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ijp-154
Bulk heterojunction blend (NiPcTs:PEDOT:PSS) in gas sensing
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Thin films of bulk heterojunction blend Ni-Phthalocyanine
Tetrasulfonic acid tetrasodium salt and dpoly
(3, 4-ethylenedioxythiophene) poly (styrenesulfonate) (NiPcTs:
PEDOT: PSS) with different (PEDOT:PSS) concentrations (0.5, 1, 2)
are prepared using spin coating technique with thickness 100 nm on
glass and Si substrate. The X-Ray diffraction pattern of NiPcTs
powder was studied and compared with NiPc powder, the pattern
showed that the structure is a polycrystalline with monoclinic phase.
XRD analysis of as-deposited (NiPcTs/PEDOT:PSS) thin films
blends in dicated that the film appeared at(100), (102) in
concentrations (0.5, 1) and (100) in concentration (2). The grain size
is increased with increasing (PEDOT:PSS) concentrations. FTIR
measurements for these bulk heterojunction blend thin films also
carried out in this work and gave good information about the bonds
and their locations. Sensor measurements of Si/NiPcTS:PEDOT:PSS
bulk heterojunctions blend thin films show a good sensitivity for NO2
gas Compared to NH3gas. The NiPcTS/PEDOT:PSS gas sensor
device work at room temperature than high temperature for NO2 gas
but good sensitivity at100ºC for NH3 gas and sensor work more
effectively in 0.5 concentration for both gases.

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Publication Date
Mon Jan 01 2024
Journal Name
Explainable Artificial Intelligence In The Digital Sustainability Administration
Artificial Intelligence and Trends Using in Sustainability Audit: A Bibliometric Analysis
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Publication Date
Wed May 01 2024
Journal Name
Journal Of Physics: Conference Series
A modified ARIMA model for forecasting chemical sales in the USA
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Abstract<p>model is derived, and the methodology is given in detail. The model is constructed depending on some measurement criteria, Akaike and Bayesian information criterion. For the new time series model, a new algorithm has been generated. The forecasting process, one and two steps ahead, is discussed in detail. Some exploratory data analysis is given in the beginning. The best model is selected based on some criteria; it is compared with some naïve models. The modified model is applied to a monthly chemical sales dataset (January 1992 to Dec 2019), where the dataset in this work has been downloaded from the United States of America census (www.census.gov). Ultimately, the forecasted sales </p> ... Show More
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Publication Date
Thu Dec 01 2016
Journal Name
Chemical Engineering Science
Carbon dioxide rich microbubble acceleration of biogas production in anaerobic digestion
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Publication Date
Thu Apr 04 2024
Journal Name
Chemchemtech
ANALYTICAL TECHNIQUES IN PHARMACEUTICAL POLLUTION OF THE WORLD’S RIVERS; A REVIEW
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Recent reports of new pollution issues brought on by the presence of medications in the aquatic environment have sparked a great deal of interest in studies aiming at analyzing and mitigating the associated environmental risks, as well as the extent of this contamination. The main sources of pharmaceutical contaminants in natural lakes and rivers include clinic sewage, pharmaceutical production wastewater, and sewage from residences that have been contaminated by drug users' excretions. In evaluating the health of rivers, pharmaceutical pollutants have been identified as one of the emerging pollutants. The previous studies showed that the contaminants in pharmaceuticals that are widely used are non-steroidal anti-inflammatory drugs, ant

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Publication Date
Mon Feb 27 2023
Journal Name
Applied Sciences
Comparison of ML/DL Approaches for Detecting DDoS Attacks in SDN
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Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

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Publication Date
Sun Apr 02 2023
Journal Name
Journal Of Oral Microbiology
Current concepts in the pathogenesis of periodontitis: from symbiosis to dysbiosis
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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
In Vitro Cytotoxicity Study of Pt Nanoparticles Decorated TiO2 Nanotube Array
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Titanium dioxide nanotubes were synthesized by anodizing Ti sheets in the ethylene glycol solution and were covered in Pt nanoparticles onto the surface of TiO2NTs using electrodeposition method from using five derivatives of Mannich base Pt complexes which have been used as precursor of platinum. The mean size, shape, elemental composition of the titanium dioxide nanotubes and platinum deposited on the template were evaluated by different techniques such as field emission scanning electron microscope (FE-SEM), transmission electron microscopy (TEM), X-ray diffraction pattern (XRD), and energy dispersive X-ray (EDX) technique. From all these analyses, the TiO2NTs prepared and Ptnanoparticles deposited on it were ide

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Correlation between Serum and Tissue Markers in Breast Cancer Iraqi Patients
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Breast cancer is the most prevalent malignancy among women worldwide, in Iraq it ranks the first among the population and the leading cause of cancer related female mortality. This study is designed to investigate the correlations between serum and tissue markers in order to clarify their role in progression or regression breast cancer. Tumor Markers are groups of substances, mainly proteins, produced from cancer cell or from other cells in the body in response to tumor.  The study was carried out from April 2018 to April 2019 with total number of 60 breast cancer women. The blood samples were collected from breast cancer women in postoperative and pretherapeutic who attended teaching oncology hospital of the medical city in Baghdad and

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Publication Date
Thu Sep 01 2016
Journal Name
Current Pharmaceutical Design
Dry Eye Disease: Present Challenges in the Management and Future Trends
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Classification of Diseases in Oil Palm Leaves Using the GoogLeNet Model
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The general health of palm trees, encompassing the roots, stems, and leaves, significantly impacts palm oil production, therefore, meticulous attention is needed to achieve optimal yield. One of the challenges encountered in sustaining productive crops is the prevalence of pests and diseases afflicting oil palm plants. These diseases can detrimentally influence growth and development, leading to decreased productivity. Oil palm productivity is closely related to the conditions of its leaves, which play a vital role in photosynthesis. This research employed a comprehensive dataset of 1,230 images, consisting of 410 showing leaves, another 410 depicting bagworm infestations, and an additional 410 displaying caterpillar infestations. Furthe

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