Search results for: optimal hysteretic energy dissipation systems

Authors: Luleka Dlamini, Olivier Crespo, Jos van Dam

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Accurately estimating crop growth and yield is pivotal for timely sustainable agricultural management and ensuring food security. Crop models and remote sensing can complement each other and form a robust analysis tool to improve crop growth and yield estimations when combined. This study thus aims to systematically evaluate how research that exclusively focuses on assimilating RS data into crop models varies among countries, crops, data assimilation methods, and farming conditions. A strict search string was applied in the Scopus and Web of Science databases, and 497 potential publications were obtained. After screening for relevance with predefined inclusion/exclusion criteria, 123 publications were considered in the final review. Results indicate that over 81% of the studies were conducted in countries associated with high socio-economic and technological advancement, mainly China, the United States of America, France, Germany, and Italy. Many of these studies integrated MODIS or Landsat data into WOFOST to improve crop growth and yield estimation of staple crops at the field and regional scales. Most studies use recalibration or updating methods alongside various algorithms to assimilate remotely sensed leaf area index into crop models. However, these methods cannot account for the uncertainties in remote sensing observations and the crop model itself. l. Over 85% of the studies were based on commercial and irrigated farming systems. Despite a great global interest in data assimilation into crop models, limited research has been conducted in resource- and data-limited regions like Africa. We foresee a great potential for such application in those conditions. Hence facilitating and expanding the use of such an approach, from which developing farming communities could benefit.

Keywords: crop models, remote sensing, data assimilation, crop yield estimation

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Authors: Sanjal Gavande, Thomas Mazzuchi, Shahram Sarkani

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In a complex aerospace operational environment, identifying failures in a procedure involving multiple human-machine interactions are difficult. These failures could lead to accidents causing loss of hardware or human life. The likelihood of failure further increases if operational procedures are tested for a novel system with multiple human-machine interfaces and with no prior performance data. The existing approach in the literature of reviewing complex operational tasks in a flowchart or tabular form doesn’t provide any insight into potential system failures due to human decision-making ability. To address these challenges, this research explores an agent-based simulation approach for reliability assessment and fault detection in complex human-machine systems while utilizing a human decision-making model. The simulation will predict the emergent behavior of the system due to the interaction between humans and their decision-making capability with the varying states of the machine and vice-versa. Overall system reliability will be evaluated based on a defined set of success-criteria conditions and the number of recorded failures over an assigned limit of Monte Carlo runs. The study also aims at identifying high-likelihood failure locations for the system. The research concludes that system reliability and failures can be effectively calculated when individual human and machine agent states are clearly defined. This research is limited to the operations phase of a system lifecycle process in an aerospace environment only. Further exploration of the proposed agent-based and human decision-making model will be required to allow for a greater understanding of this topic for application outside of the operations domain.

Keywords: agent-based model, complex human-machine system, human decision-making model, system reliability assessment

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Authors: Ali Etemadi, Claudia Fernanda Yasar

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Elevated water storage tank structures (EWSTs) are high elevated-ponderous structural systems and very vulnerable to seismic vibrations. In past earthquake events, many of these structures exhibit poor performance and experienced severe damage. The dynamic analysis of the EWSTs under earthquake loads is, therefore, of significant importance for the design of the structure and a key issue for the development of modern methods, such as active control design. In this study, a reduced model of the EWSTs is explained, which is based on a tuned mass damper model (TMD). Vibration analysis of a structure under seismic excitation is presented and then used to propose an active vibration controller. MATLAB/Simulink is employed for dynamic analysis of the system and control of the seismic response. A single degree of freedom (SDOF) and two degree of freedom (2DOF) models of ELSTs are going to be used to study the concept of active vibration control. Lab-scale experimental models similar to pendulum are applied to suppress vibrations in ELST under seismic excitation. One of the most important phenomena in liquid storage tanks is the oscillation of fluid due to the movements of the tank body because of its base motions during an earthquake. Simulation results illustrate that the EWSTs vibration can be reduced by means of an input shaping technique that takes into account the dominant mode shape of the structure. Simulations with which to guide many of our designs are presented in detail. A simple and effective real-time control for seismic vibration damping can be, therefore, design and built-in practice.

Keywords: elevated water storage tank, tuned mass damper model, real time control, shaping control, seismic vibration control, the laplace transform

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Authors: C. Mendoza Ramírez, M. Gambús Ordaz, R. Mercado Ojeda.

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Chemical solutions flooding with surfactants, based on their property of reducing the interfacial tension between crude oil and water, is a potential application of chemical enhanced oil recovery (CEOR), however, the high-rate retention of surfactants associated with adsorption in the porous medium and the complexity of the mineralogical composition of the reservoir rock generates a limitation in the efficiency of displacement of crude oil. This study evaluates the effect of the concentration of a mixture of anionic-non-ionic surfactants with silica nanoparticles, in a rock sample composed of 25.14% clay minerals of the kaolinite, chlorite, halloysite and montmorillonite type, according to the results of X-Ray Diffraction analysis and Scanning Electron Spectrometry (XRD and SEM, respectively). The amount of the surfactant mixture adsorbed on the clay rock minerals was analyzed from the construction of its calibration curve and the 4-Region Isotherm Model in a UV-Visible spectroscopy. The adsorption rate of the surfactant in the clay rock averages 32% across all concentrations, influenced by the presence of the surface area of the substrate with a value of 1.6 m2/g and by the mineralogical composition of the clay that increases the cation exchange capacity (CEC). In addition, on Region I and II a final concentration measurement is not evident in the UV-VIS, due to its ionic nature, its high affinity with the clay rock and its low concentration. Finally, for potential CEOR applications, the adsorption of these mixed surfactant systems is considered due to their industrial relevance and it is concluded that it is possible to use concentrations in Region III and IV; initially the adsorption has an increasing slope and then reaches zero in the equilibrium where interfacial tension values are reached in the order of x10-1 mN/m.

Keywords: anionic–nonionic surfactants, clay rock, adsorption, 4-region isotherm model, cation exchange capacity, critical micelle concentration, enhanced oil recovery

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Authors: Jefferson Camacho Mejía, Jenny Paola Forero Pachón, Luis Carlos Gómez Flórez

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Action research is a qualitative research methodology, which leads the researcher to delve into the problems of a community in order to understand its needs in depth and finally, to propose actions that lead to a change of social paradigm. Although this methodology had its beginnings in the human sciences, it has attracted increasing interest and acceptance in the field of information systems research since the 1990s. The countless possibilities offered nowadays by the use of Information Technologies (IT) in the development of different socio-economic activities have meant a change of social paradigm and the emergence of the so-called information and knowledge society. According to this, governments, large corporations, small entrepreneurs and in general, organizations of all kinds are using IT to virtualize their processes, taking them from the physical environment to the digital environment. However, there is a potential risk for organizations related with exposing valuable information without an appropriate framework for protecting it. This paper shows progress in the development of a methodological design to manage the information security risks associated with the IT-based processes virtualization, by applying the principles of the action research methodology and it is the result of a systematic review of the scientific literature. This design consists of seven fundamental stages. These are distributed in the three stages described in the action research methodology: 1) Observe, 2) Analyze and 3) Take actions. Finally, this paper aims to offer an alternative tool to traditional information security management methodologies with a view to being applied specifically in the planning stage of IT-based process virtualization in order to foresee risks and to establish security controls before formulating IT solutions in any type of organization.

Keywords: action research, information security, information technology, methodological design, process virtualization, risk management

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Authors: David L. Olson, Stephen B. H. Bruder, Adam S. Watkins, Cleon E. Davis

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In global navigation satellite systems (GNSS), denied settings such as indoor environments, autonomous mobile robots are often limited to dead-reckoning navigation techniques to determine their position, velocity, and attitude (PVA). Localization is typically accomplished by employing an inertial measurement unit (IMU), which, while precise in nature, accumulates errors rapidly and severely degrades the localization solution. Standard sensor fusion methods, such as Kalman filtering, aim to fuse precise IMU measurements with accurate aiding sensors to establish a precise and accurate solution. In indoor environments, where GNSS and no other a priori information is known about the environment, effective sensor fusion is difficult to achieve, as accurate aiding sensor choices are sparse. However, an opportunity arises by employing a depth camera in the indoor environment. A depth camera can capture point clouds of the surrounding floors and walls. Extracting attitude from these surfaces can serve as an accurate aiding source, which directly combats errors that arise due to gyroscope imperfections. This configuration for sensor fusion leads to a dramatic reduction of PVA error compared to traditional aiding sensor configurations. This paper provides the theoretical basis for the depth camera aiding sensor method, initial expectations of performance benefit via simulation, and hardware implementation, thus verifying its veracity. Hardware implementation is performed on the Quanser Qbot 2™ mobile robot, with a Vector-Nav VN-200™ IMU and Kinect™ camera from Microsoft.

Keywords: autonomous mobile robotics, dead reckoning, depth camera, inertial navigation, Kalman filtering, localization, sensor fusion

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Authors: Srinivas Vangari

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In the era of big data, ensuring the accuracy, consistency, and reliability of critical data assets is crucial for data-driven enterprises. Master Data Management (MDM) plays a crucial role in this endeavor. This paper investigates the role of Artificial Intelligence (AI) in enhancing MDM, focusing on how AI-driven solutions can automate and optimize various stages of the master data lifecycle. By integrating AI (Quantitative and Qualitative Analysis) into processes such as data creation, maintenance, enrichment, and usage, organizations can achieve significant improvements in data quality and operational efficiency. Quantitative analysis is employed to measure the impact of AI on key metrics, including data accuracy, processing speed, and error reduction. For instance, our study demonstrates an 18% improvement in data accuracy and a 75% reduction in duplicate records across multiple systems post-AI implementation. Furthermore, AI’s predictive maintenance capabilities reduced data obsolescence by 22%, as indicated by statistical analyses of data usage patterns over a 12-month period. Complementing this, a qualitative analysis delves into the specific AI-driven strategies that enhance MDM practices, such as automating data entry and validation, which resulted in a 28% decrease in manual errors. Insights from case studies highlight how AI-driven data cleansing processes reduced inconsistencies by 25% and how AI-powered enrichment strategies improved data relevance by 24%, thus boosting decision-making accuracy. The findings demonstrate that AI significantly enhances data quality and integrity, leading to improved enterprise performance through cost reduction, increased compliance, and more accurate, real-time decision-making. These insights underscore the value of AI as a critical tool in modern data management strategies, offering a competitive edge to organizations that leverage its capabilities.

Keywords: artificial intelligence, master data management, data governance, data quality

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Authors: Hannah K. M. Tang, Muhammad Ateeq, Mark J. Lake, Badr Abdullah, Frederic A. Bezombes

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There is little research applying virtual reality (VR) to the treatment of musculoskeletal injury in athletes. This is despite their prevalence, and the implications for physical and psychological health. Nevertheless, developments of wireless VR headsets better facilitate dynamic movement in VR environments (VREs), and more research is expected in this emerging field. This systematic review identified publications that used VR interventions for the analysis or treatment of lower-limb musculoskeletal injury of athletes. It established a search protocol, and through narrative discussion, identified existing trends. Database searches encompassed four term sets: 1) VR systems; 2) musculoskeletal injuries; 3) sporting population; 4) movement outcome analysis. Overall, a total of 126 publications were identified through database searching, and twelve were included in the final analysis and discussion. Many of the studies were pilot and proof of concept work. Seven of the twelve publications were observational studies. However, this may provide preliminary data from which clinical trials will branch. If specified, the focus of the literature was very narrow, with very similar population demographics and injuries. The trends in the literature findings emphasised the role of VR and attentional focus, the strategic manipulation of movement outcomes, and the transfer of skill to the real-world. Causal inferences may have been undermined by flaws, as most studies were limited by the practicality of conducting a two-factor clinical-VR-based study. In conclusion, by assessing the exploratory studies, and combining this with the use of numerous developments, techniques, and tools, a novel application could be established to utilise VR with dynamic movement, for the effective treatment of specific musculoskeletal injuries of athletes.

Keywords: athletes, lower-limb musculoskeletal injury, rehabilitation, return-to-sport, virtual reality

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Authors: Sharda Kumari, Saiman Shetty

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Autonomous trucking is just one of the numerous significant shifts impacting fleet management services. The Society of Automotive Engineers (SAE) has defined six levels of vehicle automation that have been adopted internationally, including by the United States Department of Transportation. On public highways in the United States, organizations are testing driverless vehicles with at least Level 4 automation which indicates that a human is present in the vehicle and can disable automation, which is usually done while the trucks are not engaged in highway driving. However, completely driverless vehicles are presently being tested in the state of California. While autonomous trucking can increase safety, decrease trucking costs, provide solutions to trucker shortages, and improve efficiencies, logistics, too, requires advancements to keep up with trucking innovations. Given that artificial intelligence, machine learning, and automated procedures enable people to do their duties in other sectors with fewer resources, CRM (Customer Relationship Management) can be applied to the autonomous trucking business to provide the same level of efficiency. In a society witnessing significant digital disruptions, fleet management is likewise being transformed by technology. Utilizing strategic alliances to enhance core services is an effective technique for capitalizing on innovations and delivering enhanced services. Utilizing analytics on CRM systems improves cost control of fuel strategy, fleet maintenance, driver behavior, route planning, road safety compliance, and capacity utilization. Integration of autonomous trucks with automated fleet management, yard/terminal management, and customer service is possible, thus having significant power to redraw the lines between the public and private spheres in autonomous trucking logistics.

Keywords: autonomous vehicles, customer relationship management, customer experience, autonomous trucking, digital transformation

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Authors: N. Stoeva, I. Spassova, R. Nickolov, M. Khristova

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Exhaust gases from stationary and mobile combustion sources contain nitrogen oxides that cause a variety of environmentally harmful effects. The most common approach of their elimination is the catalytic reaction in the exhaust using various reduction agents such as NH3, CO and hydrocarbons. Transition metals (Co, Ni, Cu, etc.) are the most widely used as active components for deposition on various supports. However, since the interaction between different catalyst components have been extensively studied in different types of reaction systems, the possible cooperation between active components and the support material and the underlying mechanisms have not been thoroughly investigated. The support structure may affect how these materials maintain an active phase. The objective is to investigate the addition of carbonaceous materials with different nature and texture characteristics on the properties of the resulting silica-carbon support and how it influences of the catalytic properties of the supported copper and cobalt catalysts for reduction of NO with CO. The versatility of the physico-chemical properties of the composites and the supported copper and cobalt catalysts are discussed with an emphasis on the relationship of the properties with the catalytic performance. The catalysts were prepared by sol-gel process and were characterized by XRD, XPS, AAS and BET analysis. The catalytic experiments were carried out in catalytic flow apparatus with isothermal flow reactor in the temperature range 20–300оС. After the catalytic test temperature-programmed desorption (TPD) was carried out. The transient response method was used to study the interaction of the gas phase with the catalyst surface. The role of the interaction between the support and the active phase on the catalyst’s activity in the studied reaction was discussed. We suppose the carbon particles with small sizes to participate in the formation of the active sites for the reduction of NO with CO along with their effect on the kind of deposited metal oxide phase. The existence of micropore texture for some of composites also influences by mass-transfer limitations.

Keywords: catalysts, no reduction, composites, bet analysis

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Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: Devi Eka Septiyani Arifin, Jrjeng Ruan

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As an approach to manipulate the performance of polymer thin film, epitaxy crystallization within polymer blends of poly(vinylidene fluoride) (PVDF) and its copolymer poly(vinylidene fluoride-trifluoroethylene) P(VDF-TrFE) was studied in this research, which involves the competition between phase separation and crystal growth of constitutive semicrystalline polymers. The unique piezoelectric feature of poly(vinylidene fluoride) crystalline phase is derived from the packing of molecular chains in all-trans conformation, which spatially arranges all the substituted fluorene atoms on one side of the molecular chain and hydrogen atoms on the other side. Therefore, the net dipole moment is induced across the lateral packing of molecular chains. Nevertheless, due to the mutual repulsion among fluorene atoms, this all-trans molecular conformation is not stable, and ready to change above curie temperature, where thermal energy is sufficient to cause segmental rotation. This research attempts to explore whether the epitaxial interactions between piezoelectric crystals and crystal lattice of hexamethylbenzene (HMB) crystalline platelet is able to stabilize this metastable all-trans molecular conformation or not. As an aromatic crystalline compound, the melt of HMB was surprisingly found able to dissolve the poly(vinylidene fluoride), resulting in homogeneous eutectic solution. Thus, after quenching this binary eutectic mixture to room temperature, subsequent heating or annealing processes were designed to explore the involve phase separation and crystallization behavior. The phase transition behaviors were observed in-situ by X-ray diffraction and differential scanning calorimetry (DSC). The molecular packing was observed via transmission electron microscope (TEM) and the principles of electron diffraction were brought to study the internal crystal structure epitaxially developed within thin films. Obtained results clearly indicated the occurrence of heteroepitaxy of PVDF/PVDF-TrFE on HMB crystalline platelet. Both the concentration of poly(vinylidene fluoride) and the mixing ratios of these two constitutive polymers have been adopted as the influential factors for studying the competition between the epitaxial crystallization of PVDF and P(VDF-TrFE) on HMB crystalline. Furthermore, the involved epitaxial relationship is to be deciphered and studied as a potential factor capable of guiding the wide spread of piezoelectric crystalline form.

Keywords: epitaxy, crystallization, crystalline platelet, thin film and mixing ratio

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Authors: S. Amirhossein Tabatabaei, Abdulghader A. Aldaeef, Mohammad T. Rayhani

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As the permafrost continues to melt in the northern regions due to global warming, a soil-water mixture is left behind with drastically lower strength; a phenomenon that directly impacts the resilience of existing structures and infrastructure systems. The frozen soil-structure interaction, which in ice-poor soils is controlled by both interface shear and ice-bonding, changes its nature into a sole frictional state. Adfreeze, the controlling mechanism in frozen soil-structure interaction, diminishes as the ground temperature approaches zero. The main purpose of this paper is to capture the altered behaviour of frozen interface with respect to rising temperature, especially near melting states. A series of pull-out tests are conducted on model piles inside a cold room to study how the strength parameters are influenced by the phase change in ice-poor soils. Steel model piles, embedded in artificially frozen cohesionless soil, are subjected to both sustained pull-out forces and constant rates of displacement to observe the creep behaviour and acquire load-deformation curves, respectively. Temperature, as the main variable of interest, is increased from a lower limit of -10°C up to the point of melting. During different stages of the temperature rise, both skin deformations and temperatures are recorded at various depths along the pile shaft. Significant reduction of pullout capacity and accelerated creep behaviour is found to be the primary consequences of rising temperature. By investigating the different pull-out capacities and deformations measured during step-wise temperature change, characteristics of the transition from frozen to unfrozen soil-structure interaction are studied.

Keywords: Adfreeze, frozen soil-structure interface, ice-poor soils, pull-out capacity, warming permafrost

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Authors: Yuexi Xiong, Jingwu He

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The structural components in an energy facility such as steam turbine machines are operated under high stress and elevated temperature in an endured time period and thus the creep deformation and creep rupture failure are important issues that need to be addressed in the design of such components. There are numerous creep models being used for creep analysis that have both advantages and disadvantages in terms of accuracy and efficiency. The Isochronous Creep Analysis is one of the simplified approaches in which a full-time dependent creep analysis is avoided and instead an elastic-plastic analysis is conducted at each time point. This approach has been established based on the rupture dependent creep equations using the well-known Larson-Miller parameter. In this paper, some fundamental aspects of creep deformation and the rupture dependent creep models are reviewed and the analysis procedures using isochronous creep curves are discussed. Four rupture failure criteria are examined from creep fundamental perspectives including criteria of Stress Damage, Strain Damage, Strain Rate Damage, and Strain Capability. The accuracy of these criteria in predicting creep life is discussed and applications of the creep analysis procedures and failure predictions of simple models will be presented. In addition, a new failure criterion is proposed to improve the accuracy and effectiveness of the existing criteria. Comparisons are made between the existing criteria and the new one using several examples materials. Both strain increase and stress relaxation form a full picture of the creep behaviour of a material under high temperature in an endured time period. It is important to bear this in mind when dealing with creep problems. Accordingly there are two sets of rupture dependent creep equations. While the rupture strength vs LMP equation shows how the rupture time depends on the stress level under load controlled condition, the strain rate vs rupture time equation reflects how the rupture time behaves under strain-controlled condition. Among the four existing failure criteria for rupture life predictions, the Stress Damage and Strain Damage Criteria provide the most conservative and non-conservative predictions, respectively. The Strain Rate and Strain Capability Criteria provide predictions in between that are believed to be more accurate because the strain rate and strain capability are more determined quantities than stress to reflect the creep rupture behaviour. A modified Strain Capability Criterion is proposed making use of the two sets of creep equations and therefore is considered to be more accurate than the original Strain Capability Criterion.

Keywords: creep analysis, high temperature mateials, rapture evalution, steam turbine machines

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Authors: Leila Azadbakht, Maedeh Moradi, Mohammad Reza Merasi, Farzaneh Jahangir

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Maternal dietary intake during lactation might affect the growth rate of an exclusive breastfed infant. The present study was conducted to evaluate the effect of maternal dietary patterns and quality during lactation on the growth of the exclusive breastfed infant. Methods: 484 healthy lactating mothers with their infant were enrolled in this study. Only exclusive breastfed infants were included in this study which was conducted in Iran. Dietary intake of lactating mothers was assessed using a validated and reliable semi-quantitative food frequency questionnaire. Diet quality indices such as alternative Healthy eating index (HEI), Dietary energy density (DED), and adherence to Mediterranean dietary pattern score, Nordic and dietary approaches to stop hypertension (DASH) eating pattern were created. Anthropometric features of infant (weight, height, and head circumference) were recorded at birth, two and four months. Results: Weight, length, weight for height and head circumference of infants at two months and four months age were mostly in the normal range among those that mothers adhered more to the HEI in lactation period (normal weight: 61%; normal height: 59%). The prevalence of stunting at four months of age among those whose mothers adhered more to the HEI was 31% lower than those with the least adherence to HEI. Mothers in the top tertiles of HEI score had the lowest frequency of having underweight infants (18% vs. 33%; P=0.03). Odds ratio of being overweight or obese at four months age was the lowest among those infants whose mothers adhered more to the HEI (OR: 0.67 vs 0.91; Ptrend=0.03). However, there was not any significant association between adherence of mothers to Mediterranean diet as well as DASH diet and Nordic eating pattern and the growth of infants (none of weight, height or head circumference). Infant weight, length, weight for height and head circumference at two months and four months did not show significant differences among different tertile categories of mothers’ DED. Conclusions: Higher diet quality indices and more adherence of lactating mother to HEI (as an indicator of diet quality) may be associated with better growth indices of the breastfed infant. However, it seems that DED of the lactating mother does not affect the growth of the breastfed infant. Adherence to the different dietary patterns such as Mediterranean, DASH or Nordic among mothers had no different effect on the growth indices of the infants. However, higher diet quality indices and more adherence of lactating mother to HEI may be associated with better growth indices of the breastfed infant. Breastfeeding is a complete way that is not affected much by the dietary patterns of the mother. However, better diet quality might be associated with better growth.

Keywords: breastfeeding, growth, infant, maternal diet

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Authors: Suraj Makkar, Asis Isor, Jeetendra Gupta, Simran Bareja, Maushumi K. Talukdar

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During the exploratory testing phase of an offshore oil and gas well, when the tubing string was pulled out after production testing, it was observed that there was visible corrosion/pitting in a few of the 3-1/2” API 5 CT L-80 Grade tubing. The area of corrosion was at the same location in all the tubing, i.e., just above the pin end. Since the corrosion was observed in the tubing within two months of their installation, it was a matter of concern, as it could lead to premature failures resulting in leakages and production loss and thus affecting the integrity of the asset. Therefore, the tubing was analysed to ascertain the mechanism of the corrosion occurring on its surface. During the visual inspection, it was observed that the corrosion was totally external, which was near the pin end, and no significant internal corrosion was observed. The chemical compositional analysis and mechanical properties (tensile and impact) show that the pipeline material was conforming to API 5 CT L-80 specifications. The metallographic analysis of the tubing revealed tempered martensitic microstructure. The grain size was observed to be different at the pin end as compared to the microstructure at base metal. The microstructures of the corroded area near threads reveal an oriented microstructure. The clearly oriented microstructure of the cold-worked zone near threads and the difference in microstructure represents inappropriate heat treatment after cold work. This was substantiated by hardness test results as well, which show higher hardness at the pin end in comparison to hardness at base metal. Scanning Electron Microscope (SEM) analysis revealed the presence of round and deep pits and cracks on the corroded surface of the tubing. The cracks were stress corrosion cracks in a corrosive environment arising out of the residual stress, which was not relieved after cold working, as mentioned above. Energy Dispersive Spectroscopy (EDS) analysis indicates the presence of mainly Fe₂O₃, Chlorides, Sulphides, and Silica in the corroded part indicating the interaction of the tubing with the well completion fluid and well bore environment. Thus it was concluded that residual stress after the cold working of male pins during threading and the corrosive environment acted in synergy to cause this pitting corrosion attack on the highly stressed zone along the circumference of the tubing just below the threaded area. Accordingly, the following suitable recommendations were given to avoid the recurrence of such corrosion problems in the wells. (i) After any kind of hot work/cold work, tubing should be normalized at full length to achieve uniform microstructure throughout its length. (ii) Heat treatment requirements (as per API 5 CT) should be part of technical specifications while at the procurement stage.

Keywords: pin end, microstructure, grain size, stress corrosion cracks

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Authors: Waqqas-ur-Rehman Butt, Martin Servin, Marion Pause

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In recent years, object detection has gained much attention and very encouraging research area in the field of computer vision. The robust object boundaries detection in an image is demanded in numerous applications of human computer interaction and automated surveillance systems. Many methods and approaches have been developed for automatic object detection in various fields, such as automotive, quality control management and environmental services. Inappropriately, to the best of our knowledge, object detection under illumination with shadow consideration has not been well solved yet. Furthermore, this problem is also one of the major hurdles to keeping an object detection method from the practical applications. This paper presents an approach to automatic object detection in images under non-standardized environmental conditions. A key challenge is how to detect the object, particularly under uneven illumination conditions. Image capturing conditions the algorithms need to consider a variety of possible environmental factors as the colour information, lightening and shadows varies from image to image. Existing methods mostly failed to produce the appropriate result due to variation in colour information, lightening effects, threshold specifications, histogram dependencies and colour ranges. To overcome these limitations we propose an object detection algorithm, with pre-processing methods, to reduce the interference caused by shadow and illumination effects without fixed parameters. We use the Y CrCb colour model without any specific colour ranges and predefined threshold values. The segmented object regions are further classified using morphological operations (Erosion and Dilation) and contours. Proposed approach applied on a large image data set acquired under various environmental conditions for wood stack detection. Experiments show the promising result of the proposed approach in comparison with existing methods.

Keywords: image processing, illumination equalization, shadow filtering, object detection

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Authors: Bahadır Erişti

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Values are the behavioral procedures of society based communication and interaction process that includes social and cultural backgrounds. The policy of learning and teaching in higher education is oriented towards constructing knowledge and skills, based on theorist framework of cognitive and psychomotor aspects. This approach makes people not to develop generosity, empathy, affection, solidarity, justice, equality and so on. But the sensorial gains of education system provide the integrity of society interaction. This situation carries out the necessity of values education’s in higher education. The current study aims to consider values education from the viewpoint of students in higher education. Within the framework of the current study, an open ended survey based scenario of higher education students was conducted with the students’ social, cognitive, affective and moral developments. In line with this purpose, the following situations of the higher education system were addressed based on the higher education students’ viewpoint: The views of higher education students’ regarding values that are tried to be gained at the higher education system; The higher education students’ suggestions regarding values education at the higher education system; The views of the higher education students’ regarding values that are imposed at the higher education system. In this study, descriptive qualitative research method was used. The study group of the research is composed of 20 higher education postgraduate students at Curriculum and Instruction Department of Educational Sciences at Anadolu University. An open-ended survey was applied for the purpose of collecting qualitative data. As a result of the study, value preferences, value judgments and value systems of the higher education students were constructed on prioritizes based on social, cultural and economic backgrounds and statues. Multi-dimensional process of value education in higher education need to be constructed on higher education-community-cultural background cooperation. Thus, the act of judgement upon values between higher education students based on the survey seems to be inherent in the system of education itself. The present study highlights the students’ value priorities and importance of values in higher education. If the purpose of the higher education system gains on values, it is possible to enable society to promote humanity.

Keywords: higher education, value, values education, values in higher education

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Authors: Hauwau Mohammed

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Research purpose: the integration of Traditional Birth Attendants (TBAs) has long been initiated into healthcare systems. This has been to help improve maternal mortality, particularly in developing countries. Nigeria is seen as one of the countries with a high maternal death rate due to common pregnancy complications and low resources. Communities with challenges of universal coverage of skilled workers rely on TBAs for pregnancy-related services, including delivery. The Sokoto State government has conducted several training programs on a significant number of TBAs to enable a formal integration of relationships with skilled healthcare for women in rural regions. This study aims to explore a standard method and develop an assessment framework for improving TBAs training programs in Sokoto State. Research Design, Methodology & Methods : Using a qualitative design, an interpretive phenomenology approach will be applied to explore the lived-experiences of 28 TBAs, who have undergone a form of training while also examining the strategies used to develop those programs through 8 policymakers and/or program trainers. For the collection stage, a focus group discussion and a face-to-face interview will be conducted, where the latter is for TBAs and the former for policymakers and training officials. Analysis: Data will be analyse through IPA format while using Nvivo to code and catalog personal experiential generated patterns. Secondary review: a scoping review of secondary data from Nigeria was used to map the knowledge gap and the extent of available data. The thematic analytic findings suggested that there are various approaches used to incorporate TBAs into the healthcare system, which include interventional programs targeted at specific health issues. In addition, incentives were used to encourage TBAs to facilitate the frequent use of skilled care for women.

Keywords: traditional birth attendants, Nigeria, training, program

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Authors: Linghui Meng, James Atlas, Deborah Munro

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There is an increasing demand for prosthetics capable of mimicking natural limb movements and hand gestures, but precise movement control of prosthetics using only electrode signals continues to be challenging. This study considers the implementation of machine learning as a means of improving accuracy and presents an initial investigation into hand gesture recognition using models based on electromyographic (EMG) signals. EMG signals, which capture muscle activity, are used as inputs to machine learning algorithms to improve prosthetic control accuracy, functionality and adaptivity. Using logistic regression, a machine learning classifier, this study evaluates the accuracy of classifying two hand gestures from the publicly available Ninapro dataset using two-time series feature extraction algorithms: Time Series Feature Extraction (TSFE) and Convolutional Neural Networks (CNNs). Trials were conducted using varying numbers of EMG channels from one to eight to determine the impact of channel quantity on classification accuracy. The results suggest that although both algorithms can successfully distinguish between hand gesture EMG signals, CNNs outperform TSFE in extracting useful information for both accuracy and computational efficiency. In addition, although more channels of EMG signals provide more useful information, they also require more complex and computationally intensive feature extractors and consequently do not perform as well as lower numbers of channels. The findings also underscore the potential of machine learning techniques in developing more effective and adaptive prosthetic control systems.

Keywords: EMG, machine learning, prosthetic control, electromyographic prosthetics, hand gesture classification, CNN, computational neural networks, TSFE, time series feature extraction, channel count, logistic regression, ninapro, classifiers

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Authors: G. Ravindranath, S. Savitha

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This paper presents heat transfer analysis of single horizontal bare tube and heat transfer analysis of staggered arrangement of bare tube bundles bare tube bundles in gas-solid (air-solid) fluidized bed and predictions are done by using Artificial Neural Network (ANN) based on experimental data. Fluidized bed provide nearly isothermal environment with high heat transfer rate to submerged objects i.e. due to through mixing and large contact area between the gas and the particle, a fully fluidized bed has little temperature variation and gas leaves at a temperature which is close to that of the bed. Measurement of average heat transfer coefficient was made by local thermal simulation technique in a cold bubbling air-fluidized bed of size 0.305 m. x 0.305 m. Studies were conducted for single horizontal Bare Tube of length 305mm and 28.6mm outer diameter and for bare tube bundles of staggered arrangement using beds of large (average particle diameter greater than 1 mm) particle (raagi and mustard). Within the range of experimental conditions influence of bed particle diameter ( Dp), Fluidizing Velocity (U) were studied, which are significant parameters affecting heat transfer. Artificial Neural Networks (ANNs) have been receiving an increasing attention for simulating engineering systems due to some interesting characteristics such as learning capability, fault tolerance, and non-linearity. Here, feed-forward architecture and trained by back-propagation technique is adopted to predict heat transfer analysis found from experimental results. The ANN is designed to suit the present system which has 3 inputs and 2 out puts. The network predictions are found to be in very good agreement with the experimental observed values of bare heat transfer coefficient (hb) and nusselt number of bare tube (Nub).

Keywords: fluidized bed, large particles, particle diameter, ANN

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Authors: A. Pietro Rimoldi, B. Anilkumar Gopinath, C. Minimol Korulla

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Coastal engineering structure is conventionally designed for a shorter planning horizon usually 20 years. These structures are subjected to different offshore climatic externalities like waves, tides, tsunamis etc. during the design life period. The probability of occurrence of these different offshore climatic externalities varies. The impact frequently caused by these externalities on the structures is of concern because it has a significant bearing on the capital /operating cost of the project. There can also be repeated short time occurrence of these externalities in the assumed planning horizon which can cause heavy damage to the conventional coastal structure which are mainly made of rock. A replacement of the damaged portion to prevent complete collapse is time consuming and expensive when dealing with hard rock structures. But if coastal structures are made of Geo-synthetic containment systems such replacement is quickly possible in the time period between two successive occurrences. In order to have a better knowledge and to enhance the predictive capacity of these occurrences, this study estimates risk of encounter within the design life period of various externalities based on the concept of exponential distribution. This gives an idea of the frequency of occurrences which in turn gives an indication of whether replacement is necessary and if so at what time interval such replacements have to be effected. To validate this theoretical finding, a pilot project has been taken up in the field so that the impact of the externalities can be studied both for a hard rock and a Geosynthetic tube structure. The paper brings out the salient feature of a case study which pertains to a project in which Geosynthetic tubes have been used for reformation of a seawall adjacent to a conventional rock structure in Alappuzha coast, Kerala, India. The effectiveness of the Geosystem in combatting the impact of the short-term externalities has been brought out.

Keywords: climatic externalities, exponential distribution, geosystems, planning horizon

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Authors: Veerle Van Hoeck, Ingrid Somers, Dany Morisset

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Anti-nutritional factors such as non-starch polysaccharides (NSP) are present in viscous cereals used to feed poultry. Therefore, exogenous carbohydrases are commonly added to monogastric feed to degrade these NSP. Our hypothesis is that xylanase not only improves laying hen performance and digestibility but also induces a significant shift in microbial composition within the intestinal tract and, thereby, can cause a prebiotic effect. In this context, a better understanding of whether and how the chicken gut flora can be modulated by xylanase is needed. To do so, in the herein laying hen study, the effects of dietary supplementation of xylanase on performance, digestibility, and cecal microbiome were evaluated. A total of 96 HiSex laying hens was used in this experiment (3 diets and 16 replicates of 2 hens). Xylanase was added to the diets at concentrations of 0, 45,000 (15 g/t XygestTM HT) and 90,000 U/kg (30 g/t Xygest HT). The diets were based on wheat (~55 %), soybean, and sunflower meal. The lowest dosage, 45,000 U/kg, significantly increased average egg weight and improved feed efficiency compared to the control treatment (p < 0.05). Egg quality parameters were significantly improved in the experiment in response to the xylanase addition. For example, during the last 28 days of the trial, the 45,000 U/kg and the 90,000 U/kg treatments exhibited an increase in Haugh units and albumin heights (p < 0.05). Compared with the control, organic matter digestibility and N retention were drastically improved in the 45,000 U/kg treatment group, which implies better nutrient digestibility at this lowest recommended dosage compared to the control (p < 0.05). Furthermore, gross energy and crude fat digestibility were improved significantly for birds fed 90,000 U/kg group compared to the control. Importantly, 16S rRNA gene analysis revealed that xylanase at 45,000 U/kg dosages can exert a prebiotic effect. This conclusion was drawn based on studying the sequence variation in the 16S rRNA gene in order to characterize diverse microbial communities of the cecal content. A significant increase in beneficial bacteria (Lactobacilli spp and Enterococcus casseliflavus) was documented when adding 45,000 U/kg xylanase to the diet of laying hens. In conclusion, dietary supplementation of xylanase, even at the lowest dose of (45,000 U/kg), significantly improved laying hen performance and digestibility. Furthermore, it is generally accepted that a proper bacterial balance between the number of beneficial bacteria and pathogenic bacteria in the intestine is vital for the host. It seems that the xylanase enzyme is able to modulate the laying hen microbiome beneficially and thus exerts a prebiotic effect. This microbiome plasticity in response to the xylanase provides an attractive target for stimulating intestinal health.

Keywords: laying hen, prebiotic, XygestTM HT, xylanase

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Authors: Douglas Arthur, Oluwayemisi Ekor, Ernest Obese, Andrew Kissi Agyei, Elvis Ofori Ameyaw

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bjective: Pain negatively impacts every aspect of health, and patients with pain disorders create enormous demands on healthcare systems globally, costing economies up to $635 billion annually. The study was therefore conducted at the Cape Coast Teaching Hospital (CCTH), the only Tertiary Hospital in the Central Region of Ghana and was designed to assess pain disorders in patients between 18 and 90 years attending Urology Clinic. Methods: The study employed a descriptive cross-sectional design, and 149 subjects (16-24, 25-34, 35-44, 45-54, 55-64, 65-90 years) were conveniently selected. The McGill Pain Questionnaire (MPQ), a multidimensional instrument that assesses several aspects of pain by the use of words (descriptors) that the patient chooses to express his/her pain, was used as the primary instrument for data collection. A patient profile form (PPF) was also designed to document the demographics and history of patients. Results: The prevalence of pain disorders was higher among females compared to males. The univariate and multivariate analysis showed that females were more likely to experience pain while being married correlated with a lower likelihood of pain. Again, the 45-54 age group exhibited the highest prevalence of pain disorders. Results from the MPQ showed that half of the patients experienced pain on a daily basis, 15.91% had experienced pain for 3-6 months and 37% experienced pain for more than one year. Pain intensity was described by 25% of the subjects as excruciating for their worst pain experience, followed by 21% for the distressing experience. The most frequently reported area of pain was the abdominal region (22.72%). The co-administration of NSAIDs and opioid compounds was provided for 17.46% of the patients with chronic pain. Conclusion: The treatment interventions improved the pain and associated symptoms such as nausea, improved daily activities and ability to sleep. However, attention and resources should be devoted to 45-54 age group.

Keywords: pain, opioids, distressing, excruciating

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Authors: Jessy Rugeyo, William Donner

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This research delves into the resilience of Rwanda's public health infrastructure amidst natural disasters, a critical issue given that the Northern Province alone has witnessed no fewer than 1500 cases of disaster ranging from floods and landslides in the last five years, with more than 200 people killed and thousands of homes destroyed, according to MINEMA. In an era where climate change escalates the frequency and intensity of such disasters, fortifying the resilience of public health systems is paramount. This study offers a comprehensive analysis of the existing state of Rwanda's public health infrastructure and its ability to manage such crises. Employing a mix of literature review, case studies, and policy analysis, the study discerns key vulnerabilities and brings to light the intricacies of disaster management in Rwanda. Case studies centered around past natural disasters in Rwanda provide critical insights into the strengths and weaknesses of the existing disaster response mechanisms. A thorough critique of related disaster management and public health infrastructure policies reveals areas of commendable practice, along with gaps calling for policy enhancements. Findings guide the proposition of targeted strategies to bolster the resilience of Rwanda's public health infrastructure. This research serves as a significant contribution to the domains of disaster studies and public health, offering valuable insights for policymakers, public health and disaster management professionals in Rwanda and similar contexts. It presents actionable recommendations for improvement, underscoring the potential for enhancing Rwanda's disaster management capacity. By advocating for the strengthening of public health infrastructure resilience, the research highlights the potential for improved public health outcomes following natural disasters, thereby showcasing significant implications for public health and disaster management in the country, particularly in the face of a changing climate.

Keywords: public health infrastructure, disaster resilience, natural disaster, disaster management, emergency preparedness, health policy

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Authors: Paolo Di Pietro, Matteo Lelli, Kinjal Parmar

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Water hazards are consistently identified as among the highest global risks in terms of impact. Riverbank protection plays a key role in flood risk management. For erosion control and scour protection, flexible solutions like gabions & mattresses are being used since quite some time now. The efficacy of erosion control systems depends both on the ability to prevent soil loss underneath, as well as to maintain their integrity under the effects of the water flow. The paper presents the results of a research carried out at the Colorado State University on the performance of double twisted wire mesh products, known as Reno Mattresses, used as soil erosion control system. Mattresses were subjected to various flow conditions on a 10m long flume where they were placed on a 0.30 m thick soil layer. The performance against erosion was evaluated by assessing the effect of the stone motion inside the mattress combined with the condition of incipient soil erosion underneath, in relationship to the mattress thickness, the filling stone properties and under variable hydraulic flow regimes. While confirming the stability obtained using a conventional design approach (commonly referred to tractive force theories), the results of the research allowed to introduce a new performance limit based on incipient soil erosion underneath the revetment. Based on the research results, the authors propose to express the shear resistance of mattresses used as soil erosion control system as a function of the size of the filling stones, their uniformity, their unit weight, the thickness of the mattress, and the presence of vertical connecting elements between the mattress lid and bottom.

Keywords: Reno Mattress, riverbank protection, hydraulics, full scale tests

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Authors: Lisa Shambare, Jean Mulopo, Sehliselo Ndlovu

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One of the major challenges of sustainable development is promoting an industry which is both ecologically durable and economically viable. This requires processes that are material and energy efficient whilst also being able to limit the production of waste and toxic effluents through effective methods of process synthesis and intensification. In South Africa and globally, both miniaturisation and technological advances have substantially increased the amount of electronic wastes (e-waste) generated annually. Vast amounts of e-waste are being generated yearly with only a minute quantity being recycled officially. The passion for electronic devices cannot ignore the scarcity and cost of mining the noble metal resources which contribute significantly to the efficiency of most electronic devices. It has hence become imperative especially in an African context that sustainable strategies which are environmentally friendly be developed for recycling of the noble metals from e-waste. This paper investigates the recovery of gold, silver and palladium from electronic wastes, which consists of a vast array of metals, using ionic liquids which have the potential of reducing the gaseous and aqueous emissions associated with existing hydrometallurgical and pyrometallurgical technologies while also maintaining the economy of the overall recycling scheme through solvent recovery. The ionic liquids 1-butyl-3-methyl imidazolium hydrogen sulphate (BmimHSO4) which behaves like a protic acid and was used in the present research for the selective leaching of gold and silver from e-waste. Different concentrations of the aqueous ionic liquid were used in the experiments ranging from 10% to 50%. Thiourea was used as the complexing agent in the investigation with Fe3+ as the oxidant. The pH of the reaction was maintained in the range of 0.8 to 1.5. The preliminary investigations conducted were successful in the leaching of silver and palladium at room temperature with optimum results being at 48hrs. The leaching results could not be explained because of the leaching of palladium with the absence of gold. Hence a conclusion could not be drawn and there was the need for further experiments to be run. The leaching of palladium was carried out with hydrogen peroxide as oxidant and 1-butyl-3-methyl imidazolium chloride (BmimCl) as the solvent. The experiments at carried out at a temperature of 60 degrees celsius and a very low pH. The chloride ion was used to complex with palladium metal. From the preliminary results, it could be concluded that pretreatment of the treatment e-waste was necessary to improve the efficiency of the metal recovery process. A conclusion could not be drawn for the leaching experiments.

Keywords: BmimCl, BmimHSO4, gold, palladium, silver

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Authors: Parinyaporn Thanaboonpuang, Siridej Sujiva, Shotiga Pasiphul

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The higher education reform that integration of nursing programmes into the higher education system. Learning outcomes represent one of the essential building blocks for transparency within higher education systems and qualifications. The purpose of this study is to develop a toolkit of undergraduate nursing student’desirable characteristics assessment on Thai Qualifications Framework for Higher education and to test psychometric property for this instrument. This toolkit seeks to improve on the Computer Multimedia test. There are three skills to be examined: Cognitive skill, Responsibility and Interpersonal Skill, and Information Technology Skill. The study was conduct in 4 phases. In Phase 1. Based on developed a measurement model and Computer Multimedia test. Phase 2 two round focus group were conducted, to determine the content validity of measurement model and the toolkit. In Phase 3, data were collected using a multistage random sampling of 1,156 senior undergraduate nursing student were recruited to test psychometric property. In Phase 4 data analysis was conducted by descriptive statistics, item analysis, inter-rater reliability, exploratory factor analysis and confirmatory factor analysis. The resulting TNDC consists of 74 items across the following four domains: Cognitive skill, Interpersonal Skill, Responsibility and Information Technology Skill. The value of Cronbach’ s alpha for the four domains were .781, 807, .831, and .865, respectively. The final model in confirmatory factor analysis fit quite well with empirical data. The TNDC was found to be appropriate, both theoretically and statistically. Due to these results, it is recommended that the toolkit could be used in future studies for Nursing Program in Thailand.

Keywords: toolkit, nursing student’ desirable characteristics, Thai qualifications framework

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Authors: Jamie Sundvall, Lisa Jennings

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A decline in writing skills and abilities of students entering graduate school has become a focus for university systems within the United States. This decline has become a national trend that requires reflection on the intervention strategies used to address the deficit and unintended consequences as outcomes in the profession. Social work faculty is challenged to increase written scholarship within the academic setting. However, when a large number of students in each course have writing deficits, there is a shift from focus on content, ability to demonstrate competency, and application of core social work concepts. This qualitative study focuses on the experiences of online faculty who support increasing scholarship through writing and are following best practices preparing students academically to see improvements in written presentation in classroom work. This study outlines best practices to improve written academic presentation, especially in an online setting. The research also highlights how a student’s ability to show competency and application of concepts may be overlooked in the online setting. This can lead to new social workers who are prepared academically, but may unable to effectively advocate and document thought presentation in their writing. The intended progression of writing across all levels of higher education moves from summary, to application, and into abstract problem solving. Initial findings indicate that it is important to reflect on practices used to address writing deficits in terms of academic writing, competency, and application. It is equally important to reflect on how these methods of intervention impact a student post-graduation. Specifically, for faculty, it is valuable to assess a social worker’s ability to engage in continuity of documentation and advocacy at micro, mezzo, macro, and international levels of practice.

Keywords: intervention, professional impact, scholarship, writing

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Authors: M. Ekiert, T. Uhl, A. Mlyniec

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Tendons are the biological soft tissue structures composed of collagen, proteoglycan, glycoproteins, water and cells of extracellular matrix (ECM). Tendons, which primary function is to transfer force generated by the muscles to the bones causing joints movement, are exposed to many micro and macro damages. In fact, tendons and ligaments trauma are one of the most numerous injuries of human musculoskeletal system, causing for many people (particularly for athletes and physically active people), recurring disorders, chronic pain or even inability of movement. The number of tendons reconstruction and transplantation procedures is increasing every year. Therefore, studies on soft tissues storage conditions (influencing i.e. tissue aging) seem to be an extremely important issue. In this study, an atomic-scale investigation on the kinetics of decomposition of two selected tendon components – collagen type I (which forms a 60-85% of a tendon dry mass) and elastin protein (which combine with ECM creates elastic fibers of connective tissues) is presented. A molecular model of collagen and elastin was developed based on crystal structure of triple-helical collagen-like 1QSU peptide and P15502 human elastin protein, respectively. Each model employed 4 linear strands collagen/elastin strands per unit cell, distributed in 2x2 matrix arrangement, placed in simulation box filled with water molecules. A decomposition phenomena was simulated with molecular dynamics (MD) method using ReaxFF force field and periodic boundary conditions. A set of NVT-MD runs was performed for 1000K temperature range in order to obtained temperature-depended rate of production of decomposition by-products. Based on calculated reaction rates activation energies and pre-exponential factors, required to formulate Arrhenius equations describing kinetics of decomposition of tested soft tissue components, were calculated. Moreover, by adjusting a model developed for collagen, system scalability and correct implementation of the periodic boundary conditions were evaluated. An obtained results provide a deeper insight into decomposition of selected tendon components. A developed methodology may also be easily transferred to other connective tissue elements and therefore might be used for further studies on soft tissues aging.

Keywords: decomposition, molecular dynamics, soft tissue, tendons

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