Brooding fathers actively consume viable embryos to take up nutrients in a monogamous syngnathid fish

Syngnathid fishes often experience a reduction in brood size and an increase in immunity during pregnancy. Researchers have studied the polygamous broad-nosed pipefish (Syngnathus typhle) and revealed that some eggs from low-quality females in the male’s brood pouch serve as nurse eggs that are absorbed by the father. It is unclear whether nurse eggs also exist in other syngnathid fishes, especially in monogamous syngnathid fishes. In monogamous syngnathid fishes, the male pouch only carries eggs from a single female. Thus, the question remains: do some eggs of monogamous syngnathid fishes also serve as nurse eggs? And if so, are these nurse eggs impaired eggs, or are they viable eggs that are consumed by the brooding father? In the present study, we used the monogamous lined seahorse (Hippocampus erectus) and asked whether nurse eggs exist in this species. We also explored whether nurse eggs potentially originate from viable versus inviable eggs. Using isotope labeling, we found that nutrients from embryos could be transferred to brooding fathers. Furthermore, we also found that brooding fathers with limited food had a higher isotope content and a smaller brood size compared to individuals with sufficient food. These results have demonstrated that nurse eggs exist in the lined seahorse, and also suggested that the brooding fathers actively consume viable embryos to absorb nutrients in response to low food availability. These findings help us better understand parent–embryo conflict, filial cannibalism, and male-only care in teleost fishes

Data Envelopment Analysis for Relative Efficiency Measurement of Chinese Hospitals: A Systematic Review

The purpose was to explore the gap between China and the international world in efficiency measurement of hospitals with Data Envelopment Analysis, and to improve the standardization of healthcare efficiency measurement in China. A systematic review was conducted using appropriate search strategies. Studies were included containing DEA approaches regarding general hospital efficiency, published in international literature and in both Chinese and English about Chinese hospitals from January 2004 to October 2014. The results showed that statistical significances were found in indicators such as number of DMUs, percentage of allocative efficiency studies, ratio of studies with multiple years, number of studies with monetary indicators in input and output sets, etc. The statistical insignificance in some indicators such as the number of input and output indicators were also found among China, Europe, USA and others. Some problems were found in current DEA-based hospital efficiency studies in China, such as inappropriate selection of input-output indicators, no bias-correction on efficiency scores, etc. The standardization of DEA methods applied in China’s hospital efficiency research needs to be improved. Chinese researchers should pay more attention to latest international research findings, so as to keep pace with the cutting edge hospital efficiency research

Numerical and experimental evaluation of nasopharyngeal aerosol administration methods in children with adenoid hypertrophy

Article no 12390

Perceção de mulheres grávidas relativamente à informação disponível acerca do consumo de álcool durante a gravidez

info:eu-repo/semantics/draf

Measuring and Benchmarking Technical Efficiency of Public Hospitals in Tianjin, China

China has long been stuck in applying traditional data envelopment analysis (DEA) models to measure technical efficiency of public hospitals without bias correction of efficiency scores. In this article, we have introduced the Bootstrap-DEA approach from the international literature to analyze the technical efficiency of public hospitals in Tianjin (China) and tried to improve the application of this method for benchmarking and inter-organizational learning. It is found that the bias corrected efficiency scores of Bootstrap-DEA differ significantly from those of the traditional Banker, Charnes, and Cooper (BCC) model, which means that Chinese researchers need to update their DEA models for more scientific calculation of hospital efficiency scores. Our research has helped shorten the gap between China and the international world in relative efficiency measurement and improvement of hospitals. It is suggested that Bootstrap-DEA be widely applied into afterward research to measure relative efficiency and productivity of Chinese hospitals so as to better serve for efficiency improvement and related decision making

Culturing low quality juveniles of the lined seahorse, Hippocampus erectus

Juvenile quality has become a crucial factor for determining the commercial culture success of the lined seahorse, Hippocampus erectus. There is an urgent need for developing techniques to improve the survival of the low-quality juveniles. The present study investigated the effects of green water and light intensity (200–500 lx and 700–1000 lx) on the survival and growth of low-quality juveniles of the lined seahorse over 35 days. Juveniles of H. erectus reared in green water had superior survival rate compared to the juveniles reared in clear water. Generally, the growth of juveniles in green water was also better than in the clear water. At light intensities of 200–500 lx, the survival rate of low-quality juveniles was significantly improved as well. Generally, the growth of juveniles under low light intensity was better than under high light intensity. Based on the findings of the present study, culturing low-quality juveniles of the lined seahorse in green water or under lower light intensities (200–500 lx) is recommended

The Regional Total Factor Productivity Changes of Healthcare Delivery in China: A Bootstrap Malmquist Data Envelopment Analysis

Improving the productivity of healthcare delivery and optimizing the allocation of regional healthcare resources are crucial for the health providers. The objective of this study is to evaluate the productivity dynamics of healthcare delivery at the regional (provincial) level in China, to provide evidence-based policy implications. After a review of literature, actual number of open beds, number of occupational or assistant doctors, number of registered nurses, and number of other staff were selected as input variables. The number of diagnostic visits and number of discharged inpatients were adopted as the output indicators. The panel data of 31 provinces in mainland China from 2010 to 2019 were extracted from Health Statistics Yearbook. Bootstrap-Malmquist Data Envelopment Analysis (DEA) model was used to measure the total factor productivity changes (TFPC) and its components. During the study period, the analysis of total factor productivity (TFP) in China revealed a declining trend with an average annual decline of 0.9% (ranging from 0.860 to 1.204). For each of the 31 provinces, the annual TFP scores varied from 0.971 to 1.029. On average, technical efficiency changes (TEC) had showed a downward trend from 2010-2011 (0.980) to 2013-2014 (0.982), and then an upward trend in 2014-2015 (1.029) and the following three consecutive years since 2016-2017 (1.000, 1.013, 1.009). Similarly, the trend in technological changes (TC) was consistent with the TEC from 2010-2019, which fluctuated between 0.969 and 1.011 on average per year at the provincial level. Notably, the point of inflection appeared at 2013-2014. Regional healthcare inputs and outputs in mainland China saw an upward trend from 2010 to 2019. However, TFPC, TEC, and TC decreased across all 31 provinces. TFP experienced a declining trend from 2010 to 2014, followed by growth until 2019. This may be related to the new healthcare reform being implemented since 2009, as service efficiency and capacity may undergo a reversal at the beginning of the reform

Discriminative Learning for Alzheimer’s Disease Diagnosis via Canonical Correlation Analysis and Multimodal Fusion

To address the challenging task of diagnosing neurodegenerative brain disease, such as Alzheimer’s disease (AD) and mild cognitive impairment (MCI), we propose a novel method using discriminative feature learning and canonical correlation analysis (CCA) in this paper. Specifically, multimodal features and their CCA projections are concatenated together to represent each subject, and hence both individual and shared information of AD disease are captured. A discriminative learning with multilayer feature hierarchy is designed to further improve performance. Also, hybrid representation is proposed to maximally explore data from multiple modalities. A novel normalization method is devised to tackle the intra- and inter-subject variations from the multimodal data. Based on our extensive experiments, our method achieves an accuracy of 96.93% (AD vs. normal control (NC)), 86.57 % (MCI vs. NC), and 82.75% (MCI converter (MCI-C) vs. MCI non-converter (MCI-NC)), respectively, which outperforms the state-of-the-art methods in the literature