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

The fiscal position of governments in rentier economies depends heavily on oil revenues. The relationship between oil prices and the budget surplus or deficit is often nonlinear and characterized by complex temporal dependencies, which may limit the predictive capability of conventional econometric models. Accordingly, this study aims to forecast the Iraqi budget surplus and deficit and compare the predictive performance of the ARDL, NARDL, LSTM, 1D-CNN, and hybrid 1D-CNN-LSTM models using oil prices as the primary predictive variable. The hybrid model integrates the feature-extraction capability of One-Dimensional Convolutional Neural Networks (1D-CNN) with the ability of Long Short-Term Memory (LSTM) networks to capture long-term

Objective: The aim of the study is to assess the personal hygiene of adult patients with
diabetic foot.
Methodology: A descriptive study was carried out in Baghdad teaching hospital, Al-Karama teaching hospital
and Al-Kindey teaching hospital for the period of 10/1/2006 to 1/9/2006. A purposive "non probability" sample
of (100) patient.
Questionnaire was constructed for achieving the purpose of the study. Data were collected through the
application of the questionnaire and interview technique. Data were analyzed through descriptive statistical
approach (frequency & percentage) and inferential statistical approach (chi-square & correlation) by using of
SPSS.
Results: The study results indicated that the

Objective: The aim of the study is to assess the personal hygiene of adult patients with
diabetic foot.
Methodology: ٨ descriptive study was carried out in Baghdad teaching hospital, Al-Karama teaching hospital
and Al-Kindey teaching hospital for the period of 10/1/2006 to 1/9/2006. A purposive "non probability" sample
of (100) patient.
Questionnaire was constructed for achieving the purpose of the study. Data were collected through the
application of the questionnaire and interview technique. Data were analyzed through descriptive statistical
approach (frequency & percentage) and inferential statistical approach (chi-square ع correlation) by using of
SPSS.
Results: The study results indicated that the ra

      The effect of fiber volume fraction of the carbon fiber on the thermal conductivity of the polymer composite material was studied. Different percentages of carbon fibers were used (5%, 10%, 15%, 20%, and 25%). Specimens were made in two groups for unsaturated polyester as a matrix and carbon fibers, first group has parallel arrangement of fibers and the second group has perpendicular arrangement of fibers on the thermal flow, Lee's disk method was used for testing the specimens. This study showed that the values of the of thermal conductivity of the specimens when the fibers arranged in parallel direction was higher than that when the fibers arranged in the perpendicular direction  

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Background: Alterations in the microhardness and roughness are commonly used to analyze the possible negative effects of bleaching products on restorative materials. This in vitro study evaluated the effect of in-office bleaching (SDI pola office +) on the surface roughness and micro-hardness of four newly developed composite materials (Z350XT –nano-filled, Z250XT-nano-hybrid, Z250-mico-hybrid and Silorane-silorane based). Materials and methods: Eighty circular samples with A3 shading were prepared by using Teflon mold 2mm thickness and 10mm in diameter. 20 samples for each material, 10 samples for base line measurement (surface roughness by using portable profillometer, and micro-hardness by usingDigital Micro Vickers Hardness Test

The work was carried out in two stages. The first stage concerned
with study of silicon carbide (SiC) ratio (1.5, 2.5, 3.5, and 4.5 wt%)
effect on the Thermal conductivity of polyvinyl chloride (PVC); and
the second stage concerned with the UV – weatherizing (25, 50, and
75 hr), thermal aging (40, 50, and 60 °C), and rain- weatherizing (1,
2.5, and 4 hr) effect on the samples involved. Thermal conductivity
results proved that there was slight increase in thermal conductivity
by (SiC) loading; it increased from 0.17 W/m.K for PVC to 0.19
W/m.K for 4.5% SiC/PVC; where as it was systematically decreased
by UV- weatherizing, thermal aging, and rain- weatherizing. This
property is in a good agreement with gene

This study used a continuous photo-Fenton-like method to remediate textile effluent containing azo dyes especially direct blue 15 dye (DB15). A Eucalyptus leaf extract was used to create iron/copper nanoparticles supported on bentonite for use as catalysts (E@B-Fe/Cu-NPs). Two fixed-bed configurations were studied and compared. The first one involved mixing granular bentonite with E@B-Fe/Cu-NPs (GB- E@B-Fe/Cu-NPs), and the other examined the mixing of E@B-Fe/Cu-NPs with glass beads (glass beads-E@B-Fe/Cu-NPs) and filled to the fixed-bed column. Scanning electron microscopy (SEM), zeta potential, and atomic forces spectroscopy (AFM) techniques were used to characterize the obtained particles (NPs). The effect of flow rate and DB15 concent

Despite their potential as a sustainable energy technology, the operation of proton exchange membrane fuel cells (PEMFCs) in sub-freezing conditions remains a critical challenge due to the risk of ice formation and performance degradation. This study introduces a new passive thermal management technique using strategically arranged multi-layer phase change materials (PCMs) to address this challenge. A numerical model was developed to evaluate the thermal behavior across various PCM configurations, incorporating one, two, and three layers arranged both in parallel and series with distinct melting points ranging from 55 to 65 ◦C. The results show that multi-layer PCM configurations provide significant improvements over the single-layer base