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The current work is aimed to study the thermoluminescence (TL) properties of natural milky quartz associated with Metamorphic Rocks extracted from the Eastern Desert of Egypt. Atomic absorption spectrometer was used to assess the chemical compositions of the samples, and X-ray diffraction was used to examine the structural properties (XRD). The deconvolution of the glow curve was carried out and revealed that there were ten trapping sites at 0.623, 0.936, 1.02, 1.06, 1.31, 1.47, 1.58, 1.76, 2.49, and 2.96 eV. The linearity of the sample was examined for each glow peak. The analysis of the glow curve was studied also by T m  −  T stop and various heating rates (VHR) giving the kinetics parameters (activation energy E , eV).The minimum detectable dose of the investigated samples was found to be 24 µGy. The dosimeter demonstrated a high level of repeatability. The fading signal was investigated for varying storage times up to 30 days . Graphical abstract

CaAl 2 O 4 :0.1% La nanoparticles doped with different concentrations of Mg were prepared using the sol–gel method and annealed at 400 °C, 500 °C, and 800 °C, respectively. The prepared nanophosphors show a highly crystalline orthorhombic structure with a crystallite size of about 81.2 nm. The optimum concentration of Mg dopants is about 0.7 mol%. The thermoluminescence (TL) glow curve of 11 Gy of beta-ray irradiated CaAl 2 O 4 :0.1% La:0.7% Mg measured at heating rates of 5 K/s has 16 overlapping glow peaks. The TL kinetic parameters for the prepared nanoparticles were evaluated using two different methods and they exhibited good agreement. Moreover, the linearity dose response of dosimetric peaks follows a good linearity up to 220 Gy in nanophosphor. The minimum detectable dose of the prepared nanophosphor was 125.7 mGy. The results of the prepared nanophosphors suggest good candidates for dosimetric applications. Graphical abstract

Pulmonary nodule detection in CXR is challenging. Recently, the use of artificial intelligence (AI) has been a major attraction. The current study aimed to evaluate the diagnostic performance of the AI in the detection of pulmonary nodules or masses on CXR compared to the radiologist's interpretation and to assess its impact on the reporting process. The current study included 150 patients who had CXR interpreted by radiologists and by AI software. CT detected pulmonary nodules in 99 cases (66%) while the visual model of analysis, as well as AI, detected nodules among 92 cases (61.3%) compared to 93 (62%) cases detected by combined visual/AI model. A total of 216 nodules were detected by CT (64.4% solid and 31.5% GG). Only 188 nodules were detected by the AI while 170 nodules were detected by visual analysis. As per case classification or nodule analysis, the AI showed the highest area under curve (AUC) (0.890, 95% CI) and (0.875, 95% CI), respectively, followed by the combined visual/AI model. Regarding the nodules' texture, the AI model's sensitivity for solid nodules was 91.4% which was greater than the combined visual/AI and visual models alone, while in GG nodules, the combined visual/AI model's sensitivity was higher than the AI and visual models. The probability score using the combined visual/AI model was significantly higher than using the visual model alone (P value = 0.001). The use of the AI model in CXR interpretation regarding nodules and masses detection helps in more accurate decision-making and increases the diagnostic performance affecting the patient's morbidity and mortality.

One of the dangerous pathogens that display high resistance to antibiotics is Salmonella enterica ( S. enterica ), which infects humans and animals. In this study, a new approach was proposed to fight antibiotic-resistant bacteria by using silver nanoparticles (AgNPs) with adding the phage ZCSE6. The biosynthesized AgNPs were characterized by analysis of spectroscopy profile of the UV–Vis, visualize the morphology, and size with transmission electron microscopy. Both minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were assessed. In addition, the AgNPs were able to control the biofilm formation of S. enterica , also, heavy metals detection by AgNPs and their application in milk. UV–Vis spectra showed a surface resonance peak of 400 and 430 nm corresponding to the formation of AgNPs capping with Ocimum basilicum L. and Hibiscus sabdariffa L., respectively. The MIC and MBC values were 6.25 µg/ml to inhibit the growth of S. enterica and 12.5 µg/ml from killing the bacteria and it was decreased to 1.5 µg/ml when combined with the phage. In the present study, AgNPs were combined with phage ZCSE6 to obtain a synergetic antimicrobial activity. Moreover, it increases the milk’s shelf-life and senses the Cd 2+ at a concentration of 1 mM in the water. Graphical Abstract