Livestock industries have an important role in ensuring global food security. This review discusses the importance of quantifying the heat stress response of ruminants, with an emphasis on identifying thermo-tolerant breeds. There are numerous heat stress prediction models that have attempted to quantify the response of ruminant livestock to hot climatic conditions. This review highlights the importance of investigating prediction models beyond the temperature-humidity index (THI). Furthermore, this review highlights the importance of incorporating other climatic variables when developing prediction indices to ensure the accurate prediction of heat stress in ruminants. Prediction models, particularly the heat load index (HLI) were developed to overcome the limitations of the THI by incorporating ambient temperature (AT), relative humidity (RH), solar radiation (SR) and wind speed (WS). Furthermore refinements to existing prediction models have been undertaken to account for the interactions between climatic variables and physiological traits of livestock. Specifically, studies have investigated the relationships between coat characteristics, respiration rate (RR), body temperature (BT), sweating rate, vasodilation, body weight (BW), body condition score (BCS), fatness and feed intake with climatic conditions. While advancements in prediction models have been occurring, there has also been substantial advancement in the methodologies used to quantify animal responses to heat stress. The most recent development in this field is the application of radio frequency identification (RFID) technology to record animal behaviour and various physiological responses. Rumen temperature measurements using rumen boluses and skin temperature recording using infrared thermography (IRT) are making inroads to redefine the quantification of the heat stress response of ruminants. Further, this review describes several advanced biotechnological tools that can be used to identify climate resilient breeds of ruminant livestock.
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http://dx.doi.org/10.1007/s00484-019-01735-9 | DOI Listing |
Genet Med
December 2024
Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN; Center for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN. Electronic address:
Purpose: The value of genetic information for improving the performance of clinical risk prediction models has yielded variable conclusions. Many methodological decisions have the potential to contribute to differential results. We performed multiple modeling experiments integrating clinical and demographic data from electronic health records (EHR) with genetic data to understand which decisions may affect performance.
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December 2024
School of Mechanical and Electrical Engineering, North University of China, Taiyuan, 030051, Shanxi, China.
Due to the sensitivity of the shaped charge jet to standoff and the complexity of its impact under lateral disturbances, this study aims to investigate the dynamic impact evolution of the jet influenced by standoff and lateral disturbances. A finite element model for the dynamic impact of shaped charge jets was established. Dynamic impact experiments were designed and conducted to validate the effectiveness of the numerical simulations.
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December 2024
School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China.
A novel adaptive model-based motion control method for multi-UAV communication relay is proposed, which aims at improving the networks connectivity and the communications performance among a fleet of ground unmanned vehicles. The method addresses the challenge of relay UAVs motion control through joint consideration with unknown multi-user mobility, environmental effects on channel characteristics, unavailable angle-of-arrival data of received signals, and coordination among multiple UAVs. The method consists of two parts: (1) Network connectivity is constructed and communication performance index is defined using the minimum spanning tree in graph theory, which considers both the communication link between ground node and UAV, and the communication link between ground nodes.
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December 2024
School of Civil Engineering, Southeast University, Nanjing, 211189, China.
Collapsible loess soils, known for their significant volume reduction upon the wetting, pose critical challenges in the geotechnical engineering. The estimation of the wetting-induced settlement is crucial for the foundation design and the determination of the negative skin friction on the pile. In this paper, a new method is proposed to estimate the wetting induced collapse from the wetting soil-water characteristic curve (SWCC) and the index properties of the loess soils.
View Article and Find Full Text PDFBehav Res Methods
December 2024
ETSI de Telecomunicación, Universidad Politécnica de Madrid, Avenida Complutense, 30, 28040, Madrid, Spain.
This study investigates the potential of large language models (LLMs) to estimate the familiarity of words and multi-word expressions (MWEs). We validated LLM estimates for isolated words using existing human familiarity ratings and found strong correlations. LLM familiarity estimates performed even better in predicting lexical decision and naming performance in megastudies than the best available word frequency measures.
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