Results of computer modeling of a modular independent tubular suspension of a logging truck

The necessity of increasing the efficiency of timber trucks by improving the designs of their suspensions has been substantiated. The main disadvantages of traditional suspension structures used in modern logging trucks have been described. A promising design of a modular independent tubular torsion bar suspension for a logging truck has been proposed. The aim of the research consisted of two stages. At the first stage, a mathematical model for the functioning of the proposed torsion bar suspension has been developed. At the second stage, a computer program for a preliminary assessment of the effectiveness of the functioning of this suspension (when driving on an insufficiently equipped forest road) has been made. Time dependences of the angular positions of suspension arm fork and ends of the tubular torsion bars were obtained. The regularities of the influence of the movement speed, average height of irregularities, coefficient of dry friction on the relative spread of vertical loads and suspension indicators of vibration dispersions were revealed.

A Global Perspective of Tropical Cyclone Precipitation in Reanalyses

This study compares the spread in climatological tropical cyclone (TC) precipitation across eight different reanalysis datasets: NCEP-CFSR, ERA-20C, ERA-40, ERA5, ERA-Interim, JRA-55, MERRA-2 and NOAA-20C. TC precipitation is assigned using manual tracking via a fixed 500-km radius from each TC center. The reanalyses capture similar general spatial patterns of TC precipitation and TC precipitation fraction, defined as the fraction of annual precipitation assigned to TCs, and the spread in TC precipitation is larger than the spread in total precipitation across reanalyses. The spread in TC precipitation relative to the inter-reanalysis mean TC precipitation, or relative spread, is larger in the East Pacific than in the West Pacific. Partitioned by reanalysis intensity, the largest relative spread across reanalyses in TC precipitation is from high intensity TCs. Compared to satellite observations, reanalyses show lower climatological mean annual TC precipitation over most areas. A comparison of area-averaged precipitation rate in TCs composited over reanalysis intensity shows the spread across reanalyses is larger for higher intensity TCs. Testing the sensitivity of TC precipitation assignment to tracking method shows that climatological mean annual TC precipitation is systematically larger when assigned via manual tracking versus objective tracking. However, this tendency is minimized when TC precipitation is normalized by TC density. Overall, TC precipitation in reanalyses is not only affected by horizontal output resolution or any TC pre-processing, but also data assimilation and parameterization schemes. The results indicate that improvements in the representation of TCs and their precipitation in reanalyses are needed to improve overall precipitation.

Delineating Efficient Cropping Zones of Potato and Chilli in Tamilnadu

Potato and Chilli are the most significant horticultural vegetable crops commercially cultivated in both field level and homestead gardening. India is leading producer of chilli and 2nd leading of potato in the world, but inadequate storage and huge unpredictable weather conditions leads to loses. This study was done to analyse trend changes in area, production and productivity over 30 years study period (1985-2015) and also identify Efficient Cropping zones of potato and chillies, at district level for Tamil Nadu during 2000-2015, in order to venture the hotspots of 21st century. Results of trend analysis revealed that potato production was decreasing till early 21st century and thereafter increasing gradually with respect to cropping area and chilli showed reduction in production over the years. Relative Yield Index (RYI) and Relative Spread Index (RSI) were used to figured out potential cropping districts for both crops over Tamil Nadu. Dindigul, Erode and Krishnagiri districts were found to be efficient cropping zone, while Nilgiris is sole district of Most Efficient Cropping Zone (MECZ) for potato. Virudhunagar district has been the Most Efficient Cropping Zone for chilli crop, while Ramanathapuram, Sivagangai, Tirunelveli, and Thoothukkudi districts were identified as potential efficient zone (ECZs) in Tamil Nadu. Hence, this paper attempts to identify the hotspot area and to study the deviation in cultivable land, production and productivity of the crops where farmers are facing most of the problems. The climate change scenarios could influence crop cultivation, and this paper is evident on the changes in efficient cropping zones.

Identification of Efficient Cropping Zone for Maize in Tamil Nadu

An analytical study was made in the Department of Agronomy, Tamil Nadu Agricultural University (TNAU), Coimbatore. The study was conducted for finding the identification of potential district of maize in Tamil Nadu based on the area, production, productivity data collected from 1998-1999 to 2015-2016. Based on the data relative spread index (RSI) and relative yield index (RYI) were calculated. The results showed that among 32 districts of Tamil Nadu five districts such as Ariyalur, Coimbatore, Erode, Theni, Tiruppur are very potential districts for cultivating the maize crop. From the analysis, parameters like RYI and RSI are high and these are potential districts and some districts are having RSI more but RYI less which indicates that non-suitability of the crop to that area.

Ultrafast component effects on quartz single grains dose estimation from Khutagt Uul Mountains, Mongolia

This study presents single-grain optically stimulated luminescence (OSL) results from pottery and sediments from the archaeological site “The burials in Khutag Uul Mountains (Mongolia)”. A global fitting procedure was used on a selection of single grains from pottery, D0 values obtained were between 16 to 40 Gy and 25 to 82 Gy and the equivalent doses De ranged from ~8 to 12 Gy and from 4.2 ± 0.4 Gy to 37.3 ± 2.5 Gy for pottery and sedimentary quartz, correspondingly.For pottery, the relative spread in CAM De values increases as higher precision constraints are applied and lead to significant increases in the relative standard error from 2.7% to ~7.5%. The number of accepted grains which passed acceptance criteria reduced from 180 to 65. For sedimentary quartz, there is a trend observed that both MAM De and FMM De values increase as higher precision in De is applied, and the number of accepted grains reduces from 146 to 53. The detailed study of the OSL decay curves identified an ultrafast OSL component with the decay rates of 53 ± 1 s–1 in addition to the fast and medium components and its effect on De was examined.

Delineation of Efficient Cotton Growing Regions of Tamil Nadu

Cotton is an immensely important crop for the sustainable economy of India and livelihood of the Indian cotton farming community. Identification of potential regions would help in increasing the productivity, ensures better utilization of available resources and avoid wastage of resources in the inefficient zones. Efficient cropping zones of the Cotton crop of Tamil Nadu were keyed out with 30 years data (1985-2015) using Relative Yield Index (RYI) and Relative Spread Index (RSI). The results reveled that in Tamil Nadu, fifteen districts were found for MECZ and three for ECZ. Coimbatore is most essential area for cotton crop. Similarly eight districts are coming under LECZ because RSI were very less compare to RYI. Tiruchirapalli and Ramanathapuram both the district have less RYI and RSI indicating NECZ for cotton crop.

Stock market stress from the central counterparty’s perspective

Purpose The purpose of this paper is to investigate the possibility of monitoring stress on stock markets from the perspective of a central counterparty (CCP). Due to their balanced positions, CCPs are exposed to extreme price movements in both directions; thus, the major risk for them derives from extreme returns and market illiquidity. The authors examined the connection of the stress alarms of return- and liquidity-based measures to find an objective basis for stress measurement. Design/methodology/approach The authors defined two types of stress measures: indicators based on extreme returns and liquidity. It is suggested that the stress indicators should be based on the existing risk management methodology that examines different risk measure oversteps. The stress signals of the past nine years on the German stock market were analyzed. The authors investigated the connection between the chosen stress measures to obtain a robust measure for alarming stress. Findings Although extreme returns and illiquidity are both characteristics of stress, the correlation of returns- and liquidity-based stress indicators is low when taking daily values. On the other hand, the moving averages of the indicators correlate significantly in the case of measures of downward and upward extreme returns and liquidity measured by the relative spread. The results are robust enough to be used for monitoring stress periods. Originality/value This paper contributes to understanding the characteristics of stress periods and points to the fact that stress signals measured by different aspects can also differ within the same asset class. The moving averages of returns- and relative spread-based indicators, however, could provide a cost-effective quantitative support for the risk management of a CCP and make the margin calculation predictable for clearing members as well.

Modeling and Predictability of Exchange Rate Changes by the Extended Relative Nelson–Siegel Class of Models

This paper investigates the predictability of exchange rate changes by extracting the factors from the three-, four-, and five-factor model of the relative Nelson–Siegel class. Our empirical analysis shows that the relative spread factors are important for predicting future exchange rate changes, and our extended model improves the model fitting statistically. The regression model based on the three-factor relative Nelson–Siegel model is the superior model of the extended models for three-month-ahead out-of-sample predictions, and the prediction accuracy is statistically significant from the perspective of the Clark and West statistic. For 6- and 12-month-ahead predictions, although the five-factor model is superior to the other models, the prediction accuracy is not statistically significant.