Koichi Tanaka, Ren Kishimoto, Bushun Kawagishi
et al.
We study off-policy learning (OPL) in contextual bandits, which plays a key role in a wide range of real-world applications such as recommendation systems and online advertising. Typical OPL in contextual bandits assumes an unconstrained environment where a policy can select the same item infinitely. However, in many practical applications, including coupon allocation and e-commerce, limited supply constrains items through budget limits on distributed coupons or inventory restrictions on products. In these settings, greedily selecting the item with the highest expected reward for the current user may lead to early depletion of that item, making it unavailable for future users who could potentially generate higher expected rewards. As a result, OPL methods that are optimal in unconstrained settings may become suboptimal in limited supply settings. To address the issue, we provide a theoretical analysis showing that conventional greedy OPL approaches may fail to maximize the policy performance, and demonstrate that policies with superior performance must exist in limited supply settings. Based on this insight, we introduce a novel method called Off-Policy learning with Limited Supply (OPLS). Rather than simply selecting the item with the highest expected reward, OPLS focuses on items with relatively higher expected rewards compared to the other users, enabling more efficient allocation of items with limited supply. Our empirical results on both synthetic and real-world datasets show that OPLS outperforms existing OPL methods in contextual bandit problems with limited supply.
Abstract In the Global North, materials production accounts for a limited share of territorial greenhouse gas (GHG) emissions, and national low‐carbon strategies typically focus on direct emissions in the energy, transport, buildings, and agricultural sectors. However, GHG emissions from materials production represent a significant portion of global emissions and are predominantly embodied in imports for these countries. This paper estimates and maps the carbon footprint of materials production (CFM) for France, serving as a representative case study of the Global North, for both the current situation and future scenarios. Our findings indicate that in 2015, the CFM accounted for 3 tCO 2 eq per capita, of which almost 90% were indirect emissions embodied in imports, while emissions from domestic materials production accounted for only 0.7 tCO 2 eq per capita. The CFM is notably distributed across all final consumption sectors, including purchased services, with heterogeneous contributions from different material types. Moreover, the latest national net‐zero emissions strategy is projected to reduce the total French carbon footprint by only half by 2050, with 60% of the remaining GHG emissions corresponding to an unchanged CFM from 2015 to 2050. Based on a detailed mapping of present and projected carbon footprints across supply chains and trade, we identify critical areas for policy intervention. Beyond standard international collaborations and incentives aimed at reducing the carbon content of imports (e.g., Carbon Border Adjustment Mechanism, climate clubs, and climate finance), domestic policies fostering greater circularity and reindustrialization, coupled with shifts toward lower‐demand lifestyles, emerge as essential strategies for effectively diminishing the CFM.
Abstract Assessing bottled mineral water (BMW) against drinking water guidelines set by the World health organization, international bottled water association, and Pakistan standards and quality control authority is critical for ensuring product safety. The present study used physico-chemical parameters to conduct a spatio-temporal analysis of BMW brands in Pakistan. Data were collected from the Pakistan council of research in water resources (PCRWR), comprised of 33 water quality reports (2013–2024) from various districts of Pakistan. The prime objective was to create spatial maps of physico-chemical parameters, including pH, electrical conductivity (EC), hardness, total dissolved solids (TDS), chloride (Cl) and arsenic (As). Comparative analysis of water samples from BMW brands revealed that safe brands met the permissible ranges for pH, EC, hardness, TDS, Cl, and arsenic (As), while unsafe brands did not meet these limit and were deemed for consumption. Integrating spatial data with geographic information systems enabled a more efficient and timely assessment of physico-chemical parameters. Additionally, classifying brands as safe, unsafe, disappeared and emerging over quarterly periods helped allowed for clear differentiation. Overall, the results underscore the importance of continued regulatory efforts by the PCRWR to maintain high standards for BMW in Pakistan. Future strategies could include more frequent testing, public disclosure of non-compliant brands, and incentives for consistent performers to further improve market safety and reliability.
Camila García-Echeverri, Christian Rodríguez-Castiblanco, Nestor Alonso Mancipe-Muñoz
et al.
Las curvas de duración de caudales (CDC) reflejan los efectos de las características de una cuenca sobre los caudales, esto sin tener en cuenta la temporalidad de ocurrencia. Tradicionalmente, se construyen a partir de registros históricos registrados por estaciones y son insumo para el cálculo de índices de gestión del recurso hídrico, como el índice de regulación hídrica (IRH). Debido a la escasez de registros hidrológicos, en la práctica se recurre a estrategias de regionalización de las CDC para estudiar aquellas cuencas no instrumentadas. Este trabajo busca evaluar el desempeño del modelo DWB a partir de entradas diarias en la simulación de CDC en dos subcuencas del río Sogamoso que tienen características diferentes (El Tablazo y Puente Colonial). Se desarrolla una metodología que usa el índice de aridez para identificar cuatro periodos hidrológicamente contrastantes: dos periodos húmedos y dos periodos secos. Posteriormente, se implementaron ocho experimentos de calibración-validación a partir de la combinación de los periodos previamente identificados. Por último, a partir de la revisión cualitativa y cuantitativa con firmas de sesgo en los flujos medios, altos y bajos se evaluaron los resultados arrojados por el modelo DWB. En términos generales, se encontró que el ejercicio fue exitoso en la subcuenca de mayor tamaño (El Tablazo) y que el modelo no logra reproducir los caudales bajos, lo que genera subestimaciones en todos los experimentos realizados.
Hydraulic engineering, Water supply for domestic and industrial purposes
In supply chain networks, firms dynamically form or dissolve partnerships to adapt to market fluctuations, posing a challenge for predicting future supply relationships. We model the occurrence of supply edges (firm i to firm j) as a non-homogeneous Poisson process (NHPP), using historical event counts to estimate the Poisson intensity function up to time t. However, forecasting future intensities is hindered by the limitations of historical data alone. To overcome this, we propose a novel Graph Double Exponential Smoothing (GDES) model, which integrates graph neural networks (GNNs) with a nonparametric double exponential smoothing approach to predict the probability of future supply edge formations.Recognizing the interdependent economic dynamics between upstream and downstream firms, we assume that the Poisson intensity functions of supply edges are correlated, aligning with the non-homogeneous nature of the process.Our model is interpretable, decomposing intensity increments into contributions from the current edge's historical data and influences from neighboring edges in the supply chain network. Evaluated on a large-scale supply chain dataset with 87,969 firms, our approach achieves an AUC of 93.84 % in dynamic link prediction, demonstrating its effectiveness in capturing complex supply chain interactions for accurate forecasting.
Yutecia Karunia Maleakhi, Rainisa Maini Heryanto, Vivi Arisandhy
ABSTRAKPerkembangan industri di era globalisasi berjalan sangat pesat dan diiringi dengan meningkatnya persaingan antar perusahaan. Untuk mempertahankan daya saing yang tinggi dalam memenuhi kebutuhan pasar, kinerja operasional suatu perusahaan harus terus ditingkatkan. Penelitian ini menggunakan model Supply Chain Operations Reference (SCOR) yang diberikan bobot dengan Best Worst Method (BWM) serta diukur dengan Objective Matrix (OMAX) dan Traffic Light System (TLS) untuk evaluasi kinerja pada salah satu perusahaan penanaman modal dalam negeri di Indonesia. Perusahaan telah menetapkan target bisnis kinerja rantai pasok pada sektor pelapis dan aksesoris pipa. Pengukuran kinerja diperlukan untuk meningkatkan kinerja rantai pasok. Pengolahan data menghasilkan 17 indikator kinerja untuk mengukur kinerja rantai pasok. Berdasarkan pengukuran OMAX, kinerja berada pada angka 5,496 yang menunjukkan kategori 'rata-rata' namun memerlukan peningkatan pada masing-masing indikator. Peningkatan kinerja rantai pasok dilakukan dengan cara mengatasi empat indikator yang masuk kategori 'buruk' dan meningkatkan enam indikator yang masuk kategori 'rata-rata'. ABSTRACTIndustrial development during globalization is rapid and is accompanied by increasing competition among companies. To maintain high competitiveness in meeting market needs, a company's operational performance must continuously improve. This research utilizes the Supply Chain Operations Reference (SCOR) model, weighted using the Best Worst Method (BWM), and measured using the Objective Matrix (OMAX) and Traffic Light System (TLS) for performance evaluation at a domestic investment company in Indonesia. The company has set business targets for supply chain performance in the coating and pipe accessories sector. Performance measurements are necessary to enhance supply chain performance. Data processing yields 17 performance indicators for measuring supply chain performance. According to the OMAX measurements, the performance is rated at 5.496, indicating a 'average' category but requiring improvement in each indicator. Improving supply chain performance involves addressing the four indicators in the 'poor' category and enhancing the six indicators in the 'average' category.
This study aims to examine the trophic state conditions in the three major urban perennial lakes of the Coimbatore district based on the physicochemical properties and rotifer community structure. The study was conducted for a period of three months, from January 2023 to March 2023. The water and plankton samples were collected twice a month. The measured physicochemical properties showed that pH, salinity, total hardness, nitrate, and phosphate were found to be higher in Kumarasamy lake, followed by Ukkadam and Valankulam lake ecosystems. The higher rotifer population density was observed in Valankulam lake (1820 Ind./L), and lower in Kumarasamy lake (1080 Ind./L). In this study, Brachionidae species were abundantly found in the three perennial lake water environments, followed by Asplanchnidae, Lecanidae, Trichocercidae, and Filiniidae. In addition, a total of 28 freshwater rotifer species were reported for the first time from the three perennial lakes of the Coimbatore district, respectively. The determined trophic state index (TSI) (47.57) and rotifer trophic state index (TSIROT) (51.25) values affirm that the three perennial lakes are under meso-eutrophic conditions. The examined diversity indices values revealed that species dominance (D) and species richness (SR) are higher in Valankulam lake, followed by Ukkadam and Kumaraswamy lake ecosystems. This difference may be due to the influence of human activities and the mixing of various points and non-point sources of pollutants. The present study concluded that the three perennial lakes were moderately polluted by various sources of pollutants; therefore, continuous monitoring is needed for the conservation of flora and fauna diversity in the three perennial lakes of the Coimbatore district.
Human activities and the climate change affects the river flow therefore monitoring flow rate of river for an extended period can reveal the detail of involved mechanisms in these changes. The previous studies show impact of human activities and climate change on river temporal variations varies in different locations. Water scarce is one of most problem in this area therefore finding affected parameters in water accessibility is important for water management in Middle East. This study aimed to investigate the trend of annual and monthly flow changes in the Dez River branches in southwestern Iran by several nonparametric methods. A structural equation model was used to assess the effects of land use and climate changes on river discharge. The study results showed that the annual precipitation at all stations has no significant trend, but temperature and evaporation at most stations increased significantly. Additionally, more than 30% of the study area's rangeland and forestlands have been converted into agricultural and residential lands. The results showed that land use and climate can determine 43.2% of discharge changes. Also, land use changes are more effective than climate change on river discharge changes.
Jorien Favere, Fien Waegenaar, Mingsheng Jia
et al.
Abstract Safeguarding the drinking water quality remains a challenge from the production site to the tap. Alternatively to chemical disinfection, biostable drinking water could serve as a more sustainable approach to produce microbially safe drinking water and to maintain the microbial quality in the drinking water distribution system (DWDS). In this study, the potential of hydrogen-oxidizing bacteria (HOB) to produce biostable drinking water was examined in a continuous trickling filter supplied with hydrogen gas. A biofilm was naturally enriched for 5 months and the bacterial regrowth, invasion potential, and nutrient composition of the water were determined. Treatment improved the biostability significantly, and it is hypothesized that nutrient limitation, especially phosphorous, was a driving force. As a result, the regrowth and invasion potential were lowered, as shown with specific biostability bioassays. Overall, this study demonstrates the proof-of-concept of HOB for producing biostable drinking water through nutrient limitation.
Mrinalini Mulukutla, Robert Robinson, Danial Khatamsaz
et al.
Materials design is a critical driver of innovation, yet overlooking the technological, economic, and environmental risks inherent in materials and their supply chains can lead to unsustainable and risk-prone solutions. To address this, we present a novel risk-aware design approach that integrates Supply-Chain Aware Design Strategies into the materials development process. This approach leverages existing language models and text analysis to develop a specialized model for predicting materials feedstock supply risk indices. To efficiently navigate the multi-objective, multi-constraint design space, we employ Batch Bayesian Optimization (BBO), enabling the identification of Pareto-optimal high entropy alloys (HEAs) that balance performance objectives with minimized supply risk. A case study using the MoNbTiVW system demonstrates the efficacy of our approach in four scenarios, highlighting the significant impact of incorporating supply risk into the design process. By optimizing for both performance and supply risk, we ensure that the developed alloys are not only high-performing but also sustainable and economically viable. This integrated approach represents a critical step towards a future where materials discovery and design seamlessly consider sustainability, supply chain dynamics, and comprehensive life cycle analysis.
This study describes the correlation between emission of gaseous pollutants to the atmosphere and the combustion parameters of a coal-fired 25 MW heating capacity water boiler with mechanical grate (boiler type WR-25) in unstable working conditions: start-up, shutdown and loads below the technical minimum. Whereas measurements were made for a specific type and size of coal-fired water boiler with mechanical grate, the measurements and calculations are applicable to WR boilers with a different heating power as well as OR type steam boilers, which have a practically identical design. In sum, there are more than 1,000 coal-fired water and steam boilers of these types in Poland. In addition, the analysis reported in this paper highlights the important role played by boilers operating in unstable conditions in terms of emission of gaseous pollutants to the atmosphere. The conclusions are relevant for other boilers fired with gas, oil or biomass operating under conditions such as start-up, shutdown and loads below the technical minimum. This article fills a gap in air protection engineering practice and the literature with regard to indicators and emission standards, drawing on measurements of pollutant concentrations in the exhaust gases from unstable WR boiler working conditions. The measurements can be used to assess the emission of pollutants to the atmosphere in such boiler working conditions and their impact on air quality. The analyses presented were based on the authors’ own measurements in WR-25 boiler technical installations using portable gas analyser GASMET DX-4000, which uses the FT-IR measurement method for compounds such as SO2, NOx, HCl, HF, NH3, CH4, and CO. Concentrations of CO, NOx and SO2 in exhaust gases were determined with multiple regression with the STATISTICA statistical software and with linear regression complemented by the “smart” package in the MATLAB environment. The study provides computational models to identify pollutant concentrations in the exhaust gases in any working conditions of WR-25 boilers. Operational determinants of gaseous air pollutants emissions from coal-fired district heating sources 109 on outdoor temperature, the heating plant provides heat for space heating purposes and for consumable hot water demand, and reaches nominal power usually at temperatures below minus 20°C. Optimal load and maximum energy efficiency occurs at 80–95% of a boiler’s nominal power. At that point the WR boiler reaches its peak energy efficiency of 82% (boiler no. 2 in heating plant A – 78%). In these conditions heat is generated efficiently with minimum fuel consumption, stable furnace operating parameters and good dust removal. Work at optimal load, with almost perfect and complete combustion, delivers the lowest fuel consumption index and the lowest air pollution emissions index per unit of heat generated. At optimal load, monitoring can be restricted to the emission of gases: SO2, NOx and CO2 alone. There are only trace amounts of VOC, HF, HCl, NH3 and CO, as they are mostly caused by incomplete and imperfect combustion. There is a clear increase in emissions of these substances when combustion takes place in substoichiometric conditions, such as start-up, shutdown and load below the technical minimum. A number of legal regulations determine emission standards relating to fuel combustion. The Environmental Protection Law; Regulation of the Climate Minister; CAFE Directive; IED Directive; MCP Directive all determine emission standards for normal conditions of boiler operation. No documents set standards for unstable conditions, such as start-up, shutdown or loads below the technical minimum of boiler operation. Observations of and experience with the operation of boilers in unstable conditions indicate that they lead to increased emissions of pollutants to the atmosphere. Therefore, it was assumed at the start of this study that a boiler operating under unstable conditions experiences significant changes in the concentration of pollutants in the exhaust gases. The novelty of this paper lies in developing an optimization model using multiple and linear regression that is valid for every make of WR boiler operating in unstable conditions. Review of literature China is currently the largest coal consumer in the world and coal has traditionally been its primary energy source. Although the share of coal in the energy consumption of China has decreased in recent years, it still accounted for 62% of its total energy consumption in 2016 and the total consumption of coal has increased by 14% in the last 10 years (Wang et al. 2019). Searching for effective low carbon solutions for coal-fired DH sources is therefore just as important to China as it is to the world. The heating sector, mostly in the form of DH, is a large coal consumer (Lin and Lin 2017), burning 241 million tons in 2015. Heating generation will continue to depend on coal for decades to come, as the share of renewable energy in China is forecast to reach only 30% by 2050. Recently, the Chinese government introduced clean coal technologies into DH, as pilot projects aimed at energy saving and carbon reduction (Wang et al. 2019). The geological resources of coal on the Earth, recalculated as primary energy units, are an estimated 18,000 EJ ‒ two and a half times greater than oil reserves (Wilczyński 2013). The International Energy Agency (IEA) stated that the demand for coal in 2035 in OECD countries would be falling by 1.1% annually, while in China it would be going up by 2.1% each year (Wilk and Bocheńska 2003). Increasing demand for electricity and heat directly contribute to the eventual exhaustion of coal deposits in the world. With the present energy policy of the Chinese state, these deposits will suffice for over 180 years (Miller and Tillman 2008). Moreover, the Indian power sector is playing a key role in global emissions and efforts to mitigate climate change. Lifetime emissions over the next five decades from Indian coal-fired power generation could range from 18 to 39 Pg (Yang and Urpelainen 2019). Global consumption of total energy in 2018 stood at 4,488.2 PJ. This figure differs slightly from the European average – gross inland energy consumption per capita in Poland in 2017 was 115.9 GJ, against the EU average of 137.1 GJ. An increase in global consumption compared to the previous year was observed in the case of hard coal, crude oil, natural gas, renewable energy and other sources, while there was a decrease in brown coal. Charcoal plays a significant role in energy sectors, especially in many developing countries (Marousek et al. 2014). In Poland, the share of the various sources were as follows: hard coal 37.0%, brown coal 9.1%, crude oil 26.3%, natural gas 16.1%, renewables 9.3%, others 2.2%. Domestically sourced primary energy was mostly coal: hard coal with a 56.2% share in 2019, followed by brown coal with 15.2%. The share of natural gas in indigenous production was 5.5%, crude oil 1.5%, and the others, mostly renewables, 18.3% (Statistics Poland, 2019). In 2018, the EU’s consumption of hard coal and brown coal combined reached 596 million Mg, with about 60% of hard coal and more than 90% of brown coal used for electricity and heat production. Between 1990 and 2018 the number of member states of the EU producing hard coal fell from 15 to only 5: Poland, Czech Republic, Germany, United Kingdom and Spain. In 2018, Poland mined 63.4 million Mg of hard coal, 86% of the total EU production (Eurostat, 2019). In Poland, coal is still a strategic source of energy and the vast majority of power plants burn mainly this fuel (EuroHeat and Power 2019, Demirbas 2006, Beom et al. 2018, Wasilewski et al. 2020). This is mostly due to its easy availability and price, as well as the fact that the plants were built in the 1970s and 1980s and designed for coal. Coal consumption in Poland initially rose steeply in the post-war period: it went from 51 million Mg in 1950 to a peak of 164 million Mg in 1980 before trending downward to 63 million Mg in 2018. The significant reduction in coal consumption in Poland is due to the EU’s energy policy, which incentivizes a switch from coal and toward renewable energy sources and, during the transition period, gas and oil combustion. The widely desired decarbonization of the EU economy (in Poland too) is revealing anomalies in its implementation that are throwing an increasingly critical light on the EU’s climate policies and rigorous approach to the combustion of resources such as hard coal and brown coal. The EU itself is an important coal importer. Despite numerous decarbonization programs and a fall in coal mining in EU countries, the EU is actually experiencing rising demand for coal – both hard coal and brown coal. The biggest producer of brown coal in the world is Germany, where extraction of this resource is running at over 170 million Mg 110 R. Zwierzchowski, E. Różycka-Wrońska annually, providing over 30% of the national energy balance. Similar situations can be observed in the economies of some other countries. WR water boilers with movable grate, powered with hard coal culm (coal particles type MI 20–0 mm or MII 10–0 mm) are installed in HOB plants, CHP plants and in industrial plants as heat generating units. A boiler is built in a two-pass system, with one pass in a gas-tight water-wall furnace chamber. Refractory lining is applied to protect front ceiling and sides walls of the furnace in the area of coal combustion. The second pass is a finned convective bundle. The boiler is equipped with installations that control the combustion process, i.e., a secondary air installation over the grate and recirculation of exhaust gases under the grate. The mechanical grille is equipped with a cascade system of fuel supply, offering an option of simultaneous waste co-incineration (Różycka-Wrońska et al. 2014). Refractory lining is applied to protect front ceiling and sides walls of the furna
Abstract The combination of wind energy as a source of production and hydrogen as a carrier and reservoir of energy has been a successful partnership. The unstable nature of wind and the long-term storage capability of hydrogen make them a prosperous pair. Many researches have been done in this field. In most of these researches, the focus has been on the production at the scale of wind farms or on the wind potential of the region. But in this project, the goal was to answer this question: is it possible to meet the energy needs of a household using the combination of wind energy and hydrogen? This project has created a step-by-step algorithm to answer this question. This algorithm starts by modeling the wind speed and finally ends by determining the overall dimensions of the system, including the active surface of the electrolyzer and the surface covered by the turbine. In this way, various components of the mini-Factory, such as electrolyzer, wind turbine, generator, and converter, have been investigated. Finally, an effort was made to select the most optimal operating conditions as well as the appropriate type for each of these components to achieve the expected output.
This paper investigates the inter-regional intra-industry disparity within selected Indian manufacturing industries and industrial states. The study uses three measures - the Output-Capital Ratio, the Capital-Labor Ratio, and the Output-Labor Ratio - to critically evaluate the level of disparity in average efficiency of labor and capital, as well as capital intensity. Additionally, the paper compares the rate of disparity of per capita income between six major industrial states. The study finds that underutilization of capacity is driven by an unequal distribution of high-skilled labor supply and upgraded technologies. To address these disparities, the paper suggests that policymakers campaign for labor training and technology promotion schemes throughout all regions of India. By doing so, the study argues, the country can reduce regional inequality and improve economic outcomes for all.
Ambra Amico, Luca Verginer, Giona Casiraghi
et al.
Supply chain disruptions cause shortages of raw material and products. To increase resilience, i.e., the ability to cope with shocks, substituting goods in established supply chains can become an effective alternative to creating new distribution links. We demonstrate its impact on supply deficits through a detailed analysis of the US opioid distribution system. Reconstructing 40 billion empirical distribution paths, our data-driven model allows a unique inspection of policies that increase the substitution flexibility. Our approach enables policymakers to quantify the trade-off between increasing flexibility, i.e., reduced supply deficits, and increasing complexity of the supply chain, which could make it more expensive to operate.
A novel wireless microstrip-based RF sensor designed for detecting changes in ionic content of water and the addition of solid contaminant objects is proposed and demonstrated. The sensor can be installed on the exterior wall of dielectric containers and customized according to the material of the container to enable wireless sensing. Its operation within the lower microwave frequency range (670-730 MHz) serves to minimize signal attenuation in water and streamlines circuitry design. The most significant feature of this sensor is its unique design, rendering it impervious to its surrounding environment. This not only shields it from environmental noise but also maximizes its sensitivity by efficiently utilizing incoming power for sensing purposes. The sensor exhibits remarkable sensitivity, capable of detecting solute concentrations as low as 0.003125 M in water. It can also detect the insertion of foreign solid objects into the container from the exterior wirelessly and distinguish them from liquids being added. As a proof-of-concept demonstration, the sensor in this study was optimized for a porcelain wall of 10-12 mm thickness. The sensor's small size and the materials used for its fabrication make it adaptable to a wide range of applications in industries such as food, pharmaceuticals, and bathroom fixtures. The aforementioned properties position the sensor as an ideal choice for various smart bathroom applications, where accurate and reliable water use monitoring is essential for efficient water conservation.
As a pivotal innovation in digital infrastructure, blockchain ledger technology catalyzes the development of nascent business paradigms and applications globally. Utilizing Rothwell and Zegveld's taxonomy of twelve innovation policy tools, this study offers a nuanced comparison of domestic blockchain policies, dissecting supply, environment, and demand-driven policy dimensions to distill prevailing strategic orientations towards blockchain healthcare adoption. The findings indicate that blockchain technology has seen rapid growth in the healthcare industry. However, a certain misalignment exists between the corporate and policy layers in terms of supply and demand. While companies focus more on technological applications, existing policies are geared towards regulations and governance. Government emphasis lies on legal supervision through environmental policies, aiming to guide the standardization and regulation of blockchain technology. This maintains a balance between encouraging innovation and market and legal regulatory order, thereby providing a reference for the development of the distributed intelligent healthcare industry in our country.