Gelatin a promising biomaterial which is useful and interesting natural polymer which offer possibilities of chemical modification through grafted copolymerization with an saturated acid anhydride such as methyl nadic anhydride formatted gelatin –g- methyl nadic anhydride copolymer (A1), then modified to its corresponding polymer (A2) by substituted salbutamol as useful derivative as biomaterial .the prepared drug biopolymer was characterization by FTIR spectroscopy and thermal analysis was studied controlled drug release was measured in different buffer solution at 37C0 .

We study clusters in warm dark matter (WDM) models of a thermally produced dark matter particle 0.5 keV in mass. We show that, despite clusters in WDM cosmologies having similar density profiles as their cold dark matter (CDM) counterparts, the internal properties, such as the amount of substructure, show marked differences. This result is surprising as clusters are at mass scales that are a thousand times greater than that at which structure formation is suppressed. WDM clusters gain significantly more mass via smooth accretion and contain fewer substructures than their CDM brethren. The higher smooth mass accretion results in subhaloes which are physically more extended and less dense. These fine-scale differences can be probed by strong

<span>Digital audio is required to transmit large sizes of audio information through the most common communication systems; in turn this leads to more challenges in both storage and archieving. In this paper, an efficient audio compressive scheme is proposed, it depends on combined transform coding scheme; it is consist of i) bi-orthogonal (tab 9/7) wavelet transform to decompose the audio signal into low &amp; multi high sub-bands, ii) then the produced sub-bands passed through DCT to de-correlate the signal, iii) the product of the combined transform stage is passed through progressive hierarchical quantization, then traditional run-length encoding (RLE), iv) and finally LZW coding to generate the output mate bitstream.

The availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conv

The study aims to review the literature on the fundamental changes in Managerial Accounting (MA) in light of accelerating Digital Transformations (DT) and increasing Sustainability Requirements (SR) from 2020 to August 2025, with the purpose of informing researchers and professionals about recent developments. The study relied on a qualitative analysis of the content of a group of studies indexed in the Scopus database. The study included a literature review of topics such as artificial intelligence tools and techniques, cloud computing, linear programming, sustainability reporting, and strategic managerial accounting practices. The study results revealed that accelerated DT improves the efficiency of managerial accounting practices