Separation Distress Call in the Human Neonate in the Absence of Maternal Body Contact

1996 ◽  
Vol 51 (2) ◽  
pp. 86-87
Author(s):  
K. Christensson ◽  
T. Cabrera ◽  
E. Christensson ◽  
K. Uvnas-Moberg ◽  
J. Winberg
1995 ◽  
Vol 84 (5) ◽  
pp. 468-473 ◽  
Author(s):  
K Christensson ◽  
T Cabrera ◽  
E Christensson ◽  
K Uvnäs–Moberg ◽  
J Winberg

Author(s):  
Jaak Panksepp ◽  
Larry Normansell ◽  
Barbara Herman ◽  
Paul Bishop ◽  
Loring Crepeau

2018 ◽  
Vol 592 ◽  
pp. 267-281 ◽  
Author(s):  
F Christiansen ◽  
F Vivier ◽  
C Charlton ◽  
R Ward ◽  
A Amerson ◽  
...  

Author(s):  
Alexandra Cremona ◽  
Amanda Cotter ◽  
Khadijah Ismail ◽  
Kevin Hayes ◽  
Alan Donnelly ◽  
...  

2020 ◽  
Vol 15 ◽  
Author(s):  
Fahad Layth Malallah ◽  
Baraa T. Shareef ◽  
Mustafah Ghanem Saeed ◽  
Khaled N. Yasen

Aims: Normally, the temperature increase of individuals leads to the possibility of getting a type of disease, which might be risky to other people such as coronavirus. Traditional techniques for tracking core-temperature require body contact either by oral, rectum, axillary, or tympanic, which are unfortunately considered intrusive in nature as well as causes of contagion. Therefore, sensing human core-temperature non-intrusively and remotely is the objective of this research. Background: Nowadays, increasing level of medical sectors is a necessary targets for the research operations, especially with the development of the integrated circuit, sensors and cameras that made the normal life easier. Methods: The solution is by proposing an embedded system consisting of the Arduino microcontroller, which is trained with a model of Mean Absolute Error (MAE) analysis for predicting Contactless Core-Temperature (CCT), which is the real body temperature. Results: The Arduino is connected to an Infrared-Thermal sensor named MLX90614 as input signal, and connected to the LCD to display the CCT. To evaluate the proposed system, experiments are conducted by participating 31-subject sensing contactless temperature from the three face sub-regions: forehead, nose, and cheek. Conclusion: Experimental results approved that CCT can be measured remotely depending on the human face, in which the forehead region is better to be dependent, rather than nose and cheek regions for CCT measurement due to the smallest


2019 ◽  
Vol 220 (1) ◽  
pp. S257
Author(s):  
Shelly Soni ◽  
Matthew J. Blitz ◽  
Lakha Prasannan ◽  
Meir Greenberg ◽  
Michael Qiu ◽  
...  

2010 ◽  
Vol 202 (3) ◽  
pp. 263.e1-263.e5 ◽  
Author(s):  
Jason N. Hashima ◽  
Yinglei Lai ◽  
Ronald J. Wapner ◽  
Yoram Sorokin ◽  
Donald J. Dudley ◽  
...  

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 55-56
Author(s):  
Christian D Ramirez-Camba ◽  
Crystal L Levesque

Abstract A mechanistic model was developed with the objective to characterize weight gain and essential amino acid (EAA) deposition in the different tissue pools that make up the pregnant sow: placenta, allantoic fluid, amniotic fluid, fetus, uterus, mammary gland, and maternal body were considered. The data used in this modelling approach were obtained from published scientific articles reporting weights, crude protein (CP), and EAA composition in the previously mentioned tissues; studies reporting not less than 5 datapoints across gestation were considered. A total of 12 scientific articles published between 1977 and 2020 were selected for the development of the model and the model was validated using 11 separate scientific papers. The model consists of three connected sub-models: protein deposition (Pd) model, weight gain model, and EAA deposition model. Weight gain, Pd, and EAA deposition curves were developed with nonparametric statistics using splines regression. The validation of the model showed a strong agreement between observed and predicted growth (r2 = 0.92, root mean square error = 3%). The proposed model also offered descriptive insights into the weight gain and Pd during gestation. The model suggests that the definition of time-dependent Pd is more accurately described as an increase in fluid deposition during mid-gestation coinciding with a reduction in Pd. In addition, due to differences in CP composition between pregnancy-related tissues and maternal body, Pd by itself may not be the best measurement criteria for the estimation of EAA requirement in pregnant sows. The proposed model also captures the negative maternal Pd that occurs in late gestation and indicates that litter size influences maternal tissue mobilization more than parity. The model predicts that the EAA requirements in early and mid-gestation are 75, 55 and 50% lower for primiparous sows than parity 2, 3 and 4+ sows, respectively, which suggest the potential benefits of parity segregated feeding.


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