This database is the Third Small Astronomy Satellite (SAS-3) Y-Axis Pointed Observation Log. It identifies possible pointed observations of celestial X-ray sources which were performed with the y-axis detectors of the SAS-3 X-Ray Observatory. This log was compiled (by R. Kelley, P. Goetz and L. Petro) from notes made at the time of the observations and it is expected that it is neither complete nor fully accurate. Possible errors in the log are (i) the misclassification of an observation as a pointed observation when it was either a spinning or dither observation and (ii) inaccuracy of the dates and times of the start and end of an observation. In addition, as described in the HEASARC_Updates section, the HEASARC added some additional information when creating this database. Further information about the SAS-3 detectors and their fields of view can be found at: http://heasarc.gsfc.nasa.gov/docs/sas3/sas3_about.html Disclaimer: The HEASARC is aware of certain inconsistencies between the Start_date, End_date, and Duration fields for a number of rows in this database table. They appear to be errors present in the original table. Except for one entry where the HEASARC corrected an error where there was a near-certainty which parameter was incorrect (as noted in the 'HEASARC_Updates' section of this documentation), these inconsistencies have been left as they were in the original table. This database table was released by the HEASARC in June 2000, based on the SAS-3 Y-Axis pointed Observation Log (available from the NSSDC as dataset ID 75-037A-02B), together with some additional information provided by the HEASARC itself. This is a service provided by NASA HEASARC .

This database is a collection of maps created from the 28 SAS-2 observation files. The original observation files can be accessed within BROWSE by changing to the SAS2RAW database. For each of the SAS-2 observation files, the analysis package FADMAP was run and the resulting maps, plus GIF images created from these maps, were collected into this database. Each map is a 60 x 60 pixel FITS format image with 1 degree pixels. The user may reconstruct any of these maps within the captive account by running FADMAP from the command line after extracting a file from within the SAS2RAW database. The parameters used for selecting data for these product map files are embedded keywords in the FITS maps themselves. These parameters are set in FADMAP, and for the maps in this database are set as 'wide open' as possible. That is, except for selecting on each of 3 energy ranges, all other FADMAP parameters were set using broad criteria. To find more information about how to run FADMAP on the raw event's file, the user can access help files within the SAS2RAW database or can use the 'fhelp' facility from the command line to gain information about FADMAP. This is a service provided by NASA HEASARC .

Multispectral radiometry resolutely quantifies canopy attributes of similarly managed monocultures over wide and varied temporal arrays. Likewise, liquid phthalocyanine-containing products are commonly applied to turfgrass as a spray pattern indicator, dormancy colorant, and/or product synergist. While perturbed multispectral radiometric characterization of putting greens within 24 h of treatment by synthetic phthalocyanine colorant has been reported, explicit guidance on subsequent use is absent from the literature. Our objective was to assess creeping bentgrass (Agrostis stolonifera L. ‘Penn G2’) putting green reflectance and growth one to 14 d following semi-monthly treatment by synthetic Cu II phthalocyanine colorant (Col) and petroleum-derived spray oil (PDSO) combination product at a 27 L ha–1 rate and/or 7.32 hg ha–1 soluble N treatment by one of two commercial liquid fertilizers. As observed in a bentgrass fairway companion study, mean daily shoot growth and canopy dark green color index (DGCI) increased with Col+PDSO complimented N treatment. Yet contrary to the fairway study results, deflated mean normalized differential red edge (NDRE) or vegetative index (NDVI) resulted from an associated Col+PDSO artifact that severely impeded near infrared (810-nm) putting green canopy reflectance. Regardless of time from Col+PDSO combination product treatment, the authors strongly discourage turfgrass scientists from employing vegetative indices that rely on 760- or 810-nm canopy reflectance when evaluating such putting green systems. Methods The requested information is described ad nauseum in the Materials & Methods section of the ‘Related Works.’

On 2. Nov., the author mistakenly uploaded a raw data file. Within, the first worksheet/tab titled MSR contained all 475 lines of MSR and vegetative index data. However, consideration for abidance of ANOVA assumptions precluded a small number of dependent variable observations, as employ of garden variety transformations were unsuccessful. Specifically, for percent reflectance of 510-, 560-, 610-, 660-, 760-, and 810-nm spectra; 2, 2, 2, 3, 3, and 4 observations were omitted as missing data, respectively. Likewise, since the dark green color index (DGCI) is calculated by 460, 560, and 660-nm reflectance, five (5) DGCI observations were conceded as missing data. Results described in the ‘Related Works’ report 510-, 560-, 610-, 660-, 760-, and 810-nm reflectance means and inference from 473-, 473-, 473-, 472-, 472-, and 471-observation datasets, respectively. No data were replaced and degree of freedom penalties were incurred in analysis reported in ‘Related Works.’ Likewise, the daily clipping yield data, dCY (2nd worksheet/tab) in the original 2 Nov. file upload, contained 150 observations. The statistical model and analysis of dCY data described in the ‘Related Works’ results report means and inference from a 148-observation dataset. The SAS output for each the reduced (n=148) and full (n=150) datasets are now included in data files. Model diagnostics on the reduced datasets, uploaded 11 Dec., 2022 meet all required assumptions. For the dCY data, the model diagnostics issue and resolution are squarely depicted in the two attached SAS outputs. The same is true for the MSR data, but SAS outputs are not attached. Motivated parties are invited to reanalyze the above-noted dependent variables using the 2 Nov. (full) and 11 Dec. (reduced) data freely available to you in ‘Data Files.’ It is strict Dryad policy that voluntarily uploaded data files not be deleted. Thus, the authors were compelled to append the two regrettably-conflicting datasets with the above explanation, today, 11 Dec. 2022. We hope you have found this explanation helpful and encourage you to forward your questions or comments to Max Schlossberg at mjs38@psu.edu.

Number of observations and percentage classified (in bracket) in different locations for female and male sample population using discriminant analysis.

Rainfall: Cumulative: Punjab: Sas Nagar: Normal data was reported at 22.100 mm in 24 Mar 2025. This records an increase from the previous number of 21.500 mm for 23 Mar 2025. Rainfall: Cumulative: Punjab: Sas Nagar: Normal data is updated daily, averaging 31.150 mm from Jun 2018 (Median) to 24 Mar 2025, with 2434 observations. The data reached an all-time high of 644.500 mm in 30 Sep 2018 and a record low of 0.000 mm in 01 Oct 2024. Rainfall: Cumulative: Punjab: Sas Nagar: Normal data remains active status in CEIC and is reported by India Meteorological Department. The data is categorized under India Premium Database’s Environment – Table IN.EVB012: Rainfall: by District: Cumulative.