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Application of Taguchi orthogonal array in optimization of the synthesis and crystallinity of metal organic framework 5 (MOF 5)
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Purpose: To use the L25 Taguchi orthogonal array for optimizing the three main solvothermal parameters that affect the synthesis of metal-organic frameworks-5 (MOF-5). Methods: The L25 Taguchi methodology was used to study various parameters that affect the degree of crystallinity (DOC) of MOF-5. The parameters comprised temperature of synthesis, duration of synthesis, and ratio of the solvent, N,N-dimethyl formamide (DMF) to reactants. For each parameter, the volume of DMF was varied while keeping the weight of reactants constant. The weights of 1,4-benzodicarboxylate (BDC) and Zn(NO3)2.6H2O used were 0.390 g and 2.166 g, respectively. For each parameter investigated, five different levels were used. The MOF-5 samples were synthesized using the solvothermal reaction method, and successful synthesis was confirmed with x-ray diffraction (XRD), microscopy, Fourier transform infrared spectroscopy (FTIR) and energy-dispersive x-ray spectroscopy (EDS). The DOC obtained via XRD served as a parameter of objective quality. Results: The optimum conditions that gave the highest DOC were synthesis temperature of 130 °C, duration of 60 h, and a vehicle volume of 50 mL, with optimum Brunauer-Emmett-Teller surface area (BET -SA) of 800 m2/g. All the three synthesis parameters significantly influenced the DOC of the synthesized MOF-5 (p < 0.05). Sub-optimal conditions resulted in distorted MOFs, products that deviated from MOF-5 specifications, or MOF-5 with low DOC. Conclusion: Based on DOC and BET-SA, the best conditions for synthesis of MOF-5 when using Taguchi OA, were temperature of 130 °C, duration of 60 h, and a DMF volume of 50 mL.

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Publication Date
Sat Jan 01 2022
Journal Name
Ieee Access
Wrapper and Hybrid Feature Selection Methods Using Metaheuristic Algorithms for English Text Classification: A Systematic Review
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Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
A Cut-off low at 500 hPa Geopotential Height and Rainfall Events over Iraq: Case Studies
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A cut-off low is a closed low with a low value of geopotential height at the upper atmospheric levels that has been fully detached (cut-off) from the westerly flow and move independently. A cut-off low causes extreme rainfall events in the mid-latitudes regions. The main aim of this paper is to investigate the cut-off low at 500 hPa over Iraq from a synoptic point of view and the behavior of geopotential height at 500 hPa. To examine the association of the cut-off low at 500 hPa with rainfall events across Iraq, two case studies of heavy rainfall events from different times were conducted. The results showed that the cut-off low at 500 hPa with a low value of geopotential height will strengthen the low-pressure system at the surface, lea

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Publication Date
Wed Jan 01 2020
Journal Name
Soil Science Society Of America Journal
Agroforestry, grass, biofuel crop, and row‐crop management effects on soil water dynamics for claypan landscapes
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Soil water use and water storage vary by vegetative management practices, and these practices affect land productivity and hydrologic processes. This study investigated the effects of agroforestry buffers (AB), grass buffers (GB), and biofuel crops (BC), relative to row crops (RC) on soil water use for a claypan soil in northern Missouri, USA. The experiment located at the Greenley Memorial Research Center included RC, AB, GB, and BC established in 1991, 1997, 1997, and 2012, respectively. Soil water reflectometer sensors installed at 5‐, 10‐, 20‐, and 40‐cm depths monitored soil water from April to November in 2017 and 2018. Results showed significant differences in weekly volumetric water content (VWC) among treatments for all fou

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Developing Load Balancing for IoT - Cloud Computing Based on Advanced Firefly and Weighted Round Robin Algorithms
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The evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities.   Cloud computing can be used to store big data.  The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual r

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Publication Date
Wed Jul 27 2022
Journal Name
Journal Of Chemical Technology &amp; Biotechnology
Broad‐ranging review: configurations, membrane types, governing equations, and influencing factors on microbial desalination cell technology
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Abstract<p>Seawater might serve as a fresh‐water supply for future generations to help meet the growing need for clean drinking water. Desalination and waste management using newer and more energy intensive processes are not viable options in the long term. Thus, an integrated and sustainable strategy is required to accomplish cost‐effective desalination via wastewater treatment. A microbial desalination cell (MDC) is a new technology that can treat wastewater, desalinate saltwater, and produce green energy simultaneously. Bio‐electrochemical oxidation of wastewater organics creates power using this method. Desalination and the creation of value‐added by‐products are expected because of this ionic mov</p> ... Show More
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Publication Date
Sat Jun 15 2019
Journal Name
Agriculture
Cover Crop Influence on Soil Enzymes and Selected Chemical Parameters for a Claypan Corn–Soybean Rotation
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Cover crops (CC) improve soil quality, including soil microbial enzymatic activities and soil chemical parameters. Scientific studies conducted in research centers have shown positive effects of CC on soil enzymatic activities; however, studies conducted in farmer fields are lacking in the literature. The objective of this study was to quantify CC effects on soil microbial enzymatic activities (β-glucosidase, β-glucosaminidase, fluorescein diacetate hydrolase, and dehydrogenase) under a corn (Zea mays L.)–soybean (Glycine max (L.) Merr.) rotation. The study was conducted in 2016 and 2018 in Chariton County, Missouri, where CC were first established in 2012. All tested soil enzyme levels were significantly different between 2016 and 2018

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Publication Date
Thu Aug 04 2022
Journal Name
Contemporary Nurse
ICU nurses’ safety performance related to respect for safety and management commitment: A cross-sectional study
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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Aquatic Oligochaeta (Annalida:Clitellata) as Bio Indication for Sediment Quality Assessment in Tigris River Within Baghdad City /Iraq
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Aquatic Oligochaeta is an important group of Macroinvertebrates that has been very remarkable as bioindicators for assessing water pollution and determining its degree in water bodies. Hence, the idea of the current study aims at studying the impact of Baghdad effluents on the Tigris River by using oligochaetes community as bioindicators . For this purpose, four sites along the inside of Baghdad has been chosen. Site S1 has been located upstream, site S2 and S3 has been at midstream and site S4 at the downstream of the River.This investigation has used different types of biological indicators, including the  percentage of oligochaeta  within benthic invertebrates, which ranged from 49.2-51.28%. The highest percentage of the tubificid w

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Publication Date
Sun Sep 01 2024
Journal Name
International Immunopharmacology
Evaluating treatment effect on interferon-alpha in female patients with systemic lupus erythematosus: a case-control study
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Evaluating treatment effect on interferon-alpha in female patients with systemic lupus erythematosus: a case-control study

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