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In order to determine the range of medium temperature zone of road asphalt, it is hoped that the evolution of viscoelastic characteristics of road asphalt under medium temperature state can be deeply explored.

In this paper, the needle penetration test and temperature scanning test were designed for 90# and 70# bitumen as test materials, and the boundary of medium temperature zone of 90# and 70# bitumen was accurately determined by data analysis method. A mathematical model was established based on principal component analysis, and a comprehensive evaluation index was proposed to evaluate the evolution of temperature viscoelastic characteristics of road asphalt by means of standardization and rotational dimensionality reduction.

The test results show that the medium temperature zone of 90# asphalt is [−5 ± 1°C, 38 ± 1°C], and the medium temperature zone of 70# asphalt is [0 ± 1°C, 51 ± 1°C]. According to the viscoelastic response of road asphalt in the medium temperature zone, the medium temperature zone can be divided into three evolution stages: weak viscoelastic stage, viscoelastic equilibrium stage, strong viscoelastic weak stage. Analysis based on the intrinsic viscosity fillip target describing the various intrinsic viscoelastic index represents the viscoelastic properties of bitumen from different angles, and limitations inherent stick fillip for target put forward the integrated the inherent stick fillip mark information, as well as targeted and accurate evaluation of road asphalt temperature comprehensive evaluation indexes in the evolution of the viscoelastic properties of I_M-T. Finally, the temperature data of asphalt pavement in several representative regions of China are compared with the determined medium temperature region, and it is proved that the research on the evolution of viscoelastic characteristics of asphalt pavement under the medium temperature condition has important practical significance.

The boundary of medium temperature zone of 90# and 70# base asphalt was determined, and the viscoelastic characteristic evolution of road asphalt under medium temperature state was studied deeply. Aiming at the limitation of intrinsic viscoelastic index, a comprehensive evaluation index IM-T which not only integrates the information of intrinsic viscoelastic index but also can accurately evaluate the evolution of temperature viscoelastic characteristics in road asphalt is proposed.

Climate change is a problem that concerns all of us. Despite the information produced by organizations such as the Expert Team on Climate Change Detection and Indices and the United Nations, only a few cities have been planned taking into account the climate changes indices. This paper aims to study climatic variations, how climate conditions might change in the future and how these changes will affect the activities and living conditions in cities, specifically focusing on Mexico city.

In this approach, two distinct machine learning regression models, k-Nearest Neighbors and Support Vector Regression, were used to predict variations in climate change indices within select urban areas of Mexico city. The calculated indices are based on maximum, minimum and average temperature data collected from the National Water Commission in Mexico and the Scientific Research Center of Ensenada. The methodology involves pre-processing temperature data to create a training data set for regression algorithms. It then computes predictions for each temperature parameter and ultimately assesses the performance of these algorithms based on precision metrics scores.

This paper combines a geospatial perspective with computational tools and machine learning algorithms. Among the two regression algorithms used, it was observed that k-Nearest Neighbors produced superior results, achieving an R² score of 0.99, in contrast to Support Vector Regression, which yielded an R² score of 0.74.

The full potential of machine learning algorithms has not been fully harnessed for predicting climate indices. This paper also identifies the strengths and weaknesses of each algorithm and how the generated estimations can then be considered in the decision-making process.

This is a companion paper to our previous study in Cao and Wei (2005) on stock market temperature anomaly for eight international stock markets. The temperature anomaly is characterized by a negative relationship between stock market returns and temperature. This line of work relies on the impact of environmental variables, such as temperature, on mood and behavior changes. In this paper, we expand the sample in Cao and Wei (2005) to include 19 additional financial markets. Our evidence confirms the identified negative relationship for the expanded sample. More importantly, our nonparametric tests, as opposite to the parametric or semi-parametric approaches used by previous related studies, demonstrate that this negative relationship is robust to distributional assumptions. Based on the sub-sample analysis, we find that this negative relationship is stable over time. Furthermore, we consider temperature deviation and demonstrate that this negative relationship is not just a level effect.

The purpose of this paper is to investigate physiological indices related to comfort and health condition, based on which corresponding electronic equipment are selected and applied. A wearable monitoring system using sensor and liquid crystal display (LCD) techniques are then designed. Sensors are used to collect and transmit recording required signals from the wearer. A microcomputer with the type of AT89C52 is used to record and analyze the collected data. LCD is applied to display the health and comfort condition of the wearer.

A novel wearable monitoring system for the measurement of physiological indices and clothing microclimate is proposed in this study in order to monitoring both health and comfort condition of the wearer.

The proposed system provides reference for the application of sensor and display technologies in the field of smart clothing, which can be further applied to infant and child care, health care, home entertainment, military and industry.

This paper, first, investigated a framework of a wearable monitoring system considering both comfort and health condition and summarized the related physiological indices. The requirements of both comfort and health condition monitoring are analyzed to select appropriate electronic elements.

The authors determine the effectiveness of the Rainfall Index Annual Forage Program (RIAFP) in offsetting yield risk of winter annual forage growers. The authors also evaluate the effectiveness in reducing risk of potential alternative weather indices.

The RIAFP is designed to compensate forage producers when yield losses occur. Prior research found weak correlation between the rainfall index and actual winter annual forage yields. The authors use long-term small-plot variety trials of rye, ryegrass, wheat, triticale and oats with rainfall recorded on site and measure the correlation of the index with actual rainfall and actual yields. The alternative indices include frequency of precipitation events and of days with temperature below freezing.

The correlation between actual rainfall and the current RMA index was strongly positive as in previous research. Correlations between forage yields and monthly intervals of the current RMA index were mostly statistically insignificant, and many had an unexpected sign. All indices had some correlations that were inconsistent across time intervals and forage variety. The inconsistent signs suggest a nonlinear relationship with weather and forage yield, indicating that rainfall can be too much or too little. The number of days below freezing has the most potential of the three measures examined.

Producers should view the winter forage RIAFP as a risk-increasing income-transfer farm program. A product to reduce the risk for forage producers may need to use a crop growth simulation model or another approach that can capture the nonlinearity.

Considerably more data were considered than in past research. Past research did not consider alternative weather indices. The program should be continued if its goal is to serve as disguised income transfer, but it should be discontinued if its goal is to reduce risk.

The purpose of this paper is to investigate whether is Belgrade (Serbia) suitable candidate for introduction of Heat Health Warning System (HHWS). Belgrade has high population density, considerable share of built up area and lot of multi floor buildings that are factors of heat-health vulnerability.

The authors analyzed the impact of weather conditions on human health in Belgrade during the summer 2007 that was extremely warm in Southeastern Europe and Serbia. Daily cardiovascular, cerebrovascular and respiratory mortality counts were used in Poisson regression model with air temperature as predictor variable. Also, three different heat wave indices (Warm Spell Duration Index, apparent temperature and index based on daily minimum temperature) were tested in order to estimate their ability to capture episodes with mortality higher than expected.

The temperature has the highest influence on cerebrovascular and cardiovascular mortality, while slightly modifies respiratory mortality. According to regression equation, a 1°C increase in mean daily temperature is associated with a 4.6 percent (p<0.0001), 2.2 percent (p<0.0001) and 1.6 percent (insignificant for p<0.10) increase in cerebrovascular, cardiovascular and respiratory mortality, respectively.

Even thought the Law recognizes the heat wave as natural hazard, there is no concrete measures and action for prevention of excess mortality. It is shown that extreme temperature had numerous social consequences on city's residents in the summer 2007. Given the results the authors got, it is recommended that the HHWS should be implemented in health protection plans in Belgrade.

The purpose of this paper is to demonstrate a simple fiber sensor for simultaneous measurement of liquid refractive-index (RI) and temperature.

The sensor structure is formed by a long period fiber grating cascaded with a section of thin-core fiber. The long period fiber grating is fabricated on single mode fiber, followed by a section of 20-mm length thin-core fiber which is a modal interferometer.

Cladding mode interference between long period fiber grating and thin-core fiber modal interferometer is weak in the experimental investigation. Both of these two cladding mode type fiber devices are sensitive to surrounding RI and temperature. So the RI and temperature can be measured simultaneously by monitoring the spectral characteristics of the compound sensor. The sensitivity is calibrated and sensor matrix is provided in the experiment.

This proposed fiber sensor is simple, tough, cost-effective and suitable for discriminate the liquid RI and temperature with high sensitivity.

The purpose of this paper is to compare the sensing characteristics of uniform fiber Bragg grating (FBG) and tilted fiber Bragg grating (TFBG) by presenting a detailed research review. Temperature, axial strain, bending, vibration and refractive index measurands of FBG and TFBG sensor are presented and some significant differences are found.

Theoretical analysis and practical application in engineering are investigated and compared from other authors' research papers and self analysis. Spectra behavior of both FBG and TFBG are discussed.

There are found to be significant differences in temperature, axial strain, bending, vibration and refractive index sensing characteristics of FBG and TFBG.

The paper's analysis is comprehensive and clear and provides readers with the sensing characteristics of FBG and TFBG in detail.

Major segments of the U.S. economy are affected by weather. With the emergence of weather derivatives, exposure to weather‐related risk has evolved from being merely accepted. As a result, weather risk management strategies are increasingly being adopted in strategic decision‐making by senior management. Weather derivatives enable managers to focus on core operating risks by trading away those business exposures related to temperature, precipitation, snow level, etc. These contracts offer a unique opportunity to discretely trade a new category of risk, which was previously considered to be an inevitable cost of doing business. This article describes the weather derivatives market and its contracts and outlines the principles of pricing and risk analysis in weather markets. In closing, the article discusses the application of these products for portfolio and business risk management using illustrative examples from the energy markets.

Extreme high temperatures are a significant feature of global climate change and have become more frequent and intense in recent years. These pose a significant threat to both human health and economic activity, and thus are receiving increasing research attention. Understanding the hazards posed by extreme high temperatures are important for selecting intervention measures targeted at reducing socioeconomic and environmental damage.

In this study, detrended fluctuation analysis is used to identify extreme high-temperature events, based on homogenized daily minimum and maximum temperatures from nine meteorological stations in a major grassland region, Hulunbuir, China, over the past 56 years.

Compared with the commonly used functions, Weibull distribution has been selected to simulate extreme high-temperature scenarios. It has been found that there was an increasing trend of extreme high temperature, and in addition, the probability of its indices increased significantly, with regional differences. The extreme high temperatures in four return periods exhibited an extreme low hazard in the central region of Hulunbuir, and increased from the center to the periphery. With the increased length of the return period, the area of high hazard and extreme high hazard increased. Topography and anomalous atmospheric circulation patterns may be the main factors influencing the occurrence of extreme high temperatures.

These results may contribute to a better insight in the hazard of extreme high temperatures, and facilitate the development of appropriate adaptation and mitigation strategies to cope with the adverse effects.