Total Amount Of Resources Research Articles

Financial Performance and Total Resources: Trend and sensitivity Analysis of Indian Oil Exploration and Production Companies

The firms involved in the exploration and production (E&P) of natural gas resources and crude oil play a crucial role in the energy sector and contribute to the economy. Exploration and production refer to discovering, drilling, and extracting natural gas resources and crude oil from beneath the earth’s surface. Exploration and production firms provide a base for the downstream companies to make crude oil consumable. The financial performance of the downstream companies depends on the cost efficiency of the E&P firms. The purpose of the study is to determine the relationship between the total resources and measures of financial performance. The study is based on secondary data and financial ratios, index numbers applied to get the financial performance, and variability of financial performance. Correlation is used to get the trend and quick impact of variability on the total assets on the financial measures in the short and long run. The study found that while return on total resources is positively influenced in the long run, profitability based on sales and short-term paying ability is negatively governed by the absolute quantity of expansion of all available resources. Although the long-term association is positive, there is a short-term lag in the positive increase of the total resources on the ROA. Overall, based on their average absolute amount of total resources, relatively, the mutual study of the mean growth rate of all resources and financial indicators of Indian E&P explore negativity.

Evaluating ecological sustainability of mechanized and traditional systems of damaskrose production using extended exergy analysis

Environmental resource efficiency is a major challenge in the management of agroecosystems and their sustainability. The Extended Exergy Analysis (EEA) is a novel approach that assesses the total amount of resources extracted from the environment to produce agroecosystem products. This study applied the EEA to compare the sustainable development of Damask rose flower production in two mechanized and traditional systems in Nehbandan County, South Khorasan province, using the data of 2021–2022. The EEA calculated the flows of labor, capital, and environmental costs in the systems based on the first and second thermodynamic laws. The results showed that the traditional system had lower cumulative exergy consumption (CExC) and environmental modification cost than the mechanized system, indicating higher ecological sustainability. The extended exergy indices, such as the special capital conversion of energy and material input (kcap), the special capital conversion of product sale (KCAPEEA), extended exergy cost (eec) and the cumulative degree of perfection (CDP), also revealed that the traditional system was more cost-effective, economical, technologically efficient, and closer to the optimal conditions than the mechanized system. To achieve a sustainable agricultural crop production system, new patterns and models for selecting inputs and reducing environmental costs are recommended.

Revealing the influence mechanism of the service lifespan of residential buildings in China

The total amount of resources and energy consumed by long-lifespan residential buildings (RBs) is far less than that of short-lifespan RBs with repeated demolitions and constructions. This study aims to expand revealing of comprehensive influencing of the service lifespan of RBs beyond the previous approach that focused only on the one aspect of physical conditions with RBs. This study proposed these latent variables (i.e., physical, functional, economic, environmental and social lifespans), which made a better understanding of the service lifespan of RBs. To analyze the influence mechanism of the service lifespan of RBs, an empirical RB's lifespan dataset was established and tested utilizing a two-stage structural equation modeling (SEM) method. The results indicated that: (1) functional lifespan (total effects = 2.15) and environmental lifespan (total effects = 1.46) have an obvious positive impact on the service lifespan of RBs; (2) the influencing factors including structure design, land finance, employment of migrant workers, planning forward, and technical measures have a significant impact in corresponding lifespan dimension; and (3) improving construction technology and guaranteeing land value are regarded as the fundamental extending measure for the service lifespan of RBs. This study complements the connotation of RB service lifespan to a certain extent and further improves the sustainable development theory. Policy implications derived from the results were discussed at the end of the study.

Control–Communication–Computing Co-Design in Cyber–Physical Production System

The cyber–physical production system (CPPS) has practical requirements, such as distributed, reconfigurable, and high-performance, which bring a new challenge to performance guarantee of remote manufacturing with time delay under shared resources. Time delay has a great influence on system performance, and the mainstream methods mainly reduce its influence by optimizing control. However, due to the uncertainty of time delays, the existing methods have great limitations, and the configuration complexity is high. To address this issue, we take teleoperation as the control model, then we introduce 5G slicing and edge computing technologies to turn this control problem into a control–communication–computing co-design problem. An industrial teleoperation testbed is implemented to help clarify this problem and explore the key points in solving it. Then, a novel co-design teleoperation platform (CdTP) is designed that can quantitatively describe the relationship between the time delay and system configuration. Based on CdTP, system performance assurance does not have to be achieved by blindly increasing the total amount of resources, but can be achieved by improving the utilization of shared control–communication–computing resources. In addition, CdTP can dynamic configure resources based on changing requirements, which make it combines flexibility, real time, and reliability. Finally, we propose a resource allocation method to minimize the maximum job delay. The evaluation and experimental results indicate that our platform can achieve an all-in-one configuration, and validation of the proposed method is conducted to provide deterministic delay guarantees.

An Intelligent Resource Management Solution for Hospital Information System Based on Cloud Computing Platform

With the rapid growth in medical data, hospitals need to make enormous investments annually to expand computing resources. Cloud computing offers a platform for running medical services. However, sharing of medical data with unknown neighbors in the cloud environment may threaten the sensitive data of medical services. Private cloud provides a safety way to protect the sensitive data of medical services. But it is quite different from public cloud, since it is not easy to obtain more resources timely when the unpredictable workload is over the total amount of resources of private cloud. In addition, optimal resource allocation becomes a key issue as medical services possess distinctive features require different kinds of resource combination. In this article, an efficient resource management solution for medical services in hospital information system based on private cloud is proposed. We use intelligent control theory to adjust the resource allocation based on the dynamic workload adaptively, that effectively utilizes the limited resources of the private cloud while ensures the quality of services. The experiment results suggest that the proposed solution enables the efficient application of resources and reactions to unpredictable situations, which reduces the IT resources to hospitals.

ПРОДОВОЛЬЧЕ ЗАБЕЗПЕЧЕННЯ ДОМОГОСПОДАРСТВ УКРАЇНИ: РЕАЛІЇ СЬОГОДЕННЯ

Today, Ukraine's food security is an important component of national security. The almost two-year war with the Russian Federation disrupted the sustainable production of basic food products and their availability to the population. Overcoming the complex challenges that Ukraine faces today requires transformational actions that embrace the principles of sustainability and the elimination of the consequences of martial law, which, since the beginning of the full-scale intervention of the aggressor country, caused a break in the food chain between rural areas, with rational use of nature and subjects of food provision in the regions of the country. The purpose of the article is to study the theoretical and methodological aspects of the formation of household food supply in wartime conditions. It has been established that the key criterion of food security is not ensured in Ukraine today - the economic availability of food of the necessary volume and quality for all social groups of the population. The obstacle to this is the system of distribution of national income, which is discriminatory towards the majority of the country's population. Therefore, to ensure economic access to food for the entire population of our country, changes in the current model of Ukraine's economy are necessary. It was determined that for the period of 2023-2026, provided that the production of meat and meat products by the rural OTG of Ukraine increases by 10%, the total amount of resources of the agricultural sector of the economy will increase by 14.4%, the increase in the consumption fund will be 15.5%, which will lead to an increase in the general needs of the population for this type of agricultural products up to 7.1%. Accordingly, this will allow to increase the food self-sufficiency index of the agricultural sector from 0.65 to 0.70, respectively. Thus, in Ukraine, even in the conditions of a crisis military conflict, it is necessary to increase the aggregate income of households on the basis of a balanced socio-economic policy of the state.Summary. Today, Ukraine's food security is an important component of national security. The almost two-year war with the Russian Federation disrupted the sustainable production of basic food products and their availability to the population. Overcoming the complex challenges that Ukraine faces today requires transformational actions that embrace the principles of sustainability and the elimination of the consequences of martial law, which, since the beginning of the full-scale intervention of the aggressor country, caused a break in the food chain between rural areas, with rational use of nature and subjects of food provision in the regions of the country. The purpose of the article is to study the theoretical and methodological aspects of the formation of household food supply in wartime conditions. It has been established that the key criterion of food security is not ensured in Ukraine today - the economic availability of food of the necessary volume and quality for all social groups of the population. The obstacle to this is the system of distribution of national income, which is discriminatory towards the majority of the country's population. Therefore, to ensure economic access to food for the entire population of our country, changes in the current model of Ukraine's economy are necessary. It was determined that for the period of 2023-2026, provided that the production of meat and meat products by the rural OTG of Ukraine increases by 10%, the total amount of resources of the agricultural sector of the economy will increase by 14.4%, the increase in the consumption fund will be 15.5%, which will lead to an increase in the general needs of the population for this type of agricultural products up to 7.1%. Accordingly, this will allow to increase the food self-sufficiency index of the agricultural sector from 0.65 to 0.70, respectively. Thus, in Ukraine, even in the conditions of a crisis military conflict, it is necessary to increase the aggregate income of households on the basis of a balanced socio-economic policy of the state.

A model for recognizing farming behaviors of plantation workers

In properly managed plantation farms, farming behaviors of workers should be properly recorded. Both the accuracy of the model and the total amount of resources required during processing need to be considered, considering farms only have ordinary computers and they are difficult to have large computing servers. This paper proposes a lightweight method FWNet for recognizing farming behaviors of plantation workers. Firstly, a dataset (FBD) of farming behaviors is established, which includes 1154 video samples involving four types of farming behaviors: spraying pesticides, hoeing, weeding and transplanting seedlings. Secondly, in FWNet, we refer to (2 + 1) D convolution and residual structure, adopt a smaller network input shape and a shallower number of network layers, and use Swish as the activation function. In experiments, FWNet's accuracy, F1-score and mAP are 97.5%, 97.41% and 97.31% which are higher than P3D, R3D, R(2 + 1) D, EPCI-LSTM models. Parameters amount and latency are reduced to 3.20 M and 28.91 ms, far less than baselines. Experiment results indicate that FWNet can recognize farming behaviors with high accuracy and faster.

Multiparameter quantum metrology in the Heisenberg limit regime: Many-repetition scenario versus full optimization

We discuss the Heisenberg limit in the multiparameter metrology within two different paradigms: one where the measurement is repeated many times (so the Cram\'er-Rao bound is guaranteed to be asymptotically saturable). and the second one where all the resources are allocated into one experimental realization (analyzed with the mimimax approach). We investigate the potential advantage of measuring all the parameters simultaneously compared to estimating them individually, while spending the same total amount of resources. We show that in general the existence of such an advantage, its magnitude, and conditions under which it occurs depends on which of the two paradigms has been chosen. In particular, for the problem of magnetic field sensing using $N$ entangled spin $\frac{1}{2}$, we show that the predictions based purely on the Cram\'er-Rao formalism may be overly pessimistic in this matter: the minimax approach reveals the superiority of measuring all the parameters jointly whereas the Cram\'er-Rao approach indicates lack of such an advantage.

Integrating hepatitis B care and treatment with existing HIV services is possible: cost of integrated HIV and hepatitis B treatment in a low-resource setting: a cross-sectional hospital-based cost-minimisation assessment

BackgroundHepatitis B and HIV care share health system challenges in the implementation of primary prevention, screening, early linkage to care, monitoring of therapeutic success and long-term medication adherence.SettingArua regional referral...

O papel das instituições na aquisição e distribuição de alimentos: uma análise do Programa de Aquisição de Alimentos (PAA) na Região Sul do Brasil nos anos de 2009 a 2018

The PAA, created in 2003, aims to strengthen family farming by purchasing agricultural production and distributing it to people in a state of food insecurity. This work aims to analyze the execution of the PAA in terms of application of resources, volume of production, and coverage of the program in the southern region of Brazil in the years 2009 to 2018. The research used secondary data made available by the National Supply Company (CONAB). The main results were: the southern region received the total amount of resources of R$ 845 million in the analyzed period, which accounts for 28% of the national amount for the period; in state terms, Rio Grande do Sul stood out with approximately 59% of the volume purchased, followed by Paraná (26%) and Santa Catarina (15%). With regard to the number of suppliers, a drop of approximately 97% in the number of participants was found when comparing the years 2009 and 2018. It can be concluded that in 2019 it showed greater prominence in all categories analyzed, in 2013, operational problems pointed out a weakness in the execution of the program with expressive consequences in the following years. The data evidenced indicate that the program presented itself as a public policy instrument that exposes deficiencies.

Effect of soil spatial configuration on Trifolium repens varies with resource amount.

Soil spatial heterogeneity involves nutrients being patchily distributed at a range of scales and is prevalent in natural habitats. However, little is known about the effect of soil spatial configurations at the small scale on plant foraging behavior and plant growth under different resource amounts. Here, we experimentally investigated how a stoloniferous species, Trifolium repens, responded to varied resource amounts and spatial configuration combinations. Plant foraging behavior (i.e., the orientation of the primary stolon, mean length of the primary stolon, foraging precision, and foraging scale) and plant growth (i.e., total biomass, root biomass, shoot biomass, and root/shoot) were compared among differently designed configurations of soil resources in different amounts. The relationships of foraging behavior and plant biomass were analyzed. The results showed that the effect of the spatial configuration of soil resources on Trifolium repens depended on the resource amount. Specifically, when the total resource amount was low, fragmented soil patches promoted root foraging and increased Trifolium repens plant biomass; however, when the total resource amount was high, the soil spatial configuration did not affect foraging behavior or plant growth. Our results also showed that plant growth was facilitated by root foraging scale to adapt to low resource amounts. We conclude that the spatial configuration of soil resources at small scales affects whole plant growth, which is mediated by a distinct foraging strategy. These findings contribute to a better understanding of how the growth strategy of clonal plants responds to heterogeneous environments caused by different resource amounts and its spatial configurations.

Анализ возрастной динамики потребности в амбулаторной медицинской помощи по поводу состояний, определяющих базовую величину потребности у женщин при болезнях системы кровообращения

INTRODUCTION: The results obtained from the analysis of age dynamics are insufficient for development a program of reducing morbidity and, ultimately, mortality, since a need of medical care already indicates a problem; so prevention and screening programs should surpass the emergence of these problems. AIM: To analyze the age dynamics of the need for outpatient medical care for conditions that determine the basic value of the need in women with diseases of the circulatory system. MATERIALS AND METHODS: We used data on 780,000 visits during one year to medical organizations that provide medical care on an outpatient basis. We studied the probability of an episode and the dynamics of the frequency of episodes depending on age in six five-year age groups: 31 to 35 years, 36 to 40 years, 41 to 45 years, 46 to 50 years, 51 to 55 years, and 56 to 60 years. The dynamics of the frequency of episodes was modeled by a mathematical function with the largest value of the approximation coefficient. The dynamics of the frequency of episodes was modeled by a mathematical function with the largest value of the approximation coefficient. RESULTS: The dynamics of the need for outpatient medical care for hypertensive diseases [Diseases characterized by high blood pressure] (I10 – I15), ischemic heart diseases (I20 – I25) and vascular diseases of the brain (I60 – I69) is characterized by an increasing trend in demand indicators throughout the studied age period. The greatest increase in indicators is observed in the age groups of 31–40 years for ischemic heart diseases and vascular diseases of the brain and 41–50 years for hypertensive conditions. The greatest increase in demand is observed for coronary heart diseases (I20 – I25). The total amount of resources required increases more than 350 times over the 30-year age period, despite the stable value of the average duration of treatment. The increase in the total amount of resources required for vascular diseases of the brain is 30 times. The lowest growth gradient is registered in relation to hypertensive conditions (10-fold growth). As a critical age period, it is most appropriate to consider the age of a woman under 35 years. CONCLUSION: Mathematical modeling is optimally performed using power functions for hypertensive conditions and vascular diseases of the brain and exponential functions for ischemic heart diseases. All the proposed models are characterized by high approximation coefficients.

Decentralized online integer programming problems with a coupling cardinality constraint

We consider a problem involving a set of agents who need to coordinate their actions to optimize the sum of their objectives while satisfying a common resource constraint. The objective functions of the agents are unknown to them a priori and are revealed in an online manner. The resulting problem is an online optimization problem to optimally allocate the resource among the agents prior to observing the objective functions. For any deterministic online algorithm for this problem, it has been shown that there exists a lower bound of Ω(T) on regret. When the agents’ integer programs satisfy a discrete concavity condition, we propose a randomized online algorithm that is decentralized and guarantees an upper bound of O(KTlnm) on the expected regret, where K is the total amount of resource to be shared and m is the number of agents.

The ecology of competition: A theory of risk-reward environments in adaptive decision making.

In many choice environments, risks and rewards-or probabilities and payoffs-seem tightly coupled such that high payoffs only occur with low probabilities. An adaptive mind can exploit this association by, for instance, using a potential reward's size to infer the probability of obtaining it. However, a mind can only adapt to and exploit an environmental structure if it is ecologically reliable, that is if it is frequent and recurrent. We develop the competitive risk-reward ecology theory (CET) that establishes how the ecology of competition can make the association of high rewards with low probabilities ubiquitous. This association occurs because of what is known as the ideal free distribution (IFD) principle. The IFD states that competitors in a landscape of resource patches distribute themselves proportionally to the gross total amount of resources in the patches. CET shows how this principle implies a risk-reward structure: an inverse relationship between probabilities and payoffs. It also identifies boundary conditions for the risk-reward structure, including heterogeneity of resources, computational limits of competitors, and scarcity of resources. Finally, a set of empirical studies (N = 1,255) demonstrate that people's beliefs map onto properties predicted by CET and change as a function of the environment. In sum, grounding people's inferences in CET demonstrates how the behaviors of a boundedly rational mind can be better predicted once accounts of the mind and the environment are fused. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

A New Combinatorial Algorithm for Separable Convex Resource Allocation with Nested Bound Constraints

The separable convex resource allocation problem with nested bound constraints aims to allocate B units of resources to n activities to minimize a separable convex cost function, with lower and upper bounds on the total amount of resources that can be consumed by nested subsets of activities. We develop a new combinatorial algorithm to solve this model exactly. Our algorithm is capable of solving instances with millions of activities in several minutes. The running time of our algorithm is at most 73% of the running time of the current best algorithm for benchmark instances with three classes of convex objectives. The efficiency of our algorithm derives from a combination of constraint relaxation and divide and conquer based on infeasibility information. In particular, nested bound constraints are relaxed first; if the solution obtained violates some bound constraints, we show that the problem can be divided into two subproblems of the same structure and smaller sizes according to the bound constraint with the largest violation. Summary of Contribution. The resource allocation problem is a collection of optimization models with a wide range of applications in production planning, logistics, portfolio management, telecommunications, statistical surveys, and machine learning. This paper studies the resource allocation model with prescribed lower and upper bounds on the total amount of resources consumed by nested subsets of activities. These nested bound constraints are motivated by storage limits, time-window requirements, and budget constraints in various applications. The model also appears as a subproblem in models for green logistics and machine learning, and it has to be solved repeatedly. The model belongs to the class of computationally challenging convex mixed-integer nonlinear programs. We develop a combinatorial algorithm to solve this model exactly. Our algorithm is faster than the algorithm that currently has the best theoretical complexity in the literature on an extensive set of test instances. The efficiency of our algorithm derives from the combination of an infeasibility-guided divide-and-conquer framework and a scaling-based greedy subroutine for resource allocation with submodular constraints. This paper also showcases the prevalent mismatch between the theoretical worst-case time complexity of an algorithm and its practical efficiency. We have offered some explanations of this mismatch through the perspectives of worst-case analysis, specially designed instances, and statistical metrics of numerical experiments. The implementation of our algorithm is available on an online repository.

Sustainable Development of Port Economy Based on Intelligent System Dynamics

With the development of economic globalization, international trade competition is increasingly intensified. As an important hub of waterway transportation, the sustainable economic development of ports has an important impact on the economic development of the entire country. Therefore, the research on the sustainable development of port economy has been paid more and more attention by everyone, but the current results are not ideal. This paper studies the sustainable development of port economies based on networked smart sensor technologies and system dynamics. First, according to the construction principles of the sustainable development index system, combined with the actual situation of the port economy, the evaluation index system layer of the sustainable development of the port economy is divided into four sub-systems: population, environment, resources and economy. A system dynamics model for the sustainable development of the port economy will be constructed and its sensitivity will be analyzed. Then, the above system dynamics model is combined with the optimized K-means algorithm, and the K-means algorithm is used to quickly calculate the required data in the system dynamics model to form an intelligent system dynamics model for the sustainable development of port economy. Finally, this article takes a certain port economy sustainable development giant system as an example, and implements a sustainable development strategy based on the idea of the coordinated development of population, environment, resources and economy. Run the intelligent system dynamics model for the sustainable development of port economy constructed in this research to simulate the dynamics of each subsystem. Experimental results show that in the next 20 years, the total population, number of employed population and employment ratio of the port city will continue to increase. After 2025, the emissions of the Exhaust have been declining year by year, the total amount of resources has been continuously reduced, and the utilization rate of resources can be increased to 80.01%. The growth rate of GDP in 20 years is as high as 18.75%, the ratio of the secondary and tertiary industries has changed, and the tertiary industry has become the dominant one. Therefore, the sustainable development system dynamics model of the port economy based on intelligent algorithms and sensor technology can effectively predict the future economic trend, help adjust strategies and further promote the sustainable development of the port economy.

Maximizing the total population with logistic growth in a patchy environment.

This paper is concerned with a nonlinear optimization problem that naturally arises in population biology. We consider the population of a single species with logistic growth residing in a patchy environment and study the effects of dispersal and spatial heterogeneity of patches on the total population at equilibrium. Our objective is to maximize the total population by redistributing the resources among the patches under the constraint that the total amount of resources is limited. It is shown that the global maximizer can be characterized for any number of patches when the diffusion rate is either sufficiently small or large. To show this, we compute the first variation of the total population with respect to resources in the two patches case. In the case of three or more patches, we compute the asymptotic expansion of all patches by using the Taylor expansion with respect to the diffusion rate. To characterize the shape of the global maximizer, we use a recurrence relation to determine all coefficients of all patches.

Coexistence in a competition-diffusion-advection system with equal amount of total resources.

We consider a Lotka-Volterra competition-diffusion-advection system with the total resources for two competitors fixed at the same level. We reveal the combined effect of competition abilities and spatial variations on the coexistence of two competing species. It is obtained that when the ratio of advection rate α to diffusion rate d1 is appropriately large, the two competing species will always coexist if the inter-specific competition coefficients (b,c) in (0,1]×(0,1] and when the ratio is appropriately small, the two species will coexist if the inter-specific competition coefficients c is appropriately small and b is in (0,1].

Distributed algorithm for a finite time horizon resource allocation over a directed network

This work investigates a finite time horizon resource allocation problem under a strongly connected multi-agent network. In this network, each agent at each time is associated with a resource variable and a quadratic cost function. The objective is to minimise the total cost of all agents over the finite time horizon in a distributed manner, while enforcing a total amount of resources per time unit and per agent. The major challenge of this problem lies in the coupled equality constraints across the agents and time periods, which should be satisfied simultaneously in the end. In addition, the local information structure imposed by the digraph within the time horizon should be taken into account when solving the problem. This study develops a consensus-based multipliers decomposition method to solve the problem. The authors show that the convergence and optimality can be ensured provided that the digraph within the time horizon is strongly connected. Numerical simulations are presented to verify the effectiveness of the proposed algorithm.

Comparing spatial networks: A one-size-fits-all efficiency-driven approach.

Spatial networks are a powerful framework for studying a large variety of systems belonging to a broad diversity of contexts: from transportation to biology, from epidemiology to communications, and migrations, to cite a few. Spatial networks can be described in terms of their total cost (i.e., the total amount of resources needed for building or traveling their connections). Here, we address the issue of how to gauge and compare the quality of spatial network designs (i.e., efficiency vs. total cost) by proposing a two-step methodology. First, we assess the network's design by introducing a quality function based on the concept of network's efficiency. Second, we propose an algorithm to estimate computationally the upper bound of our quality function for a given network. Complementarily, we provide a universal expression to obtain an approximated upper bound to any spatial network, regardless of its size. Smaller differences between the upper bound and the empirical value correspond to better designs. Finally, we test the applicability of this analytic tool set on spatial network data-sets of different nature.