Two quantitative, environment-friendly and easily monitored assays for Ni (II) and Co (III) ions analysis in different lipstick samples collected from 500-Iraqi dinars stores located in Baghdad were introduced. The study was based on the reaction of nickel (II) ions with dimethylglyoxime (DMG) reagent and the reaction of cobalt (III) ions with 1-nitroso-2-naphthol (NN) reagent to produce colored products. The color change was measured by spectrophotometric method at 565 nm and 430 nm for Ni and Co, respectively, with linear calibration graphs in the concentration range 0.25-100 mg L^-1 (Ni) and 0.5-100 mg L^-1 (Co) and LOD and LOQ of 0.11 mg L^-1 and 0.36 mg L^-1 (Ni), and 0.15 mg L^-1 an

This study aims to determine the reasons for the increase in the frequency of sand and dust storms in the Middle East and to identify their sources and mitigate them. A set of climatic data from 60 years (1960–2022) was analyzed. Sand storms in Iraq are a silty sand mature arkose composed of 72.7% sand, 25.1% silt, and 2.19% clay; the clay fraction in dust storms constitutes 70%, with a small amount of silt (20.6%) and sand (9.4%). Dust and sand storms (%) are composed of quartz (49.2, 67.1), feldspar (4.9, 20.9), calcite (38, 5), gypsum (4.8, 0.4), dolomite (0.8, 1.0), and heavy minerals (3.2, 6.6). Increasing temperatures in Iraq, by an average of 2 °C for sixty years, have contributed to an increase in the number of dust storm

      The combined system of electrocoagulation (EC) and electro-oxidation (EO) is one of the most promising methods in dye removal. In this work, a solution of 200 mg/l of Congo red was used to examine the removal of anionic dye using an EC-EO system with three stainless steel electrodes as the auxiliary electrodes and an aluminum electrode as anode for the EC process, Cu-Mn-Ni Nanocomposite as anode for the EO process. This composite oxide was simultaneously synthesized by anodic and cathodic deposition of Cu (NO3)2, MnCl2, and Ni (NO3)2 salts with 0.075 M as concentrations of each salt with a fixed molar ratio (1:1:1) at a constant current density of 25 mA/cm2. The characteristics structure and surface morphology of the depo

Background: Traumatic ulcerative granuloma with stromal eosinophilia is an impressive benign chronic ulcerative lesion of the oral mucosa with vague etiopathogenesis. It was supposed to represent an oral counterpart of primary cutaneous CD30+ lymphoproliferative disorder. Histopathologically, it is characterized by mixed inflammatory infiltrate predominated by histiocytes, lymphocytes and eosinophils along with presence of scattered large atypical mononuclear cells. It has worrisome clinical presentation. It may heal spontaneously, but in most occasions it persists and never heal unless removed surgically (incisional or excisional biopsy). A rare subset may show worrisome immunohistochemical features. Follow up is highly recommended. Mat

Combining different treatment strategies successively or simultaneously has become recommended to achieve high purification standards for the treated discharged water. The current work focused on combining electrocoagulation, ion-exchange, and ultrasonication treatment approaches for the simultaneous removal of copper, nickel, and zinc ions from water. The removal of the three studied ions was significantly enhanced by increasing the power density (4–10 mA/cm2) and NaCl salt concentration (0.5–1.5 g/L) at a natural solution pH. The simultaneous removal of these metal ions at 4 mA/cm2 and 1 g NaCl/L was highly improved by introducing 1 g/L of mordenite zeolite as an ion-exchanger. A remarkable removal of heavy metals was reported

An Indirect simple sensitive and applicable spectrofluorometric method has been developed for the determination of Cefotaxime Sodium (CEF), ciprofloxacin Hydrochloride (CIP) and Famotidine (FAM) using reaction system bromate-bromide and acriflavine (AF) as fluorescent dye. The method is based on the oxidation of drugs with known excess bromate-bromide mixture in acidic medium and subsequent determination of unreacted oxidant by quenching fluorescence of AF. Fluorescence intensity of residual AF was measured at 528 nm after excitation at 402 nm. The fluorescence-concentration plots were rectilinear over the ranges 0.1-3.0, 0.05-2.6 and 0.1-3.8 µg ml^-1 with lower detection limits of 0.013, 0.018 and 0.021 µg ml^-1 an

Combining different treatment strategies successively or simultaneously has become recommended to achieve high purification standards for the treated discharged water. The current work focused on combining electrocoagulation, ion-exchange, and ultrasonication treatment approaches for the simultaneous removal of copper, nickel, and zinc ions from water. The removal of the three studied ions was significantly enhanced by increasing the power density (4–10 mA/cm2) and NaCl salt concentration (0.5–1.5 g/L) at a natural solution pH. The simultaneous removal of these metal ions at 4 mA/cm2 and 1 g NaCl/L was highly improved by introducing 1 g/L of mordenite zeolite as an ion-exchanger. A remarkable removal of heavy metals was reported

Room temperature ionic liquids show potential as an alternative to conventional organic membrane solvents mainly due to their properties of low vapour pressure, low volatility and they are often stable. In the present work, the technical feasibilities of room temperature ionic liquids as bulk liquid membranes for phenol removal were investigated experimentally. In this research several hydrophobic ionic liquids were synthesized at laboratory. These ionic liquids include (1-butyl-3-methylimidazolium bis (trifluoromethylsulfonyl) imide[Bmim][NTf₂], 1-Hexyl-3-methylimidazolium bis (trifluoromethylsulfonyl) imide[Hmim][NTf₂], 1-octyl-3-methylimidazolium bis (trifluoromethylsulfonyl)imide[Omim][NTf₂],1‐butyl

In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra