Refrigeration unit: Lowers the temperature through a mechanical process. In a typical refrigeration unit, electricity powers a motor that runs a pump to compress the refrigerant to maintain proper pressure. (A "refrigerant" is a substance that changes between liquid and gaseous states under desirable temperature and pressure conditions.) Heat from the compressed liquid is removed and discharged from the unit and the refrigerant then evaporates when pressure is reduced. The refrigerant picks up heat as it evaporates and it returns to the compressor to repeat the cycle. A few refrigeration units use gas (either natural gas or LPG) in an absorption process that does not use a compressor. The gas is burned to heat a chemical solution in which the refrigerant has been absorbed. Heating drives off there frigerant which is later condensed. The condensed refrigerant evaporates by a release of pressure, and it picks up heat as it evaporates. The evaporated refrigerant is then absorbed back into the chemical solution, the heat is removed from the solution and discharged as waste heat, and the process repeats itself. By definition, refrigerators, freezers, and air-conditioning equipment all contain refrigeration units.
Rural Electrification Administration (REA): A lending agency of the U. S. Department of Agriculture, the REA makes self-liquidating loans to qualified borrowers to finance electric and telephone service to rural areas. The REA finances the construction and operation of generating plants, electric transmission and distribution lines, or systems for the furnishing of initial and continued adequate electric services to persons in rural areas not receiving central station service.
a certain ratio change the station rar
The specific cause of abnormal autoimmune responses in patients with myasthenia gravis is unknown. However, researchers suggest that the thymus has some role in this process. According to reports in the medical literature, up to approximately 75 percent of individuals with myasthenia gravis have distinctive abnormalities of the thymus. In most cases, there are increased numbers of cells in the thymus (hyperplasia). In addition, in about 10 percent of affected individuals, the thymus contains a tumor (thymoma) that is typically noncancerous (benign). However, some thymomas may be malignant. Researchers suggest that the thymus of MG patients does not appropriately eliminate cells that produce antibodies that attack body tissues. In the case of MG antibodies are produced that react against acetylcholine receptors, triggering the abnormal autoimmune response within the thymus. (A lymphoid tissue organ located behind the breastbone, the thymus plays an important role in the immune system beginning during early fetal development until puberty. It is important in the maturation of certain specialized white blood cells [T lymphocytes] that have several functions, including assisting in the recognition of certain foreign proteins [antigens] or binding to cells invaded by microorganisms and destroying them.) The abnormalities that lead to production of anti-MuSK antibodies is poorly understood and appears not to involve the thymus.
Medications, such as particular antibiotics or antiarrhythmic agents, may also aggravate symptoms in individuals with myasthenia gravis and therefore should be avoided or used with caution. . Exacerbation of weakness may occur with various antibiotics, including aminoglycosides, macrolides, and some fluoroquinolones. Patients needing antibiotics should discuss this with their physicians. A complete list of medications to use with caution may be found at myasthenia.org Individuals with myasthenia gravis may have increased sensitivity to the use of certain medications, such as particular anesthetics or muscle relaxants (e.g., succinylcholine, pancuronium). Therefore, this risk must be taken into consideration by surgeons, anesthesiologists, or other health care workers when making decisions concerning potential surgery and use of anesthetics.
Powered by NORD, the IAMRARE Registry Platform is driving transformative change in the study of rare disease. With input from doctors, researchers, and the US Food & Drug Administration, NORD has created IAMRARE to facilitate patient-powered natural history studies to shape rare disease research and treatments. The ultimate goal of IAMRARE is to unite patients and research communities in the improvement of care and drug development.
Mantle plumes, first suggested by Wilson (1963) and Morgan (1971), represent relatively hot, low-density mantle material that ascends because of its buoyancy. They were introduced to explain the intraplate oceanic island chains ageing progressively along the chain in the direction of plate motions. The surface manifestation of the plumes forms large hotspots relatively fixed to each other which represent focused zones of melting characterized by high heat flow. Their thermal origin together with geochemical imprints such as high 3He/4He ratios observed in hotspot basalts (Kellogg and Wasserburg, 1990) indicate that the plumes are rooted deep in the mantle and transport primordial mantle material upwards (e.g., Condie, 2001). This is one of the fundaments that discriminate convective flows of plate tectonic movements primarily driven by sinking of cold plates in favour of deep-seated plumes driven by heat exchange (Morgan, 1971; Foulger and Natland, 2003; Foulger, 2010). Mantle plumes are supposed to consist of two parts, a large bulbous head at the top and relatively narrow tail connecting the plume with its source. They are distributed irregularly in the Earth, mostly inside tectonic plates; however, some of them occur near lithospheric plate margins reflecting the large diversity of interactions (Foulger, 2010).
The retrieved time residuals reflect not only velocity anomalies in the target area, but also errors that might be of random and/or systematic origin. The random errors comprise uncertainties in picking of the arrival times due to noise and dissimilarities in waveforms, and uncertainties in the earthquake locations. Because of strict selection criteria (cross-correlation coefficient higher than 0.8), the errors in picking by the waveform cross-correlation should be less than 0.2 s. In the case of manual picking, the errors would be of one order higher and thus they would mask the effects of the velocity perturbations. The estimates of the location errors reported in the Global CMT catalog (Ekström et al., 2012) are less than 30 km with the majority between 0 and 20 km (Fig. 7) and less than 0.3 s for the earthquake origin times. Since these errors differ for individual earthquakes, they affect the time residuals and velocity perturbations randomly and produce their scatter. Such scatter is visible in Fig. 6 for both the MSVF and RAR stations (e.g., P-wave residuals for foci deeper than 500 km at station MSVF in Fig. 6a). Nevertheless, the random noise in the residuals is not so high to deteriorate significantly the overall pattern, which shows clear systematic trends. This confirms that the random location and picking errors do not seriously affect the time residuals and the velocity perturbations determined by our analysis. This applies to both stations MSVF and RAR (Fig. 6).
In addition, the Vp/Vs ratio as the main outcome of this study is even less sensitive to systematic location errors. This is confirmed by numerical tests (provided in Sect. 4. Results). These tests reveal that the uncertainties in the Vp/Vs ratio produced by the potential systematic location errors are even more suppressed compared to the uncertainties in the time residuals and velocity perturbations of the P- and S-waves.
The histograms of the residuals between the observed and theoretical Vp/Vs ratios shown in Fig. 11. The Vp/Vs residuals at station RAR (lower plot) are amplified by a factor of 2.5 to eliminate a potential smoothing effect produced by calculating the Vp/Vs ratios for about twice longer rays than those at station MSVF (upper plot)
To illustrate essential differences in the Vp and Vs velocities and the Vp/Vs ratio between the northern and southern Tonga segments, we calculated the representative P- and S-wave velocities in the subduction region west of the Tonga slab. The traveltime residua were inverted for 1-D depth-dependent velocities with the inversion performed in iterations. In the first iteration, the rays were computed by the TauP code (Buland and Chapman, 1983; Crotwell et al., 1999) in the reference ak135 model. The observed residua were inverted for smooth velocity perturbations in three different sectors bounded by the velocity change in the ak135 model at 210, 410 and 660 km depths. The reference model was updated after each iteration; the iterative process converged fast after 4 iterations with no further improvement.
The velocity models in the Tonga subduction region calculated from the time residuals at station MSVF. a, b The whole Tonga back-arc region; (c,d) the northern Tonga segment delimited by the latitude 20S. a, c The P- and S-wave relative velocity differences from the ak135 reference as a function of depth. Blue line: P-waves; red line: S-waves; dashed black line: P- and S-waves in the ak135 model. b, d The Vp/Vs ratio as a function of depth compared to the reference ak135 model. Magenta line: the retrieved model; dashed black line: the ak135 model. Note a higher Vp/Vs ratio down to 600 km depth in the northern segment (magenta line in (d)). The grey area indicates the depths of eliminated events
This study demonstrates the retrieval of travel time variations by time-lapse analysis of a three-component broadband seismometer and a triplet hydrophone station given an underwater source. The repeated hydroacoustic activity of the submarine Monowai Volcanic Centre, observed at the hydrophone station H03S and the seismic station RAR, is used to estimate the relative travel time variation. Variations in travel time are a proxy for spatially averaged changes in the deep-ocean temperature. A proposed pre-processing workflow overcomes the differences in instrument sensitivity and sample rates. The vertical and radial seismic components are cross-correlated with all individual hydrophones. Cross-correlation functions (CCFs) eligible for time-lapse analysis are selected based on source activity and source directionality. Automatic coincidence-trigger analysis of the CCF's signal-to-noise ratio marks the active periods. The source directionality corresponds to the horizontal slowness of a plane wave traversing the hydrophone triplet, applied to the CCFs with the vertical seismic component. The time-lapse analysis is applied to the eligible CCFs by two-dimensional cross-correlation of the power spectral density in two consecutive octave bands, for 3-6 Hz and 6-12 Hz. The resulting peak two-dimensional cross-correlation coefficient and the corresponding time lag and frequency variations yield the travel time variation of use for the deep-ocean thermometry. The medium induced travel time change is assumed to be equivalent to the trimmed weighted mean variation in time lag and assuming no variation of the source signature. The estimated travel time variation per octave band reveals both a complex periodic variation as well as a distinct linear trend. The linear decrease is assumed to be associated with net temperature increase and is larger around the SOFAR channel (higher-frequency octave) compared to the deep ocean (lower-frequency octave). The peak periodicity for the lower and higher frequency octaves is estimated at 1.9 y and 1.1 y, respectively. The methodology applies to other triplet hydrophone arrays or three-component seismometers given a known source. This work intends to be a cookbook study, fostering FAIR data principles. Source code and examples are publicly available on GitLab. 2ff7e9595c
Comments