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Machine-to-machine (M2M) communication and the Internet of Things (IoT) are witnessing significant advancements in rapidly expanding technical paradigms, notably catalysed by the introduction of 5G networks. This article investigates the synergistic interaction between M2M and 5G infrastructures, revealing how 5G's unique characteristics — namely, high data throughput, low latency, and ubiquitous connectivity — stand poised to accelerate the maturity of the IoT ecosystem. The article provides detailed insights into the inherent potential of 5G by combining qualitative and quantitative research approaches. Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communication (URLLC), and Massive Machine Type Communication (mMTC) are a few examples. Such capabilities are rigorously examined within the context of M2M communication to highlight their pivotal significance in the advancement of IoT. This relates to improving operating efficiency, increasing dependability, and promoting automation across a wide range of industries, including healthcare, manufacturing, and the creation of intelligent urban settings. The article also addresses the hurdles and barriers encountered in integrating 5G with M2M, such as security concerns, interoperability problems, and legal limits. Furthermore, it explores possible solutions and future trends in this domain, outlining potential technology developments that might further optimise M2M interactions. This article seeks to serve as a key resource for policymakers, industry stakeholders, and academics interested in the future of connected technologies by thoroughly understanding the revolutionary effect of 5G on M2M and, by extension, the IoT.

Traditional computers have had difficulties in making advancements in areas such as optimisation, cryptography, and network design because they are not capable of effectively solving computationally complex problems, which are referred to as NP-hard problems. Quantum computing utilises the principles of quantum physics to solve problems with exceptional efficiency, making it a groundbreaking paradigm. The study explores the capabilities of quantum algorithms in addressing NP-hard issues and evaluates their strengths and constraints. We demonstrate how breakthroughs such as Grover's and Shor's algorithms may provide exponential and polynomial enhancements in certain situations. We do a comprehensive analysis of the current state of quantum algorithms and evaluate their strengths and weaknesses. We analyse recent progress in hardware innovation and error correction techniques to evaluate their potential in overcoming the obstacles of restricted scalability and high error rates that now impede their use. The article highlights the vast capabilities of quantum computing in tackling NP-hard problems. Notable obstacles that still exist include restrictions imposed by hardware, the lack of a universally accepted programming language, and the need for reliable error correction methods. Ultimately, it is more important to fully comprehend the capabilities and constraints of quantum computing in addressing NP-hard issues, especially as its actual use becomes more imminent. This study is a thorough manual that gives a detailed examination of state-of-the-art algorithms and explores the challenges involved in achieving a new age of computing capacity. Once these problems are addressed and there is a strong impetus for further exploration, quantum computing will fundamentally transform our approach to computationally intractable challenges in the future.

Background: In recent years, Big Data has invaded many technical sectors, enabling extraordinary advances, notably in robotics. Large amounts of data from many areas may improve robotic system functionality and adaptability. Objective: This article examines Big Data's effects on robotic learning, decision-making, and adaptability to help explain how it advances robotic capabilities and provide a thorough review of integrated data-driven robotic systems. Methods: A thorough evaluation and synthesis of the literature was undertaken to examine the integration and implementation of Big Data in robotics. Case studies, and theoretical frameworks on Big Data analytics and robotics were sought from databases and academic publications. Results: Big Data analytics in robots improves learning in predictive analytics and machine learning algorithms, improving decision-making. Industrial robots and autonomous vehicles boost operational efficiency and flexibility by improving data processing, anomaly detection, and real-time decision-making. Conclusion: Technology such as Big Data and robotics makes robots more adaptive and decision-making. Integration improves robotic capabilities and allows for innovative applications across domains, supporting data-driven robotic ability and improvement decisions. The findings propose using Big Data analytics to improve robotics and study future applications, contributing to the conversation on technological convergences and societal implications.

Background: Robotic assistants have progressed from essential, repetitive duties to sophisticated interactions requiring cognitive talents as technology advances. The interaction of Natural Language Processing (NLP) with Artificial Intelligence (AI) has become critical; consequently, establishing advanced robotic capabilities requires a more comprehensive and integrated approach. Objective: This article aims to explain how integrating NLP and AI into robotic assistants improves functionality, HRI, and applicability in various practical domains without focusing on ethics. Methods: NLP, AI, robotic assistant literature and case studies were reviewed and meta-analyzed. Quantitative investigations using tests and simulations examined robotic assistants' technical advancements and efficacy using sophisticated NLP and AI technologies. Results: Advanced NLP and AI integration improved robotic assistant comprehension, context-aware discussions, and autonomous decision-making. Improved HRI and capacity to complete complex jobs and make independent judgments in healthcare, manufacturing, and customer service. Conclusion: Combining NLP with AI allows robotic assistants to do more complicated, contextually aware activities, expanding their usefulness across many disciplines. While acknowledging the many advances, continual study and investigation are essential to navigate robotic helper technology and its many uses.

This study is intended to examine the deceptive strategies utilized in the well-renown Agatha Christie's (1926/2002) detective fiction "The Murder of Roger Ackroyd" to fill a gap in the literature by conducting a pragma-stylistic analysis of the novel. To do so, the researchers have set two objectives which are phrased as follows: firstly, examining the pragma-stylistic choices that are used to surface the deceptive strategies on the character-character level in the pre-dénouement stage and secondly, investigating the pragma-stylistic choices that are used to surface the deceptive strategies on the narrator-reader level in the pre-dénouement stage. The stylistic idiosyncrasies of Christie's Dr. Sheppard are carried out through an eclectic pragma-stylistic approach to expose his deceptive strategies for the fulfillment of his selfish ends. Therefore, the study at issue follows an eclectic conceptual framework which comprises Merzah and Abbas's deceptive principle (2020) and Chen's (2001) self-politeness, along with the stylistic effects achieved via the manipulation of such linguistic tools, to explore the two levels of discourse, namely, character-character level and narrator-reader level proposed by Black (2006). The qualitative analysis of the novel has exhibited that Dr. Sheppard is an expert deceiver who principally relies on indirect strategies, as he is cognizant of the power of what is insinuated but left unsaid.

Background/Objectives: Infective prosthesis endocarditis (IE) following transcatheter aortic valve implantation (TAVI) presents significant management challenges, marked by high mortality rates. This study reviews our center’s experience with surgical interventions for IE in patients post-TAVI, focusing on outcomes, challenges, and procedural complexities, and providing an overview of the limited literature surrounding this subject. Methods: This study was executed as a comprehensive retrospective analysis, targeting the clinical outcomes of surgical treatment in patients presenting with PVE following TAVI procedures at our institution. From July 2017 to July 2022, we identified five patients who had previously undergone transfemoral transcatheter aortic valve implantation and were later diagnosed with PVE needing surgery, strictly adhering to the modified Duke criteria. Results: All surgical procedures were reported successful with no intra- or postoperative mortality. Patients were predominantly male (80%), with an average age of 76 ± 8.6 years, presenting mostly with dyspnea (NYHA Class II). The mean follow-up was between 121 and 1973 days, with outcomes showing no occurrences of stroke, myocardial infarction, or major bleeding. One patient expired from unrelated causes 3.7 years post-surgery. The operative and postoperative protocols demonstrated effective disease management with enhanced survival and minimal complications. Conclusions: The surgical treatment of IE following TAVI, though challenging, can be successfully achieved with careful patient selection and a multidisciplinary approach. The favorable outcomes suggest that surgical intervention remains a viable option for managing this high-risk patient group. Our study also highlights the scarce literature available on this topic, suggesting an urgent need for more comprehensive research to enhance understanding and improve treatment strategies. Future studies with larger cohorts are needed to further validate these findings and refine surgical strategies for this growing patient population.

Background: The cranial base has a substantial role in determining how the maxilla and mandible are related to each other and its growth influences the maxillo-mandibular growth. Aim: The main aim of this study was to evaluate and assess the relationship of the saddle angle (NSAr) with different patterns of the sagittal interarch skeletal relationship for the Iraqi population and detect the effect of gender on it. Materials and Methods: The samples included 125 true lateral cephalometric radiographs for Iraqi patients of both genders (male and female) between the age of 18–25 years obtained from the clinic’s archives of the Orthodontic Department at the Dentistry Teaching Hospital of the Faculty of Dentistry, Baghdad University, Iraq, who was looking for orthodontic therapy. The samples were divided according to the value of ANB angle into skeletal Cl I (33 females and 14 males), skeletal Cl II (27 females, 14 males), and skeletal Cl III (17 females and 20 males) groups, then the saddle angle were digitized and recorded using AutoCAD 2012 computer program, the data then analyzed by SPSS version 24 (2016) computerized statistical analysis. Results: The results clarified that the mean value of saddle angle was smaller in the skeletal Cl III group for both genders, with females showed the smallest value with no significant difference, and the larger value of saddle angle was in the skeletal Cl II group for both genders with females showed the largest value with no significant difference. Conclusion: The sagittal skeletal relationship tends to alter from skeletal Cl III to Cl II with progressive flattening of the cranial base and vice-versa. The effect of gender on saddle angle was more than that of sagittal skeletal classes.

BackgroundVenous thrombosis (VT) is multifactorial trait that contributes to the global burden of cardiovascular diseases. Although abundant single nucleotide polymorphisms (SNPs) provoke the susceptibility of an individual to VT, research has found that the five most strongly associated SNPs, namely, rs6025 (F5 Leiden), rs2066865 (FGG), rs2036914 (F11), rs8176719 (ABO), and rs1799963 (F2), play the greatest role. Association and risk prediction models are rarely established by using merely the five strongly associated SNPs. This study aims to explore the combined VT risk predictability of the five SNPs and well-known non-genetic VT risk factors such as aging and obesity in the Hungarian population.MethodsSNPs were genotyped in the VT group (n = 298) and control group (n = 400). Associations were established using standard genetic models. Genetic risk scores (GRS) [unweighted GRS (unGRS), weighted GRS (wGRS)] were also computed. Correspondingly, the areas under the receiver operating characteristic curves (AUCs) for genetic and non-genetic risk factors were estimated to explore their VT risk predictability in the study population.Resultsrs6025 was the most prevalent VT risk allele in the Hungarian population. Its risk allele frequency was 3.52-fold higher in the VT group than that in the control group [adjusted odds ratio (AOR) = 3.52, 95% CI: 2.50–4.95]. Using all genetic models, we found that rs6025 and rs2036914 remained significantly associated with VT risk after multiple correction testing was performed. However, rs8176719 remained statistically significant only in the multiplicative (AOR = 1.33, 95% CI: 1.07–1.64) and genotypic models (AOR = 1.77, 95% CI: 1.14–2.73). In addition, rs2066865 lost its significant association with VT risk after multiple correction testing was performed. Conversely, the prothrombin mutation (rs1799963) did not show any significant association. The AUC of Leiden mutation (rs6025) showed better discriminative accuracy than that of other SNPs (AUC = 0.62, 95% CI: 0.57–0.66). The wGRS was a better predictor for VT than the unGRS (AUC = 0.67 vs. 0.65). Furthermore, combining genetic and non-genetic VT risk factors significantly increased the AUC to 0.89 with statistically significant differences (Z = 3.924, p

Background: COVID-19 accounts for more than half a billion deaths globally. The clinical manifestations may vary in due course. Despite several studies aimed at determining the extent to which the disease's severity and mortality remain high when combined with other comorbidities, more research is required. Therefore, this review aimed to measure the pooled prevalence of coronary artery disease (CAD) among COVID-19 patients, specifically those with a history of CAD. Additionally, we aim to assess the association between mortality due to CAD and the severity of COVID-19 among hospitalized patients. Method: A comprehensive search in PubMed, Web of Science, the Cochrane Library, and the WHO COVID-19 database was conducted. English studies with original data on CAD, mortality, and ARDS among COVID-19 patients were included. PRISMA guidelines were followed. Results: Among the 2007 identified articles, 76 studies met the inclusion criteria. The pooled prevalence of CAD among COVID-19 patients was 14.4%(95% CI: 12.7–16.2). The highest prevalence was observed in European studies at 18.2%(95% CI: 13.3–24.2), while the lowest was in Asian studies at 10.4% (95% CI: 6.4–16.3). Participants with concurrent CAD at the time of hospital admission had twice the odds of mortality due to COVID-19 (2.64 [95% CI: 2.30–3.04]) with moderate heterogeneity (I2 = 45%, p

Objective This study was aimed to determine the relationship between job stress and work-related quality of life (WRQoL) among emergency medical technicians (EMTs) in Lorestan province, Western Iran.Design This was a cross-sectional study.Methods Totally 430 EMTs who had been engaged in their respective units for more than 6 months from all emergency facilities in Lorestan province were selected using single stage cluster sampling method. Data were collected from April to July 2019 using two standard questionnaires: job stress (Health and Safety Executive (HSE)) and WRQoL. The OR with 95% CI was used to declare the statistical association (p≤0.05).Results All participants were exclusively males, with a mean age of 32±6.87 years. The overall average score of job stress using the HSE scale was 2.69±0.43; while the overall quality of working life score was 2.48±1.01. The type of working shift was found to have a significant impact on the HSE-average score (F(3,417)=5.26, p=0.01); and on the WRQoL-average score (F(3,417)=6.89, p

Reproductive traits are affected by many factors, including ovarian function, hormones, and genetics. Genetic polymorphisms of candidate genes are associated with reproductive traits. Several candidate genes are associated with economic traits, including the follistatin ( FST ) gene. Thus, this study aimed to evaluate whether the genetic variations in the FST gene are associated with the reproductive traits in Awassi ewes. The genomic DNA was extracted from 109 twin ewes and 123 single-progeny ewes. Therefore, 4 sequence fragments from the FST gene were amplified using polymerase chain reaction (PCR) (exon 2/240, exon 3/268, exon 4/254, and exon 5/266 bp, respectively). For a 254 bp amplicon, 3 genotypes were identified: CC, CG, and GG. Sequencing revealed a novel mutation in CG genotypes c.100C > G. The statistical analysis of c.100C > G showed an association with reproductive characteristics. Ewes carrying the c.100C > G had significantly ( P ⩽ .01) lower litter sizes, twinning rates, lambing rates, and more days to lambing compared with CG and CC genotypes. Logistic regression analysis confirmed that the c.100C > G single-nucleotide polymorphism (SNP) is responsible for decreasing litter size. According to these results, the variant c.100C > G negatively affects the traits of interest and is associated with lower reproductive traits in Awassi sheep. As a result of this study, ewes carrying the c.100C > G SNP have lower litter size and are less prolific.

The aim of this paper is to investigate the performance of a hydraulic system using an equi-volume percentage of vegetable oil and mineral oil as hydraulic fluids. The hydraulic system performance was tested at different operating conditions, such as temperature and velocity. A test rig with a definite pipe length and diameter was used. The experimental results showed that the presence of vegetable oil reduced the viscosity by 21, 18, 11, and 8% at 30, 40, 50, and 60 °C, respectively. The pressure drop (ΔP) through the hydraulic circuit was improved. The reason may be attributed to a reduction in viscosity. At 6 L/min and 60 °C, the maximum percentage of drag reduction (%Dr) was around 29%, while the maximum percentage of flow improvement (%FI) was around 21%. Statistical analysis was used to correlate %Dr as a function of dimensionless groups with a high correlation coefficient. Numerical analysis was conducted using ANSYS software. Experimental and numerical results were very close with high validity. A numerical model was used to study the effect of pipe geometry. Pressure drop was increased with pipe length and inclination angle, but it decreased with pipe diameter. In the literature, the experimental and numerical performance of hydraulic systems using a blend of vegetable and mineral oils as hydraulic fluid was limited. Therefore, the current study is quite new for the hydraulic system performance at different operating conditions.

Background: The management of patients with aortic valve pathologies can sometimes fall into a "gray zone", where the optimal treatment approach is not straightforward. The comparative benefits of sutureless aortic valve replacement (SUAVR) using the Perceval bioprosthesis versus transcatheter aortic valve implantation (TAVI) for the "gray zone" of aortic valve replacement procedures remain a topic of debate. To further explore this issue, we conducted a study with pairwise, single-arm, and Kaplan–Meier-based meta-analyses to compare the outcomes of SUAVR with the Perceval bioprosthesis versus TAVI, as well as to evaluate the efficacy, safety, and durability of SUAVR with the Perceval bioprosthesis over mid-term and long-term follow-up periods. Methods: The PubMed, PubMed Central, OVID Medline, Cochrane Library, Embase, and Web of Science databases were systematically searched. All study types were included, except study protocols and animal studies, without time restrictions. The final search was carried out in May 2024. Results: No statistically significant differences were observed in permanent pacemaker implantation (PPI) rates between the two groups. SUAVR showed a lower incidence of new-onset myocardial infarction but was associated with higher rates of new-onset atrial fibrillation and major bleeding. TAVI had higher rates of left bundle branch block and major vascular complications. Conclusions: Our findings show that SUAVR has a lower incidence of complications and a favorable mid-term overall survival compared to TAVI. SUAVR has more advantages compared to TAVI and can be considered a valuable and promising option for the "grey zone" of aortic valve pathologies. [ABSTRACT FROM AUTHOR]

Land Use / Land Cover (LULC) classification is considered one of the basic tasks that decision makers and map makers rely on to evaluate the infrastructure, using different types of satellite data, despite the large spectral difference or overlap in the spectra in the same land cover in addition to the problem of aberration and the degree of inclination of the images that may be negatively affect rating performance. The main objective of this study is to develop a working method for classifying the land cover using high-resolution satellite images using object based method. Maximum likelihood pixel based supervised as well as object approaches were examined on QuickBird satellite image in Karbala, Iraq. This study illustrated that use of textural data during the object image classification approach can considerably enhance land use classification performance. Moreover, the results showed higher overall accuracy (86.02%) in the o object based method than pixel based (79.06%) in urban extractions. The object based performed much more capabilities than pixel based.

Background: Interactions between genetic and environmental risk factors (GxE) contribute to an increased risk of venous thromboembolism (VTE). Understanding how these factors interact provides insight for the early identification of at-risk groups within a population and creates an opportunity to apply appropriate preventive and curative measures.Objective: To estimate and compare GxE for VTE risk in the general Hungarian and Roma populations.Methods: The study was based on data extracted from a database consisting of results previously obtained from a complex health survey with three pillars (questionnaire-based, physical, and laboratory examinations) involving 406 general Hungarian and 395 Roma subjects. DNA was genotyped for rs121909567 (SERPINC1), rs1799963 (F2), rs2036914 (F11), rs2066865 (FGG), rs6025 (F5), and rs8176719 (ABO) polymorphisms. After allele frequency comparisons, the odds ratio (OR) was calculated for individual SNPs. Furthermore, genetic risk scores (weighted GRS, unweighted GRS) were computed to estimate the joint effect of the genetic factors. Multivariable linear regression analysis was applied to test the impact of GxE on VTE risk after interaction terms were created between genetic and VTE risk factors [diabetes mellitus (DM), cancer, chronic kidney diseases (CKD), coronary artery diseases (CAD), migraine, depression, obesity, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high density lipoprotein (HDL-C), triglyceride (TG), and smoking].Results: Interestingly, the rs121909567 (SERPINC1, ATBp3 mutation) SNP was not present in the general population at all. However, the risk allele frequency was 1% among the Roma population, which might suggest a founder effect in this minority. This polymorphism multiplicatively interacted with CAD, CKD, cancer, DM, depression, migraine, and obesity. Even though interactions were not statistically significant, the trend of interaction showed the probability of an incremental VTE risk among the Roma population. The risk of VTE was 4.7 times higher (p > 0.05) for Roma subjects who had ≥3 wGRS (median value) compared with individuals having lower wGRS values but lower for the general subjects (OR = 3.1 × 10−8). Additionally, the risk of VTE was 6.6 times higher in the Roma population that had ≥3 risk alleles (median value) than in individuals with the 0–1 risk allele, and the overall risk was much higher for the Roma population (OR = 6.6; p > 0.05) than for the general Hungarian population (OR = 1.5; p > 0.05). Five positive and significant GxE interactions were identified in the Roma population. The risk of VTE was higher among depressive Roma subjects who carried the risk variant rs2036914 (β = 0.819, p = 0.02); however, this interaction was not significant for the general subjects. The joint presence of high levels of LDL-C and rs2066865 (FGG) increased the VTE risk only among Roma individuals (β = 0.389, p = 0.002). The possibility of VTE risk increment, as a result of a multiplicative interaction between rs8176719 (ABO) and cancer, was identified, which was higher for the Roma population (β = 0.370, p < 0.001) than for the general population (β = −0.042, p = 0.6). The VTE risk increased in the Roma population (β = 0.280, p = 0.001), but was higher in the general population (β = 0.423, p = 0.001) as a result of the multiplicative interaction between CAD and rs2036914 (F11). The presence of a multiplicative interaction between rs2066865 (FGG) and CAD increased the VTE risk for the Roma population (β = 0.143, p = 0.046) but not for the general population (β = −0.329, p < 0.001).Conclusions: rs121909567 (SERPINC1, ATBp3) was confirmed as a founder mutation in the Roma population. Our study revealed some evidence on the burden of the joint presence of genetic and environmental risk factors on VTE, although the finding is highly subjected to the selection and observational biases due to the very small number of VTE cases and the observational nature of the study design, respectively. As a result of higher genetic load and GxE interactions, this minority Roma population is at higher risk of VTE than the general Hungarian population. Thus, our results suggest the need for an intensive search for the rs121909567 (SERPINC1; ATBp3) founder mutation, which might be an important factor for the assessment of thrombotic disease susceptibility among the Roma population. In addition, we strongly recommend further studies among a large number of VTE cases to explore the more precise impact of genetic and environmental risk factors on VTE in the study populations.

Background/Objectives: Infective prosthesis endocarditis (IE) following transcatheter aortic valve implantation (TAVI) presents significant management challenges, marked by high mortality rates. This study reviews our center's experience with surgical interventions for IE in patients post-TAVI, focusing on outcomes, challenges, and procedural complexities, and providing an overview of the limited literature surrounding this subject. Methods: This study was executed as a comprehensive retrospective analysis, targeting the clinical outcomes of surgical treatment in patients presenting with PVE following TAVI procedures at our institution. From July 2017 to July 2022, we identified five patients who had previously undergone transfemoral transcatheter aortic valve implantation and were later diagnosed with PVE needing surgery, strictly adhering to the modified Duke criteria. Results: All surgical procedures were reported successful with no intra- or postoperative mortality. Patients were predominantly male (80%), with an average age of 76 ± 8.6 years, presenting mostly with dyspnea (NYHA Class II). The mean follow-up was between 121 and 1973 days, with outcomes showing no occurrences of stroke, myocardial infarction, or major bleeding. One patient expired from unrelated causes 3.7 years post-surgery. The operative and postoperative protocols demonstrated effective disease management with enhanced survival and minimal complications. Conclusions: The surgical treatment of IE following TAVI, though challenging, can be successfully achieved with careful patient selection and a multidisciplinary approach. The favorable outcomes suggest that surgical intervention remains a viable option for managing this high-risk patient group. Our study also highlights the scarce literature available on this topic, suggesting an urgent need for more comprehensive research to enhance understanding and improve treatment strategies. Future studies with larger cohorts are needed to further validate these findings and refine surgical strategies for this growing patient population. [ABSTRACT FROM AUTHOR]

Orwell's (1945/2013) Animal Farm is a rich source of manipulative discourses, especially as embodied in the character Squealer, who masterfully exploits the peripheral entities. Despite its critical and widespread acclaim, the systematic exploration of specific pragma-stylistic strategies that Orwell uses to depict manipulation and propaganda are understudied in the literature. Utilizing an eclectic theoretical framework incorporating Johnson's (2000) manifest rationality theory and the deceptive principle posited by Merzah and Abbas (2020), this study performs a qualitative intra-analysis to unearth the distinct employment of a myriad of fallacies, such as scapegoating, ad nauseam, false dilemma, domino fallacy, historical negationism, and ad ignorantiam. This research aims to explore manipulative rhetoric from the viewpoint of pragma-stylistics. The significance of this research lies in its potential to deepen our understanding of rhetorical strategies in allegorical literature, offering insights into how language can be used to manipulate and influence. This study addresses the central question: How do specific pragma-stylistic strategies enable characters in Animal Farm to manipulate and propagate fallacies, and what implications does this have for understanding similar manipulative techniques in political discourse? The findings suggest a contrast between Squealer's and Napoleon's manipulative strategies: Napoleon, akin to the uncharismatic communication style of Stalin, leverages scapegoating to undermine his adversaries, while Squealer, Napoleon's rhetorical extension, focuses on distorting historical events, exaggerating consequences, and perpetuating falsehoods. [ABSTRACT FROM AUTHOR]

Photovoltaic systems, a clean and renewable energy source, face challenges in optimizing efficiency due to temperature-induced performance loss. This research explores passive cooling strategies using phase change materials, which collect excess heat during peak solar irradiance, store it, and release it during less sunshine or high temperatures. This method efficiently controls panel temperature, enhancing performance and extending lifetime. The choice of cooling technique should be based on the specific requirements and constraints of the photovoltaic system. Solar panels receive 780 W/m2 of incoming solar radiation in summer and peak at noon. Convective heat transfer and air temperature of 25 degrees Celsius allow heat to escape. The stiff material, aluminum fins, and PCM have specific heat of 2000 J/kg.K and thermal conductivity of 0.2 W/m.K, respectively. Temperature distribution reveals significant reduction in surface temperatures with increasing Al2O3 concentrations. The best case was at 0.5wt%, achieving 49.896℃. Electrical efficiency increases with concentration. The distribution of temperatures at different CuO concentrations reveals lower surface temperatures due to increasing concentrations. The optimal concentration was 0.5 wt percent, where temperatures fell to 49.870℃. Increasing electrical efficiency is crucial for temperature improvement, with a peak at 9.26% at 0.5 weight percent mm. Temperature distribution decreases with ZnO concentration, with optimal 0.5wt% concentration, enhancing electrical efficiency with increasing concentrations. [ABSTRACT FROM AUTHOR]

The opportunity of teaching engineers is not easy as everybody thinks for many reasons, some of these issues are related to the students' disappointment as a result of getting the engineering field and the other one related to lack of available knowledge about the role of engineers in improving and developing the life quality and the country overall. So, this paper will focus the light on the main issues and challenges that face the engineering education, with the possible solutions in order to reduce the unemployment and expelled from the job due to the lack of experience or lack the communications with other team members. Also, this paper explains how and when could apply each solution separately.