Values Of Quantities Research Articles

Tea Trade Scenario in the Pre and Post Liberalization Period in India

Indian tea, which has maintained its supremacy both in production and export for more than a century, has started to lose its pre-eminence. Other tea producing countries like China, Kenya, Sri Lanka and Kenya are strongly competing for Market share. The increase in production in China has pushed India to second position in production and the country lost its domination of the export market to Kenya, China and Sri Lanka. Given this backdrop, the present study attempts to analyse the export growth, instability in export earnings, export quantity and unit value and concentration of export destinations evaluate India’s tea export performance. The growth of export quantity, value and unit value from India (1988-2022) was worked out using compound growth rate and the results indicated an increased growth in the post–WTO period which could be attributed to the expansion in trade to the Near East, with their growth and strength of the economies in the region (Hicks, 2009). Instability in export can affect the economic growth of the country as it has adverse effect on the countries export earnings, trade balance, and confidence of international trading partners. The export instability calculated using Coppock’s instability index showed an increasing trend in the post-WTO period. In 1990’s about 6 countries viz., U.S.S.R, U.K, Iran, Iraq, Egypt and Poland accounted for about 90 per cent of total tea exports from India. But over a period of time the demand in these countries weakened. The Indian exports continue to lose volume in countries like Russia Europe, USA and some middle east countries (Dutt, 2007). The share in Iraq, Netherland and Poland was maintained and it improved in UAE, Germany, Pakistan and china. Overall in the past 3 decades, India’s world ranking as an exporter has dropped to fourthowing to competition from China, Kenya and Sri Lanka. (Majumder et al., 2010). The reduction in values of the Hirschmann index indicated increased geographic diversification of tea exports thereby reducing the possibility of market risk due to dependence on few markets. The commodity diversification in the form of various tea products exported is very limited, the major share of exports being in the form of black tea especially in bulk form. Received: 1 February 2024 / Accepted: 29 April 2024 / Published: 5 May 2024

Supervised Stochastic Approach for computational analysis of convectively heated magnetized nanofluid flow with bioconvection aspects

Our study delves into the dynamics of a convective Magneto-Hydrodynamic Bioconvective Nanofluid model (MHD-BCNFM) flowing over a convectively heated stretched sheet. To accomplish this, we utilize the distinctive capabilities of the Supervised Stochastic Approach for Computational Analysis (SSACA). By integrating similarity transformations, we convert the partial differential equations (PDEs) governing the system into coupled ordinary differential equations (ODEs). We generate the dataset for our approach using the Adam numerical technique specifically tailored for the (MHD-BCNFM). Achieving this involves systematic modulation of parameters such as λ, bioconvection Péclet number Pe, Bioconvection constant σ, Brownian motion parameter Nb, and thermophoresis parameter Nt. "Moreover, we utilize a reference dataset to compute numerical values of various physical quantities in the (MHD-BCNFM) employing SSACA-based Artificial Intelligence methods. The effectiveness of our devised SSACA approach is demonstrated by a negligible mean squared error, ranging from approximately 10−8 to 10−10. Histograms exhibit a maximum error range of 10−5, closely aligning with optimal correlation/regression measures. Outstanding performance metrics in terms of Mean Squared Error (MSE) are attained at levels such as l 9.93E−12, 1.07E−11, 6.28E−10, 1.43E−11, 2.09E−09, 3.65E−11, 2.97E−11, and 2.80E−13 against 320, 430, 209, 85, 356, 295, 66, and 136 epochs. A comparative study between the proposed and reference datasets underscores the authenticity and precision of SSACA, supported by error analyses ranging from E-05 to E-09 across all scenarios.

Dynamic response of a homogeneous hygrothermoelastic slab sandwiched between elastic half-spaces

In the current study, the authors discuss a homogeneous hygrothermoelastic slab of thickness 2h sandwiched between two similar elastic half-spaces. The hygrothermoelastic slab is subjected to a mechanical source of constant magnitude. The source is applied along the interface of the slab and upper elastic half-space. The analytical expressions of the components of displacement, stresses, moisture concentration, and temperature field are obtained by the normal mode analysis technique. The analytical results are used to solve the problem numerically by taking a wood slab as a porous material. The graphical results elaborate the effect of the thickness of a slab on the physical quantities. The problem of hygrothermoelastic layers sandwiched between elastic half-spaces is a novel idea, which finds its applications in various engineering models. The results found are interesting in the context of the problem. It is observed that the thickness of a hygrothermoelastic slab affects the deformation in the medium and the values of physical quantities decrease with an increase in the thickness of the slab.

Numerical Study on Cable Force Adjustment System for Replacing Slings of In-Service Suspension Bridges

To conduct a systematic investigation on the replacement scheme for slings in service of suspension bridges, five feasible tensioning schemes were determined based on numerical simulation and analytical methods using the sling replacement project of an existing bridge as a case study. The safety performance of the bridge was evaluated by considering parameters such as sling position, quantity, order, and force value. According to the coupling relationship between different slings during the tensioning process, a precise analytical calculation model for adjusting cable force of the suspender is determined. The findings demonstrate that the dynamic performance of the completed bridge solely depends on its final state and remains unaffected by the intermediate tensioning process of suspension. The research findings suggest that symmetrically batch or stepwise tensioning can be applied to the suspension bridge slings with cable adjustment sequence from both ends to middle span replacement scheme to minimize structural response and optimize mechanical properties.

Indonesia’s Pulp Export Performance In the China Market: An Analysis Using Almost Ideal Demand System Approach

Indonesia is one of the world's leading pulp producers. Both domestic consumption and global demand are increasing annually. As Indonesia seeks to meet the escalating global demand for pulp raw materials, China is emerging as a major destination for its exports, which underscores the strategic importance of this market. This study aims to evaluate the comparative advantage of Indonesian pulp exports and to identify the price, cross-price and expenditure elasticities of pulp demand in the Chinese market. Using the Revealed Comparative Advantage (RCA) method and the Linear Approximation-Almost Ideal Demand System (LA/AIDS) model, this research analyzes annual time series data covering the period 2003-2022, focusing on the quantity and export value of chemical pulp (HS 470329). The results show that Indonesian pulp has a comparative advantage in the Chinese market, as indicated by Indonesia's RCA index greater than one. However, this comparative advantage is declining over time. At the same time, China's sustained increase in pulp consumption underscores the intensified competition among pulp-exporting countries for market share in China. Using the LA/AIDS model, the estimation results highlight a different dynamic in the Chinese pulp market: Japanese pulp emerges as a complementary product to Indonesian pulp, while Thailand and Brazilian pulp act as substitutes. These findings have valuable strategic implications for Indonesian policymakers and industry stakeholders in managing the complexities of global pulp trade dynamics

Estimation of the Resultant Expanded Uncertainty of the Output Quantities of the Measurement Chain Using the Discrete Wavelet Transform Algorithm

This paper discusses the role of the discrete wavelet transform algorithm in processing error signals present in the input quantities of the algorithm. In considering the error model of the measurement chain, the parameters of the error signals in the input quantities of the wavelet transform algorithm are estimated. Subsequently, in accounting for the algorithm’s properties, the parameters of its output values are determined, and the resulting uncertainty values of the output quantities of the measurement chain are estimated. The interval reduction arithmetic method is employed in the calculations for estimating the expanded uncertainty. All findings were validated through measurements conducted using the implemented measurement chain.

Bödewadt flow of thermally radiative hybrid nanofluid under the implication of horizontal magnetic field

It is a known fact that the implication of uniform magnetic field in transversal direction to fluid flow concerns the stabilization of velocity field and deterioration of heat transfer rate. It is now recognized that the applied uniform horizontal magnetic field is useful for stabilizing/destabilizing the flow rate, which is principally rely upon the direction angle such as cooling/heating the disk surface. Considering this, the present study investigates an incompressible three-dimensional Bödewadt flow above a stretchable with an implication of horizontal magnetic field. The Bödewadt flow defines a uniform and stable angular movement of fluid at sufficient large distance from the stationary surface. Such flow is balanced by the Centrifugal forces and is featured through radial pressure gradient. The radiative heat transfer attributes are characterized by the hybrid nanofluid, which is composition of Copper ( Cu ) and Titanium Dioxide ( Ti O 2 ) with water ( H 2 O ) as base fluid. A well-known approach of similarity variables is adopted to first normalize the flow model and then the resultant system of coupled non-linear ordinary differential equations is solved by Runge-Kutta-Fehlberg (RKF) MATLAB built-in package. The graphical results on flow and thermal fields are sketched for different values of dimensionless quantities. It is observed that direction angle in terms of horizontally applied magnetic field has stabilizing impact along radial axis close to the 0 ° or 90 ° , whereas destabilizing influence of direction angle is noticed between 30 ° − 60 ° . The temperature field is enhanced by the enlarged parametric values of thermal Biot number and solid volume fractions. Local Nusselt-number is increased at the disk surface by the radiation parameter.

Ambiguity, invisibility, and negativity *

Many widely different problems have a common mathematical structure wherein limited knowledge leads to ambiguity that can be captured conveniently using a concept of invisibility that requires the introduction of negative values for quantities that are inherently positive. Here I analyze three examples taken from perception theory, rigid body mechanics, and quantum measurement.

Using sentinel-2 satellite images and machine learning algorithms to predict tropical pasture forage mass, crude protein, and fiber content.

Grasslands cover approximately 24% of the Earth's surface and are the main feed source for cattle and other ruminants. Sustainable and efficient grazing systems require regular monitoring of the quantity and nutritive value of pastures. This study demonstrates the potential of estimating pasture leaf forage mass (FM), crude protein (CP) and fiber content of tropical pastures using Sentinel-2 satellite images and machine learning algorithms. Field datasets and satellite images were assessed from an experimental area of Marandu palisade grass (Urochloa brizantha sny. Brachiaria brizantha) pastures, with or without nitrogen fertilization, and managed under continuous stocking during the pasture growing season from 2016 to 2020. Models based on support vector regression (SVR) and random forest (RF) machine-learning algorithms were developed using meteorological data, spectral reflectance, and vegetation indices (VI) as input features. In general, SVR slightly outperformed the RF models. The best predictive models to estimate FM were those with VI combined with meteorological data. For CP and fiber content, the best predictions were achieved using a combination of spectral bands and meteorological data, resulting in R2 of 0.66 and 0.57, and RMSPE of 0.03 and 0.04g/g dry matter. Our results have promising potential to improve precision feeding technologies and decision support tools for efficient grazing management.

A Study of Geodesic Equation From Variational Principle

This paper employs variational principle in studying geodesic. In mathematical studies, a variational principle enables a problem to be solved employing calculus of variations that concerns seeking functions that increase the values of quantities that rely on those functions. For instance, the problem of ascertaining the shape of a hanging chain suspended at both ends can be solved using variational calculus. Hence, the variational principle is a function that lessens the gravitational potential energy of the chain. Geodesicis a procedure used in mathematics, specifically in Riemannian geometry that results in obtaining geodesics. Actually, these represent the paths of particles with no proper acceleration, their motion pleasing the geodesic equations. As the particles are subject to no appropriate acceleration, the geodesics generally signify the straightest path between two points in a bent spacetime. The article has investigated into the relation between the variation principle and geodesic equations that are particularly used in general relativity in physics as well.

Оптическая плотность и атомные отношения Н/С гумусовых кислот донных отложений озер Среднего Приобья

The paper presents the results of studies of the optical density of alkaline solutions of humic acids (HA) and himatomelanic acids (MMC) characteristic of the Middle Ob bottom sediments of lakes of silicate, organo-silicate and organic class and their dependence on the atomic ratios of H/S of HA macromolecules. It is established that the results of spectroscopy of the UV and visible regions of the HA spectrum depend on the results of the elemental composition. With an increase in the atomic ratios of N/S, the values of E465 quantities (quasi-extinction coefficients) decrease, which reflects the composition of the aromatic part of GC macromolecules. MMCs have been studied, however, they contain more peripheral groups than GC and do not have patterns of the relationship of E465 quantities from N/S, therefore, correlation dependencies are not given in the article. The highest content of aromatic carbon in GC was found for samples of GC K-6 of the silicate class of the Kondinsky province (left bank of the Ob) and C-5 of the organic class of the Sredneob province (right bank of the Ob). The general correlation dependence of N/S and E465 values is higher in the samples of the GK of the Kondinsky province. Keywords: SAPROPEL, HUMIC ACIDS, HIMATOMELANIC ACIDS, UV SPECTROSCOPY, MIDDLE OB

How can restricted farmland development rights be compensated to stimulate farmland protection? A provincial exploration in China

Stimulating farmland protection (FP) is crucial to ensure food security and environmental well-being. Some countries, including China, are seeking to incorporate transferable development rights (TDR) to realize economic incentives for FP. This study developed an indicator – planning regulation intensity on farmland (PRIF) – to describe the restricted farmland development rights (FDRs) and designed a compensation-oriented farmland transferable development rights (FTDR) mechanism. The threshold model and two-way fixed effect model were employed to unlock the transfer direction, quantity, and economic value of FDRs. Taking Hubei Province in China as the study area; the empirical research was conducted and demonstrated the necessity and feasibility of implementing the compensation-oriented FTDR mechanism in China. This study addresses the issue of unfair distribution of FDRs due to planning regulations and provides a promising economic-incentive policy instrument for curbing farmland loss. The FTDR mechanism considering PRIF that we propose enables the extension of TDR to countries that implement authority-exerted planning regulations.

Analyzing Physics Experiment using Sensor Smartphone in Traveling Carnival

Smartphone integration for high school students has significant potential in physics learning. This research aims to analyze smartphone sensor data in the context of physics experiments carried out at traveling carnivals. This research uses experimental methods to compare smartphone sensor data collected via the Phyphox application with video analysis data obtained using Tracker software. The research results show the effectiveness of smartphone sensors in several carnival games, including simple leg swings, bicycle spins, kora-kora vehicles, and merry-go-rounds. Smartphone sensors can show graphs of simple harmonic motion, angular velocity, and centripetal acceleration on the game vehicle. However, limitations arise in the case of Ferris wheels and mini Ferris wheels, where smartphone sensors show reduced effectiveness caused by the instability of passenger seats during the ride. This research suggests avenues for further exploration by computing physical quantity values derived from smartphone sensor data, offering insights into potential improvements and applications in dynamic environments such as theme parks.

Regression analysis of horizontal magnetic field in thermophysical convective flow of nanofluid

AbstractThe existence of magnetic field is beneficial to stabilize the fluid flow patterns in modern era industrial implications and engineering problems. A constant horizontal magnetized field is implemented to stabilize the swirl viscous fluid flow created by disk rotation. The heat transmission equation is expressed by the variable fluid property that the thermal conductivity is dependent on temperature. Buongiorno nanofluid model is applied to express the role of thermophoresis and Brownian movement. The flow governing equations are normalized through the von Kármán classical similarity variables. The impacts of magnetic and other physical parameters on velocity, thermal and concentration fields are investigated in numerical way using RKF‐45 (Runge–Kutta–Fehlberg) built‐in procedure. The critical part of horizontal magnetic field and dimensionless parameters onto physical quantities such as wall shears, thermal rate, and concentration rate are highlighted. Regression analysis is also performed to evaluate the impact of obtained numerical values of such physical quantities on flow rates. Unlike the familiar impacts of a uniformly applied transverse magnetic field that concerns the velocity field stabilizing and decreasing the thermal rate, it is established that the horizontal magnetized field is valuable for stabilizing/destabilizing the flow phenomenon. The results also matched with the published work in limiting case.

A Method for Identifying Gross Errors in Dam Monitoring Data

Real and effective monitoring data are crucial in assessing the structural safety of dams. Gross errors, resulting from manual mismeasurement, instrument failure, or other factors, can significantly impact the evaluation process. It is imperative to eliminate such anomalous data. However, existing methods for detecting gross errors in concrete dam deformation often focus on analyzing a single monitoring effect quantity. This can lead to sudden jumps in values of effect quantity caused by changes in environmental variables being mistakenly identified as gross error. Therefore, a method based on Fuzzy C-Means clustering algorithm (FCM) partitioning and density clustering algorithm (Ordering Points To Identify the Clustering Structure, OPTICS) combined with Local Outlier Factor (LOF) algorithm for gross error identification is proposed. Firstly, the FCM algorithm is used to achieve the division of measurement point areas. Then, the OPTICS and LOF algorithms are jointly utilized to determine the gross errors. Finally, the real gross errors are identified by comparing the time of occurrence of the gross errors at measurement points in the same area. Through the case study, the results indicate that the method can effectively identify spurious, gross errors in the monitoring effect quantity caused by environmental mutations. The accuracy of gross error detection is significantly improved, and the rate of misjudgment of gross errors is reduced.

Forecasting Prices and Production of Pulses in Faisalabad Market, Pakistan

Forecasting values of prices and production are important for value chain actors because they can plan their activities while considering these values in mind for improving profitability. The present study is designed to determine forecasting values of production and prices of mung bean, lentil and chickpeas using arrival quantity of pulses in the big market of pulses in Punjab, i.e. Faisalabad. Similarly price data is used to forecast future prices of pulses. ARIMA model is employed to determine forecasting arrival quantities and prices of pulses using monthly data from January, 2018 to June, 2023. Results show that there is no smooth price increases in mung beans during different months of a year. A declining value of lentil and chickpeas is an alarming indications for all value chain actors. Estimated values based on ARIMA models for price and arrival quantities of pulses have important implications for the producers and wholesalers dealing in pulses particularly chickpeas, mung beans and lentil. A declining forecasting value of lentil and chickpeas leaves a serious thought on the sustainability of value chain of these pulses in the province. A declining supply in the market with an increase in the price of lentil in future will affect stakeholders of supply chain of lentil.

Mixture composition and coal size effect on coal water mixture quality

Coal usage as a primary energy source is targeted to continue to increase and replace petroleum as the main energy source. Further processing is required to achieve the standard fuel characteristics, one of which is through a process called Coal Water Mixture (CWM) by adding water and additives to coal to produce fuel with characteristics like heavy oil. This research was conducted to analyze the best composition and size of the coal for CWM processing using variations in coal composition (20 %; 30 %; 40 %; 50 %; and 60 %) and coal particle size (40, 80, and 120 mesh). The parameters studied for each CWM product are product quantity, inherent moisture, density, pH, and calorific value. The results of the initial analysis show that the CWM product with a coal composition of 50 % has characteristics that most closely resemble Heavy Fuel Oil (HFO). CWM product with a coal composition of 50 % with all three variations of coal size was then tested for its calorific value and the respective values ​​were 3476.3153 cal/g; 4025.5551 cal/g; and 4488.4248 cal/g. The resulting product meets the physical characteristics qualifications, but to substitute HFO as fuel, it is necessary to use high quality coal, namely anthracite with a higher calorific value or upgrade the coal raw materials that will be used for the CWM processing.

Export competitiveness of Turmeric from India

The study examined the export performance of turmeric from India. The results revealed a positive growth rate in the area, production, productivity, export quantity, and export value of turmeric from India. Karnataka demonstrated the highest CAGR in both area and production of turmeric, while Odisha recorded the highest CAGR in productivity. The results of the transitional probability matrix indicated that Malaysia was the most stable market for Indian turmeric, followed by UAE and Iran. While India had a comparative advantage in turmeric exports, demonstrated by positive RSCA values, it has gradually declined. The export of turmeric was positively influenced by export price and production, whereas the domestic price had a negative effect. Forming turmeric parks would facilitate better promotion of production technology, processing, value addition, marketing, and export of turmeric from India.

Production and Export Performance of Fresh and Dried Figs from Afghanistan vis-à-vis India

The study was conducted on the production and export performance of fresh and dried figs from Afghanistan and India. The study was based on secondary data on area, production, productivity, and export of figs from 2000-01 to 2020-21. The data were analyzed using tools such as compound growth rates, coefficients of variation, the Cuddy-Della Valle Instability Index, and Markov Chain Analysis. The results revealed that the growth rates of area, production, productivity, export quantity, and export value of fresh and dried figs from both countries were favourable, with the exception of non-significant growth for the area in Afghanistan and the export quantity in India. The highest fluctuation in both countries was reflected in the exports of the quantity and value of fresh and dried figs. In contrast, instability in terms of area, production, and productivity of figs in Afghanistan was higher than in India. India was recognized as the most stable market for Afghan fresh and dried figs, followed by the UAE. In contrast, the Maldives was found to be the most loyal market for Indian fresh and dried figs, followed by Hong Kong and the USA respectively.

Orochi impact formula: An evidence-based approach for quantifying the societal harm of County Lines drug supply

The County Lines (CL) drug supply model is a rapidly increasing threat. Metropolitan Police Specialist Crime have developed a statistical formula, referred to as ‘Orochi impact formula’ for conservatively quantifying the quantity and monetary value of drugs sold per line. The novel formula, which uses known average daily consumption rates of Class A drug and customer demand telephony data, conservatively indicates deal line trade, systematically differentiating between deal lines to quantify the relative impact of each. This evidence-based approach has potential for supporting (i) prosecution of line holders, (ii) determining sentencing deterrents, and (iii) wider public information and knowledge exchange.