Incorporating water and temperature factors enhanced the performance of the stomatal conductance model for soybeans cultivated under plastic film mulching with drip irrigation in the northeast black soil region
Chunhui Zhang, Tianxiao Li, Qiang Fu
et al.
The application of plastic film mulching combined with drip irrigation can significantly alter the soil and water conditions for crop development. However, existing stomatal conductance models fail to adequately incorporate the effects of this practice on the physiological development of crops. This study employs three stomatal conductance models: Ball-Woodrow-Berry (BWB) model, Ball-Berry-Leuning (BBL) model, and Unified Stomatal Optimization (USO) model. This study introduces two model correction factors: the water response function (f(θ)) and the leaf-air temperature difference (∆T). These factors are utilized to simulate soybean stomatal conductance under various conditions, including plastic film mulching with drip irrigation, plastic film mulching without irrigation, drip irrigation without mulching, and control. The findings demonstrate that the USO model achieves superior performance, followed by the BBL and BWB models. Furthermore, the f(θ) correction factor outperforms the ∆T correction factor in enhancing model performance. The determination coefficients of the corrected BWB, BBL, and USO models increased by 15.2 %-102.2 %, 16.7 %-75.2 %, and 11.6 %-61.0 %, respectively. Meanwhile, the relative errors decreased by 7.5 %-43.2 %, 9.4 %-36.7 %, and 8.3 %-36.6 %, respectively. Additionally, the root mean square errors decreased by 8.2 %-27 %, 6.7 %-32.8 %, and 12.3 %-33.3 %. The corrected model exhibits strong reliability and universality across various soil water relative content and ∆T conditions, as evidenced by comparisons with the 95 % confidence intervals of observational data. The results of this study establish a theoretical foundation for the rational selection of stomatal conductance models in the northeast black soil region, thereby enhancing the simulation accuracy of water and carbon cycle processes under complex hydrothermal conditions.
Agriculture (General), Agricultural industries
Long-term biochar addition improves post-rice wheat production by ameliorating soil mechanical impedance and moisture condition as well as promoting root growth
Zhi Wang, Wei Ma, Yunfei Lu
et al.
Biochar has been widely applied as an efficiency soil additive to modify the quality of cultivated field. However, the effects of long-term biochar addition on spatial and temporal dynamics of soil compaction, and the changes in soil moisture condition and plant root growth remain unclear. Hence, an eight-year (2015/16–2023/24) consecutive field experiment on wheat was conducted in the subtropical humid region of east China, using three treatments: no N fertilizer (PK), chemical fertilizer (NPK), NPK plus biochar (5 t ha−1 yr−1, NPKB). Relative to NPK, across nine growing seasons of wheat, NPKB decreased the soil bulk density by 0.019 and 0.013 units (g cm−3 yr−1), and decreased the soil penetration resistance by 0.028 and 0.015 units (MPa yr−1) in 0–10 cm and 10–20 cm depths, respectively. Biochar addition improved soil water content from seeding to flowering, increased wheat root distribution during the whole growth period, and enhanced soil N supply capacity by promoting N adsorption, which gave rise to greater biomass and N accumulation and more biomass allocation in grain. As a result, NPKB increased wheat yield by 14.8 %, N recovery efficiency by 55.1 %, and crop water productivity by 14.9 %, relative to NPK, on average across four growing seasons of wheat. Therefore, long-term biochar addition has potential to substantially increase grain yield of post-rice wheat, water productivity, and N recovery efficiency. Hence, for the sustainable intensification cropping in the long-run, successive biochar addition could be a finable management for wheat production on the rainfed Yangtze River Region of China.
Agriculture (General), Agricultural industries
Structure and dynamics jointly stabilize the international trade hypergraph
Jung-Ho Kim, Sudo Yi, Sang-Hwan Gwak
et al.
To understand how fluctuations arise and are distributed in international trade, a question crucial for economic risk assessment and policymaking, we analyze strong adverse fluctuations-collapsed trades-defined as individual trades with sharp annual volume declines. Adopting a hypergraph framework for a fine-scale trade-centric representation of international trade, we find that collapsed trades (hyperedges) are clustered and their occurrence decays algebraically with trade volume (weight), which suggests inhomogeneous, epidemic-like spreading of collapse in the international trade hypergraph. Modeling collapse propagation as a contagion process and analyzing its dynamics, we show that a positive degree-weight correlation and a volume-decaying collapse rate synergistically suppress the onset of global collective collapse. Notably, the degree-weight correlation persisted but the volume-decay of the collapse rate weakened during the 2008-2009 global economic recession, resulting in a broader collapse spread. Our study shows how the interplay between structure and dynamics stabilizes complex systems.
en
physics.soc-ph, cond-mat.dis-nn
Effectiveness of spatial measurement model based on SDM-STIRPAT in measuring carbon emissions from transportation facilities
Guozhi Li, Yidan Yuan, Xunuo Chen
et al.
Abstract To gain a deeper understanding of the carbon emission mechanism from transportation facilities, all system elements affecting carbon emissions from regional transportation facilities are identified and analyzed according to panel data from 30 regions in China. A spatial econometric model for carbon emissions from transportation facilities is constructed using the Spatial Dolbin model from 2004 to 2022 as the research period. From the results, the carbon dioxide emissions from transportation facilities added from 318 million tons in 2004 to 752 million tons in 2022, with an average annual growth rate of 4.9%. The global spatial auto-correlation coefficient was significant at the 5%, with an obvious spatial correlation between carbon dioxide emissions within a geographical range. In addition, through stability testing, the model showed high stability in both spatial lag testing and spatial error testing, demonstrating strong ability to interpret data. The research shows that the carbon emission is affected by independent variables, including population, economy, technology, and transportation, and exhibit significant spatial distribution characteristics in different regions and years, providing a basis for policy formulation and carbon emission management.
Energy industries. Energy policy. Fuel trade
Does the disparity between rural and urban incomes affect rural energy poverty?
yinuo wang, Muhammad Umair, Assilova Aizhan
et al.
The persistent disparity between urban and rural incomes in China poses a critical challenge to alleviating energy poverty in rural areas. This study investigates how the income gap between urban and rural regions exacerbates rural energy poverty, focusing on the period from 2005 to 2023, utilizing data from 30 provinces. By employing a two-way fixed-effects model and asymmetry analysis, the research reveals that an increase in the urban-rural income disparity significantly intensifies rural energy poverty. Notably, at higher income quantiles, the gap's effect on energy poverty is more pronounced, while at lower quantiles, its impact is less severe. Financial development, rather than alleviating the situation, is positively associated with rural energy poverty, highlighting an unintended consequence of unequal access to financial services. The results further show that rural regions with limited financial inclusion experience a deepening of energy poverty, with financial service accessibility benefiting wealthier demographics more than the impoverished rural population. These findings imply that targeted policies promoting equitable financial access, narrowing income disparities, and integrating energy poverty reduction strategies are essential to achieving China's Rural Revitalization Strategy.
Energy industries. Energy policy. Fuel trade
Effects of intercropping and regulated deficit irrigation on the yield, water and land resource utilization, and economic benefits of forage maize in arid region of Northwest China
Maojian Wang, Wei Shi, Muhammad Kamran
et al.
Intercropping has been widely recognized to have great advantages in terms of increasing yield, controlling pests and diseases, and saving land, particularly in developing countries. Regulated deficit irrigation reduces water consumption and improves water productivity (WP). However, it is unclear whether the combination of intercropping and deficit irrigation could improve crop yield and WP simultaneously. In this experiment, three planting modes, including forage maize (Zea mays L.) monoculture (M), lablab bean (Lablab purpureus L.) monoculture (L), and maize-lablab bean intercropping (ML) were used. Six irrigation modes were set for each planting mode, including severe water deficit (W1), late water deficit (W2), alternate water deficit (W3), late moderate water deficit (W4), early moderate water deficit (W5), and full irrigation (W6). Results showed that compared with M, the ML treatment significantly increased the fresh forage yield (9.8%–17.0%), hay yield (9.5%–13.1%), crude protein yield (22.9%–25.9%), and WP (7.8%–8.7%). The W5 treatment achieved similar fresh forage yield, hay yield, and crude protein yield as that of the W6 treatment but reduced irrigation water by 25% and increased the WP (21.9%–24.8%). Intercropping achieved a high-water equivalence ratio (WER;1.52–1.81) and land equivalence ratio (LER;1.56–1.84), indicating its advantages over monocultures. The W6 treatment had the lowest WER and LER, suggesting that excessive irrigation can reduce the efficiency of utilizing land and water resource in maze-based forage production. Among all treatments, ML–W5 achieved the highest net income and output to input ratio. Overall, intercropping of forage maize and lablab bean with moderate deficit irrigation at an early stage could be used as a high-yield and efficient forage production system in the arid areas of northwest China.
Agriculture (General), Agricultural industries
Моделювання руху машини під кутом для перевезення будівельних матеріалів
Сергій Орищенко, Віктор Орищенко
Під час робочого процесу навантажувач перемішується на майже горизонтальних майданчиках, допустимий ухил яких. Розрахунок поздовжньої стійкості навантажувачів ведеться з умови перекидання вперед з урахуванням того, що деформуються пневматичні шини, якщо пневмоколісний хід. Кут додаткового нахилу навантажувача вперед внаслідок деформації опор визначається співвідношенням сили тяжкості навантажувача з вантажем жорсткість ґрунту під переднім та заднім котками гусеничного ходу або радіальна жорсткість передніх та задніх пневматичних шин навантажувача на пневмоколісному ході; відстань між центром ваги навантажувача та вертикальною віссю, що проходить через точку перекидання. Тому при розрахунку поздовжньої стійкості гусеничного та пневмоколісного навантажувачів. Найменший запас поздовжньої стійкості має навантажувач у разі руху під ухил з одночасним гальмуванням машини та робочого обладнання при його опусканні. Положення робочого обладнання відповідає максимальному вильоту.
Technological innovations. Automation, Mechanical industries
To Trade Or Not To Trade: Cascading Waterfall Round Robin Rebalancing Mechanism for Cryptocurrencies
Ravi Kashyap
We have designed an innovative portfolio rebalancing mechanism termed the Cascading Waterfall Round Robin Mechanism. This algorithmic approach recommends an ideal size and number of trades for each asset during the periodic rebalancing process, factoring in the gas fee and slippage. The essence of the model we have created gives indications regarding whether trades should be made on individual assets depending on the uncertainty in the micro - asset level characteristics - and macro - aggregate market factors - environments. In the hyper-volatile crypto market, our approach to daily rebalancing will benefit from volatility. Price movements will cause our algorithm to buy assets that drop in prices and sell as they soar. In fact, the buying and selling happen only when certain boundaries are crossed in order to weed out any market noise and ensure sound trade execution. We have provided several numerical examples to illustrate the steps - including the calculation of several intermediate variables - of our rebalancing mechanism. The Algorithm we have developed can be easily applied outside blockchain to investment funds across all asset classes at any trading frequency and rebalancing duration. Shakespeare As A Crypto Trader: To Trade Or Not To Trade, that is the Question, Whether an Optimizer can Yield the Answer, Against the Spikes and Crashes of Markets Gone Wild, To Quench One's Thirst before Liquidity Runs Dry, Or Wait till the Tide of Momentum turns Mild.
Irrigation practices affect relationship between reduced nitrogen fertilizer use and improvement of river and groundwater chemistry
Edoardo Severini, Monia Magri, Elisa Soana
et al.
In the last decades, the intensification of agricultural practices has deeply altered nitrogen (N) and water cycles. Climate change and drought events are expected to further increase the human impacts on the hydrological and biogeochemical cycles, and these impacts are gaining the attention of the scientific community. Here we show how the Chiese River watershed (Lombardy Region, Italy) represents an interesting opportunity to analyse the effects of traditional irrigation practices on N contamination in the context of water scarcity. During summer, flood irrigation is mostly sustained by groundwater withdrawal. Additional water withdrawals from the river contribute to the dry out of the Chiese River. The use of wells for irrigation over permeable and fertilized soils and the percolation of nitrate (NO3-) from the vadose zone to groundwater result in the accumulation of NO3- in groundwater and limited N losses via denitrification due to dominant oxic conditions. These practices contrast other measures targeting the reduction of N excess over arable land. In the Chiese River watershed, the N surplus from Soil System Budget calculations decreased by 43% since the early 2000 s but NO3- concentration in groundwater remained high and stable (up to 98.0 mg NO3- L−1). The dried-out Chiese River gains groundwater and NO3- concentration at the river mouth approaches 32.2 mg NO3- L−1. Our results suggest how the mismanagement of the watershed (overabundant fertilization and flood irrigation using groundwater) increases the N concentration both in the river and groundwater, leading to the violation of both Nitrate and Water Framework directives. We anticipate our assay to be a starting point for the conversion of the northern Po Plain to more efficient irrigation and fertilization practices to contrast severe droughts driven by climate change like the one who struck the Po Plain in summer 2022.
Agriculture (General), Agricultural industries
Towards efficient N cycling in intensive maize: role of cover crops and application methods of digestate liquid fraction
Federico Capra, Diego Abalos, Stefania Codruta Maris
et al.
Abstract Digestate, a by‐product of biogas production, is widely recognized as a promising renewable nitrogen (N) source with high potential to replace synthetic fertilizers. Yet, inefficient digestate use can lead to pollutant N losses as ammonia (NH3) volatilization, nitrous oxide (N2O) emissions and nitrate (NO3−) leaching. Cover crops (CCs) may reduce some of these losses and recycle the N back into the soil after incorporation, but the effect on the N balance depends on the CC species. In a one‐year field study, we tested two application methods (i.e., surface broadcasting, BDC; and shallow injection, INJ) of the liquid fraction of separated co‐digested cattle slurry (digestate liquid fraction [DLF]), combined with different winter cover crop (CC) options (i.e., rye, white mustard or bare fallow), as starter fertilizer for maize. Later, side‐dressing with urea was required to fulfil maize N‐requirements. We tested treatment effects on yield, N‐uptake, N‐use efficiency parameters, and N‐losses in the form of N2O emissions and NO3− leaching. CC development and biomass production were strongly affected by their contrasting frost tolerance, with spring‐regrowth for rye, while mustard was winter killed. After the CCs, injection of DLF increased N2O emissions significantly compared with BDC (emission factor of 2.69% vs. 1.66%). Nitrous oxide emissions accounted for a small part (11%–13%) of the overall yield‐scaled N losses (0.46–0.97 kg N Mg grain−1). The adoption of CCs reduced fall NO3− leaching, being 51% and 64% lower for mustard and rye than under bare soil. In addition, rye reduced NO3− leaching during spring and summer after termination by promoting N immobilization, thus leading to −57% lower annual leaching losses compared with mustard. DLF application method modified N‐loss pathways, but not the cumulative yield‐scaled N losses. Overall, these insights contribute to inform an evidence‐based design of cropping systems in which nutrients are recycled more efficiently.
Renewable energy sources, Energy industries. Energy policy. Fuel trade
Correction : Low carbon futures: assessing the status of decarbonisation efforts at universities within a 2050 perspective
Walter Leal Filho, Diogo Guedes Vidal, Maria Alzira Pimenta Dinis
et al.
Renewable energy sources, Energy industries. Energy policy. Fuel trade
Machine learning's own Industrial Revolution
Yuan Luo, Song Han, Jingjing Liu
Machine learning is expected to enable the next Industrial Revolution. However, lacking standardized and automated assembly networks, ML faces significant challenges to meet ever-growing enterprise demands and empower broad industries. In the Perspective, we argue that ML needs to first complete its own Industrial Revolution, elaborate on how to best achieve its goals, and discuss new opportunities to enable rapid translation from ML's innovation frontier to mass production and utilization.
Multi-Sensory HMI for Human-Centric Industrial Digital Twins: A 6G Vision of Future Industry
Bin Han, Hans D. Schotten
The next revolution of industry will turn the industries as well as the entire society into a human-centric shape. The human presence in industrial environment and the human participation in industrial processes will be magnified more than ever before. To cope with the emerging challenges raised by this revolution, 6G ambitions to bridge the three domains of digital information, physical assets and humans into one merged cyber-physical-human world. This proposes not only an unprecedented demand for digital twin solutions, but also new technical requirements. Especially, aiming at a human-centric industrial DT system, novel multi-sensory human-machine interfaces will play a key role in this paradigm shift.
Constant Function Market Makers: Multi-Asset Trades via Convex Optimization
Guillermo Angeris, Akshay Agrawal, Alex Evans
et al.
The rise of Ethereum and other blockchains that support smart contracts has led to the creation of decentralized exchanges (DEXs), such as Uniswap, Balancer, Curve, mStable, and SushiSwap, which enable agents to trade cryptocurrencies without trusting a centralized authority. While traditional exchanges use order books to match and execute trades, DEXs are typically organized as constant function market makers (CFMMs). CFMMs accept and reject proposed trades based on the evaluation of a function that depends on the proposed trade and the current reserves of the DEX. For trades that involve only two assets, CFMMs are easy to understand, via two functions that give the quantity of one asset that must be tendered to receive a given quantity of the other, and vice versa. When more than two assets are being exchanged, it is harder to understand the landscape of possible trades. We observe that various problems of choosing a multi-asset trade can be formulated as convex optimization problems, and can therefore be reliably and efficiently solved.
Inverse Tensor Variational Inequalities & Market Models: the policymaker’s point of view
A. Barbagallo
Appropriate technology for soil remediation in tropical low-income countries - a pilot scale test of three different amendments for accelerated biodegradation of diesel fuel in Ultisol
Henrik Haller, A. Jonsson, Joel Ljunggren
et al.
Abstract Polluted land in marginalized regions, such as tropical low-income countries and sparsely populated regions in industrialised countries, demand special remediation strategies that are energy-efficient, locally adapted, economically viable. Strategies for appropriate bioremediation technology under such circumstances can be based on locally available resources in combination with in situ bioremediation technologies to keep energy and material costs down. A pilot scale experiment was set up to test the application of three organic by-products from the local industry (whey, pyroligneous acid and compost tea) to enhance the natural biodegradation of diesel in ultisol. Biweekly applications of 6 mL whey kg−1 soil significantly increased the degradation rate but no positive effect on degradation was found with any of the other amendments. Tropical climate is favourable for biodegradation but many tropical soils are rich in clay which can inhibit the bioavailability of the pollutant which in turn may be decisive for biodegradation kinetics. If low cost is a crucial factor, our results indicate that whey treatment has the potential to be an appropriate technology for treating petroleum-contaminated soils in tropical regions.
5 sitasi
en
Environmental Science
Low‐carbon energy policy analysis based on power energy system modeling
Xiao Han, Jing Qiu, Lingling Sun
et al.
Abstract The effect of carbon policies and mechanisms on the behavior of market participants and market equilibrium has been increasingly recognized, of which tax incidence is one of these important issues. Tax incidence is the market output of both producers and consumers that respond to taxes with market equilibrium, whether the tax is levied on sellers or buyers. This paper aims to study the carbon tax incidence on the transmission level of a power system based on different carbon tax collection methods in electricity market environment. A statistical demand elasticity model, power flow and carbon emission flow models are applied to simulate the electricity market equilibrium to analyze the effects of the tax levied on demand‐side or supply‐side. Furthermore, the Australian 59‐bus system is employed in the case study with four stages and four main cases. The results demonstrate that consumers share more burden of the carbon tax in all carbon tax collection methods. Moreover, the proportion of the tax burden and emission reduction effect are different in each method and degree of renewable energy capacity. The results of this paper contribute to the establishment of emission‐related energy policies toward a low‐carbon economy.
Energy industries. Energy policy. Fuel trade, Production of electric energy or power. Powerplants. Central stations
Modeling natural gas consumption, capital formation, globalization, CO2 emissions and economic growth nexus in Malaysia: Fresh evidence from combined cointegration and causality analysis
Mfonobong Udom Etokakpan, Sakiru Adebola Solarin, Vedat Yorucu
et al.
The discovery of natural gas in the 20th century has increased aggregate energy consumption while spurring economic development. However, very little attention has been given in the energy economics literature, especially in Malaysia. As such, this paper primarily revisited the natural gas — economic growth nexus hypothesis in the case of Malaysia. The study was conducted with data from 1980 to 2014 in a multivariate framework with the inclusion of capital formation, globalization, and CO2 emissions to avoid omitted variable bias. We investigated the stationarity properties with a method that accommodates a single structural break. Subsequently, the novel combined co-integration test in conjunction with several techniques were used to assess the magnitude of the long-run equilibrium relationship. The empirical findings trace the long-run equilibrium relationship among the variables over the sampled period. The Granger causality test analysis confirmed the growth-energy driven hypothesis in Malaysia. The findings call for the adoption of cleaner and environmentally friendly energy sources in the Malaysian energy mix. We highlight the need for pragmatic strides from both private and public energy sector stakeholders to prioritize clean and accessible energy in line with the Sustainable Development Goals.
Energy industries. Energy policy. Fuel trade
Modified release of furosemide from Eudragits® and poly(ethylene oxide)-based matrices and dry-coated tablets
Vlachou Marilena, Geraniou Efthymia, Siamidi Angeliki
Modified release of furosemide from tablet formulations is preferred by patients, because of physiological problems, acute diuresis being the most serious, compared to the forms designed for immediate release. With this in view, we aimed at achieving furosemide’s longer gastric retention and waste minimization by preparing matrix and compression coated tablets incorporating different grades of Eudragit® and poly(ethylene oxide) (PEO), polyvinylpyrrolidone (PVP) and lactose monohydrate. Dissolution profiles of the new formulations were compared with that of the main stream drug Lasix®, 40 mg tablets. The results indicate that the use of Eudragit® in conjunction with either PVP or lactose monohydrate led to a slower release rate in the intestinal fluids compared to Lasix®. Moreover, furosemide release in the intestinal pH from matrix tablets and compression coated tablets was not noticeably different. Formulations incorporating PEO led to sustained release, in intestinal fluids, which depended on the molecular weight of PEO.
Multilayer Network Analysis of the Drug Pipeline in the Global Pharmaceutical Industry
Hiromitsu Goto, Wataru Souma, Mari Jibu
et al.
Generally, open innovation is a lucrative research topic within industries relying on innovation, such as the pharmaceutical industry, which are also known as knowledge-intensive industries. However, the dynamics of drug pipelines within a small-medium enterprise level in the global economy remains concerning. To reveal the actual situation of pharmaceutical innovation, we investigate the feature of knowledge flows between the licensor and licensee in the drug pipeline based on a multilayer network constructed with the drug pipeline, global supply chain, and ownership data. Thus, our results demonstrate proven similarities between the knowledge flows in the drug pipeline among the supply chains, which generally agrees with the situation of pharmaceutical innovation collaborated with other industries, such as the artificial intelligence industry.
en
physics.soc-ph, q-fin.GN