Fiber optic microphone having a pressure sensing reflective membrane and a voltage source for calibration purpose

A fiber optic microphone is provided for measuring fluctuating pressures. An optical fiber probe having at least one transmitting fiber for transmitting light to a pressure-sensing membrane and at least one receiving fiber for receiving light reflected from a stretched membrane is provided. The pressure-sensing membrane may be stretched for high frequency response. Further, a reflecting surface of the pressure-sensing membrane may have dimensions which substantially correspond to dimensions of a cross section of the optical fiber probe. Further, the fiber optic microphone can be made of materials for use in high temperature environments, for example greater than 1000 F. A fiber optic probe is also provided with a back plate for damping membrane motion. The back plate further provides a means for on-line calibration of the microphone

High temperature fiber optic microphone having a pressure-sensing reflective membrane under tensile stress

A fiber optic microphone is provided for measuring fluctuating pressures. An optical fiber probe having at least one transmitting fiber for transmitting light to a pressure-sensing membrane and at least one receiving fiber for receiving light reflected from a stretched membrane is provided. The pressure-sensing membrane may be stretched for high frequency response. Further, a reflecting surface of the pressure-sensing membrane may have dimensions which substantially correspond to dimensions of a cross section of the optical fiber probe. Further, the fiber optic microphone can be made of materials for use in high temperature environments, for example greater than 1000 F. A fiber optic probe is also provided with a backplate for damping membrane motion. The backplate further provides a means for on-line calibration of the microphone

Exploratory approach for network behavior clustering in LoRaWAN

The interest in the Internet of Things (IoT) is increasing both as for research and market perspectives. Worldwide, we are witnessing the deployment of several IoT networks for different applications, spanning from home automation to smart cities. The majority of these IoT deployments were quickly set up with the aim of providing connectivity without deeply engineering the infrastructure to optimize the network efficiency and scalability. The interest is now moving towards the analysis of the behavior of such systems in order to characterize and improve their functionality. In these IoT systems, many data related to device and human interactions are stored in databases, as well as IoT information related to the network level (wireless or wired) is gathered by the network operators. In this paper, we provide a systematic approach to process network data gathered from a wide area IoT wireless platform based on LoRaWAN (Long Range Wide Area Network). Our study can be used for profiling IoT devices, in order to group them according to their characteristics, as well as detecting network anomalies. Specifically, we use the k-means algorithm to group LoRaWAN packets according to their radio and network behavior. We tested our approach on a real LoRaWAN network where the entire captured traffic is stored in a proprietary database. Quite important is the fact that LoRaWAN captures, via the wireless interface, packets of multiple operators. Indeed our analysis was performed on 997, 183 packets with 2169 devices involved and only a subset of them were known by the considered operator, meaning that an operator cannot control the whole behavior of the system but on the contrary has to observe it. We were able to analyze clusters’ contents, revealing results both in line with the current network behavior and alerts on malfunctioning devices, remarking the reliability of the proposed approach

Grazing Management and Nitrogen Fertilizer Effects in Grazing Systems for Beef Cows

Four 8-ha areas, primarily Cynodon dactylon forage, were overseeded in autumn with annual ryegrass (Lolium multiflorum) and clover (Trifolium incarnatum and Trifolium repens). Two areas received no nitrogen (N) fertilizer and two received 168 kg N/ha annually. Within N level (2 x 2 factorial), one area was divided into 4 paddocks (pad) and the other into 16 pad for rotational grazing. Spring-calving beef cows were stocked (2.5/ha) year-round on each area with calves weaned in October. Annual dry matter forage accumulation was greater where N was applied (18.2 vs 14.2 Mg/ha, P=.02) but was unaffected by pad number. Forage availability and annual days of grazing were affected positively both by N and pad number (P\u3c.05). N x pad number interaction affected forage quality (P\u3c.07), cowcalf performance and net returns (P\u3c.01). Generally, responses were similar between 4 and 16 pad at 0 N, but at 168 N, responses were greater for 4 compared with 16 pad. Overall, there was little benefit of increasing pad number from 4 to 16 irrespective of N level, although increased carrying capacity was indicated particularly where N was applied

Artificial Intelligence Language Model Performance for Rapid Intraoperative Queries in Plastic Surgery: ChatGPT and the Deep Inferior Epigastric Perforator Flap

Background: The integration of artificial intelligence in healthcare has led to the development of large language models that can address various medical queries, including intraoperatively. This study investigates the potential of ChatGPT in addressing intraoperative questions during the deep inferior epigastric perforator flap procedure. Methods: A series of six intraoperative questions specific to the DIEP flap procedure, derived from real-world clinical scenarios, were proposed to ChatGPT. A panel of four experienced board-certified plastic surgeons evaluated ChatGPT’s performance in providing accurate, relevant, and comprehensible responses. Results: The Likert scale demonstrated to be medically accurate, systematic in presentation, and logical when providing alternative solutions. The mean readability score of the Flesch Reading Ease Score was 28.7 (±0.8), the Flesch–Kincaid Grade Level was 12.4 (±0.5), and the Coleman–Liau Index was 14.5 (±0.5). Suitability-wise, the DISCERN score of ChatGPT was 48 (±2.5) indicating suitable and comprehensible language for experts. Conclusions: Generative AI tools such as ChatGPT can serve as a supplementary tool for surgeons to offer valuable insights and foster intraoperative problem-solving abilities. However, it lacks consideration of individual patient factors and surgical nuances. Nevertheless, further refinement of its training data and rigorous scrutiny under experts to ensure the accuracy and up-to-date nature of the information holds the potential for it to be utilized in the surgical field

Relations among structural parameters in barred galaxies with a direct measurement of bar pattern speed

We investigate the relations between the properties of bars and their host galaxies in a sample of 77 nearby barred galaxies, spanning a wide range of morphological types and luminosities, with 34 SB0-SBa and 43 SBab-SBc galaxies. The sample includes all the galaxies with reliable direct measurement of their bar pattern speed based on long-slit or integral-field stellar spectroscopy using the Tremaine-Weinberg method. We limited our analysis to the galaxies with a relatively small relative error on the bar pattern speed (smaller than 50 per cent) and not hosting an ultrafast bar. For each galaxy, we collected the radius, strength, pattern speed, corotation radius, and rotation rate for the bar and we also collected the Hubble type and absolute SDSS r-band magnitude. We also used literature bulge-to-total luminosity ratio for a subsample of 53 galaxies with an available photometric decomposition. We confirmed earlier observational findings that longer bars rotate with lower bar pattern speeds, shorter bars are weaker, and bars with a small bar rotation rate rotate with higher bar pattern speeds and have smaller corotation radii. In addition, we found that stronger bars rotate with lower bar pattern speeds, as predicted from the interchange of angular momentum during bar evolution, which in turn may depend on different galaxy properties. Moreover, we report that brighter galaxies host longer bars, which rotate with lower bar pattern speeds and have larger corotation radii. This result is in agreement with a scenario of downsizing in bar formation, if more massive galaxies formed earlier and had sufficient time to slow down, grow in length, and push corotation outwards.Comment: revised and accepted for pubblication in Astronomy & Astrophysic

Numerical tests of the large charge expansion

We perform Monte-Carlo measurements of two and three point functions of charged operators in the critical O(2) model in 3 dimensions. Our results are compatible with the predictions of the large charge superfluid effective field theory. To obtain reliable measurements for large values of the charge, we improved the Worm algorithm and devised a measurement scheme which mitigates the uncertainties due to lattice and finite size effects.Comment: 16 pages, 12 figures. v2: Improved finite size scaling. v3: Added comparison between Monte Carlo update