Introduction & Aim: Long-term diabetes mellitus (DM) is known to have a deleterious impact on bone health, resulting in change in bone mineral density, bone turnover, and bone quality, all of which increase the risk of fractures. The aim of. this study was to link immunological and pro-inflammatory cytokine (I.L-6, I.L-1, and TNF-alpha) markers in patients.with type 1 diabetes to Their connection to bones formation (sPINP) and bone resorption parameters (sCTX).   Materials & Methods: This study included 80 patients suffering from T1DM in the age range of 20-45 years. The patients were assayed for their biochemical (Vitamin D and HbA1c), Immunological (IL-6, IL-1 and TNF-alpha) parameters, as well as bone formation and resor

Select 30 isolate from Bacillus to detect the ability to produce pullulanase enzyme in liquid and solid state fermentation, and use the isolate Bacillus licheniformis (Bs18) because the highest production of enzyme, the optimum condition for the production of enzyme by liquid state fermentation (LSF) in growen with: media contains starch + pullulan as a carbon source, peptone as a nitrogen source, inoculums size 2 ml, and incubated at 40 C° with pH 7 for 48 hrs. In addition pullulanase production by solid state fermentation (SSF) was investigated using isolated Bacillus licheniformis (Bs18). Optimization of process parameters were carried out ,the optimum solid substrate , Temperature , pH , incubation period , inoculation size , hydrat

This research aims to examine the relationship between hydrothermal alteration and mineralization (ore mineralogy) in the study area and geological structures in the deformation mechanism. The hydrothermal alteration was determined based on petrographic analysis, and ore mineralogy which was determined based on the ore microscopic analysis. The deformation mechanism is determined by paleo stress analysis using win-tensor, and the direction of principal stress on joints/veins and faults is calculated by the right-dihedron method. Hydrothermal alteration includes silicification, argillic, propylitic, and phyllic alterations; and ore mineralogy consists of stibnite, cinnabar, pyrite, chalcopyrite, sphalerite, covellite, hematite, and a

The efforts embedded in this paper have been devoted to designing, preparing, and testing warm mix asphalt (WMA) mixtures and comparing their behavior against traditional hot mix asphalt mixtures. For WMA preparation, the Sasobit wax additive has been added to a 40/50 asphalt binder with a concentration of 3%. An experimental evaluation has been performed by conducting the Marshall together with volumetric properties, indirect tensile strength, and wheel tracking tests to acquire the tensile strength ratio (TSR), retained stability index (RSI), and rut depth. It was found that the gained benefit of reduction in mixing and compaction temperatures was reversely associated with a noticeable decline in Marshall properties and moisture s

      The study investigates the anion and cation concentrations and their distribution in the Dammam  aquifer to assess the groundwater suitability for irrigation and livestock in Sayed Al-Shuhadaa, Karbala, central Iraq. It lies between longitudes 43º 29' 00'' – 43^º 40' 00'' E and latitudes (32^º 17' 00'' – 32^º22' 00'') N. The physicochemical properties, cations and anions were measured in 14 active wells distributed in the study area. The assessment was conducted based on the sodium adsorption rate (SAR), sodium percentage (Na%), electrical conductivity (EC), total dissolved solids (TDS), and Hydrogen number (pH). Groundwater in the study area is very good for livestock and characterised b

     As a result of the pandemic crisis and the shift to digitization, cyber-attacks are at an all-time high in the modern day despite good technological advancement. The use of wireless sensor networks (WSNs) is an indicator of technical advancement in most industries. For the safe transfer of data, security objectives such as confidentiality, integrity, and availability must be maintained. The security features of WSN are split into node level and network level. For the node level, a proactive strategy using deep learning /machine learning techniques is suggested. The primary benefit of this proactive approach is that it foresees the cyber-attack before it is launched, allowing for damage mitigation. A cryptography algorithm is put