Amount Of Demand Research Articles

Climate Resilient Agriculture Practices - The Future of Farming

Climate-resilient agriculture (CRA) harnesses the intrinsic roots of agricultural and oxen production systems to generate increased long-term yields and farm income through sustainability. This review paper aims to draw attention to climate-resilient farming practices for medicinal plants and other cereal crops. There are several techniques and strategies that can be used to adapt to climate change, including yield-tolerant strains in poultry and cattle, Feed administration, irrigation, Agro-consulting and clay organic carbon. Governmental climate change adaptation programs such as the National Action Plan on Climate Change (NAPCC), the Pradhan Mantri Krishi Sinchayee Yojana (PMKSY), the Indian Council of Agricultural Research (ICAR), the Paramparagat Krishi Vikas Yojana and the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) continue to be implemented. Agriculture in India offers a living for the bulk of the populace and should never be disregarded. Increased demand for quantity, healthful food and diversity, as well as globalization effects and rising median income, would be revealed by India's growing population, globalization effects and increasing median income. Nutrient deficiencies in Indian soils, Imbalanced fertilizer application and Lack of Nitrogen-fixing crops have all caused significant climatic stress in India and the rest of the world. Various programs and policies, such as the Soil Health (Vitality) Card Scheme, are in place to improve fertilizer use efficiency. This cultivation practice pays attention to maintaining the environmental balance and bio-dynamization of agricultural systems so that ethical yield can be obtained.

The Effect of Market Capitalization, Trading Volume, Book Value, and Capital Structure on Share Prices

The share price represents the company's value on the share market; buyers and sellers establish the company's value based on the quantity of demand and supply of shares. This research looks at how market capitalization, trading volume, BV, and DER are used to analyze share price variations. The research aims to understand investor behavior in fluctuating market situations. The method used is to analyze multiple linear regression, and the data collection method is secondary data. This study's results indicate a relatively significant correlation between market capitalization, trading volume, BV, DER, and share prices, implying that predictor variables may adequately describe the reasons for price fluctuations. The conclusion of the research results reveals that from 2019 to 2021, investors act rationally in making judgments while conducting transactions or preserving their cash in the Bank and Insurance Sub-Sector.
 JEL, classification：
 G11 G12
 Keywords: Market Capitalization; Trading Volume; BV; DER; Share Stocks

Scenario modeling to predict changes in land use/cover using Land Change Modeler and InVEST model: a case study of Karaj Metropolis, Iran

Models for land cover/land use simulation are appropriate and important tools for decision-makers, helping them build future plausible landscape scenarios. Due to the fact that the simulation results of different models may be different, it is sometimes difficult for users to choose a suitable model. Therefore, in this study, an integrated approach is used, combining the data obtained from remote sensing and GIS with Land Change Modeler (LCM) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) models to simulate and predict land cover/land use changes for 2028 in Karaj metropolis (Northern Iran as a poor region-in terms of data-which is under intense and rapid urbanization. In this sense, three land cover/land use maps related to the study area were primarily generated using satellite image data for the period 2006, 2011, and 2017. They were used as a basis to define two scenarios: business-as-usual (BAU) scenario and participatory plausible scenario (PPS) for 2028. Afterwards, the necessary input data used in running of both models were prepared and, then, the outputs of the models were interpreted and compared. According to the results, while human-made coverage and low-density grasslands increased by about 74% and 12%, respectively, it was from 2006 to 2017 that agricultural lands, gardens, and high-density grasslands decreased by 42%, 34%, and 7%, respectively. According to the business-as-usual scenario, which was projected using the LCM model, the increase in human-made cover will continue by about 29% by 2028, and the reduction rate of agricultural lands, gardens, and low-dense and dense grasslands will experience decrease by about 20%, 3%, 11%, and 9%, respectively. The participatory plausible scenario for 2028, which was defined using the InVEST model, confirmed the same results, but having different quantities. Accordingly, while human-made cover will increase by about 73%, the reduction rate of agricultural lands, gardens, and low-dense and dense grasslands will decrease by about 41%, 10%, 16%, and 1%, respectively. The output quantities of InVEST scenario model seem to be closer to reality with less uncertainty, because this model estimates the quantity of demand for land and its suitability for different uses, based on the views of different stakeholders, and considers landscape development future policies and plans. In contrast, the LCM model is based solely on trend extrapolation from the past to current time and changes in the landscape structure.

Maintenance Skill Training Gives Agricultural Socialized Service Providers More Advantages

Agricultural machinery maintenance skill training is conducive to improving the fault diagnosis and maintenance levels of agricultural machinery for agricultural socialized service providers and plays an important role in providing stable and reliable agricultural machinery operation services. This paper aims to study whether maintenance skill training gives agricultural socialized service providers more advantages than untrained providers, exploring the relationship between maintenance skill training and agricultural machinery service area. Based on a survey of 4905 farmers from 10 provinces in China, an empirical analysis was carried out using a fixed effect model and a propensity score matching method. The results showed the following: First, maintenance skill training had a significant positive impact on agricultural machinery operation service area, including 10.426 ha of machinery tilling service area and 8.524 ha of machinery harvesting service area. Second, since maintenance skill training gave agricultural socialized service providers more advantages in agricultural machinery operation services and enabled them to obtain more orders, it had an indirect positive impact on the quantity of demand for large- and middle-sized agricultural machinery.

Numerical solution for solving fuzzy volterra integral 2nd –kind by using modified decomposition technique

We discuss methods for solving the second-class fuzzy nonlinear Volterra -integral formula using novel error analysis and convergence techniques. The modified decomposition method is utilized to investigate convergence in the solution of the second class of fuzzy nonlinear Volterra integral formula. Moreover, some numerical examples were solved using our fuzzy equation. The presented methods were discussed in detail, and we compared the existing methods through the illustrative example that has been presented and applied creation classes to all the programming in Maple version (22). The quantity demand and investment in research and development, while the other model focuses on a more realistic relationship between the quantity demand and the price.

A review of solar thermal desalination using nanotechnology

Freshwater is the mandatory requirement for the humankind as it provides health and prosperity. According to WHO, safe drinking water, sanitation, and hygienic conditions are essential to protect us during all infectious disease outbreaks. However, 97% of the water on our earth is salty and only 3% is freshwater and merely less than 1% of water is potable. This scare commodity is required for drinking, domestic use, irrigation, and also for industrial applications. The population explosion with a better standard of living demands for the mammoth quantity of potable water. The demand cannot be met from various natural sources and hence desalination process compels us to adopt. The water obtained from various sources is treated for microorganisms and other harmful contaminants. The present-day desalination process is expensive and also degrades the environment by leaving the carbon footprints. Solar energy-based desalination plants help to receive potable water at economic and environment friendly. In this review article, the applications of nanotechnology in solar thermal desalination are discussed.

Intensification of cultivation of seedlings of Siberian spruce (Picea obovata Ledeb.) in the Southern Urals

The study underscores the vital demand for efficient cultivation of Siberian spruce seedlings in reforestation and land reclamation. It delves into diverse peat substrate types, densities, and nutrient additives, providing insights for optimizing growth. The comprehensive approach involves microbiological preparations and mycorrhiza to enhance seedling development. The recommendation is to use high-density peat, introducing microbiological preparations post-emergence for fostering robust Siberian spruce seedlings. The relevance of the research stems from the high demand for large quantities of planting material in reforestation efforts. Siberian spruce, known for shade tolerance and cold resistance, is a significant carbon accumulator. The paper reports 2023 experiments on peat substrates with varying densities and nutrient additives, emphasizing pre-sowing seed treatment with growth stimulants. Results show increased germination energy and germination on denser and more acidic peat substrates. However, superior biometric indicators at the season's end are observed in seedlings grown on substrates with lower density and additives like a complex of humic acids, salts, mineral fertilizers, trace elements, soil microflora, and mycorrhiza. The proposal advocates using high-density peat (at least 0.6 g/cm3) for growing Siberian spruce seedlings, introducing microbiological preparations post-emergence, and regular fertilizing for enhanced first-year development.

PENERAPAN METODE IMPROVED EXPONENTIAL APPROACH DALAM MENYELESAIKAN MASALAH TRANSPORTASI FUZZY DI PERUM BULOG SUB.DIVRE MEDAN

Transportation is an activities that affect the smooth wheels of the economy. The core problem of transportation is to minimize distribution costs. Matters that affect distribution costs are in the form of demand quantities, supply quantities, and transportation costs. In 2021, the rice distribution costs of Perum Bulog Sub Divre Medan was very high accompanied by uncertain demand and supply so it is expressed in fuzzy numbers. It is necessary to use a method that can solve this transportation problem optimally. In this study, the improved exponential approach method was used to find the optimal solution in rice distribution and combined with fuzzy integer transportation to find the integer value of the parameters with fuzzy values. The improved exponential approach method is a method of solving balanced and unbalanced transportation problems directly. The results showed that the improved exponential approach method can be applied to solve the fuzzy transportation problem. The cost of distributing rice in 2021 using the improved exponential approach method has decreased by IDR 41,155,480 from the actual distribution cost. Through these results, it can be concluded that the improved exponential approach method can optimally solve the fuzzy transportation problem in 2021 at Bulog Sub-Divre Perum Medan

An Analytical Study of the Pattern Consumption of Children's Milk in Qalyubia Governorate

During the last two decades of the twentieth century, Egyptian society has undergone many changes in income, increasing the number of people, especially the number of children, and increasing health awareness, which in turn was reflected in the change in the pattern of food consumption in general and on the consumption of children's milk in particular, which led to an increase in demand in quantity and quality, where the imported quantities of children's milk in Egypt increased to about 1387 tons on average for the period (2008-2020). Based on the above, it was found that there is a national problem that requires research and analysis to identify in general the various economic aspects of the children's dairy sector in Egypt and in particular on the possibility of local manufacturing of this product.

SoftHebb: Bayesian inference in unsupervised Hebbian soft winner-take-all networks

Hebbian plasticity in winner-take-all (WTA) networks is highly attractive for neuromorphic on-chip learning, owing to its efficient, local, unsupervised, and on-line nature. Moreover, its biological plausibility may help overcome important limitations of artificial algorithms, such as their susceptibility to adversarial attacks, and their high demands for training-example quantity and repetition. However, Hebbian WTA learning has found little use in machine learning, likely because it has been missing an optimization theory compatible with deep learning (DL). Here we show rigorously that WTA networks constructed by standard DL elements, combined with a Hebbian-like plasticity that we derive, maintain a Bayesian generative model of the data. Importantly, without any supervision, our algorithm, SoftHebb, minimizes cross-entropy, i.e. a common loss function in supervised DL. We show this theoretically and in practice. The key is a ‘soft’ WTA where there is no absolute ‘hard’ winner neuron. Strikingly, in shallow-network comparisons with backpropagation, SoftHebb shows advantages beyond its Hebbian efficiency. Namely, it converges in fewer iterations, and is significantly more robust to noise and adversarial attacks. Notably, attacks that maximally confuse SoftHebb are also confusing to the human eye, potentially linking human perceptual robustness, with Hebbian WTA circuits of cortex. Finally, SoftHebb can generate synthetic objects as interpolations of real object classes. All in all, Hebbian efficiency, theoretical underpinning, cross-entropy-minimization, and surprising empirical advantages, suggest that SoftHebb may inspire highly neuromorphic and radically different, but practical and advantageous learning algorithms and hardware accelerators.

A global perspective of entomopathogens as microbial biocontrol agents of insect pests

The growing global population has created a significant demand for both quality and quantity of agricultural products, resulting in a significant increase in the use of agrochemicals such as chemical pesticides to counter insect pests. Consumers, on the other hand, have grown increasingly concerned in recent years about the adverse effects of chemical insecticides on human health and the environment. As a result, researchers worldwide have been compelled to conduct research into alternative crop protection solutions. Biological control through entomopathogens has gained prominence among these alternatives, and several microbial biocontrol agents, including baculoviruses, Bacillus , Beauveria , Steinernema , and Heterorhabditis species, have been tested. Microbial biopesticide products are currently being used to combat specific insects that harm crops. The modes of action of entomopathogens, their advantages and constraints are discussed. An overview of processes for their development are highlighted with examples, as well as the issues that impede their development. Finally, special attention was paid to the gaps identified in this sector and the factors limiting their application particularly with respect to market potential. The future potential of entomopathogens may be affected by changing agricultural systems. • Entomopathogens have great potential in controlling insect pest populations in agroecosystems. • Commercial application of a microbial biopesticide necessitates large-scale mass production, formulation with appropriate additives to increase the product's shelf-life, and storage. • Stringent regulatory framework due to biosafety or environmental concerns raises overall costs and delays microbial biopesticide commercialization. • Additional regulatory challenges will be required for the new microbial biopesticide products in order to define low-risk contenders for easy commercialization and free market entry.

Analysis of Procurement and Demand for Raw Materials of Dried Fish Making Business in Bengkulu City

This study is intended to analyze the source of fresh fish and the quantity of fresh fish used in the business of making dried fish in Bengkulu City and analyze what factors affect the quantity of demand for fresh fish in the business of making dried fish in Bengkulu City. This research was conducted from January to February 2022 in Bengkulu City, more precisely, Sumber Jaya Village, Kampung Melayu District. The research location was determined purposively, and 86 dried fish makers were selected using the census method. The data used are primary and secondary, and the data analysis used is qualitative and quantitative. Sources of raw materials in dried fish are divided into three: self-catch, buy, and self-catch and buy. The largest percentage of sources of raw materials is to buy, where the place to get the most comes from fishermen directly. The quantity of raw material used is 10,563 Kg per production process. The factors that partially affect the quantity of demand for fresh fish by dried fish makers are the price of ice and the dummy of the business scale at the 95% confidence level.

A dataset of a proxy variable for the poultry trade flows in China

Understanding the intercity poultry trading network is crucial for assessing the risk of avian influenza prevalence. Unfortunately, the poultry trading network in China has rarely been described. Here, with a modified radiation model, we obtain values for a proxy variable for poultry trade flows among 318 prefecture-level cities in China in 2015 utilizing the product capacity and demand quantity of poultry of the cities. The results are validated by comparing the proxy variable values with the trade volumes investigated in the literature, and it is found that the modified radiation model can accurately predict the main poultry trade flows among cities. This is the first dataset on China’s poultry trade pattern, and it can be used to analyze the production and consumption structure of poultry in prefecture-level cities within China. The dataset can be a tool for avian influenza epidemic risk assessment as well as a basis to develop prevention and control measures during an epidemic.

Research on coal demand forecast and carbon emission reduction in Shanxi Province under the vision of carbon peak

Facing the increasingly severe climate situation, China strives to improve its Nationally Determined Contributions, promising to reach its carbon peak by 2030. Accurately predicting the future demand quantity and changing the trends of coal resources is the key to maintaining national energy security and achieving the goal of “carbon peak” and is also an important research topic in the future. To improve the prediction accuracy, this study sorts out eight common factors affecting the coal demand from the aspects of the economy, population, and energy. The grey relational analysis method was used to describe the degree of importance of each factor and screen out the relatively vital factors. The system dynamics model for coal demand in Shanxi Province was also established. The coal demand and carbon emission trends in Shanxi Province from 2021 to 2030 were predicted under business-as-usual, low-speed and high-speed development scenarios. The study results show that: 1) During the 14th Five-Year Plan to 15th Five-year Plan, the trend of coal demand has changed from increasing to decreasing. Under the three scenarios, the coal demand in 2021 is expected to be 372.03 million tons, 365.97 million tons, 360.04 million tons, and it is expected that the coal demand will peak in 2025, and will reach 394.77 million tons, 390.27 million tons, and 385.66 million tons under the three scenarios, respectively. 2) With the development of population and economy, the total energy demand shows a continuously increasing trend. It is estimated that the total energy consumption will reach 237.46-242.93 million tons of standard coal in 2030, and the total energy demand will continue to grow in the foreseeable future. 3) The carbon dioxide emission is closely related to the coal demand, showing a similar variation trend. Under the business-as-usual development scenario, carbon emissions in 2021 are 699.62 million tons, and carbon emissions are expected to reach 681.12 million tons in 2030. The low-speed development and high-speed development scenarios have different degrees of energy saving and emission reduction benefits. Compared with the business-as-usual development scenario in 2030, the carbon dioxide emissions will be reduced by 1.64 million tons and 3.56 million tons respectively. Finally, we put forward important policy measures to promote the economic transformation and upgrading of Shanxi Province and accelerate the realization of the “carbon peak” goal.

A New Approached Method for Solving the Four Index Transportation Problem with Fuzzy Parameters and Application Perspective in Industry

The four index transportation problem (4ITP: origin, destination, goods type, vehicle type) is an extension of the Hitchcock problem, a problem best suited for the goods allocation planning in the case for using the shuttle type. Based on the research results in 1979, in 2011, we developed an exact method for fully solving the 4ITP with determinist parameters. However, because of the limitation of human in recognizing the imprecise natural events in the decision making science, it is necessary to use fuzzy numbers for uncertain condition. By extending the problem toward this direction, in this paper, we develop a method, an extension of fuzzy programming, solving the 4ITP when all parameters such as the cost coefficients, the supply and demand quantities, the goods type and vehicle type quantities are fuzzy numbers and obey the Gaussian law in order 2. We use Gauss method in the fuzzy programming to obtain the costs under form of point cloud. From these results, we use Pham’s method, a method for the conventional 4ITP, to obtain a point cloud with the agglomerating costs. By using Kronechker’s method, we extract the obtained minimal cost under form of an interval for a given solution. It allows us to obtain a goods allocation planning with the minimal total transportation cost.

Life cycle assessment of fly ash bottom ash in coal power plants: A review

Fly ash (FA) and bottom ash (BA) from coal combustion give environmental impacts and health problems. As the demand for coal increases, FABA quantity and environmental impacts will also increase. Thus, to reduce the environmental impact, the utilisation of FABA is key. To properly utilise FABA as a sustainable material, FABA’s life cycle in Indonesian power plants needs to be studied. For initial work and comparison, this study conducted a literature review related to Life Cycle Assessment (LCA) of FABA from coal-fired power plants. The literature review used descriptive method, with the criteria for the main articles’ selection are published papers within the last ten years. This paper discusses system boundary, inventory, environmental impact, improvement efforts, and challenges. The main beneficiaries of FABA are construction and geotechnical industries, other studies have also shown a wider range of uses in various fields. The wide utilisation of FABA faces challenges from the intrinsic character variation, non-technical issues, standards, and knowledge for proper utilisation in composite materials.

The role of forecasting in preventing supply chain disruptions during the COVID-19 pandemic: a distributor-retailer perspective

Strengthen the resilience of supply chains was observed to be critical issue by firms to confront disruptions triggered by unprecedented demand and severe disasters. However, the extraordinarily challenging disruptions of COVID-19 pandemic, unlike any disasters seen in recent times. This study aims to provide a practical solution to supply chain (SC) disruptions by estimating the best forecasting models for demand fluctuations in the context of food and beverages. A method is proposed to predict SC disruptions and enhance SC resilience. Double exponential smoothing (DES) and the ARIMA model are adopted as forecasting approaches to estimate demand and optimum inventory quantities during three different periods of disruption associated with the COVID-19 outbreak. A downstream SC involving 2 distributors and 56 retailers is considered to elaborate inventory measurements (optimal inventory levels and total costs). The results demonstrate that distributors can reduce costs by dispensing with some retailers, particularly those who order low quantities and thus incur unjustified expenses. Furthermore, high accuracy is obtained, with minimal differences between the real data and the model’s forecast. Existing research has largely ignored supply disruptions in the distributor-retailer relationship. This study provides distributors and SC managers important knowledge on SC disruptions and identifies appropriate forecasting methods to increase SC resilience. It also provides distributors and other SC managers unprecedented insights on tackling crises of stability like COVID-19.

Research on the Mathematical Model for Optimal Allocation of Human Resources in the Operation and Maintenance Units of a Heavy Haul Railway

According to the existing personnel structure, quantity, development strategy, and market demand of the Shuohuang Railway Company’s operation and maintenance project, the demand quantity of various employees of the company for the past three years is predicted, and a human resource optimization model based on existing human resources and future plans is established. Then, the optimal solutions of the two mathematical models were calculated and analyzed using LINGO software. Finally, combined with the actual situation, the optimal allocation of human resources for the operation and maintenance project of KY company was obtained. The following conclusions are obtained. (1) For the optimal allocation model of existing human resources, the maximum net profit of the optimal staffing model is CNY 3258000. (2) The human resources allocation cost of the minimum dismissal model is CNY 81000. (3) The human resources allocation cost of the lowest cost model is CNY 15500. The research results can effectively guide the human resource management of the operation and maintenance project of the Shuohuang Railway Company, and have important theoretical and practical significance for further analysis of human resources model and its optimal allocation method.

How to make the EU Energy Platform into an effective emergency tool

Abstract Uncertainty regarding the supply of Russian natural gas is causing European gas and electricity prices to become extremely high and volatile. Coordination is essential to ensure that disruptions during difficult winter months do not lead to a break-up of the EU internal gas market with potentially serious political repercussions. One part of the EU response is the establishment of an EU Energy Platform for the purchase of gas, LNG and hydrogen. The platform can be developed into an effective emergency tool – if Member States buy gas jointly they will find it much easier to let markets allocate scarce volumes across borders in case of a full supply disruption from Russia. We detail two complementary proposals to achieve this. First, there should be EU-wide auctioning of a remuneration for filling storage sites in specific regions. Secondly, EU demand for additional LNG quantities, and the sourcing of this on international markets, should be coordinated through a platform – this creates a transparent market for said volumes.

Model of operational planning of freight transportation by tram as part of a green logistics system

The introduction of environmentally friendly technologies is becoming increasingly necessary to combat global warm-ing and air pollution in cities. The concept of eco-logistics is seen as an effective approach to the management of materials and related flows in order to reduce environmental and economic damage to the environment. The sustaina-ble development of green supply chains is based on the use of environmentally friendly types of vehicles, reduction of energy and other resources consumption, optimization of transport and technological processes in delivery systems. As part of the development of green supply chain, it is proposed to transport goods by freight trams, which eliminates the need for heavy trucks in the city, improves traffic conditions and reduces the environmental impact of transport. The research was conducted for the city of Poznan. The distribution system of the city of Poznan operates in conditions of stochastic demand for deliveries from clients and the risk of lack of sufficient supplies in distribution centers. To take into account the specificity of the distribution system of cargo delivery in conditions of uncertainty and risk, a simula-tion model of the organization of the material flows within the transport system of the city of Poznan has been pro-posed. The result of simulation is the optimal assignment of clients to the distribution centers, as well as the value of total mileage with the load, which is a random variable. It is assumed that the random variable is distributed according to the normal distribution law. The results were calculated and compared for two variants, i.e. for constant demand and sufficient quantity of cargo in distribution centers, and for variable demand and uncertainty conditions, e.g. insuffi-cient cargo quantity in distribution centers. The purpose of the paper is to develop a simulation model for planning supplies of small consignments of goods by trams implementing green logistics concept with variable demand for transportation. After a short introduction of the problem, the literature review related to the concept of green logistics and requirements of transport and distribution system are presented in section 2. In section 3, the research problem and research methodology are described. Section 4 provides the results of assignment of clients to distribution centers. The paper ends with concluding remarks.