Millimetric Wave Seeker for Third Generation Antitank Guided Missiles

For the third generation antitank guided missiles (ATGMs) with fire-and-forget and top attack capabilities, a noncoherent millimetric wave (MMW) active radar seeker has been configured with all weather capabilities. To meet the stringent dimensional and weight constraints and beamwidth requirements of ATGM, a W-band system has been designed with trans-twist antenna with a compact comparator. The paper covers the system description and critical design issues, and presents the performance results achieved so far. Areas for improvements, especially for achieving a higher range, have also been pointed out

A Novel Hybrid AI Federated ML/DL Models for Classification of Soil Components

The soil is the most fundamental component for the survival of any living thing that can be found on this planet. A little less than 41 percent of Indians are employed in agriculture, which accounts for approximately 19 percent of the country's gross domestic product. As is the case in every other industry, researchers and scientists in this one are exerting a lot of effort to enhance agricultural practices by utilising cutting-edge methods such as machine learning, artificial intelligence, big data, and so on. The findings of the study described in this paper are predicated on the assumption that the method of machine learning results in an improvement in the accuracy of the prediction of soil chemical characteristics. The correlations that were discovered as a result of this research are essential for comprehending the comprehensive approach to predicting the soil attributes using ML/DL models. A number of findings from previous study have been reported and analysed. A state of the art machine learning algorithm, including Logistic Regression, KNN, Support Vector Machine and Random Forest are implemented and compared. Additionally, the innovative Deep Learning Hybrid CNN-RF and VGG-RNN Model for Categorization of Soil Properties is also implemented along with CNN. An investigation into the significance of the selected category for nutritional categorization revealed that a multi-component technique provided the most accurate predictions. Both the CNN-RF and VGG-RNN models that were proposed were successful in classifying the soil with average accuracies of 95.8% and 97.9%, respectively, in the test procedures. A study was carried out in which the CNN-RF model, the VGG-RNN model, and five other machine learning and deep learning models were compared. The suggested VGG-RNN model achieved superior accuracy of classification and real-time durability, respectively

The Platelet-activating Factor Receptor Protects Epidermal Cells from Tumor Necrosis Factor (TNF) α and TNF-related Apoptosis-inducing Ligand-induced Apoptosis through an NF-κB-dependent Process

A number of chemical mediators can induce human keratinocytes and epidermal-derived carcinomas to undergo apoptosis, or programmed cell death. Recent evidence suggests pro-inflammatory cytokines, such as interleukin-1β or transforming growth factor α, protects carcinomas from numerous pro-apoptotic stimuli. Platelet-activating factor (1-alkyl-2-acetyl-3-glycerophosphocholine; PAF) is a lipid mediator with pro-inflammatory effects on numerous cell types. Although PAF can be metabolized to other bioactive lipids, the majority of PAF effects occur through activation of a G protein-coupled receptor. Using a model system created by retroviral transduction of the PAF receptor (PAF-R) into the PAF-R-negative human epidermal cell line KB and the PAF-R-expressing keratinocyte cell line HaCaT, we now demonstrate that activation of the epidermal PAF-R results in protection from apoptosis induced by tumor necrosis factor (TNF) α or TNF-related apoptosis-inducing ligand. The PAF-mediated protection was inhibited by PAF-R antagonists, and protection did not occur in PAF-R-negative KB cells. Additionally, we show protection from TNFα- or TRAIL-induced apoptosis by PAF-R activation is dependent on the transcription factor nuclear factor (NF)-κB, because PAF-R activation-induced NF-κB and epidermal cells transduced with a super-repressor form of inhibitor κB were not protected by the PAF-R. These studies provide a mechanism whereby the epidermal PAF-R, and possibly other G protein-coupled receptors, can exert anti-apoptotic effects through an NF-κB-dependent process

Free radical scavenging and α-glucosidase inhibitory activity of (E)-methyl/ethyl-3-(2-hydroxyphenyl)acrylates

111-116(E)-Methyl/ethyl-3-(2-hydroxyphenyl)acrylates 3a-x have been prepared by the reaction of salicylaldehydes 1a-l with Wittig reagents such as methyl (triphenylphosphoranylidene)acetate 2a and ethyl (triphenylphosphoranylidene)acetate 2b in dry DCM at room temperature. All the synthesized compounds have been evaluated for free-radical scavenging and α-glucosidase inhibitory activities. Compounds 3c and 3d display DPPH free radical scavenging activity. All the compounds have shown ABTS free radical scavenging activity except four compounds 3s-t and 3w-x. Compounds 3g, 3p and 3r display α-glucosidase inhibitory activity

Dependence receptor UNC5A restricts luminal to basal breast cancer plasticity and metastasis

BACKGROUND: The majority of estrogen receptor-positive (ERα+) breast cancers respond to endocrine therapies. However, resistance to endocrine therapies is common in 30% of cases, which may be due to altered ERα signaling and/or enhanced plasticity of cancer cells leading to breast cancer subtype conversion. The mechanisms leading to enhanced plasticity of ERα-positive cancer cells are unknown. METHODS: We used short hairpin (sh)RNA and/or the CRISPR/Cas9 system to knockdown the expression of the dependence receptor UNC5A in ERα+ MCF7 and T-47D cell lines. RNA-seq, quantitative reverse transcription polymerase chain reaction, chromatin immunoprecipitation, and Western blotting were used to measure the effect of UNC5A knockdown on basal and estradiol (E2)-regulated gene expression. Mammosphere assay, flow cytometry, and immunofluorescence were used to determine the role of UNC5A in restricting plasticity. Xenograft models were used to measure the effect of UNC5A knockdown on tumor growth and metastasis. Tissue microarray and immunohistochemistry were utilized to determine the prognostic value of UNC5A in breast cancer. Log-rank test, one-way, and two-way analysis of variance (ANOVA) were used for statistical analyses. RESULTS: Knockdown of the E2-inducible UNC5A resulted in altered basal gene expression affecting plasma membrane integrity and ERα signaling, as evident from ligand-independent activity of ERα, altered turnover of phosphorylated ERα, unique E2-dependent expression of genes effecting histone demethylase activity, enhanced upregulation of E2-inducible genes such as BCL2, and E2-independent tumorigenesis accompanied by multiorgan metastases. UNC5A depletion led to the appearance of a luminal/basal hybrid phenotype supported by elevated expression of basal/stem cell-enriched ∆Np63, CD44, CD49f, epidermal growth factor receptor (EGFR), and the lymphatic vessel permeability factor NTN4, but lower expression of luminal/alveolar differentiation-associated ELF5 while maintaining functional ERα. In addition, UNC5A-depleted cells acquired bipotent luminal progenitor characteristics based on KRT14+/KRT19+ and CD49f+/EpCAM+ phenotype. Consistent with in vitro results, UNC5A expression negatively correlated with EGFR expression in breast tumors, and lower expression of UNC5A, particularly in ERα+/PR+/HER2- tumors, was associated with poor outcome. CONCLUSION: These studies reveal an unexpected role of the axon guidance receptor UNC5A in fine-tuning ERα and EGFR signaling and the luminal progenitor status of hormone-sensitive breast cancers. Furthermore, UNC5A knockdown cells provide an ideal model system to investigate metastasis of ERα+ breast cancers

STUDIES ON LAND USE/LAND COVER AND CHANGE DETECTION OF G.MADUGULA TRIBAL MANDAL OF VISAKHAPATNAM DISTRICT, ANDHRA PRADESH, INDIA -USING REMOTE SENSING AND GIS TECHNIQUES

ABSTRACT Land use/ land cover is an important component in understanding the interactions of the human activities with the environment and thus it is necessary to monitor and detect the changes to maintai

Pharmacological Dual Inhibition of Tumor and Tumor-Induced Functional Limitations in a Transgenic Model of Breast Cancer

Breast cancer progression is associated with systemic effects, including functional limitations and sarcopenia without the appearance of overt cachexia. Autocrine/paracrine actions of cytokines/chemokines produced by cancer cells mediate cancer progression and functional limitations. The cytokine-inducible transcription factor NF-κB could be central to this process, as it displays oncogenic functions and is integral to the Pax7:MyoD:Pgc-1β:miR-486 myogenesis axis. We tested this possibility using the MMTV-PyMT transgenic mammary tumor model and the NF-κB inhibitor dimethylaminoparthenolide (DMAPT). We observed deteriorating physical and functional conditions in PyMT+ mice with disease progression. Compared with wild-type mice, tumor-bearing PyMT+ mice showed decreased fat mass, impaired rotarod performance, and reduced grip strength as well as increased extracellular matrix (ECM) deposition in muscle. Contrary to acute cachexia models described in the literature, mammary tumor progression was associated with reduction in skeletal muscle stem/satellite-specific transcription factor Pax7. Additionally, we observed tumor-induced reduction in Pgc-1β in muscle, which controls mitochondrial biogenesis. DMAPT treatment starting at 6 to 8 weeks age prior to mammary tumor occurrence delayed mammary tumor onset and tumor growth rates without affecting metastasis. DMAPT overcame cancer-induced functional limitations and improved survival, which was accompanied with restoration of Pax7, Pgc-1β, and mitochondria levels and reduced ECM levels in skeletal muscles. In addition, DMAPT restored circulating levels of 6 out of 13 cancer-associated cytokines/chemokines changes to levels seen in healthy animals. These results reveal a pharmacological approach for overcoming cancer-induced functional limitations, and the above-noted cancer/drug-induced changes in muscle gene expression could be utilized as biomarkers of functional limitations

Evaluation of banana germplasm and genetic analysis of an F 1 population for resistance to Fusarium oxysporum f. sp. cubense race 1

Open Access Article; Published online: 23 Sept 2019Fusarium wilt of bananas (Musa spp.), caused by Fusarium oxysporum f. sp. cubense (Foc) causes up to 100% yield loss in bananas. Foc race 1 in particular is very devastating to dessert bananas in Uganda. One of the effective control strategies for the disease is the development of resistant cultivars through breeding. The objectives of this study were to identify suitable banana germplasm for generating a segregating population for resistance to Foc race 1 and understand the mode of inheritance of resistance to Foc race 1. Twenty-two banana accessions sourced from the National Agricultural Research Organisation in Uganda were challenged with Foc race 1 in a screen house experiment. Monyet, resistant to Foc race 1 and Kokopo, susceptible, were selected and crossed to generate 142 F1 genotypes. These F1 genotypes were also challenged with Foc race 1 in a screen house experiment. Data were collected on rhizome discoloration index (RDI), leaf symptom index (LSI) and pseudo-stem splitting (PSS), and analysed for variability. The banana accessions evaluated showed varying degrees of resistance to Foc race 1. Segregation ratios for resistant versus susceptible progenies fitted 13:3 (χ2 = 0.12, P = 0.73) for RDI and 11:5 (χ2 = 3.04, P = 0.08) for PSS. Estimated broad sense heritability was 27.8% for RDI, 13.9% for LSI and 14.7% for PSS. The results suggest that resistance to Foc race 1 in banana is controlled by at least two dominant genes with epistatic interaction and that heritability of resistance to Foc race 1 is low in Musa spp

Facile synthesis and proposed mechanism of α,ω‐oxetanyl-telechelic poly(3-nitratomethyl-3-methyl oxetane) by an SN2(i) nitrato displacement method in basic media

The synthesis of a novel heterocyclic–telechelic polymer, α,ω-oxetanyl-telechelic poly(3-nitratomethyl-3-methyl oxetane), is described. Infrared spectroscopy (IR), gel permeation chromatography (GPC), and nuclear magnetic resonance (NMR) spectroscopy have been used to confirm the successful synthesis, demonstrating the presence of the telechelic-oxetanyl moieties. Synthesis of the terminal functionalities has been achieved via displacement of nitrato groups, in a manner similar to that employed with other leaving groups such as azido, bromo, and nitro, initiated by nucleophiles. In the present case, displacement occurs on the ends of a nitrato-functionalized polymer driven by the formation of sodium nitrate, which is supported by the polar aprotic solvent N,N-dimethyl formamide. The formation of an alkoxide at the polymer chain ends is favored and allows internal back-biting to the nearest carbon bearing the nitrato group, intrinsically in an SN2(i) reaction, leading to α,ω-oxetanyl functionalization. The telechelic-oxetanyl moieties have the potential to be cross-linked by chemical (e.g., acidic) or radiative (e.g., ultraviolet) curing methods without the use of high temperatures, usually below 100°C. This type of material was designed for future use as a contraband simulant, whereby it would form the predominant constituent of elastomeric composites comprising rubbery polymer with small quantities of solids, typically crystals of contraband substances, such as explosives or narcotics. This method also provides an alternative approach to ring closure and synthesis of heterocycles

Evaluation of methods and marker systems in genomic selection of oil palm (Elaeis guineensis Jacq.)

Background Genomic selection (GS) uses genome-wide markers as an attempt to accelerate genetic gain in breeding programs of both animals and plants. This approach is particularly useful for perennial crops such as oil palm, which have long breeding cycles, and for which the optimal method for GS is still under debate. In this study, we evaluated the effect of different marker systems and modeling methods for implementing GS in an introgressed dura family derived from a Deli dura x Nigerian dura (Deli x Nigerian) with 112 individuals. This family is an important breeding source for developing new mother palms for superior oil yield and bunch characters. The traits of interest selected for this study were fruit-to-bunch (F/B), shell-to-fruit (S/F), kernel-to-fruit (K/F), mesocarp-to-fruit (M/F), oil per palm (O/P) and oil-to-dry mesocarp (O/DM). The marker systems evaluated were simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). RR-BLUP, Bayesian A, B, Cπ, LASSO, Ridge Regression and two machine learning methods (SVM and Random Forest) were used to evaluate GS accuracy of the traits. Results The kinship coefficient between individuals in this family ranged from 0.35 to 0.62. S/F and O/DM had the highest genomic heritability, whereas F/B and O/P had the lowest. The accuracies using 135 SSRs were low, with accuracies of the traits around 0.20. The average accuracy of machine learning methods was 0.24, as compared to 0.20 achieved by other methods. The trait with the highest mean accuracy was F/B (0.28), while the lowest were both M/F and O/P (0.18). By using whole genomic SNPs, the accuracies for all traits, especially for O/DM (0.43), S/F (0.39) and M/F (0.30) were improved. The average accuracy of machine learning methods was 0.32, compared to 0.31 achieved by other methods. Conclusion Due to high genomic resolution, the use of whole-genome SNPs improved the efficiency of GS dramatically for oil palm and is recommended for dura breeding programs. Machine learning slightly outperformed other methods, but required parameters optimization for GS implementation