Economic Input Research Articles

Research on the Optimization and Development of Low Carbon Energy Economy from the Perspective of Water Conservancy Engineering

In order to explore the optimal development path of low-carbon energy economy in universities, this paper proposes a new method based on complex network theory to describe the global evolution and transformation characteristics of multivariate time series correlation patterns. In order to more intuitively see the impact of product extraction inputs as endogenous factors on economic growth, this article explores the relationship between economic growth and product extraction inputs by constructing a Hamiltonian function and using optimization methods. When considering whether the extraction input share of products with different extraction ratios is different, this article found the relationship between the total extraction input of products with different extraction ratios and the input share of green and low-carbon products, and analyzed consumers' preferences; Extractive investment of products under budget constraints and policy constraints. In addition, this article uses the dynamic equation of household utility function and environmental quality to prove that the extractive input of products not only promotes carbon reduction, but also has a positive effect on promoting economic growth. The simulation results show that the low-carbon economic development model based on energy efficiency proposed in this paper can effectively improve the development path of low-carbon energy economy.

Macroeconomic Productivity Effects of Artificial Intelligence

Abstract Some observers expect that the current wave of new tools based on artificial intelligence (AI) models, such as the large language models, will have strong effects on labor productivity. I present definitions and classifications that help understanding AI as an economic input. I then review theoretical and empirical arguments about macroeconomic productivity effects of AI and conclude that research has so far found no indication that productivity effects of the diffusion of AI are likely to be higher than those associated with the internet boom around the year 2000. While considerable uncertainty around future effects remains, a recent review and calibration exercise by Acemoglu, D. (2024. The Simple Macroeconomics of AI. Cambridge, MA: National Bureau of Economic Research, Working Paper 32487) suggests that the effects might be a lot lower.

Emergy-Based Evaluation of the Sustainability of Agricultural Ecosystem in Dazhou, China, from 2002 to 2022

Our aim is to analyze the emergy evaluation indicators of the agricultural ecosystem in Dazhou, northeastern Sichuan, and provide practical and effective recommendations for sustainable agricultural development. Using emergy analysis, the emergy inputs and outputs of an agricultural ecosystem from 2002 to 2022 were calculated. Five emergy indicators were selected for evaluation: emergy yield ratio (EYR), emergy self-sufficiency ratio (ESR), emergy input ratio (EIR), environmental load ratio (ELR), and emergy sustainable indices (ESI). The total emergy input of the agricultural ecosystem showed an upward trend from 2002 to 2017, thus the industrial auxiliary emergy input decreased, somewhat curbing its continued rise from 2017 to 2022. The structure of emergy inputs, in descending order, is as follows: industrial auxiliary > organic emergy > renewable environmental resources > non-renewable environmental resources. The total emergy output of the agricultural ecosystem was highest in 2007, reaching 2.31 × 1022 Sej, and lowest in 2012, at 1.83 × 1022 Sej. The structure of emergy outputs, in descending order, is as follows: livestock > planting > fishery > forestry. The emergy yield ratio fluctuated down from 3.12 to 2.51, with an average of 2.88, below the provincial average of 3.07. The emergy self-sufficiency ratio fluctuated down from 0.30 to 0.26, with an average of 0.27, above the provincial average of 0.13. The emergy input ratio fluctuated up from 2.31 to 2.91, with an average of 2.66, above the provincial average of 1.86. The environmental load ratio fluctuated from 3.8 to 4.75, with an average of 4.40, which is higher than the provincial average of 1.68. The emergy sustainable indices fluctuated down from 0.81 to 0.53, with an average of 0.67, below the provincial average of 1.17. The efficiency of resource utilization in the agricultural ecosystem of Dazhou has decreased, economic inputs have increased, and it is in a consumptive production process. The pressure on the local natural environment is increasing, and the capacity for sustainable development remains at a low level over the long term.

Effect of Organic Nutrient Sources on Growth, Seed Yield and Seed Quality of Radish (Raphanus sativus L.) cv. Chinese Pink

Seed is the ultimate economic input in any crop production programme. Two field experiments were conducted to study the effect of organic inputs on seed production of radish at Organic Block of Department of Vegetable Science, Dr YS Parmar University of Horticulture and Forestry, Nauni, Solan (HP) during Rabi season of 2019-20 & 2020-21. Various combinations of organic and liquid manures were replicated thrice in the form of twelve treatments in Randomized Block Design (RBD) Factorial. The pooled data of two years revealed that treatment with Vermicompost @ 8 t/ha + Jeevamrit @ 10 per cent was rated as best treatment for majority of characters like days to 50 per cent initiation of bolting (61.00), days to 50 per cent flowering (93.33), number of primary branches per plant (11.13), plant height (171.50 cm), pod length (5.82 cm), number of seeds per pod (5.01), seed yield per plot (225.25 g) & hectare (417.13 kg) and seed quality parameters like 1000 seed weight (12.02 g), seed germination (97.03 %), seedling length (28.26 cm), seedling dry weight (8.87 mg), seed vigour index-I (2742.07) and seed vigour index-II (860.42). Vermicompost along with jeevamrit recorded 61.41 per cent increase in yield over control. Hence application of vermicompost @ 8 t/ha + jeevamrit @ 10 per cent can be recommended for getting higher seed yield and better growth for organic seed production of radish.

An assessment of economy- and transport-oriented health performance

BackgroundGood health can prolong one’s lifespan and is a fundamental human right. Thus, human health is being influenced by prejudiced from sociological, environmental, economic, and geographic aspects. The economy and transportation system pose a serious challenge to the assessment of the health performance of economies.ObjectiveThis study aims to assess the health performance of Organization for Economic Cooperation and Development (OECD) economies by using economic and transport-related indicators and examining the role of health expenditure and governance in improving efficiency.MethodsThis study measures the economy- and transport-oriented health efficiency of 35 OECD economies for the period of 2000–2022. In the first stage, this study employs a slacks-based measure and the data envelopment analysis–window analysis approach to conduct individual (economy and transportation) and joint assessments to measure health efficiency. In the second stage, this study uses the tobit regression method to investigate the effects of influencing factors, namely, government general health and pharmaceutical expenditures, the medical infrastructure, and governance, on health efficiency.ResultsEmpirical results reveal that a 1-unit change in the health expenditure during the research period improves economy-oriented health efficiency by 71% and transport-oriented health efficiency by 58%. The econometric analysis demonstrates that all the coefficients of economy- and transport-oriented health efficiency are significant and positive. Notably, a 1-unit change in the medical infrastructure increases economy- and transport-oriented health efficiency by 50.8%, and a 1% increase in pharmaceutical expenditure increases the health, economy, and transport efficiency scores by 16.3%, 33%, and 58.6%, respectively.ConclusionsThe findings suggest that some of the economies were efficient with regard to their health-oriented outputs, that is, quality of life and mortality and morbidity rates, and most of the economies demonstrated excellent economic performance. The findings of the transport-oriented health efficiency assessment reveal that the economies were unable to perform well in the last year of the research period owing to the nationwide lockdowns. Nonetheless, they demonstrated efficiency in the first half of the research period. The joint assessment of economy- and transport-oriented health efficiency indicates that economic and transport input resources can adversely affect the GDP and life expectancy simultaneously, and the medical infrastructure, pharmaceutical expenditure, and number of medical graduates serve as constructive stimuli for health efficiency improvement.

Predicted Expenditure for Prescription Drugs for Multiple Sclerosis in the Italian Market Between 2023 and 2028: Results of the Oracle Project.

Multiple sclerosis (MS) is a chronic neurodegenerative disease that leads to impaired cognitive function and accumulation of disability, with significant socioeconomic burden. Serious unmet need in the context of managing MS has given rise to ongoing research efforts, leading to the launch of new drugs planned for the near future, and subsequent concerns about the sustainability of healthcare systems. This study assessed the changes in the Italian MS market and their impact on the expenditures of the Italian National Healthcare Service between 2023 and 2028. A horizon-scanning model was developed to estimate annual expenditure from 2023 to 2028. Annual expenditure for MS was calculated by combining the number of patients treated with each product (clinical inputs) and the yearly costs of therapy (economic inputs). Baseline inputs (2020-2022) were collected from IQVIA® real-world data, while input estimation for the 5-year forecast was integrated with analog analyses and the insights of clinicians and former payers. The number of equivalent patients treated in 2028 in Italy was estimated at around 67,000, with an increase of 10% versus 2022. In terms of treatment pattern evolution, first-line treatments are expected to reduce their shares from 47% in 2022 to 27% in 2028, and Bruton tyrosine kinase inhibitors are expected to reach 23% of patient shares. Overall, expenditure for MS is estimated to decrease from €721 million in 2022 to €551 million in 2028, mainly due to losses of exclusivity and renegotiation of drug prices. Despite the increase in the number of patients treated for MS and the launch of new molecules that will reach high market penetration, the model confirmed sustainability for the Italian National Healthcare Service.

Glutamine Synthetase and Glutamate Synthase Family Perform Diverse Physiological Functions in Exogenous Hormones and Abiotic Stress Responses in Pyrus betulifolia Bunge (P.be)

The unscientific application of nitrogen (N) fertilizer not only increases the economic input of pear growers but also leads to environmental pollution. Improving plant N use efficiency (NUE) is the most effective economical method to solve the above problems. The absorption and utilization of N by plants is a complicated process. Glutamine synthetase (GS) and glutamate synthase (GOGAT) are crucial for synthesizing glutamate from ammonium in plants. However, their gene family in pears has not been documented. This study identified 29 genes belonging to the GS and GOGAT family in the genomes of Pyrus betulaefolia (P.be, 10 genes), Pyrus pyrifolia (P.py, 9 genes), and Pyrus bretschneideri (P.br, 10 genes). These genes were classified into two GS subgroups (GS1 and GS2) and two GOGAT subgroups (Fd–GOGAT and NADH–GOGAT). The similar exon–intron structures and conserved motifs within each cluster suggest the evolutionary conservation of these genes. Meanwhile, segmental duplication has driven the expansion and evolution of the GS and GOGAT gene families in pear. The tissue–specific expression dynamics of PbeGS and PbeGOGAT genes suggest significant roles in pear growth and development. Cis–acting elements of the GS and GOGAT gene promoters are crucial for plant development, hormonal responses, and stress reactions. Furthermore, qRT–PCR analysis indicated that PbeGSs and PbeGOGATs showed differential expression under exogenous hormones (GA3, IAA, SA, ABA) and abiotic stress (NO3− and salt stress). In which, the expression of PbeGS2.2 was up–regulated under hormone treatment and down–regulated under salt stress. Furthermore, physiological experiments demonstrated that GA3 and IAA promoted GS, Fd–GOGAT, and NADH–GOGAT enzyme activities, as well as the N content. Correlation analysis revealed a significant positive relationship between PbeGS1.1, PbeGS2.2, PbeNADH–GOGATs, and the N content. Therefore, PbeGS1.1, PbeGS2.2, and PbeNADH–GOGATs could be key candidate genes for improving NUE under plant hormone and abiotic stress response. To the best of our knowledge, our study provides valuable biological information about the GS and GOGAT family in the pear for the first time and establishes a foundation for molecular breeding aimed at developing high NUE pear rootstocks.

Workflow to support cost-benefits comparison and sensitivity analysis of BIPV case studies: Three examples of BIPV facades in the south of Switzerland

The building skin surfaces represent a vast potential for decentralising renewable energy investments and offering unique opportunities for prosumers thanks to the built environment. Despite the recognised potential of building-integrated photovoltaics (BIPV), cost-effectiveness is still a market barrier to accelerate deployment. The literature reports investigations on costs at product level and cost-effectiveness scenarios and prospects. However, the literature assessing the economic viability of real building processes is scarce. BIPV costs are strongly project-related and affected by construction work factors that cannot be generalised or observed at a macro-scale. Thus, the lack of concrete and documented applications in existing buildings is a missing gap for the sector and doesn’t support the market in clarifying the real economic costs and benefits of BIPV systems or the main parameters influencing the economic variability in real constructions. This study contributes to the field by developing a cost-benefit analysis of established BIPV case studies situated in the southern region of Switzerland. The approach employs a comprehensive economic evaluation, utilizing the net present value method. A sensitivity analysis is developed to assess costs by varying key economic input parameters that significantly impact the financial aspects of BIPV installations. This research aims to conduct a comprehensive analysis of specific case studies, presenting original findings that elucidate the interplay between energy and construction factors. By discerning these relationships, the study seeks to unveil the determinants of cost competitiveness, ultimately contributing to the increase of attractiveness within the realm of BIPV facade benefits throughout the entire value chain.

Solar-driven environmental fate of chlorinated parabens in natural and engineered water systems

Parabens are classified as emerging contaminants in global waters, and the ubiquitous emergence of their high-risk chlorinated products generated from chlorine-based wastewater disinfection has attracted increasing attention. However, rather limited information is available on their photofate after discharging into surface waters, and their degradation behavior after solar-based engineering water treatment is unclear. Herein, the reactivity of four chlorinated parabens with different photochemically produced reactive intermediates was measured. Quantitative contribution analysis in abating such compounds showed the dominance of direct photolysis in sunlit natural freshwaters. Introducing a technical solar/peroxymonosulfate (PMS) system could greatly improve the removal of chlorinated parabens. The economic analysis suggested that chlorinated parabens exhibited a minimum value of economic input as 93.41–158.04 kWh m-3 order-1 at 0.543–0.950 mM PMS. The high-resolution mass spectrometry analysis of the degradation products suggested that dechlorination, hydroxylation, and ester chain cleavage were the dominant transformation pathways during photolysis and solar/PMS treatment. Furthermore, the in silico prediction indicated severe aquatic toxicity of certain products but enhanced biodegradability. Overall, this investigation filled a knowledge gap on the reactivity of chlorinated parabens with diverse reactive transients and their quantitative contributions to the photolysis and solar/PMS treatment of emerging micropollutants in water.

Study on the relationship between economic input growth in Marine protected areas and environmental governance in the North Pacific Coast of Costa Rica: Based on reef fish assemblages

Reef fish communities under fishing pressure often experience reduced biomass, abundance, and altered size structure. The establishment of marine protected areas (MPAs) can help mitigate these declines. However, the success of MPAs, especially in developing countries with financial and socioeconomic challenges, largely hinges on effective enforcement. This study utilized underwater visual surveys (UVS) and baited remote underwater video stations (BRUVS) to evaluate population density, size distribution, and biomass of both economically valuable (e.g., target and ornamental species) and ecologically important (e.g., small/large predators and herbivores) fish groups within and outside a no-take MPA on the northern Pacific coast of Costa Rica.The results indicated that protective measures did not significantly affect the biomass of economically valuable fish species. However, there were notable differences in fish abundance and size distribution between no-take zones (where fishing is prohibited) and open-fishing zones. This suggests that, despite potential illegal fishing activities within the MPA, certain fish community components benefit from the protective measures.Specifically, herbivores and ornamental fish, which are often targeted by artisanal compressor fishing and the aquarium trade, exhibited higher biomass and abundance levels within the MPA. Additionally, significant shark species such as Galeocerdo cuvier, Carcharhinus leucas, and Carcharhinus limbatus were exclusively found within the MPA.The study also highlighted the crucial role of habitat quality, particularly high coral cover, in enhancing the biomass of ornamental fish.This research contributes to the growing body of evidence that MPAs, even with limited enforcement, consistently offer ecological benefits for reef fish communities

Sedaconda ACD-S for Sedation with Volatile Anaesthetics in Intensive Care: A NICE Medical Technologies Guidance.

Intensive care unit (ICU) patients receive highly complex care and often require sedation as part of their management. ICU sedation has traditionally been delivered using intravenous (IV) agents due to the impractical use of anaesthetic machines in this setting, which are used to deliver volatile sedation. Sedaconda anaesthetic conserving device (ACD)-S (previously known as AnaConDa-S) is a device which allows for the delivery of volatile sedation via the majority of mechanical ventilators by being inserted in the breathing circuit where the heat and moisture exchanger is normally placed. The National Institute of Health and Care Excellence (NICE), as part of the Medical Technologies Evaluation Programme, considered the potential benefits of using Sedaconda ACD-S compared to standard IV sedation in ICU patients. Here we describe the evidence evaluation undertaken by NICE on this technology, supported by CEDAR. CEDAR considered the evidence present in 21 publications that compared the clinical outcomes of patients receiving Sedaconda ACD-S-delivered sedation and IV sedation, and critiqued the economic model provided by the manufacturer. Clinical expert input during the evaluation process was used extensively to ensure that the relevant clinical evidence was captured and that the economic model was suitable for the UK setting. Due to the uncertainty of the evidence, sensitivity analysis was carried out on the key economic inputs to ensure the reliability of the results. Economic modelling has shown that Sedaconda ACD-S-delivered isoflurane sedation is cost saving on a 30-day horizon compared to IV sedation by £3833.76 per adult patient and by £2837.41 per paediatric patient. Clinical evidence indicated that Sedaconda ACD-S-delivered isoflurane sedation is associated with faster patient wake-up times than standard of care. Consequently, NICE recommended Sedaconda ACD-S as an option for delivering sedation in the ICU setting, but noted that further research should inform whether Sedaconda ACD-S-delivered sedation is of benefit to any particular subgroup of patients.

A stochastic production frontier model for evaluating the performance efficiency of artificial intelligence investment worldwide

As artificial intelligence (AI) begins to take center stage in technological innovations, it is essential to understand the business value of AI innovation efforts and investments. While some early work at the firm level exists, there is a shortage of literature that takes a larger country-level perspective. This study investigated the effect of AI innovation efforts on production efficiency across countries using stochastic production frontier approaches. In addition, our model also included the traditional economic inputs of capital and labor. We used both the Cobb–Douglas function and Constant Elastic Substitution model specifications. The significant findings of this study are as follows: Innovation efforts in AI measured by the number of AI-related patents and capital investment in AI have a substantial effect on economic output. The significance of AI investments indicates the need for a robust digital infrastructure as a prerequisite for harnessing AI capabilities. The complementary relationship between labor and AI-related patents implies that high-skilled labor is often necessary to incorporate AI inputs into production. However, as AI capabilities develop, they weaken the effect on labor input. The study also distinguishes between AI innovation (research and development activities indicated by AI patents) and the production efficiency of AI investments (return on every dollar invested), highlighting that more AI innovation does not always translate into better production efficiency. The findings indicate that while the United States leads innovation in AI, the UK has the best production efficiency. China ranked fourth in AI innovation and has the lowest production efficiency among the countries included in the study.

Cost-effectiveness analysis of the pediatric 20-valent pneumococcal conjugate vaccine compared with lower-valent alternatives in Argentina

ObjectivesThe 13-valent pneumococcal conjugate vaccine (PCV13) has been recommended for infants in Argentina’s national immunization program (NIP) in a 2 + 1 schedule since 2012. Licensure of the 15-valent vaccine (PCV15) is anticipated soon, and the 20-valent vaccine (PCV20) recently received regulatory approval. This cost-effectiveness analysis examined the public health and economic implications of transitioning from PCV13 to either PCV15 or PCV20 in Argentina’s pediatric NIP. MethodsA decision-analytic Markov model was used with a 10-year time horizon and a 3.0% annual discount rate for costs and benefits. Vaccine effectiveness estimates were derived from Argentinian surveillance data, PCV13 clinical effectiveness and impact studies, and PCV7 efficacy studies. Population, epidemiologic, and economic inputs were obtained from literature and Argentinian-specific data. The study adopted a healthcare system perspective; sensitivity and scenario analyses were conducted to assess input parameters and structural uncertainty. ResultsCompared with PCV13, PCV20 was estimated to avert an additional 7,378, 42,884, and 172,389 cases of invasive pneumococcal disease (IPD), all-cause pneumonia, and all-cause otitis media (OM), respectively, as well as 3,308 deaths, resulting in savings of United States Dollars (USD) 50,973,962 in direct medical costs. Compared with PCV15, PCV20 was also estimated to have greater benefit, averting an additional 6,140, 35,258, and 142,366 cases of IPD, pneumonia, and OM, respectively, as well as 2,624 deaths, resulting in savings of USD 37,697,868 in direct medical costs. PCV20 was associated with a higher quality-adjusted life year gain and a lower cost (i.e., dominance) versus both PCV13 and PCV15. Results remained robust in sensitivity analyses and scenario assessments. ConclusionOver a 10-year horizon, vaccination with PCV20 was expected to be the dominant, cost-saving strategy versus PCV13 and PCV15 in children in Argentina. Policymakers should consider the PCV20 vaccination strategy to achieve the greatest clinical and economic benefit compared with lower-valent options.

General equilibrium analysis of carbon tax policy on water-energy-food nexus efficiency

Carbon-reduction policy affects socio-economy and Water-Energy-Food (WEF) nexus contained therein. Existing studies concentrated on policy performances on resource consumption, but cannot quantify the impacts on resource utilization efficiency. To fulfill such gap, this study developed an integrated evaluation method through integrating computable general equilibrium model with data envelopment analysis to explore the impact of carbon tax on WEF environmental efficiency of China. Results show that increasing carbon taxes would improve the energy structure and reduce carbon emissions. While the increased cost of fossil fuels would have negative but limited impacts on economic output of water supply and food sectors through economic activity connections. Synergistic effect of WEF resource conservation could be observed in most production sectors, expect for clean energy sectors. Carbon tax would improve the WEF environmental efficiency expressed as the trade-offs between economic and carbon emission outputs and WEF resource inputs. There are significant differences in WEF efficiency and its growth rate among production sectors, with food sectors experiencing the most significant improvement in WEF efficiency at a carbon tax of 70 yuan/ton. The evaluation results raised the awareness of the performance of carbon tax on WEF nexus and provide a new perspective for promoting WEF nexus efficiency.

Advancing environmental assessment methodologies: A case study on Pentle's framework through component analysis for complex objective functions

This paper explores the evolution and refinement of environmental assessment methods in response to contemporary challenges. While various methodologies exist, R. Pentle's proposed calculation method, represented by a multiple linear regression equation, stands as a significant contribution. However, this method requires refinement. To address this, the paper uses a case study approach within the State National Natural Park (SNNP) Katon-Karagay to investigate the impact of recreational load on tourist routes and the associated environmental load. Through component analysis, a complex objective function is developed within Pentle's framework, emphasizing the need for a standard-setting procedure and offering a fresh perspective on environmental functions. Rather than conventional rating scales, the study advocates for an innovative approach to delineating environmental scenarios. Importantly, this approach extends beyond environmental data analysis, offering applicability across diverse datasets, including economic and social inputs. The findings contribute to advancing environmental assessment methodologies, offering a versatile framework for understanding and managing the impacts of recreational and environmental loads in protected natural areas.

Knowledge is power: Electric vehicle calculator for cold climates

We used crowdsourced data in Alaska and the literature to develop a light-duty electric vehicle model to help policymakers, researchers, and consumers understand the trade-offs between internal combustion and electric vehicles. This model forms the engine of a calculator, which was developed in partnership with residents from three partner Alaskan communities. This calculator uses a typical hourly temperature profile for any chosen community in Alaska along with a relationship of energy use vs. temperature while driving or while parked to determine the annual cost and emissions for an electric vehicle. Other user inputs include miles driven per day, electricity rate, and whether the vehicle is parked in a heated space. A database of community power plant emissions per unit of electricity is used to determine emissions based on electricity consumption. This tool was updated according to community input on ease of use, relevance, and usefulness. It could easily be adapted to other regions of the world. The incorporation of climate, social, and economic inputs allow us to holistically capture real world situations and adjust as the physical and social environment changes.

The impact of Artificial Intelligence on E-commerce supply chain sector in achieving cost efficiency and economic growth: A business and economics perspective

The study aims to find how much cost effectiveness is achieved when e-commerce supply chain operations use automation and AI technologies. therefore,ing technology of AI and its models have essentially proved to be impactful in making data driven decisions by the organisations gaining leverage in productivity and profit sustainability in a way that the companies achieve competitive advantage therefore creating sustainable value propositions from business and economics perspective. Aim/Purpose The aim of the paper is to explore the positive relationship between AI technologies and productivity levels in the e-commerce supply chain sector through achieving cost effectiveness and economic growth. Methodology/Approach The study focussed on reviewing literature on how Artificial Intelligence driven technology can optimise various supply chain functions within e-commerce sector. Solow-Swan growth model has been applied to investigate the value AI creates in utilising capital, labour input to achieve output growth. Positivist approach that allowed for objective observation and independent conclusions has been adopted. For primary data, quantitative methodology is used through survey questionnaires to gather data from a sample of 206 employees, managers, data analysts in e-commerce supply chain sectors. Findings The findings from the secondary sources inform that the use of AI and automation in the e-commerce industry leads to a high rate of productivity in terms of reducing costs and promoting economic growth. The primary research methods, through survey questionnaires collects real-time data that helps achieve quantifiable and measurable values to conclude that AI-led technology can increase productivity and competitive advantage as it saves cost while increasing productivity and overall economic input. Descriptive statistics of measures of central tendency were used to present findings in simpler, presentable way followed by interpretations of the data in percentages. Practical implications Managers and decision-making directorial board members have important lessons to learn from these findings as the quantifiable values may give them an insight into how much capital investment should be allocated for AI technologies and how predictive analytics and data analysis can accelerate their service towards becoming customer centric. Significant strategic planning and implementation of resource management can lead to higher rates of productivity profitability and eventually higher economic growth.

Cost-effectiveness of albumin in the treatment of decompensated cirrhosis in resource-limited healthcare settings.

Human albumin (HA) is an effective adjuvant treatment for patients with cirrhosis developing spontaneous bacterial peritonitis (SBP), hepatorenal syndrome (HRS) and ascites requiring large-volume paracentesis (LVP). However, cost remains a barrier to use, particularly in resource-limited settings. This study aims to assess the cost-effectiveness of HA in patients with cirrhosis with SBP, HRS or ascites requiring LVP in the Indonesian healthcare system as a representative of a resource-limited setting. Three decision-tree models were developed to assess the cost-effectiveness of (1) antibiotics and HA versus antibiotics alone in patients with SBP, (2) terlipressin and HA versus terlipressin alone in patients with HRS, and (3) LVP and HA versus LVP and gelatine for patients with ascites. Clinical utility and economic inputs were pooled from the available literature. Time horizon was 3 months. Outcomes were expressed as incremental cost-effectiveness ratios (ICER) reported as 2021 IDR per quality-adjusted life year (QALY) (exchange rate June 30, 2021: 1 EUR = 17,245 IDR). Willingness-to-pay thresholds considered were: three times the GDP per capita (199,355,561 IDR/QALY; 11,560 EUR/QALY) and one time the GDP per capita (66,451,854 IDR/QALY; 3853 EUR/QALY). The ICER for antibiotics and HA (versus antibiotics alone) for SBP was 80,562,652 IDR per QALY gained (4672 EUR/QALY). The ICER for terlipressin and HA (versus terlipressin) for HRS was 23,085,004 IDR per QALY gained (1339 EUR/QALY). The ICER for LVP and HA versus LVP and gelatine was 24,569,827 IDR per QALY gained (1425 EUR/QALY). Adjunctive HA may be a cost-effective treatment for SBP, HRS and LVP in resource-limited settings.

Synergizing biotechnology and natural farming: pioneering agricultural sustainability through innovative interventions.

The world has undergone a remarkable transformation from the era of famines to an age of global food production that caters to an exponentially growing population. This transformation has been made possible by significant agricultural revolutions, marked by the intensification of agriculture through the infusion of mechanical, industrial, and economic inputs. However, this rapid advancement in agriculture has also brought about the proliferation of agricultural inputs such as pesticides, fertilizers, and irrigation, which have given rise to long-term environmental crises. Over the past two decades, we have witnessed a concerning plateau in crop production, the loss of arable land, and dramatic shifts in climatic conditions. These challenges have underscored the urgent need to protect our global commons, particularly the environment, through a participatory approach that involves countries worldwide, regardless of their developmental status. To achieve the goal of sustainability in agriculture, it is imperative to adopt multidisciplinary approaches that integrate fields such as biology, engineering, chemistry, economics, and community development. One noteworthy initiative in this regard is Zero Budget Natural Farming, which highlights the significance of leveraging the synergistic effects of both plant and animal products to enhance crop establishment, build soil fertility, and promote the proliferation of beneficial microorganisms. The ultimate aim is to create self-sustainable agro-ecosystems. This review advocates for the incorporation of biotechnological tools in natural farming to expedite the dynamism of such systems in an eco-friendly manner. By harnessing the power of biotechnology, we can increase the productivity of agro-ecology and generate abundant supplies of food, feed, fiber, and nutraceuticals to meet the needs of our ever-expanding global population.

Collaborative optimization model and algorithm for airport capacity and traffic flow allocation.

How to efficiently utilize the existing airport capacity without physical expansion and considerable economic inputs to meet air traffic needs is one of the important tasks of air traffic management. To improve the efficiency of capacity utilization, it is necessary to find the actual airport capacity properly. In this work, taking Shuangliu International Airport as an example, a methodology for capacity estimation is proposed that combines the empirical method with an analytical approach that uses historical performance data from the airport to construct a capacity envelope to approximate the airport's actual capacity to the greatest extent, establishes a collaborative optimization model that reflects the inherent relations between airport capacity and arrival and departure traffic demand, adopts an improved optimization algorithm to solve the model, and generates an optimal flight allocation scheme. Priority ratio is introduced to dynamically adjust management preferences for arrival and departure traffic demand to further reveal the synergy mechanism between departure and arrival traffic flow demand and the airport capacity. The result shows that the Flight On-time Performance rate is lifted by 6% in the case study which proves the feasibility of the proposed method, demonstrating its value for maximizing airport capacity and traffic flow demand without requiring expansions on airport scales.