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An increasing number of record-breaking extreme precipitation events worldwide has had an incalculable socioeconomic impact, challenging the ability of cities to recover and reconstruct after disasters. The key to the effectiveness of post-disaster recovery and reconstruction lies in the rational investment and allocation of reconstruction funds. However, few studies have examined the effectiveness of reconstruction fund planning in improving urban recovery and reconstruction from a post-disaster indirect economic loss assessment perspective. This study uses an improved input-output model to evaluate the degree of change in indirect economic losses under multidimensional reconstruction fund planning (funds' amount, the time efficiency of investment, and funds allocation) to measure the effectiveness. We exemplify this through a case study: a record-breaking extreme urban flood and its reconstruction planning occurred in Henan Province, China, in July 2021. The results indicate that (1) under the premise of ensuring sufficient financial input, improving the input time efficiency is a decision with a higher benefit-cost ratio, which can improve the effectiveness by 140%. (2) If funds are guaranteed, improving time efficiency is better than adding extra funds, and when both reach 80%, additional funds may not further improve the effectiveness. (3) The funds need to meet at least the recovery production needs (about 45% of direct economic losses); otherwise, the funds cannot be used to improve fortifications. The study results will provide theoretical and practical support for urban decision-makers to develop efficient and rational recovery and reconstruction programs. • Multidimensional planning for post-disaster recovery and reconstruction funds should consider the amount, time efficiency, and allocation of funds. • The amount of funds and their time efficiency have a limit to their improvement. • The funds cannot be used to improve fortification before covering production recovery needs. [ABSTRACT FROM AUTHOR]

From the perspective of agribusiness, the market price of live pigs reflects the current demand. Therefore, tracking and forecasting market prices are important tasks in agrimanagement, by which the production schedule can be adjusted to increase profit. An agricultural internet platform was developed as an integrated cloud service for market tracking. To quantitatively forecast online pig trading, in this study, a short‐term forecasting model of the pig price index was developed; the model automatically retrieved historical data as a training data set and determined the price index forecast with an autoregressive integrated moving average (ARIMA) algorithm for a time‐series analysis. The mean square error (MSE) of the AR(1) model for predicting the pig price index in Henan Province was 159.010, and the MSE of the ARIMA(1,1) model for predicting pig price index in Fujian Province was 92.294. The results demonstrated that the error between the predicted calculation and verification test results was small, and the results efficiently improved the prediction accuracy (EconLit citations: C6, L86, Q1). [ABSTRACT FROM AUTHOR]

Giardia duodenalis is a common and widespread intestinal protozoan parasite of both humans and animals. Previous epidemiological and molecular studies have identified Giardia infections in different animals and humans, but only limited information is available about the occurrence and genotypes of Giardia in cattle in China. In this study, we determined the occurrence of giardiasis and genetically characterized G. duodenalis in dairy cattle in Henan Province, central China. The overall prevalence of G. duodenalis was 7.2% (128/1777) on microscopic analysis, with the highest infection rate (22.7%) in calves aged less than 1 month. G. duodenalis assemblages and subtypes were identified with multilocus genotyping based on the SSU rRNA, β-giardin (bg), glutamate dehydrogenase (gdh), and triosephosphate isomerase (tpi) genes. Two assemblages were detected in the successfully sequenced samples: assemblage A (n = 58), assemblage E (n = 21), with a mixed E and A assemblage (n = 2). Four novel subtypes of the gdh gene and seven of the bg gene were found among the G. duodenalis assemblage E isolates. Using the nomenclature for the multilocus genotype (MLG) model, nine novel multilocus genotypes E (MLGs E1–E9) and three MLGs A (a novel subtype AI, previously detected subtype AII-1, and a combination of both) were identified. MLG AII-1 identified in this study may be an important zoonotic subtype. The dairy cattle in Henan are a potential public health concern. [ABSTRACT FROM AUTHOR]

Highlights: [•] The overall prevalence of Cryptosporidium in goats was 3.48% (44/1256). [•] C. ubiquitum, C. andersoni and C. xiaoi were identified. [•] The zoonotic XIIa subtype 2 of C. ubiquitum was found. [•] C. ubiquitum and C. andersoni were the first identified species in goats. [•] Age-associated distribution of Cryptosporidium was noticed in goats. [ABSTRACT FROM AUTHOR]