Nahrain University

Exposure to ultraviolet (UV) radiation may cause the significant degradation of many materials. UV radiation causes photooxidative degradation which results in breaking of the polymer chains, produces free radical and reduces the molecular weight, causing deterioration of mechanical properties and leading to useless materials, after an unpredictable time. Polystyrene (PS), one of the most important material in the modern plastic industry, has been used all over the world, due to its excellent physical properties and low-cost. When polystyrene is subjected to UV irradiation in the presence of air, it undergoes a rapid yellowing and a gradual embrittlement. The mechanism of PS photolysis in the solid state (film) depends on the mobility of free radicals in the polymer matrix and their bimolecular recombination. Free hydrogen radicals diffuse very easily through the polymer matrix and combine in pairs or abstract hydrogen atoms from polymer molecule. Phenyl radical has limited mobility. They may abstract hydrogen from the near surrounding or combine with a polymer radical or with hydrogen radicals. Almost all synthetic polymers require stabilization against adverse environmental effects. It is necessary to find a means to reduce or prevent damage induced by environmental components such as heat, light or oxygen. The photostabilization of polymers may be achieved in many ways. The following stabilizing systems have been developed, which depend on the action of stabilizer: (1) light screeners, (2) UV absorbers, (3) excited-state quenchers, (4) peroxide decomposers, and (5) free radical scavengers; of these, it is generally believed that excited-state quenchers, peroxide decomposers, and free radical scavengers are the most effective. Research into degradation and ageing of polymers is extremely intensive and new materials are being synthesized with a pre-programmed lifetime. New stabilizers are becoming commercially available although their modes of action are sometimes not thoroughly elucidated. They target the many possible ways of polymer degradation: thermolysis, thermooxidation, photolysis, photooxidation, radiolysis etc. With the goal to increase lifetime of a particular polymeric material, two aspects of degradation are of particular importance: Storage conditions, and Addition of appropriate stabilizers. A profound knowledge of degradation mechanisms is needed to achieve the goal.

The simplicity, transparency, reliability, high efficiency and robust nature of PID controllers are some of the reasons for their high popularity and acceptance for control in process industries around the world today. Tuning of PID control parameters has been a field of active research and still is. The primary objectives of PID control parameters are to achieve minimal overshoot in steady state response and lesser settling time. With exception of two popular conventional tuning strategies (Ziegler Nichols closed loop oscillation and Cohen-Coon's process reaction curve) several other methods have been employed for tuning. This work accords a thorough review of state-of-the-art and classical strategies for PID controller parameters tuning using metaheuristic algorithms. Methods appraised are categorized into classical and metaheuristic optimization methods for PID parameters tuning purposes. Details of some metaheuristic algorithms, methods of application, equations and implementation flowcharts/algorithms are presented. Some open problems for future research are also presented. The major goal of this work is to proffer a comprehensive reference source for researchers and scholars working on PID controllers.

Abstract The depletion of the world's crude oil reserve, increasing crude oil prices, and issues related to conservation have brought about renewed interest in the use of bio‐based materials. Emphasis on the development of renewable, biodegradable, and environmentally friendly industrial fluids, such as lubricants, has resulted in the widespread use of natural oils and fats for non‐edible purposes. In this study, we have reviewed the available literature and recently published data related to bio‐based raw materials and the chemical modifications of raw materials. Additionally, we have analyzed the impacts and benefits of the use of bio‐based raw materials as functional fluids or biolubricants. The term biolubricants applies to all lubricants, which are both rapidly biodegradable and non‐toxic to humans and other living organisms, especially in aquatic environments. Biodegradability provides an indication of the persistence of the substance in the environment and is the yardstick for assessing the eco‐friendliness of substances. Scientists are discovering economical and safe ways to improve the properties of biolubricants, such as increasing their poor oxidative stability and decreasing high pour points. “Green” biolubricants must be used for all applications where there is an environmental risk.

The aim of this study was to determine the changes of short chain fatty acids (SCFAs) in faeces of inflammatory bowel disease (IBD) patients compared to healthy subjects. SCFAs such as pyruvic, lactic, formic, acetic, propionic, isobutyric and butyric acids were analyzed by using high performance liquid chromatography (HPLC). This study showed that the level of acetic, 162.0 micromol/g wet faeces, butyric, 86.9 micromol/g wet faeces, and propionic acids, 65.6 micromol/g wet faeces, decreased remarkably in IBD faecal samples when compared with that of healthy individuals, 209.7, 176.0, and 93.3 micromol/g wet faeces respectively. On the contrary, lactic and pyruvic acids showed higher levels in faecal samples of IBD than in healthy subjects. In the context of butyric acid level, this study also found that the molar ratio of butyric acid was higher than propionic acid in both faecal samples. This might be due to the high intake of starch from rice among Malaysian population. It was concluded that the level of SCFAs differ remarkably between faecal samples in healthy subjects and that in IBD patients providing evidence that SCFAs more likely play an important role in the pathogenesis of IBD.

Alzheimer's disease (AD) is the leading cause of dementia in older adults. There is currently a lot of interest in applying machine learning to find out metabolic diseases like Alzheimer's and Diabetes that affect a large population of people around the world. Their incidence rates are increasing at an alarming rate every year. In Alzheimer's disease, the brain is affected by neurodegenerative changes. As our aging population increases, more and more individuals, their families, and healthcare will experience diseases that affect memory and functioning. These effects will be profound on the social, financial, and economic fronts. In its early stages, Alzheimer's disease is hard to predict. A treatment given at an early stage of AD is more effective, and it causes fewer minor damage than a treatment done at a later stage. Several techniques such as Decision Tree, Random Forest, Support Vector Machine, Gradient Boosting, and Voting classifiers have been employed to identify the best parameters for Alzheimer's disease prediction. Predictions of Alzheimer's disease are based on Open Access Series of Imaging Studies (OASIS) data, and performance is measured with parameters like Precision, Recall, Accuracy, and F1-score for ML models. The proposed classification scheme can be used by clinicians to make diagnoses of these diseases. It is highly beneficial to lower annual mortality rates of Alzheimer's disease in early diagnosis with these ML algorithms. The proposed work shows better results with the best validation average accuracy of 83% on the test data of AD. This test accuracy score is significantly higher in comparison with existing works.

Signal Transducer and Activator of Transcription (STAT) pathway is connected upstream with Janus kinases (JAK) family protein and capable of integrating inputs from different signaling pathways. Each family member plays unique functions in signal transduction and crucial in mediating cellular responses to different kind of cytokines. STAT family members notably STAT3 and STAT5 have been involved in cancer progression whereas STAT1 plays opposite role by suppressing tumor growth. Persistent STAT3/5 activation is known to promote chronic inflammation, which increases susceptibility of healthy cells to carcinogenesis. Here, we review the role of STATs in cancers and inflammation while discussing current therapeutic implications in different cancers and test models, especially the delivery of STAT3/5 targeting siRNA using nanoparticulate delivery system.

A total of five new metal complex derivatives of 2N-salicylidene-5-(p-nitro phenyl)-1,3,4-thiadiazole, HL with the metal ions Vo(II), Co(II), Rh(III), Pd(II) and Au(III) have been successfully prepared in alcoholic medium. The complexes obtained are characterized quantitatively and qualitatively by using micro elemental analysis, FTIR spectroscopy, UV–Vis spectroscopy, mass spectroscopy, 1H & 13C NMR, magnetic susceptibility and conductivity measurements. From the spectral study, all the complexes obtained as monomeric structure and the metals center moieties are four-coordinated with square planar geometry except VO(II) and Co complexes which existed as a square pyramidal and tetrahedral geometry respectively. The preliminary in vitro antibacterial screening activity revealed that complexes 1–5 showed moderate activity against tested bacterial strains and slightly higher compared to the ligand, HL.

The pandemic coronavirus disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has affected millions of people worldwide. To date, there are no proven effective therapies for this virus. Efforts made to develop antiviral strategies for the treatment of COVID-19 are underway. Respiratory viral infections, such as influenza, predispose patients to co-infections and these lead to increased disease severity and mortality. Numerous types of antibiotics such as azithromycin have been employed for the prevention and treatment of bacterial co-infection and secondary bacterial infections in patients with a viral respiratory infection (e.g., SARS-CoV-2). Although antibiotics do not directly affect SARS-CoV-2, viral respiratory infections often result in bacterial pneumonia. It is possible that some patients die from bacterial co-infection rather than virus itself. To date, a considerable number of bacterial strains have been resistant to various antibiotics such as azithromycin, and the overuse could render those or other antibiotics even less effective. Therefore, bacterial co-infection and secondary bacterial infection are considered critical risk factors for the severity and mortality rates of COVID-19. Also, the antibiotic-resistant as a result of overusing must be considered. In this review, we will summarize the bacterial co-infection and secondary bacterial infection in some featured respiratory viral infections, especially COVID-19.

Heavy metals, pervasive in the environment due to natural processes and human activities, pose substantial threats to ecosystems and human health. This study aims to delve into the sources, contamination pathways in natural waters, and subsequent bioaccumulation of heavy metals across various organisms. The overview encompasses an exploration of the environmental persistence, bioaccumulation dynamics, and ecotoxicological impacts of these metals. Methodologically, this research undertakes a comprehensive review synthesizing existing literature and studies on heavy metal contamination, bioaccumulation mechanisms, and ecotoxicity. Key findings highlight the protracted environmental persistence of heavy metals, perpetuating significant threats to ecological balance and human well-being. Notably, the transfer of these metals through food chains culminates in their bioaccumulation in diverse organisms, raising concerns about potential toxicity, including human exposure. The discussion underscores the imperative nature of assessing heavy metal pollution and its ramifications on ecosystems and human health. Emphasizing the essential role of bioindicators and biomarkers, this article elucidates their significance in evaluating heavy metal-induced environmental stressors and their impact on both biota and human populations. This comprehensive study contributes to a nuanced understanding of heavy metal dynamics, advocating for proactive measures in monitoring and mitigating their deleterious effects on ecosystems and human health.

The addition of a simple amide to AlCl(3) causes the formation of a liquid of the form [AlCl(2)·nAmide](+) AlCl(4)(-). The material thus produced is liquid over a wide temperature range, is relatively insensitive to water and has the properties of an ionic liquid. This ionic liquid is shown to be a suitable medium for the acetylation of ferrocene and the electrodeposition of aluminium and demonstrated that quaternary ammonium cations are not always needed to form ionic liquids.

In recent years, the underwater wireless sensor network (UWSN) has received a significant interest among research communities for several applications, such as disaster management, water quality prediction, environmental observance, underwater navigation, etc. The UWSN comprises a massive number of sensors placed in rivers and oceans for observing the underwater environment. However, the underwater sensors are restricted to energy and it is tedious to recharge/replace batteries, resulting in energy efficiency being a major challenge. Clustering and multi-hop routing protocols are considered energy-efficient solutions for UWSN. However, the cluster-based routing protocols for traditional wireless networks could not be feasible for UWSN owing to the underwater current, low bandwidth, high water pressure, propagation delay, and error probability. To resolve these issues and achieve energy efficiency in UWSN, this study focuses on designing the metaheuristics-based clustering with a routing protocol for UWSN, named MCR-UWSN. The goal of the MCR-UWSN technique is to elect an efficient set of cluster heads (CHs) and route to destination. The MCR-UWSN technique involves the designing of cultural emperor penguin optimizer-based clustering (CEPOC) techniques to construct clusters. Besides, the multi-hop routing technique, alongside the grasshopper optimization (MHR-GOA) technique, is derived using multiple input parameters. The performance of the MCR-UWSN technique was validated, and the results are inspected in terms of different measures. The experimental results highlighted an enhanced performance of the MCR-UWSN technique over the recent state-of-art techniques.

A Flying Ad-hoc network constitutes many sensor nodes with limited processing speed and storage capacity as they institute a minor battery-driven device with a limited quantity of energy. One of the primary roles of the sensor node is to store and transmit the collected information to the base station (BS). Thus, the life span of the network is the main criterion for the efficient design of the FANETS Network, as sensor nodes always have limited resources. In this paper, we present a methodology of an energy-efficient clustering algorithm for collecting and transmitting data based on the Optimized Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol. The selection of CH is grounded on the new optimized threshold function. In contrast, LEACH is a hierarchical routing protocol that randomly selects cluster head nodes in a loop and results in an increased cluster headcount, but also causes more rapid power consumption. Thus, we have to circumvent these limitations by improving the LEACH Protocol. Our proposed algorithm diminishes the energy usage for data transmission in the routing protocol, and the network’s lifetime is enhanced as it also maximizes the residual energy of nodes. The experimental results performed on MATLAB yield better performance than the existing LEACH and Centralized Low-Energy Adaptive Clustering Hierarchy Protocol in terms of energy efficiency per unit node and the packet delivery ratio with less energy utilization. In addition, the First Node Death (FND) is also meliorated when compared to the LEACH and LEACH-C protocols.

Global warming is one of the most compelling environmental threats today, as the rise in energy consumption and CO2 emission caused a dreadful impact on our environment. The data centers, computing devices, network equipment, etc., consume vast amounts of energy that the thermal power plants mainly generate. Primarily fossil fuels like coal and oils are used for energy generation in these power plants that induce various environmental problems such as global warming ozone layer depletion, which can even become the cause of premature deaths of living beings. The recent research trend has shifted towards optimizing energy consumption and green fields since the world recognized the importance of these concepts. This paper aims to conduct a complete systematic mapping analysis on the impact of high energy consumption in cloud data centers and its effect on the environment. To answer the research questions identified in this paper, one hundred nineteen primary studies published until February 2022 were considered and further categorized. Some new developments in green cloud computing and the taxonomy of various energy efficiency techniques used in data centers have also been discussed. It includes techniques like VM Virtualization and Consolidation, Power-aware, Bio-inspired methods, Thermal-management techniques, and an effort to evaluate the cloud data center’s role in reducing energy consumption and CO2 footprints. Most of the researchers proposed software level techniques as with these techniques, massive infrastructures are not required as compared with hardware techniques, and it is less prone to failure and faults. Also, we disclose some dominant problems and provide suggestions for future enhancements in green computing.

pH and hydrogen bond donor type in DESs affects the solubility of metal oxides and selectivity of dissolution.

Novel Coronavirus, COVID-19 discovered in December, 2019 in Wuhan, China started a world-wide epidemic. It is not clear till now what is the pathogenesis of this virus infection in human or the exact strategies of host immune response in combating this novel threat to human beings. However, morbidity and mortality of COVID-19 infections vary widely from asymptomatic, mild to deadly critical. Strangely, children were found to be protected from severe or deadly critical infections, while elderly and immunocompromised adults are most affected badly by this virus. It is necessary to disclose the possible viral and host interactions that lead to such variable morbid effects among patients of COVID-19 infections.

Modified starches have been developed for a very long time and it applications in food industry are reallysignificant nowadays. This paper will elaborate more about the definition and classifications of modified starchesby considering several modification techniques such as physical, chemical, and enzymatic treatment. Review onjournal’s papers of current decade has been done so as to observe the latest applications of modified starches inthe food industry. In order to organize the findings, they have been divided into several sub-groups according toits functional applications, as fat replacer/fat mimetic, as texture improver, for high nutritional claim, for highshear and temperature stability, and for flavor oil encapsulation. Examples on its recent applications of specificfoods products were also included. Hopefully this paper will assist anyone especially students who wants to getinformation about the latest applications of modified starch in the food industry.

The study and exploration of massive multiple-input multiple-output (MMIMO) and millimeter-wave wireless access technology has been spurred by a shortage of bandwidth in the wireless communication sector. Massive MIMO, which combines antennas at the transmitter and receiver, is a key enabler technology for next-generation networks to enable exceptional spectrum and energy efficiency with simple processing techniques. For massive MIMOs, the lower band microwave or millimeter-wave band and the antenna are impeccably combined with RF transceivers. As a result, the 5G wireless communication antenna differs from traditional antennas in many ways. A new concept of the MIMO tri-band hexagonal antenna array is being introduced for next-generation cellular networks. With a total scaling dimension of 150 × 75 mm2, the structure consists of multiple hexagonal fractal antenna components at different corners of the patch. The radiating patch resonates at 2.55–2.75, 3.45–3.7, and 5.65–6.05 GHz (FR1 band) for better return loss (S11) of more than 15 dB in all three operating bands. The coplanar waveguide (CPW) feeding technique and defective ground structure in the ground plane have been employed for effective impedance matching. The deviation of the main lobe of the radiation pattern is achieved using a two-element microstrip Taylor antenna array with series feeding, which also boosts the antenna array’s bandwidth and minimizes sidelobe. The proposed antenna is designed, simulated, and tested in far-field radiating conditions and generates tri-band S-parameters with sufficient separation and high-quality double-polarized radiation. The fabrication and testing of MIMO antennas were completed, where the measurement results matched the simulation results. In addition, the 5G smartphone antenna system requires a new, lightweight phased microwave antenna (μ-wave) with wide bandwidth and a fire extender. Because of its decent performance and compact architectures, the proposed smartphone antenna array architecture is a better entrant for upcoming 5G cellular implementations.

BACKGROUND: Petroleum polymers contribute to non-degradable waste materials and it would therefore be desirable to produce ecofriendly degradable materials. Biodegradation of polyhydroxybutyrate (PHB) in the presence of oligomer hydrolase and PHB depolymerase gave 3-hydroxybutyric acid which could be oxidized to acetyl acetate. Several bacteria and fungi can degrade PHB in the soil. RESULTS: Biodegradation of PHB showed a significant decrease in the molecular weight (Mw), number-average molecular weight (Mn) and the dispersity (Mw/Mn) for all the film formulations. Nanofibers of PHB and its composites showed faster degradation compared to other films and displayed complete degradation after 3 weeks. The SEM micrographs showed various surface morphology changes including alterations in appearance of pores, cavity, grooves, incisions, slots and pointers. Such changes were due to the growth of microorganisms that secreted PHB depolymerase enzyme which lead to the biopolymer films degradation. However, PHB nanofibers and its composites films in the presence of TiO2 demonstrated more surface changes with rupture of most nanofibers in which there was a drop in fibres diameter. CONCLUSIONS: The degradation of biopolymers help to overcome some of the pollution problems associated with the use of petroleum polymers. PHB nanofiber and its TiO2 composite were degraded faster compared to other PHB film types due to their three dimensional and high surface area structures. The presence of TiO2 nanoparticles in the composite films slowdown the degradation process compared to PHB films. Additionally, the PHB and its composite films that were prepared from UV treated PHB films led to acceleration of the degradation.Graphical abstractBiodegradation of polyhydroxybutyrate films in soil.

Mobile ad hoc networks (MANETs) are self-organizing nodes in a mobile network that collaborate to form dynamic network architecture to establish connections. In MANET, data must traverse several intermediary nodes before reaching its destination. There must be security in place to prevent hostile nodes from accessing this data. Multiple methods were suggested in literature for securing routing; these techniques tackle different aspects of security. In order to enhance fault tolerance, wireless network multipath routing is typically used instead of the original single path routing. The routing protocol Genetic Algorithm with Hill climbing (GAHC) described in this article shows a hybrid GA-Hill Climbing algorithm that picks the optimal route in multipath. Prior to this in the beginning, the Improved fuzzy C-means algorithm method was built on density peak, and cluster heads (CHs) were chosen in a predicted manner, based on recent, indirect, and direct trust. The computation is based worth nodes are at the trust threshold found in addition. Even CHs take part in the alternate paths, the blend of all the many paths from these Cluster Heads that chooses the optimal route, which is based on the predicted hybrid protocol, as well as the optimum route’s aggregate features such as throughput, latency, and connection. This suggested technique requires a minimum amount of energy of 0.10 m joules and a small amount of delay time of 0.004 msec, which also yields a maximum throughput of 0.85 bits per second, a maximum detection rate of 91 percent and maximum packet delivery ratio of 89percent. The suggested approach was put through the paces with the selective packet dropping attack.

Industry 4.0 is a set of technologies that companies require to promote innovation strategies and obtain a rapid response in dynamic markets. It focuses mainly on interconnectivity, digital technology, predictive analytics and machine learning to revolutionize the way companies operate and develop. Therefore, this article proposes and motivates the implementation of Industry 4.0 in organizations. Studying the state of the art and reviewing the current situation of business intelligence (BI) technology, the way it has positively impacted organizations at the economic and business level in terms of decision-making and some success stories implemented in different business, academic, social and governmental environments. Moreover, it addresses the future expected for Industry 4.0 primarily in BI and how companies should face this revolution. This article provides knowledge contribution about the current state and positive consequences of Industry 4.0, and high development in technology when implemented in the organization and the harmonization between production and intelligent digital technology.