Ensuring data integrity in deep learning-assisted IoT-Cloud environments: Blockchain-assisted data edge verification with consensus algorithms

Ensuring the reliability and trustworthiness of massive IoT-generated data processed in cloud-based systems is paramount for data integrity in IoT-Cloud platforms. The integration of Blockchain (BC) technology, particularly through BC-assisted data Edge Verification combined with a consensus system, utilizes BC's decentralized and immutable nature to secure data at the IoT network's edge. BC has garnered attention across diverse domains like smart agriculture, intellectual property, and finance, where its security features complement technologies such as SDN, AI, and IoT. The choice of a consensus algorithm in BC plays a crucial role and significantly impacts the overall effectiveness of BC solutions, with considerations including PBFT, PoW, PoS, and Ripple in recent years. In this study, I developed a Football Game Algorithm with Deep learning-based Data Edge Verification with a Consensus Approach (FGADL-DEVCA) for BC assisted IoT-cloud platforms. The major drive of the FGADL-DEVCA algorithm was to incorporate BC technology to enable security in the IoT cloud environment, and the DL model could be applied for fault detection efficiently. In the FGADL-DEVCA technique, the IoT devices encompassed considerable decentralized decision-making abilities for reaching an agreement based on the performance of the intrablock transactions. Besides, the FGADL-DEVCA technique exploited deep autoencoder (DAE) for the recognition and classification of faults in the IoT-cloud platform. To boost the fault detection performance of the DAE approach, the FGADL-DEVCA technique applied FGA-based hyperparameter tuning. The experimental result analysis of the FGADL-DEVCA technique was performed concerning distinct metrics. The experimental values demonstrated the betterment of the FGADL-DEVCA approach with other existing methods concerning various aspects

Prospects of Hybrid Energy in Saudi Arabia, Exploring Irrigation Application in Shaqra

Dynamics in rainfall patterns due to climate change are posing a threat to crop production globally. The core issue of food security is expected to intensify, and improving crop yield using motorized power irrigation mechanisms can help in curtailing the impact of drought and changing weather patterns to meet the crop water requirement. To meet the energy demand of irrigation systems, this paper explores the use of hybrid energy sources, i.e., wind and solar energy, taking Shaqra Saudi Arabia as case study. This paper presents a systematic case study that evaluates crop water requirements for 3 different crops using the United Nations Food and Agriculture Organization’s software CROPWAT 8.0 and converts the water requirement into energy demand to design the water pumping system. The energy requirement water pumping system is used to design a hybrid energy system using HOMER PRO 3.14.4 that can reliably meet the energy demand. The results suggests that, contrary to the common consideration in Saudi Arabia, a hybrid of wind and solar energy proves to be more cost effective and yields a higher amount of energy. The results suggest that a significant reduction in cost can be achieved with a hybrid energy system as compared to a solar PV system only

The Efficiency of Wastewater Treatment Plants for the Removal of Antibiotics

Undoubtedly domestic Wastewater Treatment Plants (WWTPs) are not designed for the removal of some pollutants such as antibiotics. This chapter summarizes the occurrence and fate of six groups of the most widely used antibiotics (β-lactams, sulfonamides, quinolones, tetracyclines, macrolides, and others) in domestic WWTPs. The literature showed that the six groups of antibiotics have been frequently detected during wastewater treatment train (influent, primary treatment, secondary treatment, tertiary treatment, effluent, and sludge treatment) of domestic WWTPs. Also, it was clear that the main removal routes of antibiotics during sewage treatment of domestic WWTPs were adsorption, biodegradation, membrane filtration, and disinfection. Domestic WWTPs cannot remove most of the antibiotics which finally enter the environment through treated effluent and sludge

Enhanced Recovery After Surgery (ERAS) and the Role of Advanced Hemodynamic Monitoring

This study aimed at exploring the Enhanced Recovery After Surgery (ERAS) as a multi-modality, evidence-based approach to improving the quality of patient care after major surgery and to investigate the effectiveness of the implementation of the ERAS on the outcome measures. Therefore, the problem of this study lies in exploring the Enhanced Recovery After Surgery (ERAS) upon the role of advanced hemodynamic monitoring through examining a sample of (220) patients in two Jordanian hospitals (Jordan Hospital and the Specialty Hospital) undergoing major surgery. The study concluded that the patients had witnessed progressive outcome measures in the Improved Post-operative Morbidity Score (POMS), and the Reduced Length of Stay in Hospital, and the Reduced episodes of harm and surgical complications

Techno-Economic and Environmental Impact Analysis of Large-Scale Wind Farms Integration in Weak Transmission Grid from Mid-Career Repowering Perspective

Repowering a wind farm enhances its ability to generate electricity, allowing it to better utilize areas with high mean wind speeds. Pakistan’s present energy dilemma is a serious impediment to its economic development. The usage of a diesel generator as a dependable backup power source raises the cost of energy per kWh and increases environmental emissions. To minimize environmental emissions, grid-connected wind farms enhance the percentage of wind energy in the electricity system. These wind generators’ effects, on the other hand, are augmented by the absorption of greater quantities of reactive electricity from the grid. According to respective grid codes, integration of commercial onshore Large-Scale Wind Farms (LSWF) into a national grid is fraught with technical problems and inter-farm wake effects, which primarily ensure power quality while degrading overall system operation and limiting the optimal use of attainable wind resources. The goal of this study is to examine and estimate the techno-economic influence of large-scale wind farms linked to poor transmission systems in Pakistan, contemplating the inter-farm wake effect and reactive power diminution and compensating using a range of voltage-ampere reactive (VAR) devices. This study presents a partial repowering technique to address active power deficits produced by the wake effect by raising hub height by 20 m, which contributed to recovering the active power deficit to 48% and so reduced the effects of upstream wind farms. Simulations were conducted for several scenarios on an actual test system modeled in MATLAB for comparative study using capacitor banks and different flexible alternating current transmission system (FACTS) devices. Using the SAM (System Advisor Model) and RETscreen, a complete technical, economic, and environmental study was done based on energy fed into the grid, payback time, net present value (NPV), and greenhouse gases (GHG) emission reduction. The studies suggest that the unified power flow controller (UPFC) is the optimum compensating device via comparison analysis as it improved the power handling capabilities of the power system. Our best-case scenario includes UPFC with hub height augmentation, demonstrating that it is technically, fiscally, and environmentally viable. Over the course of its lifespan, the planned system has the potential to save 1,011,957 tCO2, resulting in a greener environment. When the energy generated annually by a current wake-affected system is compared to our best-recommended scenario, a recovered shortfall of 4.851% is seen, with improved system stability. This modest investment in repowering boosts energy production due to wake effects, resulting in increased NPV, revenue, and fewer CO2 footprints

Which level of preoperative glycated haemoglobin (HbA1c) affect early morbidity and mortality after cardiac surgery?

BackgroundDiabetics account for 34 per cent of all patients undergoing coronary artery bypass graft (CABG) surgery, and have higher rates of postoperative mortality. Furthermore, they are at risk for ICU admission postoperatively due to complications of hyperglycaemia, which in turn increases hospital mortality.AimsThe purpose of this study was to evaluate the level of glycated haemoglobin (HbA1c) in patients undergoing cardiac surgery, and to establish it is an independent predictor for postoperative mortality and morbidity.Methods This retrospective study was conducted at King Fahd University Hospital. Files of 146 diabetic patients who underwent cardiac surgery in the period between September 2015 to June 2018 were included. One hundred and five patients met the inclusion criteria. Depending on the results of HbA1c preoperatively, patients were divided into 2 groups: Group A, with a HbA1c > =8.5 per cent, accounting for 33 patients, and Group B with a HbA1c < =8.4 per cent accounting for 71 patients.Results This study included 79 males and 25 females, with ages ranging in between 17 to 87 years old, with no significant difference between both groups in age and sex. A significant difference was found between Group A and Group B in postoperative mortality (p-value < 0.002). No significant difference was found when comparing length of hospital stay, wound infection postoperatively, reoperation, or readmission.ConclusionThere was a significant difference in mortality postoperativly between the two groups, with patients who had higher HbA1c levels experiencing higher mortality. Since our sample size was small, we recommend that further studies be done in multiple centres

Association of high immunohistochemical expression of minichromosome maintenance 3 with human oral squamous cell carcinoma—a preliminary study

Background: Oral squamous cell carcinoma (OSCC) may arise from premalignant oral lesions (PMOL) in most cases. Minichromosome maintenance 3 (MCM3) is a proliferative marker that has been investigated as a potential diagnostic biomarker in the diagnosis of oral cancer. Objectives: To evaluate the association of MCM3 expression, its clinicopathologic parameters and to identify snuff (also called naswar) as a potential risk factor for changes in MCM3 expression in PMOL and OSCC. Methodology: Immunohistochemistry (IHC) of MCM3 was performed on 32 PMOL, 32 OSCC and 16 normal controls after optimization of IHC methodology. Histoscore (0–300) was used as a scoring system and seven different cut-offs were identified for analyses. Data were analyzed using various statistical tests. Results: Among the seven cutoffs, 40% strong positive cells were found to be a better cut-off as they were associated with many pathological variables (Broder’s grade, Aneroth’s grade, and mitotic activity). The differential MCM3 expression in oral lesions (PMOL and OSCC) was statistically significant (p = 0.03). Moreover, MCM3 expression is raised with increased duration and frequency of snuff use. Conclusion: High MCM3 expression is associated with disease progression and is a potential indicator of malignant transformations from PMOL to OSCC. Moreover, the use of snuff is associated with MCM3 over-expression

Chlorhexidine versus Povidone-Iodine for the prevention of ‎Surgical Site ‎Infections: A review.‎

BackgroundSurgical Site Infections (SSIs) are the third most frequently reported health care-associated ‎infection‎ and it remain a major clinical problem despite improvements in prevention, as they ‎are associated with ‎significant mortality and morbidity. Prevention strategies for SSIs are based ‎on reducing the risk of infection by bacteria, So many antiseptic agents are ‎used, the most ‎common one are Chlorhexidine and Povidone-Iodine.‎AimsTo discuss the ‎findings of RCTs that compare Chlorhexidine versus Povidone-Iodine in the prevention of ‎Surgical ‎Site ‎Infections (SSIs).‎Methods This systematic review was carried out, including PubMed, Google Scholar, and EBSCO that ‎examining randomized trials of Chlorhexidine and Povidone-Iodine to summarize the major ‎RCT that compare Chlorhexidine versus Povidone-Iodine in the prevention of Surgical Site ‎Infections (SSIs).‎Results The review included six randomized studies that compare between Chlorhexidine and Povidone-‎Iodine for the prevention of SSIs. The findings showed that many studies prefer using ‎Chlorhexidine over Povidine-Iodine to reduce SSIs, few studies prefer using PVI as antiseptic ‎and other studies reported that there is no significant difference between both. ConclusionMajority of results prefer using Chlorhexidine than Povidone-Iodine‎ as antiseptics but ‎there were few findings prefer ‎PVI and other studies reported that there was no significant ‎difference between using them as ‎antiseptics.

CustodyBlock: A Distributed Chain of Custody Evidence Framework

With the increasing number of cybercrimes, the digital forensics team has no choice but to implement more robust and resilient evidence-handling mechanisms. The capturing of digital evidence, which is a tangible and probative piece of information that can be presented in court and used in trial, is very challenging due to its volatility and improper handling procedures. When computer systems get compromised, digital forensics comes into play to analyze, discover, extract, and preserve all relevant evidence. Therefore, it is imperative to maintain efficient evidence management to guarantee the credibility and admissibility of digital evidence in a court of law. A critical component of this process is to utilize an adequate chain of custody (CoC) approach to preserve the evidence in its original state from compromise and/or contamination. In this paper, a practical and secure CustodyBlock (CB) model using private blockchain protocol and smart contracts to support the control, transfer, analysis, and preservation monitoring is proposed. The smart contracts in CB are utilized to enhance the model automation process for better and more secure evidence preservation and handling. A further research direction in terms of implementing blockchain-based evidence management ecosystems, and the implications on other different areas, are discussed

CCIPS: A Cooperative Intrusion Detection and Prevention Framework for Cloud Services

With the recent emergence and rapid advancement of cloud computing infrastructure and services, outsourcing Information Technology (IT) and digital services to Cloud Providers (CPs) has become attractive. This will allow for a reduction in IT resources (hardware, software, services, support, and staffing), and provide flexibility and agility in resource allocation, data and resource delivery, fault-tolerance, and scalability. However, the majority of cloud service providers tailor their services to address functionality (such as availability, speed, and utilization) and design requirements (such as integration), rather than protection against cyber-attacks and associated security issues. This paper considers the detection and prevention of security attacks against cloud computing systems. A proactive Cooperative Cloud Intrusion Prevention System (CCIPS) framework is proposed to detect and prevent known and zero-day threats targeting cloud computing networks. This framework provides enhanced threat detection and prevention via behavioral and anomaly data analysis. A multi-layer approach to security is employed to provide a cooperative model cloud which has both high performance and high availability