The influence of ground conductivity on the structure of RF radiation from return strokes

The combination of the finite conductivity of the Earth plus the propagation of the return stroke current up the channel which results in an apparent time delay between the fast field changes and RF radiation for distant observers is shown. The time delay predicted from model return strokes is on the order of 20 micro and the received signal has the characteristics of the data observed in Virginia and Florida. A piecewise linear model for the return stroke channel and a transmission line model for current propagation on each segment was used. Radiation from each segment is calculated over a flat Earth with finite conductivity using asymptotics approximations for the Sommerfeld integrals. The radiation at the observer is processed by a model AM radio receiver. The output voltage was calculated for several frequencies between HF-UHF assuming a system bandwidth (300 kHz) characteristic of the system used to collect data in Florida and Virginia. Comparison with the theoretical fast field changes indicates a time delay of 20 microns

Understanding the Social Networks That Form within the Context of an Obesity Prevention Intervention

Background. Antiobesity interventions have generally failed. Research now suggests that interventions must be informed by an understanding of the social environment. Objective. To examine if new social networks form between families participating in a group-level pediatric obesity prevention trial. Methods. Latino parent-preschool child dyads (N = 79) completed the 3-month trial. The intervention met weekly in consistent groups to practice healthy lifestyles. The control met monthly in inconsistent groups to learn about school readiness. UCINET and SIENA were used to examine network dynamics. Results. Children's mean age was 4.2 years (SD = 0.9), and 44% were overweight/obese (BMI ≥ 85th percentile). Parents were predominantly mothers (97%), with a mean age of 31.4 years (SD = 5.4), and 81% were overweight/obese (BMI ≥ 25). Over the study, a new social network evolved among participating families. Parents selectively formed friendship ties based on child BMI z-score, (t = 2.08; P < .05). This reveals the tendency for mothers to form new friendships with mothers whose children have similar body types. Discussion. Participating in a group-level intervention resulted in new social network formation. New ties were greatest with mothers who had children of similar body types. This finding might contribute to the known inability of parents to recognize child overweight

Culturally Tailored, Family-Centered, Behavioral Obesity Intervention for Latino-American Preschool-aged Children

http://dx.doi.org/10.1542/peds.2011-376

Proteomic and transcriptomic changes in hibernating grizzly bears reveal metabolic and signaling pathways that protect against muscle atrophy

Muscle atrophy is a physiological response to disuse and malnutrition, but hibernating bears are largely resistant to this phenomenon. Unlike other mammals, they efficiently reabsorb amino acids from urine, periodically activate muscle contraction, and their adipocytes differentially responds to insulin. The contribution of myocytes to the reduced atrophy remains largely unknown. Here we show how metabolism and atrophy signaling are regulated in skeletal muscle of hibernating grizzly bear. Metabolic modeling of proteomic changes suggests an autonomous increase of non-essential amino acids (NEAA) in muscle and treatment of differentiated myoblasts with NEAA is sufficient to induce hypertrophy. Our comparison of gene expression in hibernation versus muscle atrophy identified several genes differentially regulated during hibernation, including Pdk4 and Serpinf1. Their trophic effects extend to myoblasts from non-hibernating species (including C. elegans), as documented by a knockdown approach. Together, these changes reflect evolutionary favored adaptations that, once translated to the clinics, could help improve atrophy treatment

'H, I, J, K, L, M, N, O, PEE! Get it? Pee!': Siblings' shared humour in childhood

Humour is a central feature of social interactions in childhood that has received little attention. In a sample of 86 7‐year‐old children (M age = 7.82 years, SD = 0.80), we investigated patterns and individual differences in spontaneous humour observed during free play with their older (M age = 9.55 years, SD = 0.88) or their younger sibling (M age = 5.87 years, SD = 0.96). We coded children's instances, categories, and responses to humour. We investigated the nature of children's humour on the dyadic and individual level. Humour was common, and siblings’ production of humour was highly interdependent between play partners. Dyadic humour differed according to structural features of the sibling relationship (age, gender composition), and 7‐year‐old focal children's humour varied according to gender. This study contributes to knowledge regarding the dyadic nature of children's humour and individual patterns of humour beyond the preschool years

A global Staphylococcus aureus proteome resource applied to the in vivo characterization of host-pathogen interactions.

Data-independent acquisition mass spectrometry promises higher performance in terms of quantification and reproducibility compared to data-dependent acquisition mass spectrometry methods. To enable high-accuracy quantification of Staphylococcus aureus proteins, we have developed a global ion library for data-independent acquisition approaches employing high-resolution time of flight or Orbitrap instruments for this human pathogen. We applied this ion library resource to investigate the time-resolved adaptation of S. aureus to the intracellular niche in human bronchial epithelial cells and in a murine pneumonia model. In epithelial cells, abundance changes for more than 400 S. aureus proteins were quantified, revealing, e.g., the precise temporal regulation of the SigB-dependent stress response and differential regulation of translation, fermentation, and amino acid biosynthesis. Using an in vivo murine pneumonia model, our data-independent acquisition quantification analysis revealed for the first time the in vivo proteome adaptation of S. aureus. From approximately 2.15 × 1

Wireless transmission of biosignals for hyperbaric chamber applications

[EN] This paper presents a wireless system to send biosignals outside a hyperbaric chamber avoiding wires going through the chamber walls. Hyperbaric chambers are becoming more and more common due to new indications of hyperbaric oxygen treatments. Metallic walls physically isolate patients inside the chamber, where getting a patient's vital signs turns into a painstaking task. The paper proposes using a ZigBee-based network to wirelessly transmit the patient's biosignals to the outside of the chamber. In particular, a wearable battery supported device has been designed, implemented and tested. Although the implementation has been conducted to transmit the electrocardiography signal, the device can be easily adapted to consider other biosignals.The authors would like to thanks the University of Balearic Islands (UIB), the Miguel Hernandez University (UMH), MEDIBAROX unit of the Perpetuo Socorro Hospital and the "Catedra de Medicina Hiperbarica" (UMH) for their support allowing the use of its facilities for this work. The authors would also like to thank Borja Mas Boned for his help designing the LabVIEW application. This research has been carried out with funding and promotion of "Catedra de Medicina Hiperbarica" of the Miguel Hernandez University. http://nbio.umh.es/es/2010/12/01/catedra-de-medicina-hiperbarica-medibarox/.Perez-Vidal, C.; Gracia Calandin, LI.; Carmona, C.; Alorda, B.; Salinas, A. (2017). Wireless transmission of biosignals for hyperbaric chamber applications. PLoS ONE. 12(3):1-19. https://doi.org/10.1371/journal.pone.0172768S119123Sureda, A., Batle, J. M., Martorell, M., Capó, X., Tejada, S., Tur, J. A., & Pons, A. (2016). Antioxidant Response of Chronic Wounds to Hyperbaric Oxygen Therapy. PLOS ONE, 11(9), e0163371. doi:10.1371/journal.pone.0163371Branco, B. H. M., Fukuda, D. H., Andreato, L. V., Santos, J. F. da S., Esteves, J. V. D. C., & Franchini, E. (2016). The Effects of Hyperbaric Oxygen Therapy on Post-Training Recovery in Jiu-Jitsu Athletes. PLOS ONE, 11(3), e0150517. doi:10.1371/journal.pone.0150517Xu, Y., Ji, R., Wei, R., Yin, B., He, F., & Luo, B. (2016). The Efficacy of Hyperbaric Oxygen Therapy on Middle Cerebral Artery Occlusion in Animal Studies: A Meta-Analysis. PLOS ONE, 11(2), e0148324. doi:10.1371/journal.pone.0148324Lin, B.-S., Lin, B.-S., Chou, N.-K., Chong, F.-C., & Chen, S.-J. (2006). RTWPMS: A Real-Time Wireless Physiological Monitoring System. IEEE Transactions on Information Technology in Biomedicine, 10(4), 647-656. doi:10.1109/titb.2006.874194Hu, S., Wei, H., Chen, Y., & Tan, J. (2012). A Real-Time Cardiac Arrhythmia Classification System with Wearable Sensor Networks. Sensors, 12(9), 12844-12869. doi:10.3390/s120912844Burns, A., Greene, B. R., McGrath, M. J., O’Shea, T. J., Kuris, B., Ayer, S. M., … Cionca, V. (2010). SHIMMER™ – A Wireless Sensor Platform for Noninvasive Biomedical Research. IEEE Sensors Journal, 10(9), 1527-1534. doi:10.1109/jsen.2010.2045498Gil, Y., Wu, W., & Lee, J. (2012). A Synchronous Multi-Body Sensor Platform in a Wireless Body Sensor Network: Design and Implementation. Sensors, 12(8), 10381-10394. doi:10.3390/s120810381Chin-Teng Lin, Kuan-Cheng Chang, Chun-Ling Lin, Chia-Cheng Chiang, Shao-Wei Lu, Shih-Sheng Chang, … Li-Wei Ko. (2010). An Intelligent Telecardiology System Using a Wearable and Wireless ECG to Detect Atrial Fibrillation. IEEE Transactions on Information Technology in Biomedicine, 14(3), 726-733. doi:10.1109/titb.2010.2047401W. Y. Chung, Y. D. Lee, and S. J. Jung, &apos;A Wireless Sensor Network Compatible Wearable U-Healthcare Monitoring System Using Integrated Ecg, Accelerometer and Spo2&apos;, Conf Proc IEEE Eng Med Biol Soc, 2008 (2008), 1529–32.ZigBee Alliance; http://www.zigbee.org/Mahmood, A., Javaid, N., & Razzaq, S. (2015). A review of wireless communications for smart grid. Renewable and Sustainable Energy Reviews, 41, 248-260. doi:10.1016/j.rser.2014.08.036J.S. Lee, Y.W. Su, and C.C. Shen, &quot;A comparative study of wireless protocols: Bluetooth, UWB, ZigBee, and Wi-Fi, 33rd Annual Conference of the IEEE Industrial Electronics Society (IECON), 2007, pp. 46–51.P.P. Parikh, M.G. Kanabar, and T.S. Sidhu, &quot;Opportunities and challenges of wireless communication technologies for smart grid applications, IEEE PES General Meeting, 2010, pp. 1–7.Fadlullah, Z. M., Fouda, M. M., Kato, N., Takeuchi, A., Iwasaki, N., & Nozaki, Y. (2011). Toward intelligent machine-to-machine communications in smart grid. IEEE Communications Magazine, 49(4), 60-65. doi:10.1109/mcom.2011.5741147A.C. Olteanu, G.D. Oprina, N. Tapus, and S. Zeisberg, &quot;Enabling mobile devices for home automation using ZigBee, 19th IEEE International Conference on Control Systems and Computer Science, 2013, pp. 189–195.Shang, Y. (2014). Vulnerability of networks: Fractional percolation on random graphs. Physical Review E, 89(1). doi:10.1103/physreve.89.012813R. Barea-Navarro. Biomedical Instrumentation. Chapter 3. University of Alcala