Search Results (96)

Rainwater harvesting for sustainable agriculture (RWHSA) offers a viable and eco-friendly strategy to alleviate water scarcity in semi-arid regions, particularly for agricultural use. This study aims to identify optimal sites for implementing RWH systems in northern Iraq to enhance water availability and promote sustainable farming practices. An integrated geospatial approach was adopted, combining Remote Sensing (RS), Geographic Information Systems (GIS), and Multi-Criteria Decision Analysis (MCDA). Key thematic layers, including soil type, land use/land cover, slope, and drainage density were processed in a GIS environment to model runoff potential. The Soil Conservation Service Curve Number (SCS-CN) method was used to estimate surface runoff. Criteria were weighted using the Analytical Hierarchy Process (AHP), enabling a structured and consistent evaluation of site suitability. The resulting suitability map classifies the region into four categories: very high suitability (10.2%), high (26.6%), moderate (40.4%), and low (22.8%). The integration of RS, GIS, AHP, and MCDA proved effective for strategic RWH site selection, supporting cost-efficient, sustainable, and data-driven agricultural planning in water-stressed environments. Full article

The escalating threats of climate change, pollution, and a rapidly growing global population are putting immense pressure on water resources, highlighting the urgent need for innovative wastewater recycling solutions. This study explores the potential of biochar, derived from common kitchen waste as a sustainable and efficient adsorbent for copper removal from contaminated water. Seven factors were studied for their influence on the adsorption process, including heavy metal concentration (50–250 ppm), biochar dosage (0.5–2.5 g), contact time (30 min to 29 h), temperature (20–80 °C), pH (2.67–8.07), and the efficacy of activated versus non-activated biochar, with activation carried out using phosphoric acid, silver nitrate, and sulfuric acid. Biochar characterization using Raman spectroscopy, specific surface area by Brunauer–Emmett–Teller analysis (BET), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), Scanning Electron Microscopy—Energy Dispersive X-ray Spectroscopy (SEM-EDX), and zeta potential analysis revealed its robust adsorption capacity. Notably, silver nitrate-loaded biochar exhibited the highest adsorption capacity (24.44 mg/g) at 250 ppm of copper and the highest removal rate at about 99.3%, whereas phosphoric acid activation reduced this capacity to 5 mg/g due to structural damage. Importantly, biochar’s adsorption capacity was found to be pH-independent, simplifying operational requirements for treatment systems. Optimal conditions for maximum copper removal were determined to be 100 ppm of copper, a temperature of 60 °C, and a contact time of 30 min. The Langmuir isotherm model best described the adsorption process, indicating a monolayer adsorption with a maximum capacity of 23.25 mg/g. This comprehensive analysis underscores biochar’s potential as a cost-effective, efficient, and environmentally friendly solution for copper removal from wastewater. Full article

This study looks into the role of temporary architecture in preserving intangible heritage during the Arbaeen Pilgrimage in Holy Karbala. It seeks to find out how temporary structures contribute to Holy Karbala’s cultural and historical identity in the context of the Arbaeen Pilgrimage while meeting today’s needs. A case study approach was used in this research to analyze temporary architecture projects implemented during the Arbaeen Pilgrimage in Holy Karbala. Field observations, expert surveys, and document analysis were conducted to assess how these structures affect the preservation of intangible heritage related to the pilgrimage. The research finds that temporary architecture during the Arbaeen Pilgrimage is crucial in preserving intangible heritage. While some structures support the religious and cultural practices of the pilgrimage, others challenge the historical urban fabric. The study concludes that temporary architecture should be designed carefully to balance functionality with heritage preservation. This study contributes to the understanding of how temporary architecture can be strategically used during big religious events like the Arbaeen Pilgrimage to support heritage preservation. It provides practical tips on how to incorporate temporary structures in a way that respects Holy Karbala’s intangible heritage. Full article

Circular RNAs (circRNAs) are increasingly recognized as significant regulators in multiple cancers, such as hepatocellular carcinoma (HCC), frequently affecting microRNA (miRNA) expression. The diagnostic and prognostic roles of circRNAs, specifically circ_0009910 and circ_0027478, in conjunction with miR-1236-3p, in HCC, have not yet been fully investigated. In this pilot study, we assessed the expression levels of circ_0009910, circ_0027478, and miR-1236-3p in plasma samples from 100 patients diagnosed with HCC and 50 healthy controls through reverse transcriptase–quantitative polymerase chain reaction (RT-qPCR). The diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis, and correlations with clinicopathological features were examined. Circ_0009910 and circ_0027478 exhibited significant upregulation in patients with HCC (p < 0.05), whereas miR-1236-3p demonstrated downregulation (p < 0.05). Circ_0009910 demonstrated significant diagnostic accuracy (area under the curve [AUC] = 0.90), effectively differentiating HCC from controls and showing a correlation with tumor size, metastasis, and alpha-fetoprotein (AFP) levels (p < 0.05). Both circ_0009910 and circ_0027478 exhibited a positive correlation with clinicopathological features, whereas miR-1236-3p demonstrated an inverse correlation. Logistic regression validated the diagnostic and prognostic capabilities of these biomarkers. The results indicate that circ_0009910, circ_0027478, and miR-1236-3p, in conjunction with AFP three, present a promising diagnostic and prognostic profile for HCC. Additional validation in larger cohorts is required to establish their clinical utility. Full article

The emergence of multidrug-resistant bacterial infections is a major global public health concern. Human health is in danger from microorganisms that have developed resistance to currently used drugs. Honey is well known for its significant activity against antibiotic-resistant bacteria. In this study, the antibacterial properties of honey from various botanical sources in Saudi Arabia against seven significant nosocomial and foodborne pathogens were investigated. The physicochemical properties of four Saudi honey samples—aloe honey (HO1) (Aloe vera L.), anise honey (HO2) (Pimpinella anisum L.), moringa honey (HO4) (Moringa oleifera Lam.), and acacia honey (HO5) (Acacia sp.)—were examined. In addition, they were screened for antibacterial activity against ESKAPE pathogens (Enterobacter faecalis, Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa, Salmonella Typhimurium, Escherichia coli, and Enterobacter sp.) and anti-biofilm activity against four pathogenic bacteria strains: S. aureus, P. aeruginosa, S. typhimurium, and E. coli. ¹H NMR profiling and multivariate analysis (PCA and PLS-DA) were performed. Aloe honey (HO1) was the most distinct sample based on MVDA and its antibacterial activity, and it exhibited anti-biofilm activity against most biofilm-forming microorganisms. Its metabolic profile was deduced using LC-MS, and the resulting annotated compounds were docked against several β-lactamase enzyme classes. The results reveal the potential of honey-derived compounds to inhibit β-lactamases due to the presence of gallic acid hexoside and rosmarinic acid, suggesting their potential as competitive inhibitors. Our findings suggest that further honey antibacterial compounds could offer a novel approach to overcoming antibiotic resistance by targeting and inhibiting β-lactamase enzymes. Full article

Background/Objectives: Hesperidin (HSP) is a potent phytochemical antioxidant and anti-inflammatory agent that protects against otitis media. However, due to its low solubility and bioavailability, a suitable delivery method is needed to overcome these problems. A hydrogel is a promising nanocarrier for controlled drug delivery in response to external stimuli, such as pH variations. Methods: Graphene oxide (GO)-based nanocarriers that encapsulate hesperidin (HSP) were further coated with a polylactic-co-glycolic acid/alginate (PLGA-Alg) hydrogel before being integrated into a green neem oil (N.O.) double emulsion to produce a synergistic effect and then characterized by different assays. Results: The nanocarriers exhibited a substantial particle size (168 ± 0.32 nm), with high encapsulation (89.86 ± 0.23%) and a zeta potential of 37 ± 0.43 mV. In vitro release studies conducted over 96 h indicated a sustained HSP release of 82% at pH 5.4 and 65% at pH 7.4. The GO-HSP-loaded neem oil double emulsion formulation exhibits substantial antibacterial activity, as evidenced by inhibition zones of 39 ± 0.02 mm against Staphylococcus epidermidis, and considerable antifungal activity against Candida albicans, with an inhibition zone of 43 ± 0.13 mm, along with biofilm inhibition activity. The formulation demonstrated antioxidant activity (5.21 µg/mL) and increased cell viability (90–95%) while maintaining low cytotoxicity in HSE-2 cells. A histopathological analysis confirmed that treatment with the nanocarriers reduced the levels of pro-inflammatory cytokines (IL-1β, TNF-α, TLR4, IL-6) and raised the levels of antioxidant markers (Nrf-2, SOD) in an in vivo rat model of otitis media. Conclusions: GO-based nanocarriers integrated into a neem oil double emulsion and coated with PLGA-Alg hydrogel deliver hesperidin with sustained release and enhanced antibacterial, antifungal, and antioxidant properties. This formulation may be used to treat otitis media and other oxidative stress diseases. Full article

In the Mediterranean and Himalayan regions, the genus Mandragora (family Solanaceae), sometimes called mandrake, is widely utilized in herbal therapy and is well-known for its mythical associations. Objective: To compile up-to-date information on M. autumnalis’s therapeutic properties. Its pharmacological properties and phytochemical composition are particularly covered in managing several illnesses, including diabetes, cancer, and heart disease. Methods: Articles on the review topic were found by searching major scientific literature databases, such as PubMed, Scopus, ScienceDirect, SciFinder, Chemical Abstracts, and Medicinal and Aromatic Plants Abstracts. Additionally, general online searches were conducted using Google Scholar and Google. The time frame for the search included items released from 1986 to 2023. Results:Mandragora has been shown to contain a variety of phytochemicals, including coumarins, withanolides, and alkaloids. The pharmacological characteristics of M. autumnalis, such as increasing macrophage anti-inflammatory activity, free radicals inhibition, bacterial and fungal growth inhibition, cytotoxic anticancer activities in vivo and in vitro against cancer cell lines, and enzyme-inhibitory properties, are attributed to these phytochemicals. Furthermore, M. autumnalis also inhibits cholinesterase, tyrosinase, α-amylase, α-glucosidase, and free radicals. On the other hand, metabolic risk factors, including the inhibition of diabetes-causing enzymes and obesity, have been treated using dried ripe berries. Conclusions: Investigations into the pharmacological and phytochemical characteristics of M. autumnalis have revealed that this plant is a rich reservoir of new bioactive substances. This review aims to provide insight into the botanical and ecological characteristics of Mandragora autumnalis, including a summary of its phytochemical components and antioxidant, antimicrobial, antidiabetic, anticancer, enzyme-inhibitory properties, as well as toxicological implications, where its low cytotoxic activity against the normal VERO cell line has been shown. More research on this plant is necessary to ensure its efficacy and safety. Still, it is also necessary to understand the molecular mechanism of action behind the observed effects to clarify its therapeutic potential. Full article

This study hypothesized that alternating fresh and saline irrigation with different dripper types would optimize water use while minimizing negative effects on soil bulk density (ρb) and maize growth. The field experiment was carried out to investigate the impact of the types of the dripper and the salinity of irrigation water rotation on the ρb, maize (Zea mays L.) growth, and yield using two kinds of drippers (turbo and spiral) and two levels of irrigation water with different salinity ratios (low, symbolized by L) and (high, symbolized by H). Irrigation water was added into three rotations (L, H), (H, L, H), and (L, H, L). Soil ρb increased by 22.63% under saline irrigation, while yield was 3.07% higher with turbo drippers compared to spiral drippers. The results displayed an increase in plant height, leaf area, and yield by using the (L, H, L) as compared to (L, H) and (H, L, H), respectively. These results suggest that alternating fresh and saline water could reduce freshwater usage by 50% while maintaining acceptable crop yields, making it a cost-effective solution for water-scarce regions. Full article

Uncertainty-aware soft sensors in sign language recognition (SLR) integrate methods to quantify and manage the uncertainty in their predictions. This is particularly crucial in SLR due to the variability in sign language gestures and differences in individual signing styles. Managing uncertainty allows the system to handle variations in signing styles, lighting conditions, and occlusions more effectively. While current techniques for handling uncertainty in SLR systems offer significant benefits in terms of improved accuracy and robustness, they also come with notable disadvantages. High computational complexity, data dependency, scalability issues, sensor and environmental limitations, and real-time constraints all pose significant hurdles. The aim of the work is to develop and evaluate a Type-2 Neutrosophic Hidden Markov Model (HMM) for SLR that leverages the advanced uncertainty handling capabilities of Type-2 neutrosophic sets. In the suggested soft sensor model, the Foot of Uncertainty (FOU) allows Type-2 Neutrosophic HMMs to represent uncertainty as intervals, capturing the range of possible values for truth, falsity, and indeterminacy. This is especially useful in SLR, where gestures can be ambiguous or imprecise. This enhances the model’s ability to manage complex uncertainties in sign language gestures and mitigate issues related to model drift. The FOU provides a measure of confidence for each recognition result by indicating the range of uncertainty. By effectively addressing uncertainty and enhancing subject independence, the model can be integrated into real-life applications, improving interactions, learning, and accessibility for the hearing-impaired. Examples such as assistive devices, educational tools, and customer service automation highlight its transformative potential. The experimental evaluation demonstrates the superiority of the Type-2 Neutrosophic HMM over the Type-1 Neutrosophic HMM in terms of accuracy for SLR. Specifically, the Type-2 Neutrosophic HMM consistently outperforms its Type-1 counterpart across various test scenarios, achieving an average accuracy improvement of 10%. Full article

Accurate measurement of slip rate (SR) in agricultural tractors, particularly in Iraq, is essential for optimizing tractive efficiency, fuel economy, and field efficiency. Presently, tractors in Iraq lack sensors for SR detection, posing a challenge. This research addresses the issue by introducing a wireless technology, the novel digital slippage system (NDSS), designed to precisely measure the SR of rear wheels. The NDSS was tested across diverse field conditions, involving six soil textures and various kinds of agricultural tillage equipment (A-TE). Different tillage practices, including conservational tillage (CT) with a chisel plough, traditional tillage (TT) with a moldboard plough and disc plough, and minimum tillage (MT) using disc harrowing and spring tooth harrowing, were examined. Results from the NDSS were compared to traditional techniques, demonstrating the cost effectiveness and overall performance. Silty loam soil exhibited higher SR values, while the silty clay soil showed lower values. SR varied significantly across soil textures, with more cohesive soils leading to reduced SR percentages. Additionally, tillage methods had a marked influence on SR values. The use of CT resulted in higher SR values of 18.35% compared to TT and MT systems, which recorded lower SR values of 13.69% and 6.03%, respectively. SR measurements were also found to be affected by the draft force during the loading of A-TE, emphasizing the role of operational conditions in tractor performance, especially in challenging field environments. Comparison between NDSS and traditional techniques revealed that the NDSS offered high accuracy, flexibility, configurability, and consistent performance. The NDSS demonstrated superior precision, making it an effective tool for assessing SR in agricultural tractors. Full article

This study presents the design and implementation of a piezoelectric power harvesting device to capture vibrational energy from pipelines to self-powered IoT devices. The device utilizes key components along with the PPA-1001 piezoelectric sensor, the STM32F103C8T6 microcontroller, and LTC-3588 energy harvesting power supply. Experimental results verified the system’s performance in harvesting power within a specific frequency range of 10 Hz to 50 Hz, with the foremost overall performance at 30 Hz. The device generated the highest voltage of 3.3 V, delivering a power output of 2.18 mW, which is sufficient to power low-power electronic devices. The device maintained solid performance across a temperature range of 40 °C to 50 °C, underscoring its robustness in various environmental situations. The findings highlight the capacity of this form of generation to offer a sustainable power source for remote pipeline tracking, contributing to stronger protection and operational efficiency. Full article

Investigating the spatial-temporal evolutionary trends of future temperature and precipitation considering various emission scenarios is crucial for developing effective responses to climate change. However, researchers in Iraq have not treated this issue under CMIP6 in much detail. This research aims to examine the spatiotemporal characteristics of temperature and rainfall in northern Iraq by applying LARS-WG (8) under CMIP6 general circulation models (GCMs). Five GCMs (ACCESS-ESM1-5, CNRM-CM6-1, MPI-ESM1-2-LR, HadGEM3-GC31-LL, and MRI-ESM2-0) and two emissions scenarios (SSP245 and SSP585) were applied to project the upcoming climate variables for the period from 2021 to 2040. The research relied on satellite data from fifteen weather sites spread over northern Iraq from 1985 to 2015 to calibrate and validate the LARS-WG model. Analysis of spatial-temporal evolutionary trends of future temperature and precipitation compared with the baseline period revealed that seasonal mean temperatures will increase throughout the year for both scenarios. However, the SSP585 scenario reveals the highest increase during autumn when the spatial coverage of class (15–20) °C increased from 27.7 to 96.29%. At the same time, the average seasonal rainfall will rise in all seasons for both scenarios except autumn for the SSP585 scenario. The highest rainfall increment percentage is obtained using the SSP585 for class (120–140) mm during winter. The spatial extent of the class increased from 25.49 to 50.19%. Full article

The Industrial Internet of Things (IIoT) is pivotal in advancing industrial automation, offering significant improvements in connectivity and efficiency. However, the integration of heterogeneous devices within IIoT systems presents substantial challenges, primarily due to the diversity in device hardware, protocols, and functionalities. In this paper, we propose a new pattern language specifically designed to enhance interoperability and operational efficiency across industrial settings. Drawing from a case study of the State Company for Automotive Industry (S.C.A.I.) in Iraq, this study details the development and integration of eleven interrelated patterns. These patterns were carefully combined based on identified relationships, forming a comprehensive pattern language that addresses key aspects of system heterogeneity, including device communication, data security, and system scalability. The pattern language was validated using the Delphi process theory, engaging industry experts to refine and optimize the framework for practical application. The implementation of this pattern language led to significant improvements in system integration, enabling seamless communication between diverse devices and enhancing operational workflows. The case study demonstrates the practical viability of the proposed pattern language in enhancing interoperability within real-world Industrial Internet of Things (IIoT) applications. Furthermore, the replicable nature of this framework makes it a valuable resource for other industrial environments seeking to harness the power of IIoT technologies. Full article

Natural gas (NG) is favored for transportation due to its availability and lower CO₂ emissions than fossil fuels, despite drawbacks like poor lean combustion ability and slow burning. According to a few recent studies, using hydrogen (H₂) alongside NG and diesel in Tri-fuel mode addresses these drawbacks while enhancing efficiency and reducing emissions, making it a promising option for diesel engines. Due to the importance and novelty of this, the continuation of ongoing research, and insufficient literature studies on HNG–diesel engine emissions that are considered helpful to researchers, this research has been conducted. This review summarizes the recent research on the HNG–diesel Tri-fuel engines utilizing hydrogen-enriched natural gas (HNG). The research methodology involved summarizing the effect of engine design, operating conditions, fuel mixing ratios and supplying techniques on the CO, CO₂, NO_x and HC emissions separately. Previous studies show that using natural gas with diesel increases CO and HC emissions while decreasing NO_x and CO₂ compared to pure diesel. However, using hydrogen with diesel reduces CO, CO₂, and HC emissions but increases NO_x. On the other hand, HNG–diesel fuel mode effectively mitigates the disadvantages of using these fuels separately, resulting in decreased emissions of CO, CO₂, HC, and NO_x. The inclusion of hydrogen improves combustion efficiency, reduces ignition delay, and enhances heat release and in-cylinder pressure. Additionally, operational parameters such as engine power, speed, load, air–fuel ratio, compression ratio, and injection parameters directly affect emissions in HNG–diesel Tri-fuel engines. Overall, the Tri-fuel approach offers promising emissions benefits compared to using natural gas or hydrogen separately as dual-fuels. Full article

The blending of biodiesel with petroleum diesel attracts much attention due to its high potential in reducing emissions. In this work, waste sunflower oil was converted to biodiesel by the trans-esterification method, and it was blended with petroleum diesel in three ratios (10, 30, and 50%). The impact of using these blended fuels in a four-stroke engine on engine performance and exhaust emissions at three engine loads (2, 4, and 6 N.m) was investigated and compared with the use of petroleum diesel and biodiesel. The engine performance was evaluated by determining the brake-specific fuel consumption (BSFC), engine effective power (Ne), brake-specific energy consumption (BSEC), brake thermal efficiency (BTE), and noise intensity. The evaluation of emissions from the engine exhaust was carried out by measuring the levels of carbon oxides (CO and CO₂), hydrocarbons (HC), nitrogen oxides (NO and NO₂), and particulate matter (PM). The results show that blending diesel with up to 30% biodiesel can reduce CO, HC, and PM emissions by 29.6 ± 1%, 26.0 ± 4%, and 31.0 ± 3%, respectively. However, this decrease is associated with increasing CO₂ and NOx emissions by 18.5 ± 2.5% and 29.0 ± 6%, respectively. In addition, the engine showed acceptable performance when using up to 30% biodiesel, where the increase in fuel consumption was limited to 5.8 ± 0.3%. In addition, the engine’s effective power increased with the blending ratio of 10% by 2.0 ± 0.6%, but then decreased with the blending ratio of 30% by only 2.0 ± 0.6%. The noise intensity was also decreased by 2.4%, while BSEC and BTE were reduced by only 2.9 ± 0.9% and 3.5 ± 1%, respectively. The results of this work provide deep insights regarding the utilization of waste sunflower oil as biodiesel to be blended with petroleum diesel, which is a considerable novel approach in the energy and environmental sectors. Full article