From Newsgroup: rec.sport.rowing

<div>I was trying to download a csv file that is sent as byte-array from the server when I realized that my http response contain no headers at all. I was expecting a 'content-disposition' header in my response.</div><div></div><div></div><div></div><div></div><div></div><div>download pdf from response angular</div><div></div><div>Download: https://t.co/8xzcqiRcU9 </div><div></div><div></div><div>By default, angular will use observe: 'body', responseType: 'json' for http options, meaning that angular will only let you access the response's body, automatically turned into a json object, but not the headers.</div><div></div><div></div><div>I want to have access in the code to body field in the response. The 'body' field starts with an underscore, which means that it's a private field. When I change it to 'console.log(res._body)' I got an error.</div><div></div><div></div><div>I was making an app and I was trying to add a new user and then get a response object with that user as well as an access token and refresh token in HEADERS. I can see tokens in devTools/Network but when I console log response from the Agular app response object doesn't show headers data.</div><div></div><div></div><div>Anisotropic materials are characterized by a unique optical response, which is highly polarization-dependent. Of particular interest are layered materials formed by the stacking of two-dimensional (2D) crystals that are naturally anisotropic in the direction perpendicular to the 2D planes. Black phosphorus (BP) is a stack of 2D phosphorene crystals and a highly anisotropic semiconductor with a direct band gap. We show that the angular dependence of polarized Raman spectra of BP is rather unusual and can be explained only by considering complex values for the Raman tensor elements. This result can be traced back to the electron-photon and electron-phonon interactions in this material.</div><div></div><div></div><div>In getData() we create a new request using the Request() constructor, then use it to fetch an OGG music track. We also use AudioContext.createBufferSource to create an audio buffer source. When the fetch is successful, we read an ArrayBuffer out of the response using arrayBuffer(), decode the audio data using AudioContext.decodeAudioData(), set the decoded data as the audio buffer source's buffer (source.buffer), then connect the source up to the AudioContext.destination.</div><div></div><div></div><div></div><div></div><div></div><div></div><div>\n In getData() we create a new request using the\n Request() constructor, then use it to fetch an OGG\n music track. We also use AudioContext.createBufferSource to create an\n audio buffer source. When the fetch is successful, we read an ArrayBuffer\n out of the response using arrayBuffer(), decode the audio data using\n AudioContext.decodeAudioData(), set the decoded data as the audio buffer\n source's buffer (source.buffer), then connect the source up to the\n AudioContext.destination.\n</div><div></div><div></div><div>I'm trying to access Metabase API from my angular app but every time the preflight request from the browser ( Request Method: OPTIONS) giving status 404 and post request to "api/session" is failing.</div><div></div><div>But the same call when I'm trying from POSTMAN or tried with set up an API gateway with lambda proxy integration and a Lambda function which will do Http call to Metabase api is working.</div><div></div><div></div><div>HI flamber</div><div></div><div>yes, i follow the discussion completely..but i don't find this helpful to me as i'm trying to aceess the api from my angular app codebase like how we are access other public or private apis.</div><div></div><div>If you see the network tab preflight request to the API is giving status 404.</div><div></div><div>network-tab1886599 41.3 KB</div><div></div><div></div><div>In frontend development, it's likely that you will make API requests to retrieve data from some backend resource. However, some backends are set up in such a way that they either send too much data or not enough data back.</div><div></div><div></div><div>You can also see how we managed to map some of the fields in the response from snake_case to camelCase which is more of a convention in JavaScript as well as mapping some fields in the response to a new name (mass -> weight).We can also convert some types to other types, such as mass as string to weight as number.This can be super helpful to keep the domain language of your frontend codebase intact.</div><div></div><div></div><div>We can build this scenario out perfectly with the Star Wars API. Let's say we want to see what films the characters we are searching for appear in. The API response for the characters does contain what films they are in, but it does not give us details, just a URL that we can send a new request to get that film's data. This is also an Array of films so we may want to get the details for all the films they appear in at this time.</div><div></div><div></div><div>This is a small introduction to mapping data returned from HTTP requests with RxJS, but hopefully you can see use this as a reference point if you ever need to perform complex data mapping that involves additional API requests.</div><div></div><div></div><div>I just implemented Auth0 in an existing angular project that used token based authentication in the past. There was a custom-made interceptor.service.ts that was replaced with the default auth0 AuthHttpInterceptor.</div><div></div><div></div><div>While the average seafloor backscatter strength within a narrow range of grazing angles can be used as a first-order classification tool, this technique often fails to distinguish seafloors of known differing geological character. In order to resolve such ambiguities, it is necessary to examine the variation in backscatter strength as a function of grazing angle. For this purpose, a series of multiply overlapping GLORIA sidescan sonar images (6.5 kHz) have been obtained in water depths ranging from 1000 to 2500 m. To constrain the placement of acoustic backscatter measurements and to measure the true impinging angle of the incident wave, the corresponding seafloor was simultaneously surveyed using the Seabeam multibeam system. As a result of the multiple overlap, the angular response of seafloor backscatter strength may be derived for regions much smaller than the swath width. By using the derived angular response of seafloor backscatter strength in regions for which sediment samples exist, an empirical seafloor classification scheme is proposed based on the shape, variance, and magnitude of the angular response. Because of the observed variability in the shape of the angular response with differing seafloor types, routine normalization of single-pass swath data to an equivalent single grazing angle image cannot be achieved. As a result, for the case of single-pass surveys, confident seafloor classification may only be possible for regions approaching the scale of the swath width.</div><div></div><div></div><div>Felderhof and Cichocki [J. Chem. Phys. 107, 291 (1997), preceding paper] claim that tagged particle reorientation should play no role in theories of the angular velocity autocorrelation function (AVACF) as it is a nonlinear effect. In this reply we show that reorientation does indeed contribute to the AVACF to linear order and that the conclusions of our previous paper hold true.</div><div></div><div></div><div>Acoustic remote sensing systems such as multibeam and sidescan sonars can be used for mapping and detection of near-surface gas in marine sediments. These systems provide a realistic depiction of the seafloor by means of the simultaneous acquisition of co-registered high-resolution bathymetry and calibrated seafloor backscatter. The recognition of gas signatures in acoustic remote sensing data depends on the proper modeling of the acoustic backscatter response. In this thesis, a high frequency backscatter model that takes into account the amount of free gas in the sediments is proposed. Inversion of this model is used to estimate the distribution of near-surface gas in the sedimentary basin Additionally, analysis of backscatter images and detailed bathymetry reveals anomalous seafloor features, which are associated with gas expulsion.</div><div></div><div></div><div>Several studies have recently shown that the characteristics of prompt gamma (PG) rays emitted during proton radiation therapy are beneficial for verifying proton beam range during treatment delivery. Since PG rays are produced instantaneously upon the proton beam delivery, the viability of in vivo beam range verification using PG rays depends greatly on the design optimization of not only intrinsically highly efficient detectors, but also detector location around the beam to maximize detection efficiency. The purpose of this study is to characterize angular dependence of the PG detection rates as a function of proton beam energy to help develop the design of clinically feasible detectors.</div><div></div><div></div><div>We expect that the spectral and spatial characteristics of PG emission from a proton-irradiated target shown in this study will help design and optimize a PG detector system to maximize detection efficiency, with an appropriate choice for the number of detector nodes and their corresponding angular positions around the proton beam, taking into account geometric constraints in the treatment room.</div><div></div><div></div><div>In radiation therapy, the goal is to deliver sufficient dose to ensure local tumor control while simultaneously limiting the dose to healthy organs to avoid radiation damage. Even though x-rays have shown great success in treating cancer, the challenge in using high-energy x-rays is that the x-rays deposit an entrance and an exit dose to healthy organs as they pass through the body: the dose to healthy organs limits the dose to the tumor. Proton beam therapy potentially provides an improved dose distribution because of the steep distal falloff at the end of the proton beam range with sharp maximum dose deposition, known as the Bragg peak. However, for this advantage to be fully exploited, the location of the sharp distal gradient in the patient must be precisely controlled. Range uncertainties come from many sources including errors in patient setup or positioning, variations in patient anatomy including the size of the tumor, and limitations of the dose calculation algorithm. The process by which x-ray computed tomography (CT) numbers are converted to proton stopping powers in treatment-planning systems can lead to large range estimation uncertainties, up to 10% in extreme cases, owing to heterogeneities and the presence of anatomic structures with high atomic numbers, such as bone, along the beam path [1, 2]. Uncertainties in the dose delivery require that adequate safety margins be built into each patient treatment plan to ensure target coverage, at the cost of additional dose to healthy tissue, and furthermore the effect of range errors on dose to nearby critical organs must be considered carefully [3]. Therefore, to reduce necessary margins and to fully benefit from the advantages of proton beam therapy, a means of in vivo dose monitoring during tumor irradiation is needed to verify the dose distribution in and around the target volume.</div><div></div><div> 31c5a71286</div>
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