Preliminary Model Research Articles

Automatic Optimization for Compliant Constant Force Mechanisms

This paper presents an automatic optimization method for compliant constant force mechanisms, which eliminates the need for time-consuming parameter tuning and complex model design in the conventional design process. The proposed optimization framework is based on the finite-element analysis (FEA) and multi-objective genetic algorithm (MOGA) methods and is designed in two steps: First, the preliminary mechanism design is carried out to roughly encompass the specified constant force objective; then, the preliminary model is optimized by applying a MOGA based on FEA results. The optimized model can achieve the desired performance automatically while achieving a larger constant force stroke, which is verified by performing FEA simulations and experimental studies. The experimental results demonstrate that the designed CFMs increase the constant force stroke by 16.3% while achieving the specified design accuracy compared to the preliminary prototype.

Cost and Material Quantities Prediction Models for the Construction of Underground Metro Stations

This paper addresses the gap in the scientific literature regarding construction cost estimates for the construction of underground metro stations. It provides preliminary cost estimation models using linear regression for use by the Greek underground metro public transport authority for planning future extensions to the Athens and Thessaloniki networks. At the same time, it contributes to the body of knowledge by proposing material quantity prediction models and presents a two-stage preliminary cost estimation model for the construction of civil engineering works of underground metro stations. Stage one uses the construction cost budgets of six metro stations in Greece to develop a multilinear regression equation for the prediction of the overall cost for construction of civil engineering works; stage two provides estimates of material quantities using linear regression, key quantity ratios, and artificial neural networks. The data analyzed are from the prior measurements of quantities for the construction of the Chaidari to Piraeus extension of the Athens Metro Line 3. After comparing the actual values of costs and quantities with the corresponding predictions, acceptable discrepancies are observed. All models provide estimates within ±25% discrepancies, which are acceptable at the conceptual planning phase in order to initiate project funding quests.

The Effect of Machine Learning Algorithms on the Prediction of Layer-by-Layer Coating Properties.

Layer-by-layer film (LbL) coatings made of polyelectrolytes are a powerful tool for surface modification, including the applications in the biomedical field, for food packaging, and in many electrochemical systems. However, despite the number of publications related to LbL assembly, predicting LbL coating properties represents quite a challenge, can take a long time, and be very costly. Machine learning (ML) methodologies that are now emerging can accelerate and improve new coating development and potentially revolutionize the field. Recently, we have demonstrated a preliminary ML-based model for coating thickness prediction. In this paper, we compared several ML algorithms for optimizing a methodology for coating thickness prediction, namely, linear regression, Support Vector Regressor, Random Forest Regressor, and Extra Tree Regressor. The current research has shown that learning algorithms are effective in predicting the coating output value, with the Extra Tree Regressor algorithm demonstrating superior predictive performance, when used in combination with optimized hyperparameters and with missing data imputation. The best predictors of the coating thickness were determined, and they can be later used to accurately predict coating thickness, avoiding measurement of multiple parameters. The development of optimized methodologies will ensure different reliable predictive models for coating property/function relations. As a continuation, the methodology can be adapted and used for predicting the outputs connected to antimicrobial, anti-inflammatory, and antiviral properties in order to be able to respond to actual biomedical problems such as antibiotic resistance, implant rejection, or COVID-19 outbreak.

A preliminary depth-integrated model for tsunamis propagation including water compressibility and seafloor elasticity

A model for tsunamis propagation is derived by coupling a weakly compressible liquid layer, standing for the ocean, to a viscoelastic solid layer of constant depth, representing the upper layer of the Earth. Below this layer, the Earth is assumed to be perfectly rigid. The resulting equations are averaged over the depth of the water layer for the liquid part and are integrated over the thickness of the solid layer for the solid part. The obtained system of equations is hyperbolic and admits an exact equation of energy conservation. The model is dispersive and includes an elastic branch, an acoustic branch and a gravity branch. The elasticity of the solid layer entails: (1) a reverse dispersion effect i.e. the phase velocity of the gravity branch decreases for small wave numbers if the wave number decreases; (2) an arrival time delay of the tsunami and (3) a leading negative phase i.e. a negative water elevation before the arrival of the main wave. All these effects are absent if the sea floor is assumed to be perfectly rigid. The arrival time delay due to elasticity comes in addition to the delay due to seawater compressibility. These effects are in agreement with previous works on tsunamis propagation. This preliminary model is a promising alternative approach for tsunamis propagation due to its ability to capture the main physical effects with a relatively simple mathematical structure of equations, which is easy to solve numerically.

C-, N-, S-, and P-Substrate Spectra in and the Impact of Abiotic Factors on Assessing the Biotechnological Potential of Paracoccus pantotrophus

Modern biotechnology benefits from the introduction of novel chassis organisms in remedying the limitations of already-established strains. For this, Paracoccus pantotrophus was chosen for in-depth assessment. Its unique broad metabolism and robustness against abiotic stressors make this strain a well-suited chassis candidate. This study set out to comprehensively overview abiotic influences on the growth performance of five P. pantotrophus strains. These data can aid in assessing the suitability of this genus for chassis development by using the type strain as a preliminary model organism. The five P. pantotrophus strains DSM 2944T, DSM 11072, DSM 11073, DSM 11104, and DSM 65 were investigated regarding their growth on various carbon sources and other nutrients. Our data show a high tolerance against osmotic pressure for the type strain with both salts and organic osmolytes. It was further observed that P. pantotrophus prefers organic acids over sugars. All of the tested strains were able to grow on short-chain alkanes, which would make P. pantotrophus a candidate for bioremediation and the upcycling of plastics. In conclusion, we were able to gain insights into several P. pantotrophus strains, which will aid in further introducing this species, or even another species from this genus, as a candidate for future biotechnological processes.

Properly Substituted Benzimidazoles as a New Promising Class of Nicotinate Phosphoribosyltransferase (NAPRT) Modulators.

The prevention of nicotinamide adenine dinucleotide (NAD) biosynthesis is considered an attractive therapeutic approach against cancer, considering that tumor cells are characterized by an increased need for NAD to fuel their reprogrammed metabolism. On the other hand, the decline of NAD is a hallmark of some pathological conditions, including neurodegeneration and metabolic diseases, and boosting NAD biosynthesis has proven to be of therapeutic relevance. Therefore, targeting the enzymes nicotinamide phosphoribosyltransferase (NAMPT) and nicotinate phosphoribosyltransferase (NAPRT), which regulate NAD biosynthesis from nicotinamide (NAM) and nicotinic acid (NA), respectively, is considered a promising strategy to modulate intracellular NAD pool. While potent NAMPT inhibitors and activators have been developed, the search for NAPRT modulators is still in its infancy. In this work, we report on the identification of a new class of NAPRT modulators bearing the 1,2-dimethylbenzimidazole scaffold properly substituted in position 5. In particular, compounds 24, 31, and 32 emerged as the first NAPRT activators reported so far, while 18 behaved as a noncompetitive inhibitor toward NA (Ki = 338 µM) and a mixed inhibitor toward phosphoribosyl pyrophosphate (PRPP) (Ki = 134 µM). From in vitro pharmacokinetic studies, compound 18 showed an overall good ADME profile. To rationalize the obtained results, docking studies were performed on the NAPRT structure. Moreover, a preliminary pharmacophore model was built to shed light on the shift from inhibitors to activators.

Implementing sustainable innovation in state universities: Process and tools

Universities have the vision, the knowledge and the power to lead the change towards a more sustainable world. However, there is a lack of studies investigating how universities can systematically reorient themselves to help society become more sustainable. In general, a research gap exists in the implementation of the business model innovation process, in the tools that should be used to pass from the design stage to implementation and in the identification of the main challenges that may hinder this process. This paper adopts the concept of a sustainable business model for interpreting the core logic through which universities create value for themselves, society and the environment. In the first stage of research, a theoretical framework was proposed for diagnosis of the integration of sustainability in the business models of universities. This framework was applied in the context of Italian state universities to identify business models with different degrees of strategic orientation towards sustainability. Now the research aim is to examine the processes and tools used and challenges faced by Italian state universities when implementing sustainable innovation. A multiple-case study is carried out on four Italian state universities showing a high level of integration of sustainability in all elements of the business model. The combination of both quantitative and qualitative data, and the patterns observed across cases, led to the presentation of five theoretical propositions, which were summarized in a preliminary model of the processes, tools and challenges involved when implementing sustainable innovation in higher education. The main theoretical contributions of this study are the advancement of knowledge regarding the dynamics (process) and the elements (tools) for the implementation of sustainability strategies in state universities, and the provision of a new causal map of the relationships among the variables that affect sustainable innovation in higher education.

Tenebrio molitor as a Simple and Cheap Preclinical Pharmacokinetic and Toxicity Model.

The progression of drugs into clinical phases requires proper toxicity assessment in animals and the correct identification of possible metabolites. Accordingly, different animal models are used to preliminarily evaluate toxicity and biotransformations. Rodents are the most common models used to preliminarily evaluate the safety of drugs; however, their use is subject to ethical consideration and elevated costs, and strictly regulated by national legislations. Herein, we developed a novel, cheap and convenient toxicity model using Tenebrio molitor coleoptera (TMC). A panel of 15 drugs-including antivirals and antibacterials-with different therapeutic applications was administered to TMC and the LD50 was determined. The values are comparable with those already determined in mice and rats. In addition, a TMC model was used to determine the presence of the main metabolites and in vivo pharmacokinetics (PK), and results were compared with those available from in vitro assays and the literature. Taken together, our results demonstrate that TMC can be used as a novel and convenient preliminary toxicity model to preliminarily evaluate the safety of experimental compounds and the formation of main metabolites, and to reduce the costs and number of rodents, according to 3R principles.

Development of a Thermal-Hydraulic Model for the EU-DEMO Tokamak Building and LOCA Simulation

The EU-DEMO must demonstrate the possibility of generating electricity through nuclear fusion reactions. Moreover, it must denote the necessary technologies to control a powerful plasma with adequate availability and to meet the safety requirements for plant licensing. However, the extensive radioactive materials inventory, the complexity of the plant, and the presence of massive energy sources require a rigorous safety approach to fully realize fusion power’s environmental advantages. The Tokamak building barrier design must address two main issues: radioactive mass transport hazards and energy-related or pressure/vacuum hazards. Safety studies are performed in the frame of the EUROfusion Safety And Environment (SAE) work package to support design improvement and evaluate the thermal-hydraulic behavior of confinement building environments during accident conditions in addition to source term mobilization. This paper focuses on developing a thermal-hydraulic model of the EU-DEMO Tokamak building. A preliminary model of the heat ventilation and air conditioning system and vent detritiation system is developed. A loss-of-coolant accident is studied by investigating the Tokamak building pressurization, source term mobilization, and release. Different nodalizations were compared, highlighting their effects on source term estimation. Results suggest that the building design should be improved to maintain the pressure below safety limits; some mitigative systems are preliminarily investigated for this purpose.

MRI-derived radiomics to guide post-operative management of glioblastoma: Implication for personalized radiation treatment volume delineation.

The glioblastoma's bad prognosis is primarily due to intra-tumor heterogeneity, demonstrated from several studies that collected molecular biology, cytogenetic data and more recently radiomic features for a better prognostic stratification. The GLIFA project (GLIoblastoma Feature Analysis) is a multicentric project planned to investigate the role of radiomic analysis in GB management, to verify if radiomic features in the tissue around the resection cavity may guide the radiation target volume delineation. We retrospectively analyze from three centers radiomic features extracted from 90 patients with total or near total resection, who completed the standard adjuvant treatment and for whom we had post-operative images available for features extraction. The Manual segmentation was performed on post gadolinium T1w MRI sequence by 2 radiation oncologists and reviewed by a neuroradiologist, both with at least 10 years of experience. The Regions of interest (ROI) considered for the analysis were: the surgical cavity ± post-surgical residual mass (CTV_cavity); the CTV a margin of 1.5 cm added to CTV_cavity and the volume resulting from subtracting the CTV_cavity from the CTV was defined as CTV_Ring. Radiomic analysis and modeling were conducted in RStudio. Z-score normalization was applied to each radiomic feature. A radiomic model was generated using features extracted from the Ring to perform a binary classification and predict the PFS at 6 months. A 3-fold cross-validation repeated five times was implemented for internal validation of the model. Two-hundred and seventy ROIs were contoured. The proposed radiomic model was given by the best fitting logistic regression model, and included the following 3 features: F_cm_merged.contrast, F_cm_merged.info.corr.2, F_rlm_merged.rlnu. A good agreement between model predicted probabilities and observed outcome probabilities was obtained (p-value of 0.49 by Hosmer and Lemeshow statistical test). The ROC curve of the model reported an AUC of 0.78 (95% CI: 0.68-0.88). This is the first hypothesis-generating study which applies a radiomic analysis focusing on healthy tissue ring around the surgical cavity on post-operative MRI. This study provides a preliminary model for a decision support tool for a customization of the radiation target volume in GB patients in order to achieve a margin reduction strategy.

Behavior of lap splices in reinforced concrete beams after bar yielding

AbstractStructural ductility in the case of plastic hinges forming close to a lap splice has been an open issue with the revision process of the next version of Eurocode EC2 concerning reinforced‐concrete structures. This research has provided experimental evidence by the large experimental campaign for the background for revision of the Eurocode EC2. Within this context, 38 specimens were tested in four‐point bending, with the longitudinal bars either lap‐spliced (partly or fully), or un‐spliced (for reference). The tests were carried out involving the variation of the bar diameter (12, 16, 20, and 25 mm), and the lap length (20–60 times the bar diameter). The main result is the sizeable enhancement of the structural ductility brought in by the extension of the lap length in excess of the length required by the yielding of the longitudinal bars. Based on these findings, a preliminary model is developed to describe the bond‐stress profiles in lap splices, after the yielding of the bars.

Research on Model Calibration Method of Chiller Plants Based on Error Reverse Correction with Limited Data

Model-based optimization is an important means by which to analyze the energy-saving potential of chiller plants. To obtain reliable energy-saving results, model calibration is essential, which strongly depends on operating data. However, sufficient data cannot always be satisfied in reality. To improve the prediction accuracy of the model with limited data, a model calibration method based on error reverse correction was investigated. A traditional optimization-based calibration method was first used for preliminary model calibration to obtain simulation data and simulation errors. Then, the sources of the simulation errors were analyzed to determine the distribution characteristics of the corresponding operating conditions of the model. Finally, the performance of the model was reversely corrected by adding a correction term to the original model. The proposed calibration method was tested on a chiller plant in Xiamen, China. The results showed that the proposed calibration method improved prediction accuracy by 2.61% (the coefficient of variation of the root mean square error (CV (RMSE)) was reduced from 3.96% to 1.35%) compared to the traditional method. The maximum mean bias error (MBE) for monthly chiller energy consumption was 2.66% with the proposed calibration method, while it was 10.42% with the traditional method. Overall, in scenarios with limited data, the proposed calibration method can effectively improve the accuracy of simulation results.

Novel FRF-based fast modal testing of multi-storey CLT building in operation using wirelessly synchronised data loggers

This paper presents a novel input–output frequency-response function (FRF) based field modal testing (MT) of an operational and fully occupied tallest cross-laminated timber (CLT) building in the U.K. A custom-built MT system and testing protocol were developed to facilitate exceptionally fast field testing work lasting only 10 h, including all instrumentation and field testing work.This yielded eight fundamental and higher-order modes of vibration with natural frequencies up to 12 Hz. The higher order modes are normally not possible to measure well enough using the standard output-only operational modal analysis (OMA). An FE model was developed prior to the testing to assure quality and facilitate the fast testing process. The FE model, based on the best engineering judgement, proved to be able to predict very well the key features of the test building. This includes close matching and correct clustering of the FE-calculated and MT-estimated natural frequencies, as well as a very reasonable prediction of the static stiffness at the top of the building. The in-situ measured horizontal static stiffness at the top of the CLT building is a considerable benefit of the field FRF measurements and is not possible in the standard OMA. It was shown that the preliminary best practice FE model was over-predicting the static stiffness in the two orthogonal directions by only up to 22% of the measured values.Curve-fitting of the good quality FRF data yielded damping ratio values for the higher order modes of vibration, typically above 3%. This is quite high for a full-scale multi-storey residential building.

Trophic Modelling of the Cross River Estuary Ecosystem, Nigeria

A trophic modelling of the Cross River estuary ecosystem was undertaken using Ecopath with Ecosim (EwE). Data were obtained from peer reviewed journals, monographs and stock assessment reports and used to construct the Ecopath model used to investigate the structure, function and system throughput of the estuary. These data included biological data such as biomass, production/ biomass, consumption/biomass, fish catch and diet composition of each species or functional group included in the model. The network analysis routine was used to estimate trophic levels and trophic interactions of functional groups, health condition and developmental stage, and food web features. Results of Ecopath model revealed three apical predators: Shark, Senegalese tonguesole, and Sea catfish. The ratio of total primary production to total respiration value of 4.182 revealed that the Cross River estuary is an immature ecosystem void of biological and ecosystem pollution and is at its early developmental stage. The mean trophic level of the catch of 2.186 for the system and the high gross food conversion efficiency (GE) of 0.300 for Macrobrachium spp and 0.292 for Penaeid shrimp, revealed high fishing pressure on the herbivores. The estuary ecosystem has a short food chain and low connectance index of 0.1879 which has phytoplankton being grazed upon by zooplankton which in turn are taken up by bonga. Model results and physico-chemical parameters showed that the Cross River estuary is still relatively pristine and immature ecosystem, void of organic pollution and with relatively low primary productivity as evident in relatively low nutrient concentration. The high value of ecotrophic efficiency (EE) of 0.993 for bonga and 0.991 for Macrobrachium spp indicate that the population of these animals are heavily exploited and predated upon in the estuary. Despite that this is a preliminary trophic model, it is clear that fish populations in the estuary are experiencing excessive fishing pressure; thus necessitating management measures to reduce pressure, while relevant data especially on fish diet composition and fish landing should be collected in order to get improved model parameterization in the future.

Landscape of pediatric cancer treatment refusal and abandonment in the US: A qualitative study.

To describe United States (US) pediatric oncologists' experiences with treatment refusal or abandonment, exploring types and frequency of decision-making conflicts, and their impact. We conducted exploratory qualitative interviews of pediatric oncologists (n = 30) with experience caring for a pediatric patient who refused or abandoned curative treatment. Interviewees were recruited using convenience and nominated expert sampling, soliciting experiences from diverse geographic locations and institution sizes across the US. We analyzed transcripts using applied thematic analysis to identify and refine meaningful domains. Many oncologists reported multiple experiences with refusal and abandonment. Most anticipated case frequency would increase due to misinformation, particularly on the internet. Interviewees described cases of treatment refusal and abandonment, but also a wider variety of cases than previously described in existing publications, including cases involving: non-adherence; negotiations for different treatments; negotiations for complementary and alternative medicine; delayed treatment initiation; and refusal of a component of recommended therapy. Cases often involved multiple stages or types of conflicts. Recurring patient/family behaviors emerged: clear opposition to treatment from the outset; hesitancy about treatment despite initiating therapy; and psychosocial circumstances becoming an obstacle to treatment completion. Oncologists revealed substantial professional and personal repercussions of these cases. Oncologist interviews highlight a broad range of conflicts, yielding a taxonomy of treatment refusal, non-adherence and abandonment (TRNA) that accounts for the heterogeneity of situations described. Cases' complexity and interrelatedness points to a functional model of TRNA that includes families' behaviors. This preliminary taxonomy and model warrant further research and examination to refine the model and generate strategies to prevent and mitigate TRNA.

Self-diffusion coefficient and sound velocity of Fe-Ni-O fluid: Implications for the stratification of Earth's outer core

It is experimentally reported that the stratified layer atop Earth's outer core is hundreds of kilometers thick with a maximum sound velocity reduction of 0.3% relative to the preliminary reference Earth model. However, why the sound velocity atop the outer core is reduced remains theoretically unclear. In this paper, the Ni and vital light O in the outer core were both considered to have implications for the stratification of Earth's core, including the stratification thickness and the sound velocity profile. Ab initio molecular dynamics simulations were performed on the Fe-Ni-O fluid under the conditions of Earth's outer core, and the self-diffusion coefficients and ion-ion dynamic structure factors were calculated. The self-diffusion coefficient of O was calculated to be (19.56 ± 0.83) × 10−9 m2s−1 at the core-mantle boundary. Combining the diffusion equation with the time evolution of the O self-diffusion coefficient, the calculated stratification thickness at present is 194.7 km. The calculated ion-ion dynamic structural factors indicate that the sound velocity in the outmost outer core near the stratified layer is 7.86 km/s, which is lower than the preliminary reference Earth model values (∼8.05 km/s). These results show that Fe-Ni-O liquid atop the outer core featuring an appropriate thickness and a reduced sound velocity, thereby shedding light on the dynamic behavior of Earth's core.

Modelling the cyclic inelastic behaviour of a dissimilar metal/composite bonded joint at low frequencies

ABSTRACT The present paper is concerned with the investigation of the inelastic behaviour observed in load-unload cyclic tests performed at 50°C in single lap joints composed of a polyurethane based composite reinforced with fibreglass bonded to an ASTM A1020 steel substrate using an epoxy adhesive. The experiments presented in this research show that the inelastic behaviour of the joint is strongly dependent on the load frequency, eventually leading the structure to exhibit a progressive deformation when submitted to load-unload cyclic loading. The main goal of this study was to propose a preliminary rate-dependent mechanical model capable to describe the cyclic inelastic behaviour for an arbitrary load-unload history at low frequencies and a reasonable agreement was obtained between the experimental results and the model predictions.

Laser ablation of RB-SiC composite by femtosecond laser irradiation

Reaction-bonded silicon carbide composites (RB-SiC), consisting of SiC grains and Si matrix, have a complex ablation mechanism as two-phase composites under femtosecond laser irradiation. The ablation threshold of RB-SiC was calculated, which decreases (from 1.01 J/cm2 to 0.56 J/cm2) with increasing pulse number N and finally stabilized. At low fluence (F/Fth ≤ 5) and a low number of pulses, photochemical ablation dominates. For a higher number of pulses and high fluence (5 <F/Fth ≤ 50), photothermal ablation dominates with photochemical ablation. The results show that structures such as pits, convex, and holes exist on the surface of Crater I, while Laser-induced Periodic Surface Structures (LIPSS), and condensation structures exist on the surface of Crater II. In both types of ablation craters, the SiC grain surface produces the Low Spatial Frequency LIPSS (LSFL) with a period of about 900 nm and the High Spatial Frequency LIPSS (HSFL) with a period of about 300 nm. Based on the surface morphology, microstructure, and physical phase analysis of the ablation craters, a preliminary model of the removal mechanism of the ablation craters by femtosecond laser irradiation was established. These findings are expected to provide theoretical and experimental support for the precision processing of RB-SiC by femtosecond laser.

Heritability and genetic trend of body weight in dogs of different breeds in Sweden.

High body weight (BW) in dogs has been associated with developmental as well as degenerative diseases, but the heritability of BW in dog breeds is largely unknown. The aim of the current study was to estimate heritability and genetic change (genetic trend) for BW in a range of dog breeds in Sweden. Body weight registrations from 19 dog breeds (with n ranging from 412 to 4,710) of varying body size, type and usage were collected from 2007 to 2016. The average BW of the breeds was 8 to 56 kg. The BW registrations were performed when the dogs were 12 to 24 mo of age (18 to 30 mo for one large-sized breed) in connection with an official radiographic screening program for hip dysplasia. Collected weight records were used to estimate heritability and genetic trends for BW. Several statistical models were used. The preliminary model included the fixed effects of breed (P < 0.001), sex (P < 0.001), year of screening (P < 0.001), litter size (P = 0.06), parity of the dam (P = 0.03) and linear regression on age at screening (P < 0.001), the latter five effects all nested within breed, and the random effects of litter and dam. Season of birth and the quadratic effect of age were also tested, but were not significant (P > 0.10). For the genetic analysis, various mixed linear models were tested within breed with different combinations of random effects; the most complex model included random effects of litter, direct additive, and maternal genetic effects, and maternal permanent environmental effects. The average heritability for BW over all 19 breeds was 51%, with a range of 35% to 70%, and the additive genetic coefficient of variance was around 9%. Maternal heritability was 5% to 9% and litter variance was below 10% with one exception (15% in Shetland Sheepdogs). For nine breeds, there was a genetic trend of increasing BW, whereas seven breeds had a genetic trend of decreasing BW. The largest absolute genetic change over a 10-yr period was around 0.6 kg or about 2% of the mean. In conclusion, given the small genetic changes in spite of the high heritability, it seems that there is generally a very weak selection, if any, for BW in the included dog breeds.

Offshore Software Maintenance Outsourcing Process Model Validation: A Case Study Approach

The successful execution and management of Offshore Software Maintenance Outsourcing (OSMO) can be very beneficial for OSMO vendors and the OSMO client. Although a lot of research on software outsourcing is going on, most of the existing literature on offshore outsourcing deals with the outsourcing of software development only. Several frameworks have been developed focusing on guiding software system managers concerning offshore software outsourcing. However, none of these studies delivered comprehensive guidelines for managing the whole process of OSMO. There is a considerable lack of research working on managing OSMO from a vendor’s perspective. Therefore, to find the best practices for managing an OSMO process, it is necessary to further investigate such complex and multifaceted phenomena from the vendor’s perspective. This study validated the preliminary OSMO process model via a case study research approach. The results showed that the OSMO process model is applicable in an industrial setting with few changes. The industrial data collected during the case study enabled this paper to extend the preliminary OSMO process model. The refined version of the OSMO process model has four major phases including (i) Project Assessment, (ii) SLA (iii) Execution, and (iv) Risk.