, text categorization, electronic mail (E-mail), machine learning.
Sowing the seeds of social relations: social capital and agricultural diversity in Hararghe Ethiopia

Abstract The paper presents an analysis of the role of two forms of social capital – linking and bonding – on two key farm outcomes: on-farm crop diversity and household wellbeing. Where market transactions are limited, social capital is an important household asset for accessing seed and channelling information. The study is set in a drought-prone region of Ethiopia, with high rates of food insecurity and dependency on agriculture for livelihoods. The region is very rich in crop genetic diversity, particularly for sorghum. The data were collected for a production year that experienced a major drought shock. Results of the analysis indicate that social capital is an important determinant of farm level diversity and wellbeing, with opposing effects related to the two different forms of social capital. This suggests possible trade-offs between the two forms of social capital in terms of food security, production and diversity, which need to be considered in planning interventions.
Is Collusion Proof Auction Expensive? Estimates from Highway Procurements

Collusion in auctions affects both revenue and efficiency and are prevalent. Yet, sellers do not use collusion-proof auctions as often as they should. Why is that? We find that one reason for this could be the cost of implementing efficient collusion-proof auctions. We use California highway procurements data, to estimate the cost of implementing collusion-proof auction. Our estimates show that cost must increase by at least 10.8% to ensure efficient outcome. The cost can sometimes be as high as 48.8% (depending on the size of bidding-ring in the data).
Factors influencing adoption and intensity of adoption of orange flesh sweetpotato varieties: evidence from an extension intervention in Nyanza and Western province, Kenya

This study applied logit and logit transformed regression to examine factors affecting the adoption of orange flesh sweet-potatoes (OFSP), and intensity of such adoption, by a representative sample of 340 farmers in the Busia and Rachuonyo districts of Kenya in 2009. The study also investigated whether participation in a value chain extension intervention programme increased these farmers’ likelihood of adopting OFSP. The results suggest that the district where the farmer comes from, knowledge on value addition and nutritional benefits, and availability of vines were the key factors for adoption. The results also suggest that participation in a value chain extension programme enhanced the probability of adoption. Factors affecting intensity of adoption were site, value addition, vines availability, level of commercialization and having a child of up to five years.
New hyperspectral difference water index for the extraction of urban water bodies by the use of airborne hyperspectral images

Abstract Extracting surface land-cover types and analyzing changes are among the most common applications of remote sensing. One of the most basic tasks is to identify and map surface water boundaries. Spectral water indexes have been successfully used in the extraction of water bodies in multispectral images. However, directly applying a water index method to hyperspectral images disregards the abundant spectral information and involves difficulty in selecting appropriate spectral bands. It is also a challenge for a spectral water index to distinguish water from shadowed regions. The purpose of this study is therefore to develop an index that is suitable for water extraction by the use of hyperspectral images, and with the capability to mitigate the effects of shadow and low-albedo surfaces, especially in urban areas. Thus, we introduce a new hyperspectral difference water index (HDWI) to improve the water classification accuracy in areas that include shadow over water, shadow over other ground surfaces, and low-albedo ground surfaces. We tested the new method using PHI-2, HyMAP, and ROSIS hyperspectral images of Shanghai, Munich, and Pavia. The performance of the water index was compared with the normalized difference water index (NDWI) and the Mahalanobis distance classifier (MDC). With all three test images, the accuracy of HDWI was significantly higher than that of NDWI and MDC. Therefore, HDWI can be used for extracting water with a high degree of accuracy, especially in urban areas, where shadow caused by high buildings is an important source of classification error.