The effect of water deprivation on the pharmacokinetics of antipyrine and sulphadimidine following intravenous administration in Nubian goats

The effect of water deprivation on the pharmacokinetic parameters of antipyrine and sulphadimidine in the Nubian goat was studied. Water deprivation, to a level of dehydration at which the animals lost an average of 7.5% body weight, resulted in a significant reduction in antipyrine clearance (p < 0.05), and a consequently increased AUC value (p < 0.05). No effect was observed on the distribution parameters of the drug. In dehydrated animals which had lost an average of 10% or 12.5% of their body weight owing to water deprivation, significant changes were found in the distribution and elimination pharmacokinetic parameters of antipyrine and sulphadimidine. The volume of distribution was significantly decreased, resulting n elevated plasma levels for the two drags compared to normally watered animals. Significant decreases in clearance and subsequent prolongation of the elimination half-lives were observed during these periods of water deprivation. These changes in the disposition kinetics of the two drugs may be attributed to the loss of total body water and extracellular fluids and changes in the liver and kidney functions taking place during dehydration

BotCap: Machine Learning Approach for Botnet Detection Based on Statistical Features

In this paper, we describe a detailed approach to develop a botnet detection system using machine learning (ML)techniques. Detecting botnet member hosts, or identifying botnet traffic has been the main subject of manyresearch efforts. This research aims to overcome two serious limitations of current botnet detection systems:First, the need for Deep Packet Inspection-DPI and the need to collect traffic from several infected hosts. Toachieve that, we have analyzed several botware samples of known botnets. Based on this analysis, we haveidentified a set of statistical features that may help to distinguish between benign and botnet malicious traffic.Then, we have carried several machine learning experiments in order to test the suitability of ML techniques andalso to pick a minimal subset of the identified features that provide best detection. We have implemented ourapproach in a tool called BotCap whose test results showed its proven ability to detect individually infected hostsin a local network

Torsion Improvement of Reinforced Self-Compacting Concrete Beams Using Epoxy Injection and CFRP

Few researchers have investigated the internal torsional reinforcement of box beams, So, this study aims to find out the possibility of adding a certain percentage of RCA to the NC mixtures, as well as verifying the success achieved in repairing the cracks that occurred as a result of torsion with CFRP or injecting with epoxy, which has not been addressed in previous research and literature reviews. This study reinforces reinforced SCC box columns subjected to complete torsion with CFRP sheets and epoxy resin injections. Four types SCC specimens (the first beam with 0%, the second beams with 33.3%, the third beams with 67.7%, and the fourth beams with 100% RCA by weight) were subjected to pure torsion until failure. The dimensions and reinforcement of every specimen are identical. In addition, the applied torque-twist angle relationship at the midspan and end span was investigated. Bending experiments were performed to establish load-deflection curves and assess failure modes. After structural rehabilitation, all beams exhibited increased rigidity values, according to the results. Epoxy resin and CFRP sheet contributed to the specimens' increased ultimate load. The ultimate strength of RCA beams strengthened with CFRP and injected with epoxy increased. The specimens' flexural strength was considerably enhanced by the combination of surface roughness and fracture injection, and the effectiveness of using RCA was very good; it could be replaced with NCA in concrete mixtures, according to the ratio and need. Doi: 10.28991/CEJ-2023-09-11-05 Full Text: PD

Advancing Brain Research through Surface-Enhanced Raman Spectroscopy (SERS): Current Applications and Future Prospects

\ua9 2024 by the authors. Surface-enhanced Raman spectroscopy (SERS) has recently emerged as a potent analytical technique with significant potential in the field of brain research. This review explores the applications and innovations of SERS in understanding the pathophysiological basis and diagnosis of brain disorders. SERS holds significant advantages over conventional Raman spectroscopy, particularly in terms of sensitivity and stability. The integration of label-free SERS presents promising opportunities for the rapid, reliable, and non-invasive diagnosis of brain-associated diseases, particularly when combined with advanced computational methods such as machine learning. SERS has potential to deepen our understanding of brain diseases, enhancing diagnosis, monitoring, and therapeutic interventions. Such advancements could significantly enhance the accuracy of clinical diagnosis and further our understanding of brain-related processes and diseases. This review assesses the utility of SERS in diagnosing and understanding the pathophysiological basis of brain disorders such as Alzheimer’s and Parkinson’s diseases, stroke, and brain cancer. Recent technological advances in SERS instrumentation and techniques are discussed, including innovations in nanoparticle design, substrate materials, and imaging technologies. We also explore prospects and emerging trends, offering insights into new technologies, while also addressing various challenges and limitations associated with SERS in brain research

Ebola preparedness in Oman: An experience from the Middle East

LETTER TO THE EDITOR

An Efficient Micropayment Channel on Ethereum

Blockchain protocols for cryptocurrencies offer secure payment transactions, yet their throughput pales in comparison to centralized payment systems such as VISA. Moreover, transactions incur fees that relatively hinder the adoption of cryptocurrencies for simple daily payments. Micropayment channels are second layer protocols that allow efficient and nearly unlimited number of payments between parties at the cost of only two transactions, one to initiate it and the other one to close it. Typically, the de-facto approach for micropayment channels on Ethereum is to utilize digital signatures which incur a constant gas cost but still relatively high due to expensive elliptic curve operations. Recently, ElSheikh et al. have proposed a protocol that utilizes hash chain which scales linearly with the channel capacity and has a lower cost compared to the digital signature based channel up to a capacity of 1000 micropayments. In this paper, we improve even more and propose a protocol that scales logarithmically with the channel capacity. Furthermore, by utilizing a variant of Merkle tree, our protocol does not require the payer to lock the entire balance at the channel creation which is an intrinsic limitation with the current alternatives. To assess the efficiency of our protocol, we carried out a number of experiments, and the results prove a positive efficiency and an overall low cost. Finally, we release the source code for prototype on GitHub

Facial analysis using a new clinical device : The Kattan Facio-meter

The aim of the study was to attempt to set average faciometric standards for Egyptians using the Kattan Facio-meter. The sample consisted of 180 faculty students with age range 17-25 years. It was divided into three groups; Angle Class I, II and III. Class II was further subdivided into divisions 1 and 2. Linear and angular facial measurements in relation to K plane were taken using the Kattan facio-meter. The measurements were correlated to Angle?s classification and between genders. On comparing the different classes, Class II division 1 showed the statistically highest mean value for Orbitale-soft tissue A; p=0.042, Class II divisions 1 and 2 for Orbitale- Labrale superius; p=0.002 and soft tissue ANB; p<0.001. Females showed significantly higher mean value than males for the upper incisor/K plane; p=0.031. Males showed significantly higher mean value for the inter-incisal angle than females; p=0.001. Within the limitations of the current study, it was found that both linear and angular soft tissue measurements conformed to the antroposterior skeletal relation of the jaws and that Class II division 1 was due to protruded maxilla. Males had more prominent lips and deeper mentolabial sulcus. Egyptians had less prominent noses than Caucasians. The Kattan Facio-meter was a valuable tool for clinical analysis without the hazards of irradiation