Original Model Development Research Articles

Simulation of autonomous voltage inverters of power sources of single-phase asynchronous drives

Purpose. Development of original models of voltage inverters adapted to control a single-phase asynchronous motor with the subsequent prospect of creating automatic systems for improving the energy efficiency of household mechanisms, as well as developing educational complexes for studying the operation of frequency converters to form skills for their repair and tuning.Methodology. The provisions of the theory of electric machines, methods of synthesis of digital control systems, methods and methods of modeling in CAD electronic laboratory of the company NATIONAL INSTRUMENTS of the Multisim component, methods of circuit design were used for conducting research. Findings. Models of pulse distributors were developed and built for the cases of power supply of single-phase asynchronous motors with bridge inverters of separate and individual starting and working windings, half-bridge inverters with a bipolar power source and a three-phase inverter with control according to a 180-degree control diagram. Time diagrams of visual confirmation of the system's performance according to the declared principles have been obtained. Originality. A number of original switch diagrams of the power section of the models of impulse distributors of autonomous voltage inverters are proposed, taking into account the phase shift and the duration of the switching pauses of the switching arms of the power unit to avoid emergency modes, recommendations are given on the levels of generation frequencies that are fed to the input of the combinational circuit, the prospect of using this system as part of a single-phase asynchronous electric drive with the possibility of energy-efficient control is shown.Practical value. The proposed original model solutions for autonomous voltage inverters, which are adapted to work together with a single-phase IM, can be useful for developers of converter technology and become visual material for their use in the educational process for training specialists in specialty 141 "Electric power engineering, electrical engineering and electromechanics".

O-242 Comparing the performance of an artificial intelligence model for predicting embryo implantation between clinics with patient cohorts of different maternal age distributions

Abstract Study question Do differences in maternal age distributions contribute to the variability in the discrimination performance of an embryo viability model based on artificial intelligence (AI)? Summary answer Using a common reference age distribution, enables a less biased and thus more standardized comparison of embryo implantation prediction between clinics. What is known already Studies from different clinics have shown a quite large variation in the performance of the same AI model. The most common method of comparing performance between clinics is to use simple clinic-specific performance statistics while ignoring dissimilarities between clinics in patient cohorts, culture conditions etc. A more appropriate method is meta-analysis of performance across clinics rather than using overall performance, however, this does also not account for dissimilarities between clinics. Assessing the performance in subgroups, although common practice, reduces the sample size significantly and limits interpretation to each separate subgroup. Study design, size, duration This is a retrospective observational multi-site study with data from four clinics collected over varying time periods. In all participating clinics embryos were cultured in EmbryoScope time-lapse incubators (ES-D, ES+, ES-Flex; Vitrolife). Embryo implantation likelihood was evaluated with the iDAScore v1.0 AI decision support tool. Data from 4,805 single embryo transfers on day 5 and 6 (fresh and frozen) with known fetal heartbeat outcome were included. Donor egg cycles were strictly excluded. Participants/materials, setting, methods Performance of embryo implantation prediction was measured in terms of areas under the ROC curve (AUC). To account for age differences, we performed a standardization of the AUCs using a weighted version of the ROC curves with weights defined as the ratio between the age densities in a reference population and in the specific clinic. The reference population was comprised of data that was held out from the original model development. Main results and the role of chance Different age distributions with medians ranging from 32 to 40 years were observed in the four clinics. The unweighted overall AUC was 0.65 (95% CI: 0.64 to 0.69), whereas the AUC in the reference population was 0.67 (95% CI: 0.63 to 0.71). The predictive performance of the iDAScore model varied between clinics with the unweighted AUCs ranging from 0.58 to 0.69. Meta-analysis across all four clinics showed a summary average of 0.65 (95% CI: 0.59 to 0.70). We then standardized to the age distribution in a reference population in which the maternal age ranged from 21 to 44 years with a median of 38. The values of the AUCs after standardization ranged from 0.60 to 0.71 between clinics with a summary average of 0.67 (95% CI: 0.62 to 0.72). The standard error of the summary average was 5% lower when standardization was used and the estimated variation between clinics in the meta-analysis was 16% lower. In conclusion, we have shown with our standardized analysis method that the variability in embryo performance prediction between clinics can be partially explained by the difference in maternal age distributions. Limitations, reasons for caution The summary average of the AUC is highly dependent on the age distribution in the chosen reference population. Therefore, the exact value of this estimate should be interpreted with caution. However, comparing AUCs between clinics using this standardization approach is less biased by differences in age distribution. Wider implications of the findings Simple comparisons of the performance of AI-based embryo implantation prediction in different clinics may be influenced by factors such as age. Using a standardization approach, this influence can be mitigated, enabling a less biased comparison. Differences in other important factors apart from age can potentially also be considered. Trial registration number not applicable

Моделювання критичних вразливостей у логістиці постачання озброєння та військової техніки в умовах воєнних загроз

The systemic nature problem related to the simulation of the influence of military threats on the logistics chain of the supply of weapons and military equipment (spare parts for aircrafts, ammunition for rocket systems of volley fire, etc.) is being solved. Military threats can lead to logistical damage (destruction: airfields, bridges, railways, and highways, etc.), which is investigated in this paper. The relevance of the research is related to the systemic nature of the solution to the logistical problem. The occurrence of losses leads to the taking of preventive measures to reduce the level of critical vulnerabilities (for example, runways, ground equipment of airfields, etc.) of the logistical supply chain (for example, aviation) of weapons and military equipment under conditions of martial law. The study aims to create a set of models that will allow making a systematic analysis of the sequence of events associated with the emergence of a military threat in the logistics of the supply of weapons and military equipment: the appearance of a military threat – the emergence of critical vulnerabilities in the logistics chain – the appearance of logistical losses – the formation of preventive actions. The analysis of publications and studies on the logistics of military supplies with the identification of unresolved problems has been carried out. A model to analyze the criticality of vulnerabilities of the logistics supply chain, using the assessments of military experts and the planning of virtual experiments has been created. A model to analyze the causal chain: military threat – critical vulnerability – losses using qualitative assessments of experts in the form of linguistic variable values has been developed. The lexicographic arrangement of possible alternative ways to supply weapons and military equipment to the zone of military conflict is used. This made it possible to select a rational supply option to reduce possible logistical losses. The optimization model to reduce the level of criticality of vulnerabilities in the logistics supply chain to ensure the minimization of losses has been created. In this case, the time, risks and costs of carrying out the preventive actions under conditions of martial law are considered. An agent model to study the dynamic processes of moving forward the military cargo in the logistics supply chain, which helps simulate the occurrence of a military threat, the activation of critical vulnerabilities, and the appearance of possible logistical losses has been developed. The efficiency of the proposed approach is ensured by a systematic representation of the sequence of events on the emergence of a military threat, the activation of critical vulnerabilities, the appearance of logistical losses, which ensures the adoption of rational preventive actions to prevent the consequences of military threats. The scientific novelty of the study is related to the development of original models, which are based on the systematic presentation of the logistics chain of the supply of weapons and military equipment to the zone of military conflict under conditions of military threat to ensure that efficient preventive actions are done to minimize logistical losses. The results of the study should be used to plan the preventive measures to minimize possible losses and ensure military supplies under conditions of the risk of military threats.

Estimating the area under the ROC curve when transporting a prediction model to a target population.

We propose methods for estimating the area under the receiver operating characteristic (ROC) curve (AUC) of a prediction model in a target population that differs from the source population that provided the data used for original model development. If covariates that are associated with model performance, as measured by the AUC, have a different distribution in the source and target populations, then AUC estimators that only use data from the source population will not reflect model performance in the target population. Here, we provide identification results for the AUC in the target population when outcome and covariate data are available from the sample of the source population, but only covariate data are available from the sample of the target population. In this setting, we propose three estimators for the AUC in the target population and show that they are consistent and asymptotically normal. We evaluate the finite-sample performance of the estimators using simulations and use them to estimate the AUC in a nationally representative target population from the National Health and Nutrition Examination Survey for a lung cancer risk prediction model developed using source population data from the National Lung ScreeningTrial.

Towards the Development of an Operational Digital Twin

A digital twin is a powerful new concept in computational modelling that aims to produce a one-to-one mapping of a physical structure, operating in a specific context, into the digital domain. The development of a digital twin provides clear benefits in improved predictive performance and in aiding robust decision making for operators and asset managers. One key feature of a digital twin is the ability to improve the predictive performance over time, via improvements of the digital twin. An important secondary function is the ability to inform the user when predictive performance will be poor. If regions of poor performance are identified, the digital twin must offer a course of action for improving its predictive capabilities. In this paper three sources of improvement are investigated; (i) better estimates of the model parameters, (ii) adding/updating a data-based component to model unknown physics, and (iii) the addition of more physics-based modelling into the digital twin. These three courses of actions (along with taking no further action) are investigated through a probabilistic modelling approach, where the confidence of the current digital twin is used to inform when an action is required. In addition to addressing how a digital twin targets improvement in predictive performance, this paper also considers the implications of utilising a digital twin in a control context, particularly when the digital twin identifies poor performance of the underlying modelling assumptions. The framework is applied to a three-storey shear structure, where the objective is to construct a digital twin that predicts the acceleration response at each of the three floors given an unknown (and hence, unmodelled) structural state, caused by a contact nonlinearity between the upper two floors. This is intended to represent a realistic challenge for a digital twin, the case where the physical twin will degrade with age and the digital twin will have to make predictions in the presence of unforeseen physics at the time of the original model development phase.

A probability model to detect carbonate cementation in sandstones and other enigmatic wireline facies

Zones of carbonate cementation identified within lower Paaratte Formation sandstones of the eastern Otway Basin, Victoria, southeastern Australia, can be quantitatively detected by a wireline log-based probability model. Though trained on these zones, the same model appears to accurately predict carbonate cementation within Late Cretaceous-to-Eocene reservoir sandstones of the Latrobe Group supersequence of the Gippsland Basin, 100s of km to the east. Predicted carbonate cementation matches published evidence (a regional petrographic study) and provides a plausible interpretation for corresponding sections of Formation Micro-Imager data acquired more recently. These Latrobe Group sandstones are thought to have once been pervasively cemented prior to development of the secondary porosity responsible for providing reservoirs to the main petroleum system of the basin. However, model predictions imply that discrete, heavily cemented zones remain, which must have acted, and must still act, as local obstructions to reservoir fluid migration. These zones would also likely react with carbonic acid formed at plume fronts generated by dedicated CO2 storage operations of the future. The cemented zones that have been predicted are sparse, spatially sporadic and cannot be resolved by 3D seismic reflection survey data at present-day reservoir depths. These predictions therefore emphasise the difficulty in mapping the distribution of carbonate cemented zones. However, they provide calibration data for future mapping systems.Two different tests of the probability log model were undertaken. One benchmarks its predictions against those of a neural network trained using the original model development dataset from the Otway Basin. Predictive performance of the neural network model is significantly worse than that of the probability log model when making predictions using wireline data acquired at a well in the Gippsland Basin. The second test demonstrates that the general probability log modelling approach is amenable to classifying other cryptic ‘electro-facies’, for example those representing enigmatic or ambiguous rock types not easily interpreted from common wireline log data using standard theory. This test presents a case study by which the probability log modelling approach predicts the presence of both basic and evolved, felsic igneous sill intrusions within the stratigraphic succession of the Faroe-Shetland Basin of NW Europe.

Predicting the cumulative chance of live birth over multiple complete cycles of in vitro fertilization: an external validation study.

Are the published pre-treatment and post-treatment McLernon models, predicting cumulative live birth rates (LBR) over multiple complete IVF cycles, valid in a different context? With minor recalibration of the pre-treatment model, both McLernon models accurately predict cumulative LBR in a different geographical context and a more recent time period. Previous IVF prediction models have estimated the chance of a live birth after a single fresh embryo transfer, thereby excluding the important contribution of embryo cryopreservation and subsequent IVF cycles to cumulative LBR. In contrast, the recently developed McLernon models predict the cumulative chance of a live birth over multiple complete IVF cycles at two certain time points: (i) before initiating treatment using baseline characteristics (pre-treatment model) and (ii) after the first IVF cycle adding treatment related information to update predictions (post-treatment model). Before implementation of these models in clinical practice, their predictive performance needs to be validated in an independent cohort. External validation study in an independent prospective cohort of 1515 Dutch women who participated in the OPTIMIST study (NTR2657) and underwent their first IVF treatment between 2011 and 2014. Participants underwent a total of 2881 complete treatment cycles, with a complete cycle defined as all fresh and frozen thawed embryo transfers resulting from one episode of ovarian stimulation. The follow up duration was 18 months after inclusion, and the primary outcome was ongoing pregnancy leading to live birth. Model performance was externally validated up to three complete treatment cycles, using the linear predictor as described by McLernon et al. to calculate the probability of a live birth. Discrimination was expressed by the c-statistic and calibration was depicted graphically in a calibration plot. In contrast to the original model development cohort, anti-Müllerian hormone (AMH), antral follicle count (AFC) and body weight were available in the OPTIMIST cohort, and evaluated as potential additional predictors for model improvement. Applying the McLernon models to the OPTIMIST cohort, the c-statistic of the pre-treatment model was 0.62 (95% CI: 0.59-0.64) and of the post-treatment model 0.71 (95% CI: 0.69-0.74). The calibration plot of the pre-treatment model indicated a slight overestimation of the cumulative LBR. To improve calibration, the pre-treatment model was recalibrated by subtracting 0.35 from the intercept. The post-treatment model calibration plot revealed accurate cumulative LBR predictions. After addition of AMH, AFC and body weight to the McLernon models, the c-statistic of the updated pre-treatment model improved slightly to 0.66 (95% CI: 0.64-0.68), and of the updated post-treatment model remained at the previous level of 0.71 (95% CI: 0.69-0.73). Using the recalibrated pre-treatment model, a woman aged 30 years with 2 years of primary infertility who starts ICSI treatment for male factor infertility has a chance of 40% of a live birth from the first complete cycle, increasing to 72% over three complete cycles. If this woman weighs 70 kg, has an AMH of 1.5 ng/mL and an AFC of 10 measured at the beginning of her treatment, the updated pre-treatment model revises the estimated chance of a live birth to 30% in the first complete cycle and 59% over three complete cycles. If this woman then has five retrieved oocytes, no embryos cryopreserved and a single fresh cleavage stage embryo transfer in her first ICSI cycle, the post-treatment model estimates the chances of a live birth at 28 and 58%, respectively. Two randomized controlled trials (RCT) evaluating the effectiveness of gonadotropin dose individualization on basis of the AFC were nested within the OPTIMIST study. The strict dosing regimens, the RCT in- and exclusion criteria and the limited follow up time of 18 months might have influenced model performance in this independent cohort. Also, consistent with the original model development study, external validation was performed using the optimistic assumption that the cumulative LBR in couples who discontinue treatment without a live birth would have been equal to that of those who continue treatment. After national recalibration to account for geographical differences in IVF treatment, the McLernon prediction models can be introduced as new counselling tools in clinical practice to inform patients and to complement clinical reasoning. These models are the first to offer an objective and personalized estimate of the cumulative probability of a live birth over multiple complete IVF cycles. No external funds were obtained for this study. M.J.C.E., D.J.M. and S.B. have nothing to disclose. J.A.L, S.C.O, T.C.v.T. and H.LT. received an unrestricted personal grant from Merck BV. B.W.M. is supported by a NHMRC Practitioner Fellowship (GNT1082548) and reports consultancy for ObsEva, Merck and Guerbet. F.J.M.B. receives monetary compensation as a member of the external advisory board for Merck BV (the Netherlands) and Ferring pharmaceutics BV (the Netherlands), for consultancy work for Gedeon Richter (Belgium) and Roche Diagnostics on automated AMH assay development, and for a research cooperation with Ansh Labs (USA). Not applicable.

The development and validation of the AMPREDICT model for predicting mobility outcome after dysvascular lower extremity amputation

ObjectiveThe objective of this study was the development of AMPREDICT-Mobility, a tool to predict the probability of independence in either basic or advanced (iBASIC or iADVANCED) mobility 1 year after dysvascular major lower extremity amputation. MethodsTwo prospective cohort studies during consecutive 4-year periods (2005-2009 and 2010-2014) were conducted at seven medical centers. Multiple demographic and biopsychosocial predictors were collected in the periamputation period among individuals undergoing their first major amputation because of complications of peripheral arterial disease or diabetes. The primary outcomes were iBASIC and iADVANCED mobility, as measured by the Locomotor Capabilities Index. Combined data from both studies were used for model development and internal validation. Backwards stepwise logistic regression was used to develop the final prediction models. The discrimination and calibration of each model were assessed. Internal validity of each model was assessed with bootstrap sampling. ResultsTwelve-month follow-up was reached by 157 of 200 (79%) participants. Among these, 54 (34%) did not achieve iBASIC mobility, 103 (66%) achieved at least iBASIC mobility, and 51 (32%) also achieved iADVANCED mobility. Predictive factors associated with reduced odds of achieving iBASIC mobility were increasing age, chronic obstructive pulmonary disease, dialysis, diabetes, prior history of treatment for depression or anxiety, and very poor to fair self-rated health. Those who were white, were married, and had at least a high-school degree had a higher probability of achieving iBASIC mobility. The odds of achieving iBASIC mobility increased with increasing body mass index up to 30 kg/m2 and decreased with increasing body mass index thereafter. The prediction model of iADVANCED mobility included the same predictors with the exception of diabetes, chronic obstructive pulmonary disease, and education level. Both models showed strong discrimination with C statistics of 0.85 and 0.82, respectively. The mean difference in predicted probabilities for those who did and did not achieve iBASIC and iADVANCED mobility was 33% and 29%, respectively. Tests for calibration and observed vs predicted plots suggested good fit for both models; however, the precision of the estimates of the predicted probabilities was modest. Internal validation through bootstrapping demonstrated some overoptimism of the original model development, with the optimism-adjusted C statistic for iBASIC and iADVANCED mobility being 0.74 and 0.71, respectively, and the discrimination slope 19% and 16%, respectively. ConclusionsAMPREDICT-Mobility is a user-friendly prediction tool that can inform the patient undergoing a dysvascular amputation and the patient's provider about the probability of independence in either basic or advanced mobility at each major lower extremity amputation level.

Vascular Compromise and Hemodynamics in Pulmonary Arterial Hypertension: Model Predictions

A computer model of the normal pulmonary circulation based on animal (dog) data obtained in the literature was previously developed by Bshouty and Younes (for details see references [S1, S2]). The model is described briefly and only details not included in the original model development will be included here. The original model is a multibranch model that bifurcates sequentially starting from the pulmonary artery (PA) up to eight (four generations) precapillary and capillary channels. The model was later modified to include five generations ending in sixteen precapillary and capillary channels (Figure S1). On the venous side, the vessels converge and reunite sequentially to end in the left atrium (LA). The resistance of a given vessel in the model is dependent on vessel dimensions (length and cross-sectional area). Changes in vessel dimensions occur in response to changes in lung volume and intravascular pressure (P v ). The original multibranch model was developed between 1987 and 1989, when microprocessors operated at 4.77 MHz. At the time, each extra-alveolar vessel was divided into twenty-five segments. This was done in order to shorten the time needed to go through the thousands of calculations and iterations needed to produce a stable solution (which at the time, took several minutes per one set of data). With the development of faster microprocessors, the number of segments of each extra-alveolar vessel was gradually increased initially to one hundred segments and is currently set at a thousand segments. Results obtained with twenty-five segments differed from results obtained with one hundred segments at the second decimal level and results obtained with a thousand segments differed from results obtained with one hundred segments mostly at the third decimal level and are therefore, not clinically significant. Similarly, results obtained with the four-generation model when compared with the five-generation model differed only at the second decimal level and are therefore, also not clinically significant. All simulations presented in this paper were generated with the five-generation model and 1000 segment vessels (See footnote). Cross-sectional area of each arterial (A a ) and venous (A v ) segment is calculated based on the transmural pressure (P tm ) across that segment, P tm being intravascular minus perivascular pressure (P x ). The characteristic behaviour of A a as a function of P tm was derived from data obtained by Smith and Mitzner (S3) and Maloney et al (S4) and described in detail by Bshouty and Younes (S1). It is expressed by the following linear relationship,

Recent contributions of in vitro models to our understanding of hepatitis C virus life cycle

Hepatitis C virus is a human pathogen responsible for liver diseases including acute and chronic hepatitis, cirrhosis and hepatocellular carcinoma. Its high prevalence, the absence of a prophylactic vaccine and the poor efficiency of current therapies are huge medical problems. Since the discovery of the hepatitis C virus, our knowledge of its biology has been largely punctuated by the development of original models of research. At the end of the 1980s, the chimpanzee model led to cloning of the viral genome and the definition of infectious molecular clones. In 1999, a breakthrough was achieved with the development of a robust in vitro replication model named 'replicon'. This system allowed intensive research into replication mechanisms and drug discovery. Later, in 2003, pseudotyped retroviruses harbouring surface proteins of hepatitis C virus were produced to specifically investigate the viral entry process. It was only in 2005 that infectious viruses were produced in vitro, enabling intensive investigations into the entire life cycle of the hepatitis C virus. This review describes the different in vitro models developed to study hepatitis C virus, their contribution to current knowledge of the virus biology and their future research applications.

Review article: scoring systems for assessing prognosis in critically ill adult cirrhotics

Cirrhotic patients admitted to intensive care units (ICU) still have poor outcomes. Some current ICU prognostic models [Acute Physiology and Chronic Health Evaluation (APACHE), Organ System Failure (OSF) and Sequential Organ Failure Assessment (SOFA)] were used to stratify cirrhotics into risk categories, but few cirrhotics were included in the original model development. Liver-specific scores [Child-Turcotte-Pugh (CTP) and model for end-stage liver disease (MELD)] could be useful in this setting. To evaluate whether ICU prognostic models perform better compared with liver-disease specific ones in cirrhotics admitted to ICU. We performed a structured literature review identifying clinical studies focusing on prognosis and risk factors for mortality in adult cirrhotics admitted to ICU. We found 21 studies (five solely dealing with gastrointestinal bleeding) published during the last 20 years (54-420 patients in each). APACHE II and III, SOFA and OSF had better discrimination for correctly predicting death compared with the CTP score. The MELD score was evaluated only in one study and had good predictive accuracy [receiver operator characteristic (ROC) curve: 0.81). Organ dysfunction models (OSF, SOFA) were superior compared with APACHE II and III (ROC curve: range 0.83-0.94 vs. 0.66-0.88 respectively). Cardiovascular, liver and renal system dysfunction were more frequently independently associated with mortality. General-ICU models had better performance in cirrhotic populations compared with CTP score; OSF and SOFA had the best predictive ability. Further prospective and validation studies are needed.

Application of Highway Safety Manual Draft Chapter

Predicting highway safety performance in quantitative terms on the basis of a set of highway geometric design and traffic control features is the core of the ongoing Highway Safety Manual (HSM) development. While great efforts have been made to develop safety performance models for different types of highways, evaluating the applicability of the models with crash data from states that were not used in the original model development is equally important. This step is critical in future HSM applications because of many noticeable differences in crash data recording practice and driving behaviors across the various states. Potential application concerns need to be evaluated fully and addressed before the manual is officially published. This paper presents the application experience of the safety prediction models and methodology for segments of two-lane rural roads as proposed for inclusion in Part III of the HSM. The study used data for state routes in Louisiana. The results indicate that the prediction models performed reasonably well: there were small differences between the observed and predicted crash frequencies, with calibration parameters applied, for all segments on rural two-lane highways in Louisiana. The results at different analysis levels (from individual segments to a network of segments) are summarized, and several application issues such as the level of effort versus degree of accuracy, simplification of the calibration process, and the need for a reliability measurement are discussed.

Application ofHighway Safety ManualDraft Chapter: Louisiana Experience

Predicting highway safety performance in quantitative terms on the basis of a set of highway geometric design and traffic control features is the core of the ongoing Highway Safety Manual (HSM) development. While great efforts have been made to develop safety performance models for different types of highways, evaluating the applicability of the models with crash data from states that were not used in the original model development is equally important. This step is critical in future HSM applications because of many noticeable differences in crash data recording practice and driving behaviors across the various states. Potential application concerns need to be evaluated fully and addressed before the manual is officially published. This paper presents the application experience of the safety prediction models and methodology for segments of two-lane rural roads as proposed for inclusion in Part III of the HSM. The study used data for state routes in Louisiana. The results indicate that the prediction models performed reasonably well: there were small differences between the observed and predicted crash frequencies, with calibration parameters applied, for all segments on rural two-lane highways in Louisiana. The results at different analysis levels (from individual segments to a network of segments) are summarized, and several application issues such as the level of effort versus degree of accuracy, simplification of the calibration process, and the need for a reliability measurement are discussed.

An Application of ‘Jigsaw Learning’ to Teaching Infrastructure Model Development

SUMMARY Skills in group communication, development of problem definition and coordination of activities are essential in modern day multi-disciplinary engineering. The development of these skills requires more than just being told they exist and how the students should acquire them. Students must be exposed to these situations and taught how to handle them. This paper presents a study of a teaching technique that would encourage the development of communication skills between students: ‘jigsaw learning’. The approach consists of dividing students solving a particular problem into a number of groups. A student is first placed into an overall model development group to specify the problem to be solved. Second, he/she works in the component group to create a particular model component. Finally, once the component is developed the student moves back to the original model development group and incorporates the specific component into the overall model. In order to do this successfully, students must communicate the general description of the model to the component group, who share similar expertise. They must then communicate the findings of this expert group back to a more disparate model development group. Each student moves through the steps of: specifying the problem; specifying and considering connections between the components; developing the components; bringing them together; and presenting the results. To assess the success of the approach, a series of studies were carried out by the Higher Education Research Unit. Two questionnaires were distributed. They indicated the approach was successful but refinement was necessary.

An Empirical Assessment of the Dimensions of Softwood Lumber Quality

Abstract On the basis of previous research (Garvin 1984, Parasuraman et al. 1988), an 80-item, 12-dimension model for measuring total product quality in softwood dimension lumber was developed. This model was tested using confirmatory factor analysis and buyer perception data from three segments of the softwood dimension lumber market. Test results did not support the 12-dimension model. Consequently, exploratory factor analysis was used to develop a model consisting of five dimensions: Supplier/Salesperson Characteristics, Supplier Services, Supplier Facilities, Lumber Performance, and Lumber Characteristics. This model was tested by asking softwood lumber buyers (the same ones used for original model development) to rate their suppliers on the five dimensions. On each dimension, buyers rated most-preferred suppliers higher than least-preferred suppliers, providing evidence of the model's appropriateness. For. Sci. 42(4):407-414.

Los comienzos de la industria aeronáutica en España y la ley de Wolff (1916-1929)

During the period 1916-1929, the Spanish aeronautical industry was linked to the demand of military aircrafts. It had been created in a process of import substitution that was particularly intense during the First World War. At the beginning, this industry fried to achieve autarchy by developing its own technology but after 1923 the State decided to purchase foreign patents. The essay tries to assess the size this industry, and the resulting figures confirm its modest scale of operation due to the very low level of public finding. Nevertheless, the existence of this sector was the sign of a relative degree of modernization of the Spanish economy during the first thirty years of the twentieth century. The article argues that the fast assimilation of foreign techniques in the building and design of aircraftas and engines, and even the development of original models would not have been possible without a previous development the engineering industry. Lastly, the application of the Wolff law allows to suggest that the public sector lost an excellent chance to fasten some of the more competitive lines of this industry in the twenties. However, the technical transformations in the industry implied by the appearance of metallic aircrafts, and adverse circumstances in the international markets for military aircrafts condemned this industry to technical dependence on foreign firms.