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In recent years, the poultry breeding industry has been converted into a large-scale, intensive, and intelligent production mode. The Internet of Things (IoT) is under rapid development, which promotes the development of precision livestock farming. In this study, we developed an intelligent service platform for a facility environment based on the IoT structure, utilizing the capabilities of Platform as a Service (PaaS). The platform consists of four layers, including an information perception layer, network layer, management service layer, and application layer. By using the cloud service model with a distributed network architecture, asynchronous data transmission, and a distributed file system, the platform can centrally manage multiple farm's data. The intelligent service platform includes the following functions: displaying environmental data, water and electricity consumption, data analysis, and managing production data. Over a 500-day trial period in a live poultry house, the platform demonstrated high data integrity (>87%) and resilience against network disruptions and power outages. The data validity of each environmental element exceeded 94%, among which the validity of the temperature, humidity, and carbon dioxide concentration exceeded 99%. The overall accuracy of the dataset remained relatively high, providing a robust data foundation for further research. Key features included audio analysis, environmental monitoring, and production data management. The platform's operational status was efficiently communicated via data statistics and email alerts, facilitating timely system recovery. The demonstrated modules included sound recognition, psychrometric charts for visual alerts, and financial analysis tools, offering versatile solutions for integrating PLF models and advanced analytics. [ABSTRACT FROM AUTHOR]

Background: Hematopoietic stem and progenitor cells (HSPCs) mobilize from bone marrow to peripheral blood in response to stress. The impact of alloresponse-induced stress on HSPCs mobilization in human liver transplantation (LTx) recipients remains under-investigated. Methods: Peripheral blood mononuclear cell (PBMC) samples were longitudinally collected from pre- to post-LTx for one year from 36 recipients with acute rejection (AR), 74 recipients without rejection (NR), and 5 recipients with graft-versus-host disease (GVHD). 28 PBMC samples from age-matched healthy donors were collected as healthy control (HC). Multi-color flow cytometry (MCFC) was used to immunophenotype HSPCs and their subpopulations. Donor recipient-distinguishable major histocompatibility complex (MHC) antibodies determined cell origin. Results: Before LTx, patients who developed AR after transplant contained more HSPCs in PBMC samples than HC, while the NR group patients contained fewer HSPCs than HC. After LTx, the HSPC ratio in the AR group sharply decreased and became less than HC within six months, and dropped to a comparable NR level afterward. During the one-year follow-up period, myeloid progenitors (MPs) biased differentiation was observed in all LTx recipients who were under tacrolimus-based immunosuppressive treatment. During both AR and GVHD episodes, the recipient-derived and donor-derived HSPCs mobilized into the recipient's blood-circulation and migrated to the target tissue, respectively. The HSPCs percentage in blood reduced after the disease was cured. Conclusions: A preoperative high HSPC ratio in blood characterizes recipients who developed AR after LTx. Recipients exhibited a decline in blood-circulating HSPCs after transplant, the cells mobilized into the blood and migrated to target tissue during alloresponse. [ABSTRACT FROM AUTHOR]

Financing constraints present a significant challenge for enterprises. Given China's push for the integration of digital technology and the real economy, it is crucial to examine the impact of corporate digital transformation on financing. Using data from Chinese A-share listed companies from 2010 to 2019, we construct the digital transformation indicator employing a machine learning approach and find that corporate digital transformation can significantly alleviate financing constraints. The mechanism analysis shows that digital transformation improves corporate financing by reducing information asymmetry and transaction costs on both sides of financing and enhancing corporate performance. Combined with the mechanism analysis, we reveal that digital transformation has a significant effect on the alleviation of financing constraints among firms with private ownership, higher levels of interaction with investors, more developed financial environments and more intermediaries marketed in their locations, higher proportions of highly skilled workers, and better matching of digital technologies used for transformation. We explore micro-level measurement methods of corporate digital transformation, contributes to the literature on the economic consequences of digital transformation, and enriches the research on enterprise responses to financing constraints. The findings have important implications for promoting corporate digital transformation practices and for understanding coping strategies of different firms. [ABSTRACT FROM AUTHOR]

We examine the relationship between investments in animal breeding and productivity growth on Wisconsin dairy farms using a control function approach. We incorporate farm‐level annual investment in breeding and genetics into the law of motion of productivity as in De Loecker (2013) to test the relationship between these investments and realized productivity. Our unique dataset also allows us to look at the effect of choosing bulls with high milk yield potential on productivity. Our results indicate that breeding investments made 3 years prior are associated with higher productivity of the current cohort. However, the farms with the highest level of productivity reap the lowest benefits from breeding investments, suggesting that there are diminishing returns to investing in genetics. When milk output is not quality adjusted, the contribution of breeding to productivity is undetectable, suggesting that breeding and investments in milk quality are related. We conclude that investments in breeding and genetics significantly contribute to dairy farm productivity, especially in terms of milk quality. [ABSTRACT FROM AUTHOR]