A genetic algorithm for shortest path with real constraints in computer networks

The shortest path problem has many different versions. In this manuscript, we proposed a muti-constrained optimization method to find the shortest path in a computer network. In general, a genetic algorithm is one of the common heuristic algorithms. In this paper, we employed the genetic algorithm to find the solution of the shortest path multi-constrained problem. The proposed algorithm finds the best route for network packets with minimum total cost, delay, and hop count constrained with limited bandwidth. The new algorithm was implemented on four different capacity networks with random network parameters, the results showed that the shortest path under constraints can be found in a reasonable time. The experimental results showed that the algorithm always found the shortest path with minimal constraints

The adoption of bitcoins technology: The difference between perceived future expectation and intention to use bitcoins: Does social influence matter?

Bitcoin is a decentralized system that tries to become a solution to the shortcomings of fiat and gold-based currencies. Considering its newness, the adoption level of bitcoin is yet understood. Hence, several variables are proposed in this work in examining user perceptions regarding performance expectancy, effort expectancy, trust, adoption risk, decentralization and social influence interplay, with the context of user’s future expectation and behavioral intentions to use bitcoins. Data were gathered from 293 completed questionnaire and analised using AMOS 18. The outcomes prove the sound predictability of the proposed model regarding user’s future expectations and intentions toward bitcoins. All hypotheses were supported, they were significantly affecting the dependent variables. Social influence was found as the highest predictor of behavioral intention to negatively utilize bitcoins. The significant impact of social influence, adoption risk and effort expectancy which affect behavioral intention to use bitcoins the most, are demonstrated in this study. Bitcoins should thus, present an effective, feasible and personalized program which will assist efficient usage among users. Additionally, the impacts of social influence, adoption risk and perceived trust on behavioral intention to utilize new technology were compared, and their direct path was tested together, for the first time in this context

Hybrid feature selection method based on particle swarm optimization and adaptive local search method

Machine learning has been expansively examined with data classification as the most popularly researched subject. The accurateness of prediction is impacted by the data provided to the classification algorithm. Meanwhile, utilizing a large amount of data may incur costs especially in data collection and preprocessing. Studies on feature selection were mainly to establish techniques that can decrease the number of utilized features (attributes) in classification, also using data that generate accurate prediction is important. Hence, a particle swarm optimization (PSO) algorithm is suggested in the current article for selecting the ideal set of features. PSO algorithm showed to be superior in different domains in exploring the search space and local search algorithms are good in exploiting the search regions. Thus, we propose the hybridized PSO algorithm with an adaptive local search technique which works based on the current PSO search state and used for accepting the candidate solution. Having this combination balances the local intensification as well as the global diversification of the searching process. Hence, the suggested algorithm surpasses the original PSO algorithm and other comparable approaches, in terms of performance

Prognosis and distribution of ischemic stroke with negative diffusion-weighted imaging: a systematic review and meta-analysis

BackgroundMagnetic resonance diffusion-weighted imaging (DWI) is the most sensitive modality for ischemic stroke diagnosis. However, DWI may fail to detect ischemic lesions in a proportion of patients.MethodsFollowing PRISMA statement, a systematic search of Medline, Embase, and Web of Science was conducted until January 3, 2024. The inclusion was confined to English literature with sufficient reporting. Proportions of DWI-negative ischemic stroke were pooled. For binary variables, odds ratios (ORs) were computed using the random-effects model.ResultsFourteen studies constituting 16,268 patients with a clinical diagnosis of ischemic stroke and available DWI findings were included. Intravenous thrombolysis (IVT) was administered to 19.6% of the DWI-negative group and 15.3% of the DWI-positive group. DWI-negative ischemic stroke was reported in 16% (95% CI: 10–24%; after sensitivity analysis: 11% [95% CI: 8–15%]) of stroke patients. Among minor stroke patients (National Institutes of Health Stroke scale [NIHSS] of 5 or less), 24% (95% CI 12–42%) had negative DWI findings. Predictors of DWI-negative scans included posterior circulation stroke, history of ischemic heart disease, prior stroke, or prior transient ischemic attack. Cardioembolic stroke (OR, 0.62, 95% CI: 0.41–0.93) and history of atrial fibrillation increased the likelihood of positive DWI findings (OR, 0.56, 95% CI: 0.45–0.71). Patients with DWI-negative ischemic stroke had higher odds of good functional outcomes (modified Rankin scale [mRS] of 0–1) (OR, 2.26; 95% CI: 1.03–4.92), lower odds of stroke recurrence (OR, 0.68; 95% CI: 0.48–0.96), and lower odds of severe disability or mortality (mRS of 3–6) (OR, 0.44; 95% CI: 0.34–0.57) compared to patients with positive DWI. Rates of symptomatic intracerebral hemorrhage after IVT were comparable between groups.ConclusionDWI-negative findings were present in a significant proportion of ischemic stroke patients and may be utilized as a marker for favorable prognosis

Free-H2 deoxygenation of Jatropha curcas oil into cleaner diesel-grade biofuel over coconut residue-derived activated carbon catalyst

Diesel-like hydrocarbons were produced by the catalytic deoxygenation (DO) of Jatropha curcas oil (JCO) over novel Agx/AC and Niy-Agx/AC catalysts under an H2-free atmosphere. The AC was synthesized from coconut fibre residues (CFR), where CFR is the by-product from coconut milk extraction and is particularly rich in soft fibres with high mineral content. The Niy-Agx/AC catalyst afforded higher DO activity via the decarboxylation/decarbonylation (deCOx) route than Agx/AC due to the properties of Ni, synergistic interaction of Ni and Ag species, adequate amount of strong acid sites and large number of weak acid sites, which cause extensive C-O cleavage and lead to rich formation of n-(C15+C17) hydrocarbons. The effect of Ag and Ni content were studied within the 5 to 15 wt% range. An optimum Ni and Ag metal content (5 wt%) for deCOx reaction was observed. Excess Ni is not preferable due to a tendency for cracking and Ag-rich containing catalyst weakly enforced triglycerides breaking. The Ni5-Ag5/AC govern exclusively decarbonylation reaction, which corroborates the presence of Ni²⁺ species and a high amount of strong acid sites. Ultimately, Ni5-Ag5/AC in the present study shows excellent chemical stability with consistent five reusability without drastic reduction of hydrocarbon yield (78–95%) and n-(C15+C17) selectivity (82–83%), which indicate favourable application in JCO DO

The Effect of Mycotoxins on Human Health

The aim of the current study is, what are mycotoxins, what are the risks of mycotoxins on human health, where are mycotoxins found in nature, and what are the health effects of mycotoxins on humans. the questionnaire was created electronically via the Google Drive program, and then it was distributed via mobile phone on the social networking program (WhatsApp)? Using e-mail for all participants to respond to the questionnaire. 650 questionnaires were distributed to all mobile groups, and 600 questionnaires were received on the researcher’s e-mail. (The target group is residents of the holy city of Mecca, aged 25-55 years)

Role of Stem Cells in Orthopaedic Surgery: Theoretical Survey

This study aims at analyzing the Stem cell application is a burgeoning field of medicine that is likely to influence the future of orthopaedic surgery. Stem cells are associated with great promise and great controversy. For the orthopaedic surgeon, stem cells may change the way that orthopaedic surgery is practiced and the overall approach of the treatment of musculoskeletal disease. Stem cells may change the field of orthopaedics from a field dominated by surgical replacements and reconstructions to a field of regeneration and prevention. This review will introduce the basic concepts of stem cells pertinent to the orthopaedic surgeon and proceed with a more in depth discussion of current developments in the study of stem cells in orthopaedic surgery. Keywords: Stem cell, orthopaedic, surgery

Production of renewable diesel from Jatropha curcas oil via pyrolytic-deoxygenation over various multi-wall carbon nanotube-based catalysts

Jatropha curcas is a highly toxic plant that produces seed containing viscous oil with productivity (2 ton/ha), it grows in tropical and sub-tropical regions and offer greater adaptability to a wide range of climatic and soil conditions. Its oils have been noted as an important alternative to produce green diesel via deoxygenation reaction. This study, deoxygenation of jatropha curcas oil (JCO) was carried out over NiO–Fe2O3 and NiO–ZnO catalysts that supported onto multi-walled carbon nanotube (MWCNT). It had found that high Fe and Zn dosages were ineffective in deoxygenation and greatest activity was observed on NiO(20) Fe2O3(5)/MWCNT catalyst. Structure-activity correlations revealed that low metal loading, large density of weak + medium acidic sites and strong basic sites play key role in enhancing the catalytic activities and n-(C15+C17) selectivity. Comparing carbon nanostructures and carbon micron size supported NiO-Fe2O3 revealed that green diesel obtained from NiO–Fe2O3/MWCNT catalysed deoxygenation had the highest heating value and the lowest amounts of oxygen content. Thereby, it confirmed the importance of carbon nanostructure as the catalyst support in improving the diesel quality. Considering the high reusability of NiO-Fe2O3/MWCNT (6 consecutive runs) and superior green diesel properties (flash point, cloud properties and cetane index) demonstrated the NiO–Fe2O3/MWCNT catalyst offers great option in producing excellent properties of green diesel for energy sector

Production of green diesel from catalytic deoxygenation of chicken fat oil over a series binary metal oxide-supported MWCNTs

Deoxygenation processes that exploit milder reaction conditions under H2-free atmospheres appear environmentally and economically effective for the production of green diesel. Herein, green diesel was produced by catalytic deoxygenation of chicken fat oil (CFO) over oxides of binary metal pairs (Ni–Mg, Ni–Mn, Ni–Cu, Ni–Ce) supported on multi-walled carbon nanotubes (MWCNTs). The presence of Mg and Mn with Ni afforded greater deoxygenation activity, with hydrocarbon yields of >75% and n-(C15 + C17) selectivity of >81%, indicating that decarboxylation/decarbonylation (deCOx) of CFO is favoured by the existence of high amount of lower strength strong acidic sites along with noticeable strongly basic sites. Based on a series of studies of different Mg and Mn dosages (5–20 wt%), the oxygen free-rich diesel-range hydrocarbons produced efficiently by Ni10–Mg15/MWCNT and Ni10–Mn5/MWCNT catalysts yielded >84% of hydrocarbons, with n-(C15 + C17) selectivity of >85%. The heating value of the green diesel obtained complied with the ultra-low sulphur diesel standard