scholarly journals A Surrogate Weather Generator for Estimating Natural Gas Design Day Conditions

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7118
Author(s):  
David Kaftan ◽  
George F. Corliss ◽  
Richard J. Povinelli ◽  
Ronald H. Brown
Keyword(s):  
Natural Gas ◽  
Weather Generator ◽  
Cold Weather ◽  
Weather Data ◽  
Strongly Correlated ◽  
Heating Capacity ◽  
Out Of Sample ◽  
Kolmogorov Smirnov ◽  
Tail Of Distribution ◽  
Better Than

Natural gas customers rely upon utilities to provide gas for heating in the coldest parts of winter. Heating capacity is expensive, so utilities and end users (represented by commissions) must agree on the coldest day on which a utility is expected to meet demand. The return period of such a day is long relative to the amount of weather data that are typically available. This paper develops a weather resampling method called the Surrogate Weather Resampler, which creates a large dataset to support analysis of extremely infrequent events. While most current methods for generating weather data are based on simulation, this method resamples the deviations from typical weather. The paper also shows how extreme temperatures are strongly correlated to the demand for natural gas. The Surrogate Weather Resampler was compared in-sample and out-of-sample to the WeaGETS weather generator using both the Kolmogorov–Smirnov test and an exceedance-based test for cold weather generation. A naïve benchmark was also examined. These methods studied weather data from the National Oceanic and Atmospheric Administration and AccuWeather. Weather data were collected for 33 weather stations across North America, with 69 years of data from each weather station. We show that the Surrogate Weather Resampler can reproduce the cold tail of distribution better than the naïve benchmark and WeaGETS.

scholarly journals An analysis of Italian university students’ performance through segmented regression models: gender differences in STEM courses

Genus ◽  
2021 ◽  
Vol 77 (1) ◽  
Author(s):  
Andrea Priulla ◽  
Nicoletta D’Angelo ◽  
Massimo Attanasio
Keyword(s):  
Gender Differences ◽  
Regression Models ◽  
First Year ◽  
Strongly Correlated ◽  
Segmented Regression ◽  
Freshmen Students ◽  
Female Performance ◽  
And Mathematics ◽  
The Relationship ◽  
Better Than

AbstractThis paper investigates gender differences in university performances in Science, Technology, Engineering and Mathematics (STEM) courses in Italy, proposing a novel application through the segmented regression models. The analysis concerns freshmen students enrolled at a 3-year STEM degree in Italian universities in the last decade, with a focus on the relationship between the number of university credits earned during the first year (a good predictor of the regularity of the career) and the probability of getting the bachelor degree within 4 years. Data is provided by the Italian Ministry of University and Research (MIUR). Our analysis confirms that first-year performance is strongly correlated to obtaining a degree within 4 years. Furthermore, our findings show that gender differences vary among STEM courses, in accordance with the care-oriented and technical-oriented dichotomy. Males outperform females in mathematics, physics, chemistry and computer science, while females are slightly better than males in biology. In engineering, female performance seems to follow the male stream. Finally, accounting for other important covariates regarding students, we point out the importance of high school background and students’ demographic characteristics.

scholarly journals Impact of Unusual Features in Credit Scoring Problem

2020 ◽  
Author(s):  
Luiz Felipe Vercosa ◽  
Rodrigo Lira ◽  
Rodrigo Monteiro ◽  
Kleber Silva ◽  
Jailson Magalhaes ◽  
...  
Keyword(s):  
Multilayer Perceptron ◽  
Demographic Data ◽  
Credit Scoring ◽  
Financial Data ◽  
Unusual Feature ◽  
The Real ◽  
Kolmogorov Smirnov ◽  
Small Improvement ◽  
Better Than

Standard features used for Credit Scoring includes mainly registration and financial data from customers. However, exploring new features is of great interest for financial companies, since slight improvements in the person score directly impact the company revenue. In this work, we categorize features from open credit scoring datasets and compare them with the features found in a real company dataset. The company dataset contains unusual feature groups such as historical, geolocation, web behavior, and demographic data. We performed bivariate tests using the Kolmogorov-Smirnov metric and features to assess the performance of the particular feature groups. We also generated a score of good payer by using AdaBoost, Multilayer Perceptron, and XGBoost algorithms. Then, we analyzed the results with different metrics and compared them with the real company results. Our main finding was that these features added a small improvement to current datasets. We also identified the most promising feature groups and noticed that the tuned XGBoost performed better than the company solution in three out of four deployed metrics.

scholarly journals Stabilizing membrane domains antagonizes n-alcohol anesthesia

2016 ◽  
Author(s):  
B.B. Machta ◽  
E. Grey ◽  
M. Nouri ◽  
N.L.C. McCarthy ◽  
E.M. Gray ◽  
...  
Keyword(s):  
Plasma Membrane ◽  
Phase Separation ◽  
Critical Temperature ◽  
Hydrostatic Pressure ◽  
General Anesthesia ◽  
Membrane Domains ◽  
Strongly Correlated ◽  
Membrane Heterogeneity ◽  
Anesthetic Potency ◽  
Better Than

AbstractDiverse molecules induce general anesthesia with potency strongly correlated both with their hydrophobicity and their effects on certain ion channels. We recently observed that several n-alcohol anesthetics inhibit heterogeneity in plasma membrane derived vesicles by lowering the critical temperature (Tc) for phase separation. Here we exploit conditions that stabilize membrane heterogeneity to further test the correlation between the anesthetic potency of n-alcohols and effects on Tc. First we show that hexadecanol acts oppositely to n-alcohol anesthetics on membrane mixing and antagonizes ethanol induced anesthesia in a tadpole behavioral assay. Second, we show that two previously described ‘intoxication reversers’ raise Tc and counter ethanol’s effects in vesicles, mimicking the findings of previous electrophysiological and behavioral measurements. Third, we find that hydrostatic pressure, long known to reverse anesthesia, also raises Tc in vesicles with a magnitude that counters the effect of butanol at relevant concentrations and pressures. Taken together,these results demonstrate that ΔTc predicts anesthetic potency for n-alcohols better than hydrophobicity in a range of contexts, supporting a mechanistic role for membrane heterogeneity in general anesthesia.

scholarly journals Urban weather generation: the intercomparison of three emerging models

2021 ◽  
Author(s):  
Csilla Gal
Keyword(s):  
Land Use ◽  
Wind Speed ◽  
Air Temperature ◽  
Numerical Models ◽  
Weather Generator ◽  
Weather Data ◽  
Urban Air ◽  
Area Of Interest ◽  
Built Form ◽  
Urban Weather

<p>Cities modify the background climate through the surface-atmosphere interaction. This modification is function of urban design features, such as the configuration of buildings and the amount of vegetation. Compared to the undisturbed climate of the region, the climate of cities is characterized by higher temperature and lower wind speed. This modification is especially pronounce in dense urban areas. The climate modification of cities is not static, but varies in space and time. The spatial variations are governed by land use and built form differences, as well as by the presence or absence of green and blue infrastructures. Due to the spatial complexity of cities and the general lack of urban weather station networks in most places, the amount of available urban weather data is limited. As a consequence, planners, engineers and public health professionals can only approximate the climate impact of built environments in their respective fields.</p><p>Over the past years, several numerical simulation models have emerged that are able to model the influence of built areas on the atmosphere at the local scale and thus, deliver urban weather data for an area of interest. The aim of this study is to assess the performance of three numerical models with an ability to predict site-specific urban air temperature. The evaluated models are the Urban Weather Generator (UWG), the Vertical City Weather Generator (VCWG) and the Surface Urban Energy and Water Balance Scheme (SUEWS). Although the models differ in their scopes, modeling approaches and applications, they all derive the urban weather data from rural observations considering the land use and built form characteristics of the site.</p><p>The models are evaluated against air temperature measurements from the dense, 13<span><sup>th</sup></span> District of Budapest (Hungary). The field measurement utilized simple air temperature and relative humidity loggers placed in non-aspirated solar radiation screens at four shaded sites. The two week measurement period encompassed a five-day-long anticyclonic period with clear sky and low wind speed.<strong> </strong>Preliminary results indicate a good general agreement between modeled and observed values with root mean square error below or at 2ºC and index of agreement between 0.92-0.96. During the anticyclonic period most models slightly overestimate the daily maximum and underestimated the daily minimum urban air temperature.</p>

Identifying Terrorists using Banking Data

2012 ◽  
Vol 12 (3) ◽  
Author(s):  
Steven D. Levitt
Keyword(s):  
Retail Banking ◽  
Demographic Characteristics ◽  
Strongly Correlated ◽  
The Real ◽  
Administrative Records ◽  
Wide Range ◽  
Intelligence Agencies ◽  
Out Of Sample ◽  
And Behaviors

Abstract The fight against terrorism requires identifying potential terrorists before they have the opportunity to act. In this paper, we investigate the extent to which retail banking data – which as far as we know are not currently used by anti-terror intelligence agencies in any systematic manner – are a useful tool in identifying terrorists. Using detailed administrative records of a large British bank, we demonstrate that a number of variables in the data are strongly correlated with terrorism-related activities. Having both an Islamic given name and surname, not surprisingly, are among the strongest of these predictors, but a wide range of other demographic characteristics and behaviors observed in the data are also correlated strongly with terrorist involvement. The real key to our method, however, rests on the identification of one particular pattern of banking behavior (what we call “Variable Z”) which dramatically improves our ability to identify terrorists. Our model is demonstrated to have substantial power to identify terrorists both within sample and out of sample.

Influence of diet on development and oviposition of Forficula auricularia (Dermaptera: Forficulidae)

2001 ◽  
Vol 133 (5) ◽  
pp. 705-708 ◽  
Author(s):  
Ghislain Berleur ◽  
Jean Gingras ◽  
Jean-Claude Tourneur
Keyword(s):  
Food Preference ◽  
Rhopalosiphum Padi ◽  
Soil Surface ◽  
Cold Weather ◽  
Forficula Auricularia ◽  
Content Analyses ◽  
European Earwig ◽  
Preference Tests ◽  
Daylight Period ◽  
Better Than

In North America, the life cycle of the European earwig (Forficula auricularia L.) can be divided into a nesting phase (hypogean phase) and a free-foraging phase (epigean phase) (Crumb et al. 1941; Behura 1956; Lamb and Wellington 1975). Adults spend the nesting phase in the soil; females burrow into the ground at the onset of the cold weather, lay eggs, and then care for the eggs. Hatching occurs in spring; first- or second-instar nymphs move to the soil surface for the free-foraging period. The earwig, a nocturnal insect, spends the entire daylight period of hiding under trash or in dark crevices. Where two broods occur, females reenter the ground a second time (Lamb and Wellington 1975). Stomach content analyses (Crumb et al. 1941; Sunderland and Vickerman 1980) and food preference tests (McLeod and Chant 1952; Buxton and Madge 1976) revealed that the European earwig is omnivorous. Under laboratory conditions, nymphs fed freshly frozen aphids, Rhopalosiphum padi (L.) (Hemiptera: Aphididae), survive better than those fed green algae or carrots, develop faster, and produce heavier females (Phillips 1981; Carrillo 1985).

scholarly journals Effects of Au and Ge Additions on the Microstructures and Properties of Ag-1.5Cu-0.1Y Alloys

Materials ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 123
Author(s):  
Desheng Zhang ◽  
Qin Zhang ◽  
Sida Li ◽  
Hongying Yang
Keyword(s):  
Corrosion Resistance ◽  
Alloying Elements ◽  
Strongly Correlated ◽  
Experimental Basis ◽  
Secondary Dendrite Arm Spacing ◽  
Dendrite Arm Spacing ◽  
Better Than

The application of silver is seriously affected by its tendency to oxidize and corrode. Therefore, the addition of proper alloying elements to silver-based alloys to achieve better properties has become a hot topic at present. In this current study, the effects of the addition of the two elements Au and Ge on the microstructures and properties of Ag-1.5Cu-0.1Y alloys were investigated. The results showed that the microstructures were refined and the second dendrite was shortened in the Ag-1.5Cu-0.1Y alloys with the addition of Au and Ge. Adding Au enhanced the corrosion resistance of the Ag-1.5Cu-0.1Y alloys. Furthermore, the corrosion resistance of the Ag-1.5Cu-0.1Y alloys with the addition of both Ge and Au was better than that of the alloy samples with Au added alone. The best corrosion resistance of the Ag-1.5Cu-0.1Y alloys was achieved by adding 1.0 wt.% Au and 1.0 wt.% Ge. The microhardness was enhanced by the addition of Au and Ge, and was strongly correlated with the secondary dendrite arm spacing (λ2) of the Ag-1.5Cu-0.1Y alloys. In addition, the Au addition could improve the conductivity of the Ag-1.5Cu-0.1Y alloy; however, Ge had little effect on the conductivity of the alloy samples. This work provides an experimental basis for the design of better performing silver-based alloys.

scholarly journals Numerical Analysis of High-Pressure Direct Injection Dual-Fuel Diesel-Liquefied Natural Gas (LNG) Engines

Processes ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 261 ◽  
Author(s):  
Alberto Boretti
Keyword(s):  
High Pressure ◽  
Steady State ◽  
Liquid Phase ◽  
Natural Gas ◽  
Power Density ◽  
Conversion Efficiency ◽  
Liquefied Natural Gas ◽  
Dual Fuel ◽  
Fuel Conversion ◽  
Better Than

Dual fuel engines using diesel and fuels that are gaseous at normal conditions are receiving increasing attention. They permit to achieve the same (or better) than diesel power density and efficiency, steady-state, and substantially similar transient performances. They also permit to deliver better than diesel engine-out emissions for CO2, as well as particulate matter, unburned hydrocarbons, and nitrous oxides. The adoption of injection in the liquid phase permits to further improve the power density as well as the fuel conversion efficiency. Here, a model is developed to study a high-pressure, 1600 bar, liquid phase injector for liquefied natural gas (LNG) in a high compression ratio, high boost engine. The engine features two direct injectors per cylinder, one for the diesel and one for the LNG. The engine also uses mechanically assisted turbocharging (super-turbocharging) to improve the steady-state and transient performances of the engine, decoupling the power supply at the turbine from the power demand at the compressor. Results of steady-state simulations show the ability of the engine to deliver top fuel conversion efficiency, above 48%, and high efficiencies, above 40% over the most part of the engine load and speed range. The novelty of this work is the opportunity to use very high pressure (1600 bar) LNG injection in a dual fuel diesel-LNG engine. It is shown that this high pressure permits to increase the flow rate per unit area; thus, permitting smaller and lighter injectors, of faster actuation, for enhanced injector-shaping capabilities. Without fully exploring the many opportunities to shape the heat release rate curve, simulations suggest two-point improvements in fuel conversion efficiency by increasing the injection pressure.

scholarly journals Coronary stenosis as a modifier of the effect of cold spells on the risk of sudden cardiac death: a case-crossover study in Finland

BMJ Open ◽  
2018 ◽  
Vol 8 (8) ◽  
pp. e020865
Author(s):  
Niilo R I Ryti ◽  
M Juhani Junttila ◽  
Harri Antikainen ◽  
Marja-Leena Kortelainen ◽  
Heikki V Huikuri ◽  
...  
Keyword(s):  
Sudden Cardiac Death ◽  
Cardiac Death ◽  
Coronary Stenosis ◽  
Conditional Logistic Regression ◽  
Temporal Trends ◽  
Cold Weather ◽  
Weather Data ◽  
Channel Blockers ◽  
Total Occlusion ◽  
Case Crossover

ObjectiveTo test the a priori hypothesis that the association between cold spells and ischaemic sudden cardiac death (SCD) is modified by the severity of coronary stenosis.MethodsThe home coordinates of 2572 autopsy-verified cases of ischaemic SCD aged ≥35 in the Province of Oulu, Finland, were linked to 51 years of weather data. Cold spell was statistically defined for each home address as unusually cold weather pertinent to the location and time of year. We estimated the occurrence of cold spells during the hazard period (7 days preceding death) and reference periods (the same calendar days over 51 years) in a case-crossover setting applying conditional logistic regression, controlling for temporal trends and stratifying by severity of coronary stenosis.ResultsThe association between cold spells and ischaemic SCD was stronger among patients with 75%–95% stenosis (OR 2.03; 95% CI 1.31 to 3.17), and weaker to non-existent among patients with <75% stenosis (OR 0.97; 95% CI 0.37 to 2.55) or coronary total occlusion (100% stenosis) (OR 1.01; 95% CI 0.52 to 1.96). Lack of calcium-channel blockers and statin therapy seemed to accentuate the role of stenosis during cold spells.ConclusionsWe provide evidence that the association between cold spells and ischaemic SCD is modified by the severity of coronary stenosis. The findings suggest that disturbances in coronary circulation play part in the pathogenesis of SCD during cold weather.

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