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bsj-6652
Generative Adversarial Network for Imitation Learning from Single Demonstration
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Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing considered tasks despite the limitation in the number of expert demonstrations, which clearly indicate the potential of our model.

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Publication Date
Wed Oct 07 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Synthesis and Study the Biological Activity of New Heterocyclic Compounds Derived From Hydrazide Derivatives
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Publication Date
Fri Dec 02 2022
Journal Name
International Journal Of Corrosion And Scale Inhibition
Anticorrosion, antimicrobial and antioxidant study of ZnO nanoparticles synthesized from Punica granatum (Pomegranate) extract
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Metal and metal oxide NPs have shown to be perfectly synthesized by using plant extracts with high efficiency, low cost and low toxicity. Our goal was to synthesize ZnO NPs by using an extract of pomegranate seeds and investigate the anticorrosion, antimicrobial and antioxidant properties of the synthesized ZnO NPs. The results have shown that the use of pomegranate in the green synthesis of ZnO NPs gave a good yield, with a low cost and non-toxic approach. The electrophoretic deposition (EPD) was used to coat stainless steel (S.S) by synthesized ZnO NPs in an alcoholic solution at room temperature producing a good coating against corrosion. The corrosion properties were investigated in a saline solution and a temperature range of (293–32

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Publication Date
Sat Jan 25 2025
Journal Name
Indonesian Journal Of Chemistry
Synthesis of CuO Nanoparticles from Copper(II) Schiff Base Complex: Evaluation via Thermal Decomposition
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Copper oxide (CuO) nanoparticles were synthesized through the thermal decomposition of a copper(II) Schiff-base complex. The complex was formed by reacting cupric acetate with a Schiff base in a 2:1 metal-to-ligand ratio. The Schiff base itself was synthesized via the condensation of benzidine and 2-hydroxybenzaldehyde in the presence of glacial acetic acid. This newly synthesized symmetric Schiff base served as the ligand for the Cu(II) metal ion complex. The ligand and its complex were characterized using several spectroscopic methods, including FTIR, UV-vis, 1H-NMR, 13C-NMR, CHNS, and AAS, along with TGA, molar conductivity and magnetic susceptibility measurements. The CuO nanoparticles were produced by thermally decomposing the

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Publication Date
Sat Sep 25 2021
Journal Name
International Journal Of Drug Delivery Technology
Metal Complexes of Ligand Derived from Amine Compound: Formation, Spectral Characterization, and Biological Evaluation
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A new set of metal complexes by the general formula [M(C)2(H2O)2]Cl2 has been prepared through the interaction of the new Ligand [N1, N4-bis(4-chlorophenyl)succinamide] (C) derived from succinyl chloride with 4-Chloroaniline with the transition metal ions Mn(II), Co(II), Ni(II), Hg(II), Cu(II) and Cd(II). Compounds diagnosed by TGA, 1 H, 13CNMR and Mass spectra (for (C)), Fourier-transform infrared and Electronic spectrum, Magnetic measurement, molar conduct, (%M, %C, %H, %N). These measurements indicate that (C) is associated with the metal ion in a bi-dentate fashion by nitrogen atoms (the amide group) and the octahedral composition of these complexes is suggested. The anti-bacterial action of the compounds towards three types of bacteria

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Publication Date
Tue Aug 15 2023
Journal Name
Sumer 1
Biologically synthesized Copper Nanoparticles from S. epidermidis on resistant S. aureus and cytotoxic assay
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The risk of significant concern is resistance to antibiotics for public health. The alternative treatment of metallic nanoparticles (NPs), such as heavy metals, effects on antibiotic resistance bacteria with different types of antibiotics of - impossible to treat using noval eco-friendly synthesis technique nanoparticles copper oxide (CuO NPs) preparation from S. epidermidis showed remarkable antimicrobial activity against S.aureus Minimum inhibitory concentra range (16,32,64,256,512) µg/ml via well diffusion method in vitro, discover those concentrations effected in those bacteria and the best concentration is 64 µg/ml, characterization CuO NPs to prove this included atomic force microscope, UV, X-ray Diffraction and TEM, and ant

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Publication Date
Mon Jun 01 2020
Journal Name
Comparative Immunology, Microbiology And Infectious Diseases
Drug resistance and virulence traits of Acinetobacter baumannii from Turkey and chicken raw meat
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Publication Date
Sat Jan 25 2025
Journal Name
Indonesian Journal Of Chemistry
Synthesis of CuO Nanoparticles from Copper(II) Schiff Base Complex: Evaluation via Thermal Decomposition
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Copper oxide (CuO) nanoparticles were synthesized through the thermal decomposition of a copper(II) Schiff-base complex. The complex was formed by reacting cupric acetate with a Schiff base in a 2:1 metal-to-ligand ratio. The Schiff base itself was synthesized via the condensation of benzidine and 2-hydroxybenzaldehyde in the presence of glacial acetic acid. This newly synthesized symmetric Schiff base served as the ligand for the Cu(II) metal ion complex. The ligand and its complex were characterized using several spectroscopic methods, including FTIR, UV-vis, 1H-NMR, 13C-NMR, CHNS, and AAS, along with TGA, molar conductivity and magnetic susceptibility measurements. The CuO nanoparticles were produced by thermally decomposing the

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Publication Date
Wed Jun 01 2022
Journal Name
Journal Of Water Process Engineering
Antibiotics adsorption from contaminated water by composites of ZSM-5 zeolite nanocrystals coated carbon
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The presence of antibiotic residues such as ciprofloxacin (CIPR) in an aqueous environment is dangerous when their concentrations exceed the allowable. Therefore, eliminating these residues from the wastewater becomes an essential issue to prevent their harm. In this work, the potential of efficient adsorption of ciprofloxacin antibiotics was studied using eco-friendly ZSM-5 nanocrystals‑carbon composite (NZC). An inexpensive effective natural binder made of the sucrose-citric acid mixture was used for preparing NZC. The characterization methods revealed the successful preparation of NZC with a favorable surface area of 103.739 m2/g, and unique morphology and functional groups. Investigating the ability of NZC for adsorbing CIPR antibioti

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Publication Date
Mon Jan 12 2026
Journal Name
Babcock University Medical Journal
Evaluation and effectiveness of sulfur nanoparticles against colon cancer prepared from capsicum plant extract
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Objective: Using green chemistry, an effective, inexpensive, and environmentally safe method, sulfur nanoparticles with specific properties can be prepared and used in nanotechnology. This research aimed to prepare sulfur nanoparticles from chilli pepper extract and determine their effectiveness against colon cancer. Method: Chilli pepper extract obtained from local markets was treated with aqueous sodium thiosulfate (Na2S2O7.5H2O). After mixing, it was continuously stirred, heated, and filtered. NaBH4 was then added, resulting in a yellow precipitate. The precipitate was centrifuged, purified, and dried at 250°C. Results: Standardised tests such as UV-Vis, XRD, SEM, TEM, AFM, and EDX were used, resulting in sulfur nanoparticles with an av

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Publication Date
Sun Dec 28 2025
Journal Name
مجلة جامعة صنعاء للعلوم التطبيقية والتكنولوجيا
From Algorithms to Applications: A Review of AI-Based Face Recognition and Identity Verification
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Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni

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