Search

To better understand how a flat slab responds to a punching effect with varying effective parameters, an experimental and numerical program was carried out in this study. The studied parameters included the flexural reinforcement (RFT) ratios, whether in tension or in compression, the concrete compressive strength (fcu) and using of stirrups. For this purpose, eighteen R.C flat slab were casted and tested in the R.C laboratory at Cairo University. All slabs had the same dimensions of (1100 ×1100) mm and the slabs thickness is 120 mm with a square column dimension equal to (150 ×150) mm at the center of slabs. The ratios of flexural RFT in tension and compression sides were (1.27, 1.76, and 2.25) % and (0.48, 0.75 and 1.09) % respectively. The tested slabs were casted with fcu (35 and 45) MPa. All the previous mentioned parameters were investigated in the presence and absence of stirrups. First cracking load, ultimate load capacity, crack pattern, load-deflection relationship, stiffness, energy absorption and RFT strain were analyzed and discussed to show the parameters’ effects on all studied slabs. The results revealed that flexural tension RFT had a noticeable effect on the punching shear behavior compared to the compression one; which had a slight effect. Non-linear finite element 3-D models were verified with the experimental results and parametric study was conducted. Finally, the experimental results were compared and verified against different building design codes of practice (ACI 318, Eurocode 2 and ECP 203). The used codes were capable of estimating the shear capacity; but with conservative values. Eurocode 2 gave better prediction as it takes the flexural tension RFT into consideration. New equations were proposed to predict the punching shear strength considering flexural tension RFT ratio in case of presence and absence of stirrups.

In this study, a mathematical model of a new hydro-pneumatic damper consists of a double-acting cylinder, two oil chambers, a damping valve, and an accumulator is developed to assess its response to vertical vibrations in a passenger car. The main idea of the new damper aim to make that the damping coefficient in compression differ than that in rebound which achieve more stability specially during cornering. The damping coefficient difference in compression and rebound can be achieved due to the presence of accumulator. Both passive and active hydro-pneumatic suspension systems with the new damper employing different control strategies such as LQR, PID, and H-infinity control, are employed to assess the effectiveness of the suspension system. The investigation focuses on vertical acceleration, pitch acceleration, suspension deflection, and dynamic tire load. The half-car model is simulated using MATLAB/Simulink, and the results for both active and passive hydro-pneumatic suspensions are analyzed in terms of frequency, time, and power spectral density responses. The findings reveal that the active suspension system with H-infinity control demonstrates an 81% improvement in body acceleration and a 92% improvement in pitch acceleration (angular acceleration) compared to the passive hydro-pneumatic suspension which improve the stability of the vehicle during cornering. Similarly, the implementation of LQR-controlled suspension enhances body acceleration and step acceleration by approximately 40% and 57%, respectively, compared to the passive hydro-pneumatic suspension. Moreover, when compared to the passive hydro-pneumatic suspension, the PID-controlled active hydro-pneumatic suspension exhibits a 64% improvement in step acceleration and a 44% improvement in body acceleration.

The increasing popularity of Internet of Things (IoT)-based wireless services highlights the urgent need to upgrade fifth-generation (5G) wireless networks and beyond to accommodate these services. Although 5G networks currently support a variety of wireless services, they might not fully meet the high computational and communication resource demands of new applications. Issues such as latency, energy consumption, network congestion, signaling overhead, and potential privacy breaches contribute to this limitation. Machine learning (ML) frequently offers solutions to these problems. As a result, sixth-generation (6G) wireless technologies are being developed to address the deficiencies of 5G networks. Traditional ML methods are generally centralized. However, the vast amount of wireless data generated, growing privacy concerns, and the increasing computational capabilities of edge devices have led to a shift towards optimizing system performance in a distributed manner. This paper provides a thorough analysis of distributed learning techniques, including federated learning (FL), multi-agent reinforcement learning (MARL), and the multi-agent federated reinforcement learning (FRL) framework. It explains how these techniques can be effectively and efficiently implemented in wireless networks. These methods offer potential solutions to the challenges faced by current wireless networks, promising to create a more robust, capable, and versatile network that meets the growing demands of IoT and other emerging applications. Implementing the FRL framework can significantly improve the learning efficiency of wireless networks. To tackle the challenges posed by rapidly changing radio channels, we propose a robust FRL framework that enables local users to perform distributed power allocation, bandwidth allocation, interference mitigation, and communication mode selection. Finally, the paper outlines several future research directions aimed at effectively integrating the FRL framework into wireless networks.

In recent times, a fluid antenna system (FAS) has gained attention as a potential contender for 6G wireless networks. Fluid antenna multiple access (FAMA) is a new technology that allows each user to constantly move to the position with the strongest signal-to-interference ratio (SIR) by means of a single RF-chain port fluid antenna. Research works in FAMA mainly focus on propose models and solutions linked to the enhancement of FAMA from several aspects, including FAS system, enhancing orthogonal and non-orthogonal multiple access, channel modeling, diversity gain, artificial intelligence (AI) techniques, FAMA with other emerging technologies for 6G such as intelligent reflecting surface (IRS), multiple-input multiple-output (MIMO), terahertz (THz) communication, etc. There is no survey which covers all these important aspects of FAMA. Based on several concerns, a comprehensive taxonomy of FAMA has been presented in this study. First, FAS system is discussed. Then, FAMA mechanism is presented with its channel modeling and diversity gain. After that, FAMA is investigated with other emerging technologies such as IRS, MIMO, THz communication, etc. AI approaches to enhance FAMA are provided. In the end, we cover the potential research directions for further study in all areas. When designing and enhancing the FAS system, facilitating communication via FAMA, and integrating it with other cutting-edge technologies for 6G, this article may serve as a reference or guidance.

Abstract Cancer and different types of tumors are still the most resistant diseases to available therapeutic agents. Finding a highly effective anticancer drug is the first target and concern of thousands of drug designers. In our attempts to address this concern, a new pyrazine derivative, 1-(5-bromopyrazin-2-yl)-1-[3-(trifluoromethyl)benzyl]urea (BPU), was designed via structural optimization and synthesized to investigate its anticancer/antitumor potential. The in-vitro anticancer properties of BPU were evaluated by MTT assay using selected cell lines, including the Jurkat, HeLa, and MCF-7 cells. The Jurkat cells were chosen to study the effect of BPU on cell cycle analysis using flow cytometry technique. BPU exhibited an effective cytotoxic ability in all the three cell lines assessed. It was found to be more prominent with the Jurkat cell line (IC50 = 4.64 ± 0.08 µM). When it was subjected to cell cycle analysis, this compound effectively arrested cell cycle progression in the sub-G1 phase. Upon evaluating the antiangiogenic potential of BPU via the in-vivo/ex-vivo shell-less chick chorioallantoic membrane (CAM) assays, the compound demonstrated very significant findings, revealing a complementary supportive action for the compound to act as a potent anticancer agent through inhibiting blood vessel formation in tumor tissues. Moreover, the docking energy of BPU computationally scored − 9.0 kcal/mol with the human matrix metalloproteinase 2 (MMP-2) and − 7.8 kcal/mol with the human matrix metalloproteinase 9 (MMP-9), denoting promising binding results as compared to the existing drugs for cancer therapy. The molecular dynamics (MD) simulation outcomes showed that BPU could effectively bind to the previously-proposed catalytic sites of both MMP-2 and MMP-9 enzymes with relatively stable statuses and good inhibitory binding abilities and parameters. Our findings suggest that the compound BPU could be a promising anticancer agent since it effectively inhibited cell proliferation and can be selected for further in-vitro and in-vivo investigations. In addition, the current results can be extensively validated by conducting wet-lab analysis so as to develop novel and better derivatives of BPU for cancer therapy with much less side effects and higher activities.

Abstract In this work, an accurate, highly sensitive, and economical electrochemical sensor based on a carbon paste electrode modified by Ca2CuO3 nanostructure (Ca2CuO3 NS) was constructed using Eggshell waste recycling as a cheap source of calcium. The Ca2CuO3 NS was analyzed using FTIR, SEM, and XRD measurements. The synthesized nanomaterials utilized for the first time to enhance the electrocatalytic efficiency of carbon paste electrode (CPE) toward fluoroquinolones antibiotics ofloxacin (OFL) and ciprofloxacin (CIP), The drugs used to treat pneumonia caused by COVID-19. The synthesized Ca2CuO3 NS dramatically enhanced the anodic peak response of CPE toward both drugs compared to the unmodified one and other modified electrodes. The simultaneous detection of the two antibiotics was performed in the linear range of 0.09–1.0 μM for OFL and 0.05–0.8 μM for CIP with the LOD of 0.027 μM and 0.012 μM, respectively. The suggested method was applied successfully to determine OFL and CIP in real samples.

Abstract The transportation problem in operations research aims to minimize costs by optimizing the allocation of goods from multiple sources to destinations, considering supply, demand, and transportation constraints. This paper applies the multi-dimensional solid transportation problem approach to a private sector company in Egypt, aiming to determine the ideal allocation of their truck fleet. In order to provide decision-makers with a comprehensive set of options to reduce fuel consumption costs during transportation or minimize total transportation time, a multi-objective approach is employed. The study explores the best compromise solution by leveraging three multi-objective approaches: the Zimmermann Programming Technique, Global Criteria Method, and Minimum Distance Method. Optimal solutions are derived for time and fuel consumption objectives, offering decision-makers a broad range to make informed decisions for the company and the flexibility to adapt them as needed. Lingo codes are developed to facilitate the identification of the best compromise solution using different methods. Furthermore, non-dominated extreme points are established based on the weights assigned to the different objectives. This approach expands the potential ranges for enhancing the transfer problem, yielding more comprehensive solutions. This research contributes to the field by addressing the transportation problem practically and applying a multi-objective approach to support decision-making. The findings provide valuable insights for optimizing the distribution of the truck fleet, reducing fuel consumption costs, and improving overall transportation efficiency.

Abstract Background Resistance to antibiotics has increased steadily over time, thus there is a pressing need for safer alternatives to antibiotics. Current study aims to evaluate the influence of vitamin C as an antibacterial and anti-biofilm agent against uropathogenic E. coli (UPEC) strains. The expression of beta-lactamases and biofilm encoding genes among E. coli isolates before and after treating the isolates with sub MIC of vitamin C was analyzed by Real-time PCR. The in vivo assessment of the antibacterial and anti-biofilm effects of vitamin C against uropathogenic E. coli strains was done using a urinary tract infection (UTI) rat model. Results The effective concentration of vitamin C that could inhibit the growth of most study isolates (70%) was 1.25 mg/ml. Vitamin C showed a synergistic effect with most of the studied antibiotics; no antagonistic effect was detected at all. Vitamin C showed an excellent anti-biofilm effect against studied isolates, where 43 biofilm-producing isolates were converted to non-biofilm at a concentration of 0.312 mg/ml. The expression levels of most studied genes were down-regulated after treatment of E. coli isolates with vitamin C. In vivo assessment of vitamin C in treating UTIs showed that vitamin C has a rapid curative effect as the comparable antibiotic. Administration of both vitamin C and nitrofurantoin at a lower dose for treatment of UTI in rats had a better effect. Conclusion Vitamin C as an antibacterial and anti-biofilm agent either alone or in combination with antibiotics could markedly improve UTI in experimental rats.

Abstract Coronavirus disease 2019 (COVID-19)-associated mucormycosis (CAM) is responsible for a high mortality rate due to its unique and severe host-pathogen interactions. Critically ill or immunocompromised COVID-19 patients are more prone to suffer from aggressive mycoses. Probable victims include those with uncontrolled diabetes mellitus (DM), metabolic acidosis, prolonged neutropenia, increased ferritin levels, hypoxia, and prolonged hospitalization with/without mechanical ventilators and corticosteroids administration. The current review aims to outline the journey of patients with CAM as well as the advantages and disadvantages of the currently available diagnostic techniques. It also discussed the current status of treatment options and caveats in the management of mucormycosis. Multidisciplinary team, early diagnosis, controlling the predisposing condition(s), complete surgical debridement, effective antifungal therapies (e.g., amphotericin B, isavuconazole, and posaconazole), and implementing antifungal stewardship programs are imperative in CAM cases.

The increasing food scarcity necessitates sustainable agriculture achieved through automation to meet the growing demand. Integrating the Internet of Things (IoT) and Wireless Sensor Networks (WSNs) is crucial in enhancing food production across various agricultural domains, encompassing irrigation, soil moisture monitoring, fertilizer optimization and control, early-stage pest and crop disease management, and energy conservation. Wireless application protocols such as ZigBee, WiFi, SigFox, and LoRaWAN are commonly employed to collect real-time data for monitoring purposes. Embracing advanced technology is imperative to ensure efficient annual production. Therefore, this study emphasizes a comprehensive, future-oriented approach, delving into IoT-WSNs, wireless network protocols, and their applications in agriculture since 2019. It thoroughly discusses the overview of IoT and WSNs, encompassing their architectures and summarization of network protocols. Furthermore, the study addresses recent issues and challenges related to IoT-WSNs and proposes mitigation strategies. It provides clear recommendations for the future, emphasizing the integration of advanced technology aiming to contribute to the future development of smart agriculture systems.

Cryptocurrencies acquire user confidence by making the whole creation and transaction history transparent to the public. In exchange, the transaction history accurately captures the complete range of user activities related to cryptocurrencies. It is thought to be one of the safest and simplest payment methods that may be employed in the future. The trend of banks and other financial institutions investing in cryptocurrencies has increased rapidly in recent years. Therefore, it is necessary to synthesize the findings of previous studies on cryptocurrencies. In this paper, the use of data mining methods in Bitcoin transactions is analyzed and summarized. Cryptocurrencies, similar to the well-known Bitcoin, were targeted to ensure transaction security and privacy and overcome the drawbacks of traditional banking systems as well as other centralized systems. In addition, a comprehensive analysis of the literature on the challenges and applications of electronic currencies is conducted. The evolution of digital currency from electronic cash to cryptocurrencies is summarized and the methods used to increase user privacy are highlighted. The security threats in existing cryptocurrency systems (that compromise the privacy of Bitcoin users) are also highlighted. Finally, several research gaps and trends are identified that need to be further explored.

Blanking non-linearity is broadly used in impulsive noise communication environments due to its efficiency and ease of deployment to mitigate such noise. During the blanking procedure, data samples with impulsive noise are identified and clipped to zero, which removes impulsive noise from the system thereby, improving the system performance. In this regard, this paper investigates the performance of hybrid power line communication-visible light communication (PLC-VLC) systems with blanking nonlinearity. The signal-to-noise (SNR) ratio at the output of the blanking device is deduced using a closed-form analytical expression. The results show that there is good agreement between simulation results and theory if there is a sufficiently large number of orthogonal frequency division multiplexing (OFDM) sub-carriers. In addition, the study also indicates that the blanking method is more effective in curbing impulsive noise in comparison to the clipping technique. According to the threshold optimisation investigations, there exists a worst-case SINR value that minimizes the output SNR at the OFDM receiver after blanking. Furthermore, the findings also revealed that proper blanking threshold selection is essential for obtaining the best performance.

Abstract Aim OvSynch is a hormonal protocol for synchronization of estrus and use of artificial insemination (AI) at an optimal time without adverse effects on the ovaries or uterus. This study investigated the use of noninvasive color Doppler ultrasound to assess changes in uterine and vaginal blood flow during the Ovsynch program for synchronization of estrus and its relation to the pregnancy rates in Holstein cows. Materials and methods The experimental cows received an intramuscular dose of 10 μg of a GnRH analogue (G1), followed 7 days later with an intramuscular injection of synthetic prostaglandin F2α (P: PGF2α) analogue (500 μg cloprostenol sodium), and given a 10 μg, injection of the GnRH analogue (G2) i.m. 48 h after the PGF2α treatment, and the cows were bred 14-16 h after. Uterine and vaginal perfusion were investigated by performing transrectal Doppler ultrasonography of both the uterine and vaginal arteries in Holstein cows at different time points during the Ovsynch program to determine: peak systolic velocity (PSV), time-averaged maximum velocity (TAMV), the volume of blood flow (BFV), pulsatility index (PI), resistance index (RI), resistance impedance (S/D) and diameters of uterine (UA) and vaginal (VA) arteries. Steroid hormones were also assayed. Transrectal ultrasonography (TUS) was performed at 32 and 60 days to confirm the pregnancy per artificial insemination (P/AI). Results The uterine PSV, TAMV, and PV were greater at the time of the cloprostenol sodium and second GnRH injections (p