Articles in This Issue
Abstract
Hydrogels are among the most versatile material classes used in biomedical applications. The material is of considerable interest in various fields of medicine due to its excellent features, such as high-water content, biocompatibility, and adjustable mechanical properties. The highlighted study thoroughly reviews Schiff-base thiadiazole-modified hydrogels as a novel functional material class, emphasizing their applicability in medical science. The addition of the Schiff-base and free thiazole groups to the hydrogel matrix introduces new antimicrobial activity, drug delivery, and bioadhesive attributes. An elaborate description of the methods employed to copolymerize thermoresponsive hydrogels with carbazole of thiadiazole as a binding group through free radical polymerization and visible light initiation is given under the first step of this general approach. The section on these hydrogels' physical and chemical properties was then added with a bias on morphological characterization, water uptake studies, and mechanical properties of the materials. After that, the discussion on more applications commenced, and among these, the following sections study them in the field of life-saving biomedical devices such as wound healing, tissue engineering, delivery of drugs, and biosensing prepared biosensing. A key emphasis is given to those interaction modes between Schiff-base thiadiazole groups and the biological systems that fulfil the hydrogels' healing mechanisms. These interaction modes, which include [specific modes], play a crucial role in the hydrogels' healing mechanism. The mentioned scholarship, in addition, dwells on the issues and barriers of such materials and gives thorough and valid judgements about the present and future of the matter. This review and the hard evaluation provide a thorough insight into Schiff-base thiadiazole-modified hydrogels' transformative impacts across the entire biomedicine area. A new approach is achieved by this review, in which the audience is made conscious and fully informed by presenting the most recent discoveries concerning the potential of Schiff-base thiadiazole-modified hydrogels to bring about innovative biomedical applications.
Abstract
The goal of the study is to predict the Man in the Middle attack in the packets of Wireshark program by using Support Vector Machines (SVM).In the time of using the internet, it has become a tool targeted by attackers and hackers; it is a serious threat to the devices. A uniqueness of an attack that appears in multiple identities for legitimate agencies. It is very necessary to know the behavior attack and predict the possible actions of an attacker. In this research a detection of Man in the Middle attack by monitoring the Wireshark program and recording any changes can be recognized in packet information. The classification of packets is divided into two categories (normal and abnormal). The proposed model is designed in many stages: loading data, processing data, training data, and testing data. The detection of SVM based on abnormal network packet through movement packets in the Wireshark program that needs to deal with current packets to recognize a new attack that one does not have prior knowledge of its detection, and there is a need for an intelligent way to separate network packets that represent normal. The proposed approach achieved an accuracy of 97.34% in detecting attacks. The results show that the proposed model effectively visualizes attacker behavior from data that represents abnormal network attackers. Research achieves successful accuracy in predicting abnormalities.
Abstract
The present investigation looked at whether the Bailey approach to aggregate gradation could be used to construct Superpave HMA blends. It also looked at how this approach influenced the rutting performance associated with these mixes and compared it to mixes of asphalt created by Superpave gradations. The current research included four aggregate gradations: both fine and coarse gradations for the Superpave and Bailey gradation procedures. The repeated loading test was utilized to assess the rutting performance. The findings indicated that temperature, stress level, and aggregate gradation all had a significant impact on rutting performance. In contrast to the other three gradations, the third mixture gradation exhibited the least amount of non-reversible deformation. It translates to pavement that is more resistant to rutting and less susceptible to it.
Abstract
Enhanced signal emission from nano (ESEN) coated titanium target over than that from normal untreated one was investigated. Four samples of Ti alloy were adjusted, the first sample was left untreated, the second and third samples were coated with plasma sputter at thicknesses of 35nm and 70nm, and the last sample was treated with a drop of colloidal Au nanoparticle solution prepared by laser ablation. The (ESEN) was monitored with Ti at 413.7 and 393.3 nm. It was obtained that the spectral emission from the nano-laser ablation had a greater improvement than that from the plasma sputter coating or bulk target. Enhancement factors were found up to ten folds, and show the spectroscopic line induced patterns by laser energies (100,150, and 200mJ) from the alloy with and without gold.
Abstract
This review study emphasizes the significance of MoS2 nanomaterials, their manufacture, and their applications. This review examined nanomaterials and their generation processes, concentrating on laser ablation and nanomaterial production. This study advances nanomaterial synthesis and helps discover new applications by explaining the fundamental concepts and aspects affecting synthesis. Future studies should optimize laser settings, explore novel precursor materials, and understand laser-induced MoS2 synthesis pathways to enable customized nanomaterial design and engineering.
Abstract
Industrial activities significantly affect the environment by releasing many organic pollutants, including industrial dyes, phenols and antibiotics, which produce wastewater. Effective removal of these substances from wastewater has appeared as a noticeable research field owing to its environmental significance. Exorbitant operational expenses and the potential generation of supplementary pollutants load conventional techniques like adsorption, membrane separation, and coagulation. Semiconductor-based photocatalysis has effectively degraded organic contaminants into less toxic or biodegradable compounds. The construction of robust visible-light-sensitive photocatalytic hybrids for environmental decontamination is an inspiring task for researchers. The exceptional photocatalytic performance of silver halides (AgX, where X is I, Cl, and Br) has recently attracted significant consideration as photocatalysts. Moreover, the combination of silver halides with other photo-active semiconductors to create efficient visible-light-driven photocatalyst heterojunctions has significantly promoted the broader application of the photocatalysis process with enhanced efficiency. Ag-silver halides/semiconductors heterojunctions have developed as crucial components in efficient composites for photocatalysis through surface plasmonic actions, helping with visible light absorption. The current study overviews the most recent Ag and silver halide-based composite photocatalysts. Additionally, it provides an essential understanding of their promoted photocatalytic performances and their main applications in organic pollutant degradation. Moreover, the photocatalytic mechanisms and environmental applications of AgI and composites were discussed.
Abstract
Planning standards in most countries especially in Iraq have become old and inadequate and do not fulfill the growing needs of people in the meanwhile. Also, it does not provide solutions for the society problems since it does not came from deep and modern study of the society needs and problems. In Iraq, there is a clear neglect of the urban spaces in residential buildings. As the challenges of 21st century, climate change, pollution and health crises requires infrastructure which is capable of keeping up with people needs and capable of providing healthy life, wellbeing and economic recovery. The study explores the efficiency of urban spaces in one of the Iraqi new residential complexes which is Alamal residential complex to determine the factors that affect urban spaces in vertical residential buildings in Iraq. The evaluation of the spaces was done by using direct observation method and questionnaire method. Results revealed that the spaces in such residential complex were active and efficient but it needs more spaces to be available since vertical residential buildings have high density of people. Also, there was a good care of urban spaces that fulfill the needs of children to play and also spaces which are friendly to old people. Most participants in the questionnaire have declared that the public urban space (space 3) was the most used, most favored space since it has many activities and facilities which support social activities between people living in the residential complex.
Abstract
Concrete is considered the most important and widely used building material in the world of construction and building due to its durability, high efficiency in shaping, and relatively reasonable cost. The main component of concrete is cement, and one of the most important problems related to cement is the environmental problems associated with cement manufacturing, as the cement manufacturing process releases a large amount of carbon dioxide. Despite the essential role of concrete in construction, we cannot ignore its environmental impact. Some claim that exploring alternative materials or innovative building techniques would reduce the carbon footprint and enhance sustainability in the industry. Partial cement replacement with pozzolanic materials like zeolite is a key technique to reduce carbon dioxide emissions. Zeolite, which reduces permeability, is a typical concrete ingredient that strengthens and lasts. Recently, natural zeolite has become a prominent concrete pozzolanic component. For environmental preservation and sustainable development, various experiments were done on concrete with pozzolanic components partially substituting cement and compared to ordinary concrete. A partial replacement of cement with zeolite improves the properties of concrete up to a certain age and mixing ratio. More than 44 relevant articles from 2004–2024 were selected from 762 papers evaluated for this paper. This paper reviews natural zeolite research in real applications. Additionally, it provided a cutting-edge review of natural zeolite literature through a critical analysis of various previous investigations. It also helped to understand how zeolite influences concrete mixture workability, strength, and durability. Since zeolite is a major concrete ingredient, it should be promoted as a sustainable resource.
Abstract
With the occurrence of pathological disorders in some people or aging, metabolic energy consumption begins significantly due to the weakness of the peripheral muscles and the increase in body fat with time, which aggravates the issues for this type of people, causing the rest hours extremely lengthy and consequently may produce heart or arterial diseases and elevate the mortality rate. Regarding the significance of the matter, this study examines a number of previous researches that featured several approaches to energy calculation and strategies for lowering energy consumption through the use of various external assistance devices, such as exosuits or exoskeletons, to assist people in carrying out their everyday tasks. And additionally discussed musculoskeletal simulation employs a variety of programs, especially OpenSim, which enables users to build models of musculoskeletal structures and produce dynamic movement simulations. According to the research findings, exoskeletons and other assistive technology can successfully lower the cost of metabolic energy to varying extents, depending on the device's weight, placement within the body, and whether it is active, semi-active, or inactive. In the future, the work to design and simulate a semi-active torsional ankle-foot exoskeleton with a specialized mechanism aimed to minimize metabolic energy.
Abstract
One of the most common causes of mortality worldwide is Lung cancer, an early diagnosis crucial for a patient’s survival and recovery. Automated segmentation of lung lesions in chest CT has become a pre-eminent focal point for research, particularly with the development of hybrid methods combining traditional image processing with advanced deep learning methods such as CNN. These hybrid approaches aim to minimize individual methods limitations by controlling their merge strengths to enhance segmentation efficiency, precision, and clinical utility. This review comprehensively analyzes different hybrid techniques, such as deep learning improved by rule-based systems, multi-scale feature extraction, and ensemble learning. As well as inspect their clinical effect, particularly in improving diagnostic accuracy and optimizing treatment procedures. Despite their possibility, these approaches still face significant challenges, such as computational complexity, data requirements, and the requirement for explainable AI (XAI). Upcoming advancements in lung lesion segmentation will focus on refining these models to achieve faster processing, improved accuracy, and integration with diagnostic tools to protect transparency and ethical considerations.
Abstract
Medical image segmentation plays a crucial role in the realm of medical imaging. The process involves the division of an image to obtain a comprehensive view and ensure precise diagnostics. There are various methods that are employed, ranging from traditional approaches to the more advanced deep learning techniques. Both play a significant role in enhancing healthcare. With the continuous advancement in technology, there is a growing need for accurate segmentation. While traditional methods such as thresholding and region growing are effective, they may require human intervention for complex cases. Deep learning techniques, particularly Convolutional Neural Networks (CNNs), have significantly improved the process by learning intricate details and accurately segmenting the image. When these methods are combined, healthcare professionals can achieve high-quality, precise results. Furthermore, with the advancements in hardware and technology, real-time segmentation is now possible. Generally, the process of dividing medical images into segments is extremely important for the progress of healthcare with the help of artificial intelligence and the most recent advancements in the industry, such as explainable AI and multimodal learning. However, this meticulously detailed and in-depth review provides an all-encompassing and extensive analysis of the current methods utilized, their multitude of applications across various fields, and the promising emerging advancements that have the potential to pave the way for remarkable future improvements and innovations.
Abstract
Many difficulties were recorded during laser-assisted tattoo removal. But most of them remain unknown. The recent literatures on laser tattoo removal focuses more on removal methods and systems than on side effects, such as temperature increase over tissue and ideal treatment parameters. This study aims to assess the surface temperature in compliance with eyebrow tattoo removal. The study was carried out for 55 patients aged between 22 and 43 years. The treatment was performed using a Nd:YAG laser (1064nm, Phi laser system) with an energy of 1000 mJ, a frequency of 3Hz, and a spot size of 8mm. The surface temperature of the skin during tattoo removal process was measured with a FLIR thermal camera. The results were analyzed by testing the normal state of distribution. The Shapiro-Wilk and Kolmogorov-Smirnov tests were used. All patients finished the full treatment of three laser sessions to achieve the goal of total removal. After temperature comparison, the results showed a significant influence of skin nature and patients' age on temperature distribution on skin, as for older patients, the energy absorption increased. Additionally, patients with darker skin tones exhibited greater absorption. The benefit of deepening understanding appeared in the Temperature distribution in the tissues of the affected area and the surrounding area during laser irradiation, as it provides a guiding and reference function for the effect of photothermal therapy.
Abstract
Over the last several years, additive manufacturing (AM), sometimes known as "3D printing", has seen remarkable expansion due to mechatronics and materials science advancements. Fused filament deposition (FDM) production is the predominant technology in additive manufacturing (AM) because of its cost-effectiveness in operational and material expenses. Nevertheless, the materials often used for this technique are pristine thermoplastics. Unsuccessful printing and throwaway prototypes generate a significant quantity of trash. Utilizing green and sustainable products is crucial to minimize the environmental effects. Recycled, bio-based, and mixed recycled materials provide a promising solution for 3D printing. The absence of comprehension about the interlayer adhesion process and material degradation in FDM printing has presented a significant obstacle for these environmentally friendly materials. This study comprehensively examines many materials used for FDM three-dimensional printing filaments, including recycled, bio-based, and mixed materials. The merits and drawbacks of thermoplastics and their composites were deliberated over. This evaluation is a comprehensive guide for engineers and researchers in selecting appropriate materials for three-dimensional printing. Three-dimensional printed objects have worse mechanical characteristics in comparison to injection molded materials.
Abstract
Artificial intelligence (AI) is rapidly advancing as a valuable tool in oncology for enhancing detection and management of cancer. The integration of AI with PET/CT imaging presents significant scenarios for improving efficiency and accuracy of cancer diagnosis. This study examines the current applications of AI with PET/CT imaging, highlighting its role in diagnosing, differentiating, delineating, staging, assessing therapy response, determining prognosis, and enhancing image quality. A comprehensive literature search was conducted in six data-bases to get the most recent works, use Springer, Scopus, PubMed, Web of Science, IEEE, and Google Scholar in the last five years (2019-2024), identifying 80 studies that met the criteria for inclusion that focused on AI-driven models applied to PET/CT data in various cancers, with lung cancer being the most studied. Other cancers examined include head and neck, breast, lymph nodes, whole body, and others. All studies involved human subjects. The findings indicate that AI holds promise in improving cancer detection, identifying benign from malignant tumors, aiding in segmentation, response evaluation, staging, and determining the prognosis. However, the application of AI-powered models and PET/CT-derived radiomics in clinical practice is limited because of issues of data normalization, reproducibility, and the requirement of large multi-center data sets for improving model generalizability. All these limitations have to be solved to guarantee the dependable and ethical use of AI in day-to-day clinical activities.
Abstract
The technique of recording muscle signals is crucial in determining how effectively they can be utilized for individual benefit. This study focuses on hand movements recognized by using the Myo armband and Motion Processing Unit (MPU) 6050 sensors. Linear Discriminant Analysis (LDA), K-nearest neighbors (k-NN), and Support Vector Machine (SVM) were employed for classification. sEMG signals using the Myo armband for 7 hand gestures and 2 elbow movements were recorded from 10 healthy subjects. Results showed that SVM outperforms LDA and k-NN in accuracy in both cases, the sensor is worn once on the arm and again on the forearm. regions. The window size and choice of features significantly influence system accuracy, with SVM achieving an average accuracy of 89.84%. Besides that, the fusion of Myo Armband sensor and gyroscope sensor through OR rule makes significant enhancement in recognition accuracy with which is reached to 97.0135%. In conclusion, the Myo armband, when worn on the forearm, proves practical for hand gesture recognition, with SVM offering superior recognition accuracy. Furthermore, the combination of the Myo Armband sensor and the gyroscope sensor showed higher recognition accuracy.
Abstract
This study evaluates the performance of bridge projects in Iraq using international performance evaluation standards set by USAID. The assessment focuses on two major bridge projects in Baghdad: the Bridge Project over the Army Canal and the Design and Implementation Project for developing the Shaljia and Tobji Intersection. The evaluation standards include relevance, efficiency, effectiveness, impact, and sustainability. Data collected from these projects were analyzed to measure performance against these standards. The results revealed significant gaps between both projects' expected and actual performance. The Bridge Project over the Army Canal showed moderate performance in relevance and sustainability but had substantial weaknesses in effectiveness. The Shaljia and Tobji, Intersection Development project, exhibited major weaknesses across all standards. The study concludes a critical need for better planning, improved resource utilization, enhanced stakeholder communication, and more effective monitoring and evaluation mechanisms to address these performance gaps and achieve desired project outcomes. These findings highlight the importance of adopting comprehensive and adaptable evaluation standards to improve the efficiency and effectiveness of infrastructure projects in Iraq. The research provides valuable insights for stakeholders involved in bridge projects, emphasizing the need for ongoing improvement in project management practices to ensure infrastructure reliability and safety.
Abstract
Shallow foundation suffers from considerable settlement, displacement and tilting under earthquakes. This is particularly due to the shaking associated with earthquakes that lead to the generation of horizontal seismic load transferred through the soil to the foundation. Also, liquefaction could take place during the earthquake in the saturated loose sand. To alleviate the detrimental effect of earthquakes, ground improvement is required. This study examines the response of the shallow square foundation rested on loose sand soil reinforced with geogrid reinforcement when subjected to 2023 Turkey earthquake by using a shaking table system. Different number of geogrid layers are installed; (one, two, three and four), also various geogrid configurations were examined which are (straight, trapezoidal and reverse trapezoidal). The acceleration response, settlement, horizontal displacement, rotation and pore water pressure developed in the sand soil and the shallow foundation during 2023 Turkey earthquake has been examined. The settlement and the horizontal displacement, foundation rotation, acceleration and pore water pressure were measured using rope displacement transducers, tilt sensors, accelerometers and pore water transducers respectively. The results showed that the acceleration amplifies when passing through loose sand. The results also indicated that the shallow foundation experienced noticeable settlement, horizontal displacement and rotation when subjected to the seismic loads. On the other hand, the installation of geogrid proved to be effective in controlling the problems associated with earthquakes. The optimum geogrid reinforcement is occurred when three layers of geogrid placed in reverse trapezoidal configuration (3RT) since it gave the best reduction in the acceleration amplification and the highest decrease in the foundation settlement, displacement and tilting which is about (60-66) %. Nevertheless, the effectiveness of geogrid minimizes when the sand soil becomes saturated. In addition, liquefaction occurs during earthquakes especially at the shallower depths because of the decrease in the shear strength of saturated soil.