Iranian Journal of Science and Technology, Transactions A: Science最新文献

This study presents a new deep learning approach for detecting brain cysts and cystic tumors using magnetic resonance imaging (MRI). The research utilizes six datasets containing MRI images of both pediatric and adult brains to improve classification accuracy and model reliability. The datasets include T1-weighted sagittal and T2-weighted images, with data augmentation techniques used to balance the classes. The proposed hybrid model combines convolutional neural networks, genetic algorithms (GA), and artificial neural networks (ANN) to enhance performance. The OzNet-GA-ANN model achieves remarkable accuracy: 100% for Dataset 1 (T1-weighted sagittal images), 99.06% for Dataset 2 (T2-weighted images), 98.08% for Dataset 3, 99.17% for Dataset 4, 98.66% for Dataset 5 (cystic tumor dataset), and 95.20% for Dataset 6 (augmented cystic tumor dataset). These results suggest that T1-weighted sagittal images provide better diagnostic accuracy than T2-weighted images for detecting pediatric brain cysts. Furthermore, the hybrid model performs consistently well across different datasets, demonstrating its reliability and potential for real-world applications. This study offers a promising approach for improving the classification of brain cysts and cystic tumors in medical imaging.

Mutations in SETBP1 cause Schinzel-Giedion syndrome (SGS), which is characterized by severe mental retardation, distinctive facial features, and multiple congenital malformations. SGS neural progenitors exhibit aberrant proliferation and migration, but the underlying mechanism remains unclear. Here, we established SH-SY5Y stable cell lines of SETBP1 overexpression and knockdown. Target genes expression of SETBP1 was tested by quantitative RT-PCR and western blot. Chromatin immunoprecipitation assay and luciferase reporter assay were used to identify the binding and effect of SETBP1 to EPHA7 promoter. Cell proliferation and migration of SH-SY5Y cells were observed by cell counting kit-8 assay, colony formation assay, transwell migration assay and wound healing assay. Neuron-like differentiation of SH-SY5Y cells was detected using immunofluorescence assay. In this study, the protein expression of EPHA7 was found upregulated in SH-SY5Y cell lines with SETBP1 overexpression; in contrast, the protein expression of EPHA7 was obviously down- regulated in SH-SY5Y cell lines with SETBP1 knockdown. Moreover, the transcription of EPHA7 was mediated by SETBP1 in SH-SY5Y cells, and the -2232 bp ~ -1958 bp and -1770 bp ~ -1544 bp, was identified as two key promoter of EPHA7. SETBP1 may act through EPHA7 to enhance the neuroblastoma cell proliferation. Our results showed that the transcriptional expression of EPHA7 was regulated by SETBP1, and the SETBP1 may act through EPHA7 to promote the development of neuroblastoma, which may be one of the pathogenic mechanisms underlying neurodevelopmental disorders.

In the present paper, we introduce a new subclass ({mathcal {H}}^{*}(lambda , K,L),) (0 le lambda le 1,) (-L le K < L le 1,) of harmonic univalent functions associated with Janowski function defined by subordination. We obtain necessary and sufficient conditions and properties such as distortion bounds, compactness, extreme points and integral mean inequalities for this new class of functions. Radii of convexity and starlikeness are also determined.

In this study, the exploratory area of Zafarghand, Isfahan, is considered a case study to identify alteration and mineral potential zones. To achieve this goal, a combination of geochemical approaches and remote sensing has been employed. Specifically, the singularity and U-statistic methods are utilized for anomaly separation from the background. Additionally, the Band Ratio (BR) technique is considered a highlighting method from the set of remote sensing techniques to satellite image processing. The BR specifies the target by employing a high-reflective band in the numerator, and a high-absorptive one in the denominator. Subsequently, the singularity and U-statistic are applied as a moving window on the BR values. Considering the spatial arrangement of the image pixels, this combination significantly enhances the effectiveness of the BR technique. After applying the combination of the aforementioned approaches, the results show an acceptable match. The targets identified as the output, are closely associated with the propylitic and phyllic alterations in the region (based on field observations). Finally, the study area alteration map has been prepared using the above-mentioned integrated approach.

Dental caries is a significant public health concern globally. This research presents a mathematical model for simulating the spread of dental caries using fractional differential equations. The model incorporates fractional-order dynamics to better understand and manage the transmission and development of the disease. Numerical solutions are computed using the Adams–Bashforth–Moulton method. The study includes an examination of the model’s solutions to ensure their existence and uniqueness, and to assess the local stability of equilibrium points. Stability analysis is conducted through the Ulam–Hyers process, offering valuable insights into how the system behaves with varying parameters. The results illustrate the model’s effectiveness in accurately representing the spread of dental caries, with graphical analyses highlighting the impact of different fractional orders on infection spread, thereby improving our understanding of the model’s performance.

This study’s objective is to introduce a flexible interventional autoregressive process modified based on the random autoregressive coefficient and asymmetric innovations. The transfer function of the proposed process is designed to follow the dynamic step change structure. In interventional analysis, outliers or influential observations have a considerable influence on statistical inference. Hence, we discuss the Bayesian local influence analysis to evaluate the impact of perturbations in response variables, priors, and simultaneous perturbations regarding the Bayes factor assessor. Considering the Markov Chain Monte Carlo samples, the proposed local influences and diagnostic measures can be easily obtained. The real data of the weekly new cases of COVID-19 within the period 2020-03-01 to 2023-12-17 in Greece verifies the effectiveness of the presented methodologies.

The study of the qualitative attributes of fractional non-autonomous stochastic differential systems is rarely available in the literature. This research work investigates the solvability and Ulam–Hyers stability of non-autonomous fractional differential equations involving standard Brownian motion and fractional Brownian motion (fBm). We describe a mild solution of the considered fractional non-autonomous system through the operators generated by a family of closed linear operators and the probability density function. The existence of a mild solution is established by utilizing the successive approximation approach. Furthermore, we investigate the Ulam–Hyers stability of the considered equation. Our findings are established under Lipschitz conditions on the system parameters, leveraging Borel-Cantelli’s Lemma, Gronwall’s, and Chebyshev’s inequalities. Finally, we present an example to validate our results.

Based on the Schwinger source theory, an alternative derivation of the scattering cross section of non-relativistic bremsstrahlung is provided. In this approach, the vacuum persistence amplitude of the source theory is replaced by the wave function (otimes) vacuum persistence amplitude. It is then shown that the imaginary part of this amplitude automatically yields the scattering cross-section and the intensity of radiation. The Bethe–Heitler cross section is recovered in the Born approximation.

STAT3, as a member of the STAT family, is involved in biological processes such as cell proliferation, apoptosis, differentiation, and immune regulation. In this study, a homologue of STAT3 was cloned from Lethenteron reissneri, that is, L. reissneri STAT3. The molecular evolution of L. reissneri STAT3 gene was systematically analyzed, including motif, exon, and collinear analyses. The motif analysis revealed that L. reissneri STAT3 gene was conserved with respect to some motif compositions, except motifs 14–18. A slight difference was observed in the STAT3 exon numbers among different species, which indicates that L. reissneri STAT3 gene was relatively conserved during the evolutionary process. However, the collinear analysis showed that the adjacent genes of STAT3 in different species varied, implying that the chromosome where the L. reissneri STAT3 gene is located might have undergone chromosomal rearrangement. L. reissneri STAT3 gene was expressed in various tissues, and it was highly expressed in kidney and gills. L. reissneri STAT3was expressed differentially after lamprey was stimulated with lipopolysaccharide, which suggests that L. reissneri STAT3 was involved in lamprey immune regulation. The cell activity of STAT3 transient expression group in MCF-7 cells was higher than that in the control group. Flow cytometry analysis showed that overexpression of L. reissneri STAT3 in MCF-7 cells inhibited the apoptosis of MCF-7 cells. However, the function of STAT3 in lamprey remains to be explored. The molecular evolution, expression, and function analysis of L. reissneri STAT3 could provide a theoretical basis for further exploration of STAT3-mediated adaptive immune regulation in lamprey.

Let (gin H(mathbb {D})), the Volterra type operator (J_g) is defined by (begin{aligned} (J_g f)(z) = int _0^z f(xi ) g'(xi ) d xi , fin H(mathbb {D}), zin mathbb {D}. end{aligned})In this paper, some properties of Volterra type operator (J_g) from Cauchy transform space into weighted Zygmund space will be investigated.