54 research outputs found
The Dependence of China’s Monetary Policy Rules on Interest Rate Regimes: Empirical Analysis Based on a Pseudo Output Gap
No full textAlthough a large number of scholars have studied the policy preferences and monetary policy rules of China’s central bank, most have found no evidence that China’s central bank has adjusted the nominal interest rates against the output gap. By constructing the pseudo output gap defined by the deviation of the real output growth rate and the target growth rate, this paper finds that China’s central bank prefers to adjust the nominal interest rates against the pseudo output gap. The monetary policy preferences and rules of China’s central bank in different interest rate regimes are investigated based on the threshold Taylor rule model. It is found that, in the high-interest-rate regime, the central bank adjusts the nominal interest against the inflation gap and the pseudo output gap, while in the low-interest-rate regime, there is no evidence that the central bank adjusts the nominal interest rates against the pseudo output gap. The lower bound of interest rate reduction and the weakening of interest rate policy effects caused by the liquidity trap of the interest rate are the possible reasons for China’s central bank not to adjust the nominal interest rates against the pseudo output gap
Evolution of Agricultural Spatial Market Integration: Evidence from the Hog Market in China
No full textThis article investigates the evolution of hog spatial market integration in China based on a minimal spanning tree by using provincial hog price data. The empirical results show that hog spatial market integration in China has increased gradually and reached a high stable level after 2012. Hog spatial market integration underwent a structural break in April 2007, after which hog market integration was greatly strengthened. Moreover, the market power of hog markets in eastern China and central China is increasing, and Shandong is a price setter, whereas hog markets in southwestern, northeastern, and northern China are price followers
Digital Economy, Industry Heterogeneity, and Service Industry Resource Allocation
No full textBased on the traditional framework of resource mismatch theory analysis and existing literature studies, this paper constructs a model of resource mismatch efficiency loss including the digitalization factor of the service industry, measures the resource mismatch of China’s service industry and its sub-sectors, and empirically analyzes the impact of digital economy development on resource mismatch of service industry using panel data of each sub-sector of China’s service industry from 2001 to 2020. The findings reveal that: (1) Resource mismatch exists in China’s service industry, and the degree of mismatch of capital is more serious than that of labor. (2) Traditional service industries with low digitalization have serious efficiency losses, while emerging service industries with high digitalization have almost no efficiency losses. (3) The increase in the development of the digital economy can significantly improve the resource mismatch in the service industry; appropriate government intervention can improve the capital mismatch but not the labor mismatch; the increase in the proportion of state-owned enterprises is conducive to improving the labor mismatch but not the capital mismatch. Meanwhile, the results of the industry heterogeneity test show that the increase in the digital economy can improve the resource mismatch of both emerging and traditional service industries, but the improvement is more obvious for emerging service industries. Therefore, in the context of the development of the digital economy, we make the following suggestions. The government intervenes appropriately in the capital market, develops emerging service industries, and formulates different digital transformation policies for different industries. Relevant enterprises increase their efforts in technology research and development, and actively explore the direction of digital transformation of service industries. The government and enterprises work together to promote the improvement of China’s economic development level
cultivating in distinct nutrient concentration, combined with biofilm treating eutrophic water bodies
No full textEffects of Rice Husk Biochar Attachment Biofilm with Microorganisms on Nitrogen Removal of Digested Swine Wastewater
No full textNitrogen in digested swine wastewater is currently difficult to directly degrade by an activated sludge process in a sequencing batch reactor (SBR), with resulting failure of the effluent to meet emission standards. In this study, rice husk biochar was optionally added into SBR to enhance biochemical properties for digested swine wastewater, especially for nitrogen degradation. The relative nitrogen removal mechanism for microbial community was probed by means of high-throughput sequencing. The results indicated that chemical oxygen demand (COD), ammonia (NH4+-N), and total nitrogen (TN) removal efficiency of digested swine wastewater was separately at 85.3%, 81.3%, and 65.2% using rice husk biochar with biofilm, which was 3.5%, 24.4%, and 14.7% higher than that of activated sludge, under influent of 2609 mg·L-1 COD, 337.0 mg·L-1 NH4+-N, 344 mg/L TN, and 7.77 C/N. High-throughput sequencing revealed that rice husk biochar with biofilm contained Proteobacteria, Thauera, Comamonas, Acinetobacter, Pseudomonas, Flavobacterium, and Corynebacterium to enhance nitrogen removal of digested swine wastewater. The results not only provide theoretical support for biochar with biofilm to improve digested piggery wastewater treatment, but also have great significance in resource utilization of agricultural waste and eco-environmental protection
Temporal and Spatial Trends in Livestock Manure Discharge and Water Pollution Risk in Chaohu Lake Basin
No full textAssessments of the spatiotemporal distribution of livestock manure and its risk to the watershed are important to prevent water pollution. In this work, the spatiotemporal livestock manure distribution and its risk for the Chaohu lake basin were evaluated based on the excretion coefficient method and ArcGIS technology. In detail, the amounts of livestock manure and its associated pollutants, including chemical oxygen demand (COD), five-day biochemical oxygen demand (BOD5), ammonia (NH4+-N), total nitrogen (TN), and total phosphorus (TP), were calculated from 2009 to 2019. Then, the diffusion concentrations of COD, BOD5, NH4+-N, TN, and TP and the water pollution risk index from livestock manure were estimated and predicted for the Chaohu lake basin. The results indicated that the mean amount of livestock manure had reached 1.04 × 107 t in the Chaohu lake basin in the studied decade. The COD, BOD5, NH4+-N, TN, and TP from livestock manure in Feixi and Feidong contributed 54.26% and 54.40% of the total in the whole basin. These results demonstrate the potential pollution risk of livestock manure for the Chaohu lake basin. Moreover, the diffusion concentrations of COD, BOD5, NH4+-N, TN, and TP for the lake basin were from highest to lowest as follows: Feixi > Feidong > Chaohu > Lujiang > Wuwei > Shucheng > Hefei. The water pollution risk index was more than 20 in Feixi and Feidong, indicating that these areas were heavily affected by local livestock manure. The water pollution risk index will be approximately 18 for the Chaohu lake basin in 2030, implying that the Chaohu lake watershed will suffer moderate pollution from animal manure. These results provide scientific support for policymakers to enhance manure utilization efficiency and control livestock manure loss, causing water eutrophication in Chaohu lake basin or other similar watersheds
Effects of Rice Husk Biochar Attachment Biofilm with Microorganisms on Nitrogen Removal of Digested Swine Wastewater
No full textNitrogen in digested swine wastewater is currently difficult to directly degrade by an activated sludge process in a sequencing batch reactor (SBR), with resulting failure of the effluent to meet emission standards. In this study, rice husk biochar was optionally added into SBR to enhance biochemical properties for digested swine wastewater, especially for nitrogen degradation. The relative nitrogen removal mechanism for microbial community was probed by means of high-throughput sequencing. The results indicated that chemical oxygen demand (COD), ammonia (NH4+-N), and total nitrogen (TN) removal efficiency of digested swine wastewater was separately at 85.3%, 81.3%, and 65.2% using rice husk biochar with biofilm, which was 3.5%, 24.4%, and 14.7% higher than that of activated sludge, under influent of 2609 mg·L-1 COD, 337.0 mg·L-1 NH4+-N, 344 mg/L TN, and 7.77 C/N. High-throughput sequencing revealed that rice husk biochar with biofilm contained Proteobacteria, Thauera, Comamonas, Acinetobacter, Pseudomonas, Flavobacterium, and Corynebacterium to enhance nitrogen removal of digested swine wastewater. The results not only provide theoretical support for biochar with biofilm to improve digested piggery wastewater treatment, but also have great significance in resource utilization of agricultural waste and eco-environmental protection
Carbon Felt Composite Electrode Plates Promote Methanogenesis through Microbial Electrolytic Cells
No full textBioelectrochemical systems are widely used in waste utilization processes. Among them, anaerobic digestion (AD) and microbial electrolytic cell coupling (MEC) are cost-effective and efficient waste-to-energy technologies. In this study, the proposal was made that a carbon felt composite electrode plate be applied to an AD-MEC reactor. The control experiment was conducted using an AD reactor (without the external power supply). The result shows that the carbon felt composite electrode plate increased the biogas production of the AD-MEC reactor by 15.4%, and the average methane content increased by 9.49% compared to the control AD reactor. The total methane production of the AD-MEC reactor and control reactor was 302.51 and 407.79 mL, respectively. The total methane production of the AD-MEC reactor was 34.8% higher than the control group. In addition, the authors found that Methanosarcina and Methanosaeta activities in the AD-MEC reactor were significantly increased. The carbon felt composite electrode plate applied in AD-MEC may have promoted the methanogenic microorganisms’ interspecific acetic acid transport process and increased biogas production and methane content
Survey of General Practitioners' Cognition and Needs for AI Assisted Diagnosis and Treatment Systems
No full textBackground Artificial Intelligence (AI) is a crucial component of China's new-generation information technology development strategy. With its extensive applications in the healthcare field, the integration of AI into general practice for auxiliary diagnosis and chronic disease management plays a significant role in enhancing primary healthcare services and improving the professional skills and clinical decision-making capabilities of general practitioners. Objective Through a preliminary investigation into general practitioners' cognition of AI technology in the medical field and their needs for constructing auxiliary diagnosis and treatment systems across various provinces and cities, this study aims to provide references for establishing more clinically applicable AI-assisted diagnosis and treatment systems. Methods From March to April 2024, we selected general practitioners (GPs) from across China's provinces and municipalities as study participants through national GP WeChat groups. Using a self-designed questionnaire, we collected data on: GPs' basic demographic information; their attitudes toward and understanding of AI-assisted diagnosis and treatment systems; and their needs regarding AI applications in daily clinical practice (including clinical consultations, auxiliary diagnosis and treatment, referral and follow-up, and application formats) . Data collection was conducted via the"Questionnaire Star" platform, and descriptive analysis methods were employed to present and characterize the results. Results This study enrolled 382 general practitioners (GPs) from 27 provinces across China, comprising 52.36% (200/382) from general hospitals and 47.64% (182/382) from primary healthcare institutions. The survey revealed that 57.69% (220/382) of respondents believed physicians and AI should work synergistically, while 77.75% (297/382) of practitioners expressed willingness to adopt or continue using AI-assisted diagnostic technologies in clinical practice; The survey identified key advantages of AI adoption, including improved diagnostic efficiency [89.01% (340/382) ] , reduced clinical workload [84.29% (322/382) ] , and decreased misdiagnosis rates 80.10% (306/382) . However, significant concerns were noted regarding: over-reliance on AI diagnosis [75.13% (287/382) , ethical implications [64.14% (245/382) ] , algorithmic diagnostic bias [63.09% (241/382) ] , data security vulnerabilities [57.33% (219/382) ] , and liability ambiguity in medical incidents [53.66% (205/382) ] ; In the clinical consultation needs assessment, general practitioners most frequently requested AI-enabled alerts for"life-threatening conditions" [61.25% (234/382) ] and prompts for"urgently actionable clinical signs" [62.04% (237/382) ] . Significant demand was also observed for"associated symptom inquiry prompts" [58.90% (225/382) ] and"systematic clinical reasoning guidance" [62.57% (239/382) ] ; In the auxiliary diagnosis and treatment domain, rapid and precise imaging evaluation [67.80% (259/382) ] and prescription review [67.01% (256/382) ] emerged as the most anticipated AI functions. Significant attention was also given to personalized medication recommendations [63.88% (244/382) ] and insurance coverage alerts [66.49% (254/382) ] ; Regarding referral and follow-up management, general practitioners showed the strongest demand for three key AI functions: automated reminders for follow-up visit scheduling [72.25% (276/382) ] , remote monitoring capabilities through smart devices [71.46% (273/382) ] and personalized delivery of patient education content [70.42% (269/382) ] ; In terms of system application formats, general practitioners showed the strongest preference for"reviewing patients' historical medical records" [73.04% (279/382) ] and"voice-to-text transcription" [71.73% (274/382) ] ; In terms of priorities for incorporating undifferentiated diseases into AI-assisted diagnostic and treatment systems, 37.43% (143/382) of general practitioners recommended prioritizing the inclusion of fever in AI-assisted diagnosis and treatment systems. Conclusion General practitioners demonstrated overall high willingness to adopt AI technology for clinical diagnosis and treatment. The AI-assisted clinical decision support system showed significant demand across multiple clinical workflows, including medical history collection, physical examination, diagnostic testing, treatment planning, referral criteria determination, follow-up management, and system application formats. Moving forward, the development of AI-assisted diagnosis and treatment systems tailored for Chinese general practitioners—through overcoming technological limitations, establishing clear legal frameworks and guidelines for AI, and enhancing GPs' AI literacy—will significantly improve primary care physicians' first-contact diagnostic capabilities and facilitate the implementation of tiered healthcare delivery systems
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