Search

Coccidia poses significant challenges to poultry farming, impacting productivity and welfare. This study aimed to evaluate the efficacy of Aloe vera supplementation in managing coccidial infection in quails. A total of 360 one-day-old quails chicks were divided into five groups (six replicates with twelve birds per replicate) and challenged with mixed sporulated oocysts of Eimeria species (E. tenella, E. nicatrix, E. maxima, E. mitis). The groups included a positive control (infected, untreated), negative control (uninfected, untreated), and three treatment groups: Amprolium (1 g/l water), Aloe vera 2% (AV2), and Aloe vera 4% (AV4). Results demonstrated significant (p

Biostimulants are obtained from various sources like plants, animals, microorganisms, and industrial by-products as well as waste material. Their utilization in agriculture practices is being increased that is giving positive results. The purpose of the current study was to use plant-derived smoke (SMK) solution and biogas digestate (BGD) slurry as biostimulant to elucidate their impact on potato (Solanum tuberosum) performance. The experiment was conducted in lab as well as field conditions, and SMK and BGD solutions were prepared in varying concentrations such as SMK 1:500, SMK 1:250, BGD 50:50, and BGD 75:25. Foliar applications were performed thrice during experiments and data were collected related to photosynthesis, growth, pigments, and genome-wide methylation profiling. Net photosynthesis rate (A) and water use efficiency (WUE) were found higher in SMK- and BGD-treated lab and field grown plants. Among pigments, BGD-treated plants depicted higher levels of Chl a and Chl b while SMK-treated plants showed higher carotenoid levels. Alongside, enhancement in growth-related parameters like leaf number and dry weight was also observed in both lab- and field-treated plants. Furthermore, DNA methylation profile of SMK- and BGD-treated plants depicted variation compared to control. DNA methylation events increased in all the treatments compared to control except for SMK 1:500. These results indicate that smoke and slurry both act as efficient biostimulants which result in better performance of plants. Biostimulants also affected the genome-wide DNA methylation profile that resultantly might have changed the plant gene expression profiling and played its role in plant responsiveness to these biostimulants. However, there is need to elucidate a possible synergistic effect of SMK and BGD on plant growth along with gene expression profiling.

The present study was aimed at synthesis of polymeric hydrogels for controlled boron (B) release, as B deficiency is a major factor that decreases crops yield. Thus, graphene oxide incorporated guar gum and poly (ethylene glycol) hydrogels were prepared using the Solution Casting method for boron release. 3-Glycidyloxypropyl trimethoxysilane (GLYMOL) was used as a cross-linker. Characterizations of hydrogels were carried out by Fourier Transform Infrared Spectroscopy (FTIR), Thermo-Gravimetric Analysis and Scanning Electron scope. The FTIR outcomes confirmed the existence of functional groups, bindings and development of hydrogel frameworks from incorporated components. The quantity of GLYMOL directly increased the thermal stability and water retention but decreased the swelling %. The maximum swelling for the hydrogel formulations was observed at pH 7. The addition of GLYMOL changed the diffusion from quasi-Fickcian to non-Fickcian diffusion. The maximum swelling quantities of 3822% and 3342% were exhibited by GPP (control) and GPP-8 in distilled water, respectively. Boron release was determined in distilled water and sandy soil by azomethine-H test using UV-Visible spectrophotometer while 85.11% and 73.65% boron was released from BGPP-16, respectively. In short, water retentive, water holding capacities, swelling performances, biodegradability and swelling/deswelling features would offer an ideal platform for boron release in sustained agricultural applications.

Vehicle scheduling at shipyards can involve delays due to numerous risk factors encountered in the complicated shipyard road environment. This paper studies the problems of risk coupling in shipyard vehicle scheduling based on the risk matrix approach, considering the complicated road environment, assessing the degrees of coupling and disorder. Based on safety-engineering theory and comprehensive analysis of the road environment, four key criteria are identified, vehicles, the road environment, the working environment, and humans, including 12 factors and their specific contents. The degree of coupling between various combinations of risk criteria is quantitatively determined utilizing the N-K model. Additionally, the degree of disorder in the risk criteria is assessed based on information entropy theory. The model’s correction coefficients are determined through comparative analysis of experimental data. By integrating the degree of coupling and disorder, delays caused by different combinations of risk criteria in scheduling tasks are computed. The quantitative evaluation model enables accurate appraisal of risk events during shipyard vehicle scheduling. The model provides a valuable managerial tool to analyze delays caused when specific risk criteria are met and to compare these delays to the potential impact on time resulting from adjusting vehicle scheduling plans. This research has significant implications for enhancing vehicle distribution efficiency in shipyards.

The inherent complexities of Artificial Intelligence (AI) and machine learning (ML) technologies expose autonomous ships to a wide range of multifaceted interconnected risks. However, very few studies have aimed at the holistic risk assessment of autonomous ships. To this end, this study employs an expert-opinion-based integrated machine learning approach amalgamating logistic regression and Bayesian network to conduct risk assessment for autonomous ships. The results reveal human factor interactions and operational issues as the prominent accident causation factors. The findings of this study will contribute significantly to the existing literature on autonomous ships and the complexities involved in their operational systems. By identifying critical factors causing accidents and their impact on autonomous ship safety and resilience, stakeholders such as autonomous ship manufacturers, port authorities, shipping companies, and governments can develop more efficient and effective operational and safety systems.

Semantic tags can enrich citation graphs by inter-connecting papers with citation reasons. One of the best sources of knowledge to tell the reason for citation is the author himself. Integrating these reasons in an authoring system can help authors to choose a reason while citing. We examined various Human and Automatic authoring systems for integration of citation reasons. However, to the best of our knowledge, no such system exists that facilities authors to integrate the reasons while citing. Same is the case with Cite Packages. This research proposes integration of CCRO:Citations’ Context and Reasons Ontology’s (Ihsan and Qadir, 2019) taxonomic hierarchy of reasons within document. We have developed a CCRO Package to semantically tag citations with reasons and to create an intra-discourse relation between research articles. Furthermore, embedding these structures within RDF Data Store enables the creation of knowledge graphs that become a foundation artifact for the Semantic & Scientific Discourse.

Bacteriosis is one of the most prevalent and deadly infections that affect peach crops globally. Timely detection of Bacteriosis disease is essential for lowering pesticide use and preventing crop loss. It takes time and effort to distinguish and detect Bacteriosis or a short hole in a peach leaf. In this paper, we proposed a novel LightWeight (WLNet) Convolutional Neural Network (CNN) model based on Visual Geometry Group (VGG-19) for detecting and classifying images into Bacteriosis and healthy images. Profound knowledge of the proposed model is utilized to detect Bacteriosis in peach leaf images. First, a dataset is developed which consists of 10000 images: 4500 are Bacteriosis and 5500 are healthy images. Second, images are preprocessed using different steps to prepare them for the identification of Bacteriosis and healthy leaves. These preprocessing steps include image resizing, noise removal, image enhancement, background removal, and augmentation techniques, which enhance the performance of leaves classification and help to achieve a decent result. Finally, the proposed LWNet model is trained for leaf classification. The proposed model is compared with four different CNN models: LeNet, Alexnet, VGG-16, and the simple VGG-19 model. The proposed model obtains an accuracy of 99%, which is higher than LeNet, Alexnet, VGG-16, and the simple VGG-19 model. The achieved results indicate that the proposed model is more effective for the detection of Bacteriosis in peach leaf images, in comparison with the existing models.

Abstract pH responsive hydrogels have gained much attraction in biomedical fields. We have formulated ternary hydrogel films as a new carrier of drug. Polyelectrolyte complex of chitosan/guar gum/polyvinyl pyrrolidone cross-linked via sodium tripolyphosphate was developed by solution casting method. Fourier transform infrared spectroscopy, scanning electron microscopy and thermogravimetric analysis were conducted to examine the interactions between the polymeric chains, surface morphology and thermal stability, respectively. The swelling tests resulted that the swelling was reduced with the increase in the concentration of crosslinker due to the more entangled arrangement and less availability of pores in hydrogels. Ciprofloxacin hydrochloride was used as a model drug and its release in simulated gastric fluid, simulated intestinal fluid and phosphate buffer saline solution was studied. pH responsive behaviour of the hydrogels have subjected these hydrogels for drug release applications.

Seaports function as lifeline systems in maritime transportation, facilitating critical processes like shipping, distribution, and allied cargo handling. These diverse subsystems constitute the Port Infrastructure System (PIS) and have intricate functional interdependencies. The PIS is vulnerable to several external disruptions, and the impact of COVID-19 is severe and unprecedented in this domain. Therefore, this study proposes a novel general port safety framework to cope with recurring hazards and crisis events like COVID-19 and to augment PIS safety through a multi-state failure system. The PIS is divided into three critical subsystems: shipping, terminal, and distribution infrastructure, thereby capturing its functional interdependency and intricacy. A dynamic input–output model is employed, incorporating the spatial variability and average delay of the disruption, to determine the PIS resilience capacity under the stated disruptions. This study simulates three disruption scenarios and determines the functional failure capacity of the system by generating a functional change curve in Simulink. This study offers viable solutions to port managers, terminal operators, and concerned authorities in the efficient running of intricate interdependent processes and in devising efficient risk control measures to enhance overall PIS resilience and reliability. As part of future studies, given the difficulty in obtaining relevant data and the relatively limited validation of the current model, we aim to improve the accuracy and reliability of our model and enhance its practical applicability to real-world situations with data collected from a real-world case study of a PIS system.

With the instigation of China Pakistan Economic Corridor (CPEC), the strategic significance of South Asian and Middle Eastern ports have been vitalized. The aim of this study is to compare the technical efficiency of less explored South Asian & Middle Eastern ports with the East Asian ports and determine ways for their efficiency enhancement and management optimization. The cross sectional data for the year 2018 was collected for 15 container ports each of South & Middle Eastern and East Asian region and arranged into input and output variables. The data was analyzed through the DEA-CCR and DEA-BCC model. Results indicate that only one port each from UAE and India among the Middle & South Asian ports were found efficient on CCR model with the number of efficient ports on BCC model increased by 47%. While, in East Asian region two ports of China and one of South Korea were found efficient on CCR model, with 33% increase on BCC model. Lianyungang port was the most prominent among the efficient ports being highly benchmarked. The average efficiency for East Asian region (CCR: 0.524, BCC: 0.901) remained similar to that of South Asian and Middle East Region (CCR: 0.517, BCC: 0.906).

Stimuli-responsive drug delivery systems are urgently required for injectable site-specific delivery and release of drugs in a controlled manner. For this purpose, we developed novel pH-sensitive, biodegradable, and antimicrobial hydrogels from bio-macromolecule pectin, polyvinylpyrrolidone (PVP), 3-aminopropyl (diethoxy)methyl silane (3-APDEMS), and sepiolite clay via blending and solution casting technique. The purified sepiolite (40 um) was functionalized with 3-APDEMS crosslinker (ex-situ modification) followed by hydrogels fabrication. FTIR and SEM confirmed crosslinked structural integrity and rod-like morphology of hydrogels respectively. The swelling properties of hydrogels could be controlled by varying the concentration of modified clay in pectin/PVP blends. Moreover, the decrease in pH increased the swelling of hydrogels indicating the pH-responsiveness of hydrogels. All hydrogels were degraded after 21 days in phosphate buffer saline pH 7.4 (human blood pH). In-vitro cytotoxicity against 3T3 mouse fibroblast cell line analysis confirmed cytocompatibility of all hydrogels. Ceftriaxone sodium (CTX-S) was selected as a model drug. The release profile of the hydrogel showed 91.82% release in PBS for 2 h in a consistent and controlled manner. The chemical structure of the drug remained intact during and after release confirmed through UV-Visible spectroscopy. Overall, these hydrogels could be used as potential scaffolds for future biomedical applications.

Hong Kong's port is one of the busiest in the world. Such heavy traffic is associated with a high accident rate. The present study uses Bayesian Networks to analyze accident risk in Hong Kong waters using 331 accident reports during the period of 1999-2017. The methodology adopted is comprised of an analysis of present literature and expert judgments for the determination of nodes and states. The calculation of probabilities and conditional probability tables (CPT) were done based solely on the real data in accident reports through parameter estimation. The results indicate that the highest portion of accidents was categorized as “other” with a probability of 0.5174. The majority of such accidents took place in port waters. The second highest category was “collision” with a probability of 0.2256. Both of these accident types were associated with the highest fatality rate-one or two people killed. Poor judgment, negligence and insufficient training were found to be the most influential factors with regard to human actions. The highest rate of injuries was associated with passenger ships. The results offer valuable insights into various accident scenarios which involve setting evidence at different states of consequences and accident types to determine the most prominent contributing factors. Sensitivity analysis was also conducted to recognize the most critical variables. This study should prove useful to decision and policy makers seeking to enhance sustainable safety in maritime traffic operations.

Shipbuilding is a complex and large-scale operation involving many intermediate products (blocks) and the frequent transfer of blocks among workshops and stockyards. The reasonable use of methods to complete the transfer scheduling of intermediate products is of great importance. In this paper, the blocks and the flat transporters are the research objects. Based on organizing the various logistical processes for blocks and the circulation process in the shipyard, we established a model that takes the task time window and other factors as constraints, and minimizes the sum of delay time and no-load time of flat transporters while satisfying the punctuality of scheduling tasks. Three conclusions are reached: (1)The flat transporter utilization rate is inversely related to the value of the objective function. The smaller the value of the objective function, the more the usage rate of a particular one (2) loading is the biggest obstacle to the overall working time of flat transporters, and a simple optimization model cannot solve this problem; and (3) based on the optimization model, the load efficiency of flat transporters can be improved, and the delivery time can be reduced.

The study investigates the non-isothermal thermogravimetric analysis of cattle manure at varied heating rates to compare the kinetic and thermodynamic behaviors of cattle manure in N2 and air atmospheres. The Thermogravimetric (TG) curves indicated that the decomposition of the manure can be divided into three different regions. Exclusive of stage I (dehydration), the activation energy (Ea) values of stage II (devolatilization) for all model-free methods varied between 144 - 270 and 32–227 kJ/mol in pyrolysis and combustion respectively. While in stage III, Ea values varied in ranges of 49–336 kJ/mol and 71–136 kJ/mol for pyrolysis (carbonation) and combustion (char burning), respectively. The overall average Ea for the pyrolysis (≈146 kJ/mol) is higher than the combustion process (≈127 kJ/mol). The variation in the values of frequency factor “A” also indicated the complexity of both processes. Pyrolysis followed overall 2-Diffusion (D2) reaction models, while combustion followed 3-Power law (P3) and reaction Order-1 (O1) in stage II and III respectively. The thermodynamic study was also conducted to evaluate the important parameters, change in Enthalpy change (ΔH), Gibbs free energy (ΔG), and Entropy (ΔS).

Ulmus villosa Brandis ex Gamble, an economically and ecologically important forest tree, is native to the western Himalayas of Pakistan. The long pressure imposed by unsustainable utilization and market demands has resulted in the rapid decline of the U. villosa population in the wild. To date, very limited information on the genomic diversity of U. villosa is available and this can tremendously limit our understanding of distribution and future conservation of U. villosa. Therefore, the current study aimed to assess genetic diversity within U. villosa wild populations of the Hazara Division using four barcoding markers (i.e., rbcL, matK XF + 5R, matK 390F + 1326R and trnH-psbA). A total of six high quality sequences were obtained with rbcL, four with matK XF + 5R, four with matK 390F + 1326R, and fourteen with trnH-psbA. The sequenced regions contained insertions and deletions as well as several SNPs across the length of sequences, and PCR-based markers may be developed from these novel SNPs markers. The phylogenetic results supported the polyphyletic origin of the genus Ulmus, and the data indicated that multiple speciation events may have led to the evolution of U. villosa in this region. For deeper understanding of the origin and evolution of U. villosa, sequencing of the complete nuclear and chloroplast genomes will be pivotal. The results herein provide novel insights into the genomic diversity as well as phylogenetic relationships of U. villosa with other species, and may facilitate both in situ and ex situ conservation efforts for this endangered species.

The catastrophic environmental, life and monetary losses concomitant to the hazardous cargo accidents have remained a matter of critical concern for the maritime transportation officials. The factors that instigate these accidents while dealing with hazardous cargo in a port environment requires rigorous analysis and evaluation, which still remains in its infancy. In accord to these prevailing issues, this study focusses on the assessment of multifactor risks associated with the dealing of hazardous cargos inside a port. The methodology adopted is the amalgamation of expert judgment and literature review for the identification of factors and developing their causal relationship, while Bayesian Network (BN) for the inference, which was based on 348 past accident reports from the year 1990 to 2018. The results indicate that under normal circumstances, the probability of an accident with considerable consequences is 59.8, where human and management were found to be the highest contributing factors. Setting evidence at the environment and pollution accident to occur, the incidence probability of the "management" is raised by 7.06%. A sensitivity analysis was conducted to determine the most critical factors for the hazardous cargo accident. This study reveals that in order to evade the hazardous cargo accidents and curtail severity of the consequences, the port authorities, concerned government departments and other related institutions should pay specific attention to the qualification, training and attitude of the involved workforce. Moreover, the development and implementation of stringent safety protocols was also revealed to have critical prominence. This study holds practical vitality for enhancing safety and mitigating risks associated to hazardous cargo dealing in a port.

The focus of this study is on optimizing the schedule adjustment scheme of shared designated driver ferry vehicles to obtain a sustainable and energy-efficient system to pick up and drop off designated drivers to serve drunk customers. A two-stage matching model for driver and customer supply and demand matching and driver ferry vehicle dispatching is designed in order to optimize the total distance travelled and minimize the generalized deviation costs. A maximum residual time adjustment algorithm is designed to reduce the logarithm of new interference demand, and a tabu search algorithm is used to solve the schedule adjustment scheme for ferry vehicles. The validity of the model and the algorithm is verified by a multiperiod example constructed in the Solomon test question bank. The result of numerical experiments shows that the proposed model and algorithm can solve the disruption adjustment scheduling strategy of shared designated driver ferry vehicles. The integrated optimization strategy can effectively improve the utilization rate and the operation efficiency of the shared driver ferry vehicles to reduce operation cost and energy consumption.

Safety has been a primary concern in every industry. It includes system, personnel, environmental safety, etc. Maritime transportation safety is of the utmost importance because a lot of economic and environmental damage has been caused by ship-related accidents. The majority of these accidents have resulted from human factors. For the analysis of accidents and future safety, various accident models have been created. In this study, human-based errors are analyzed and quantified by using the fuzzy fault tree analysis, which helps calculate the failure probability of the causes. A real-life case of a chemical tanker Key Bora was studied and analyzed, which happened on 28 March 2020, at Kyleakin Pier, Isle of Skye, Scotland. The ship’s hull was seriously damaged and was flooded. According to the analysis, two main human factors that contributed the most to the occurrence of this accident were found. These incidents can be avoided by ensuring proper measures are followed, and the results can be used as guidelines for future marine accident investigations and safety.

Diffusion dialysis (DD) using anion exchange membranes (AEM) is an effective process for acid recovery and requires the preparation of suitable materials for AEMs, characterized by unique ions transport properties. In this work, novel AEMs composed of quaternized diaminobutane (QDAB) and poly(vinyl alcohol) (PVA) were cross-linked by tetraethoxysilane (TEOS) via the sol–gel process. The prepared AEMs were systematically characterized by Fourier-transform infrared (FTIR) spectroscopy, ion-exchange capacity (IEC) analysis, thermo gravimetric analysis (TGA), water uptake, linear expansion ratio (LER), and mechanical strength determination, scanning electron microscopy (SEM), and DD performance analysis for acid recovery using a hydrochloric acid/iron chloride (HCl/FeCl2) aqueous mixture and varying the QDAB content. The prepared AEMs exhibited IEC values between 0.86 and 1.46 mmol/g, water uptake values within 71.3 and 47.8%, moderate thermal stability, tensile strength values in the range of 26.1 to 41.7 MPa, and elongation from 68.2 to 204.6%. The dialysis coefficient values were between 0.0186 and 0.0295 m/h, whereas the separation factors range was 24.7–44.1 at 25 °C. The prepared membranes have great potential for acid recovery via diffusion dialysis.

Chitosan and polyethylene glycol (PEG-600) membranes were synthesized and crosslinked with 3-aminopropyltriethoxysilane (APTES). The main purpose of this research work is to synthesize RO membranes which can be used to provide desalinated water for drinking, industrial and agricultural purposes. Hydrogen bonding between chitosan and PEG was confirmed by displacement of the hydroxyl absorption peak at 3237 cm−1 in pure chitosan to lower values in crosslinked membranes by using FTIR. Dynamic mechanical analysis revealed that PEG lowers Tg of the modified membranes vs. pure chitosan from 128.5 °C in control to 120 °C in CS-PEG5. SEM results highlighted porous and anisotropic structure of crosslinked membranes. As the amount of PEG was increased, hydrophilicity of membranes was increased and water absorption increased up to a maximum of 67.34%. Permeation data showed that flux and salt rejection value of the modified membranes was increased up to a maximum of 80% and 40.4%, respectively. Modified films have antibacterial properties against Escherichia coli as compared to control membranes.

Biodegradable natural polymers have been investigated extensively as the best choice for encapsulation and delivery of drugs. The research has attracted remarkable attention in the pharmaceutical industry. The shortcomings of conventional dosage systems, along with modified and targeted drug delivery methods, are addressed by using polymers with improved bioavailability, biocompatibility, and lower toxicity. Therefore, nanomedicines are now considered to be an innovative type of medication. This review critically examines the use of natural biodegradable polymers and their drug delivery systems for local or targeted and controlled/sustained drug release against fatal diseases.

Fresh and clean water is consistently depleting and becoming a serious problem with rapid increases in population, so seawater desalination technology has captured global attention. For an efficient desalination process, this work proposes a novel, nanofibrous, thin-film composite membrane (NF-TFC) based on the deposition of the nanofibrous active layer of a blend of chitosan (CS) and poly (vinylpyrrolidone) (PVP) crosslinked with maleic acid on a 3-triethoxysilylpropylamine functionalized cellulose acetate substrate. FTIR analysis demonstrated the development of chemical and physical interactions and confirmed the incorporation of functional groups present in the NF-TFC. Scanning electron microscopy (SEM) micrographs depict the fibrous structure of the active layers. The reverse osmosis (RO) desalination characteristics of NF-TFC membranes are elevated by increasing the concentration of the crosslinker in a CS/PVP blend. Cellulose acetate (CA)-S4 attained an optimal salt rejection of 98.3% and permeation flux of 42.9 L/m2h, suggesting that the NF-TFC membranes could be favorable for seawater desalination.

Implants are widely used in the human body for the replacement of affected bones. Fatigue failure is one of the serious concerns for implants. Therefore, understanding of the underlying mechanism leading to fatigue failure is important for the longevity of biomaterial implants. In this paper, the fracture toughness and fatigue crack growth of titanium alloy biomaterial Ti-27Nb has been experimentally investigated. The Ti-27Nb material is tested for fatigue crack growth in different environmental conditions representing the ambient and in vitro environments for 504 hours and 816 hours, respectively. Fractography of the tested specimen is conducted using Scanning Electron Microscope (SEM). The results of the fatigue crack growth propagation of the ambient and in vitro samples are similar in the Paris crack growth region. However, in the threshold region, the crack growth rate is higher for the Simulated Body Fluid (SBF) treated specimen. The fracture surface morphology of in vitro samples shows brittle fracture as compared to ambient specimens with significant plasticity and striations marks. It is proposed that a similar investigation may be conducted with specimens treated in SBF for prolonged periods to further ascertain the findings of this study.

Polytetrafluoroethylene (PTFE) was coated on 316L stainless steel (SS) substrate through a spin coating technique to enhance its corrosion resistance properties in hydrochloric acid (HCl) and nitric acid (HNO3) medium. Scanning electron microscopy (SEM) revealed the morphology of the coated and uncoated substrates and showed a uniform and crack-free PTFE coating on 316L SS substrate, while a damaged surface with thick corrosive layers was observed after the electrochemical test on the uncoated sample. However, an increased concentration of HCl and HNO3 slightly affected the surface morphology by covering the corrosive pits. An atomic force microscope (AFM) showed that the average surface roughness on 316L SS and PTFE coating was 26.3 nm and 24.1 nm, respectively. Energy dispersive X-ray spectroscopy (EDS) was used for the compositional analysis, which confirmed the presence of PTFE coating. The micro Vickers hardness test was used to estimate the hardness of 316L SS and PTFE-coated substrate, while the scratch test was used to study the adhesion properties of PTFE coating on 316L SS. The anticorrosion measurements of 316L SS and PTFE-coated substrates were made in various HCl and HNO3 solutions by using the electrochemical corrosion test. A comparison of the corrosion performance of PTFE-coated substrate with that of bare 316L SS substrate in HCl medium showed a protection efficiency (PE) of 96.7%, and in the case of HNO3 medium, the PE was 99.02%, by slightly shifting the corrosion potential of the coated sample towards the anodic direction.

In the present work, the pyrolysis of acetylene was studied under steel vacuumcarburizing conditions in a tubular flow reactor. The pyrolysis temperature ranged from650 °C to 1050 °C. The partial pressure of acetylene in the feed mixture was 10 and 20mbar, respectively, while the rest of the mixture consisted of nitrogen. The total pressureof the mixture was 1.6 bar. A kinetic mechanism which consists of seven species andnine reactions has been used in the commercial computational fluid dynamics (CFD)software Fluent. The species transport and reaction model of Fluent was used in thesimulations. A comparison of simulated and experimental results is presented in thispaper.