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Limb amputation can lead to significant functional challenges in daily activities, prompting amputees to use prosthetic devices (PDs). However, the cognitive demands of PDs and usability issues have resulted in user rejections. This study aimed to create a Human Performance Model for Upper-Limb Prosthetic Devices (HPM-UP). The model used formulations of learnability, error rate, memory load, efficiency, and satisfaction to assess usability. The model was validated in an experiment with 30 healthy participants using a bypass prosthetic device. Findings indicated that the HPM-UP successfully predicted the usability of prosthetic devices, aligning with human subject data. This research proposes a quantitative approach to predict upper limb prosthetic device usability by quantifying each dimension and computationally connecting them. The model, available on Github and executable with Rstudio, could enable clinicians to assess and analyze the human performance of various commercial prostheses, aiding in recommending optimal devices for patients.

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The number of infants diagnosed with neonatal abstinence syndrome (NAS) or neonatal opioid withdrawal syndrome (NOWS) has increased. The expression of NAS/NOWS symptoms differs and typically begins within the first few days of life, considered a critical period for feeding skill establishment, nourishment, and attachment. Non-pharmacologic interventions may be deployed to reduce or eliminate the need for replacement opioids while targeting outcomes like feeding dysfunction. Critical care providers can benefit from a structured examination of disordered feeding experiences to inform their selection of non-pharmacologic interventions. This structure can be provided using the Ecology of Human Performance model.

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The Person-Environment-Occupation-Performance (PEOP) Model is one of several occupation-based models in occupational therapy. The model describes the transactional nature of person, environment, and occupation factors that support performance (doing), participation (engagement), and well-being (health and quality of life). The purpose of this study was to explore the extent and nature of evidence on the PEOP Model. We used a scoping review to identify and analyze journal articles that used the PEOP Model as a framework for study. The PRISMA extension for scoping reviews (PRISMA-ScR) criteria were used to develop the research methods. We found 109 articles that adopted the PEOP Model as an organizing framework. The studies reviewed represent the breadth of occupational therapy practice and the transactional nature of person, environment, occupation, and performance in the PEOP Model. The PEOP Model is a useful international framework for research and practice across populations, conditions, life circumstances, settings, and areas of practice.

METHOD: We searched five databases to identify published articles that used the PEOP Model. Then, we analyzed our findings from peer-reviewed journals and peer-reviewed practice publications using a recommended process called a scoping review. We summarized how often the PEOP Model was used and the way in which it was used. FINDINGS: We found the PEOP Model was used in more than 100 published articles. The PEOP Model has been used to study everyday living for different populations, life circumstances, countries, and communities. Authors found the PEOP Model was helpful for identifying what was important to individuals and determining things that were helpful and barriers to everyday living. CONCLUSION: Authors described the PEOP Model as a useful tool in their research methods and analyses. Occupational therapy professionals may find the PEOP Model helpful in current and innovative areas of practice to help people achieve their goals related to everyday living.

The Person­Environment­Occupation­Performance (PEOP) Model: Summary of Current Research on an Occupational Therapy Lens for Everyday LivingBackground and Purpose: The Person­Environment­Occupation­Performance (PEOP) Model was developed to guide occupational therapy practice. The PEOP Model summarizes all the factors that support or limit our involvement in everyday living. By everyday living, we mean all the things we do to take care of ourselves, maintain our health and home, connect with friends and family, engage in meaningful activities, and support ourselves and our community through work and volunteering. The purpose of this study was to summarize the reasons why and the extent to which the PEOP Model was used in research and practice.

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Changing ocean temperatures are predicted to challenge marine organisms, especially when combined with other factors, such as ocean acidification. Acclimation, as a form of phenotypic plasticity, can moderate the consequences of changing environments for biota. Our understanding of how altered temperature and acidification together influence species' acclimation responses is, however, limited compared with that of responses to single stressors. This study investigated how temperature and acidification affect the thermal tolerance and righting speed of the girdled dogwhelk, Trochia cingulata. Whelks were acclimated for 2 weeks to combinations of three temperatures (11°C: cold, 13°C: moderate and 15°C: warm) and two pH regimes (8.0: moderate and 7.5: acidic). We measured the temperature sensitivity of the righting response by generating thermal performance curves from individual data collected at seven test temperatures and determined critical thermal minima (CTmin) and maxima (CTmax). We found that T. cingulata has a broad basal thermal tolerance range (∼38°C) and after acclimation to the warm temperature regime, both the optimal temperature for maximum righting speed and CTmax increased. Contrary to predictions, acidification did not narrow this population's thermal tolerance but increased CTmax. These plastic responses are likely driven by the predictable exposure to temperature extremes measured in the field which originate from the local tidal cycle and the periodic acidification associated with ocean upwelling in the region. This acclimation ability suggests that T. cingulata has at least some capacity to buffer the thermal changes and increased acidification predicted to occur with climate change.

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This research evaluated the rheological behavior of conventional asphalt binders modified with TiO2 and ZnO nanoparticles and proposed mathematical equations for performance prediction. First, composites were evaluated at high temperatures to investigate the Performance Grade (PG), non-recoverable creep compliance, and Aging Index (AI). Subsequently, the fatigue damage tolerance was determined at a temperature of 20 °C through the Linear Amplitude Sweep (LAS) test. At high temperatures, for both nanoparticles, stiffness gain was observed as the nanomaterial content increased, evidenced by the increase in the dynamic shear modulus. This resulted in an increase in the Performance Grade and reduction in non-recoverable creep compliance, leading to greater resistance to permanent deformations. Furthermore, it was found that nanoparticles were able to reduce the effects of oxidation of the asphalt matrix, corroborated by the reduction of the Aging Index (AI). Regarding the fatigue damage tolerance, for both nanoparticles, an increase in performance was observed at low deformation amplitudes and a decrease at high deformation amplitudes. Finally, the analysis of each rheological parameter allowed to define the mathematical equations capable of predicting the performance of conventional asphalt binders when modified with nano-TiO2 or nano-ZnO.

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UAVs are widely used for aerial reconnaissance with imaging sensors. For this, a high detection performance (accuracy of object detection) is desired in order to increase mission success. However, different environmental conditions (negatively) affect sensory data acquisition and automated object detection. For this reason, we present an innovative concept that maps the influence of selected environmental conditions on detection performance utilizing sensor performance models. These models are used in sensor-model-based trajectory optimization to generate optimized reference flight trajectories with aligned sensor control for a fixed-wing UAV in order to increase detection performance. These reference trajectories are calculated using nonlinear model predictive control as well as dynamic programming, both in combination with a newly developed sensor performance model, which is described in this work. To the best of our knowledge, this is the first sensor performance model to be used in unmanned aerial reconnaissance that maps the detection performance for a perception chain with a deep learning-based object detector with respect to selected environmental states. The reference trajectory determines the spatial and temporal positioning of the UAV and its imaging sensor with respect to the reconnaissance object on the ground. The trajectory optimization aims to influence sensor data acquisition by adjusting the sensor position, as part of the environmental states, in such a way that the subsequent automated object detection yields enhanced detection performance. Different constraints derived from perceptual, platform-specific, environmental, and mission-relevant requirements are incorporated into the optimization process. We evaluate the capabilities of the sensor performance model and our approach to sensor-model-based trajectory optimization by a series of simulated aerial reconnaissance tasks for ground vehicle detection. Compared to a variety of benchmark trajectories, our approach achieves an increase in detection performance of 4.48% on average for trajectory optimization with nonlinear model predictive control. With dynamic programming, we achieve even higher performance values that are equal to or close to the theoretical maximum detection performance values.

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In this study, a personal acoustic comfort prediction model (PACPM) for exploring the acoustic comfort of oceanauts in a deep-sea manned submersible cabin was proposed, and an oceanauts' task performance model (OTPM) was constructed in this study. Based on oceanauts' comfort and task performance, the change characteristics in six different pure-noise environments (the sound pressure levels of the noise audio are 40 dB (A), 45 dB (A), 50 dB (A), 55 dB (A), 60 dB (A), and 65 dB (A) respectively) were analysed. An effective method for improving acoustic comfort was proposed. According to the analysis, personal comfort at 40 and 45 dB(A) was higher than that at other noise levels. The oceanaut's comfort and task performance of normal-weight people were significantly higher than those of thin people. Meanwhile, a comprehensive consideration of the demographic characteristics and physiological responses can effectively improve the prediction accuracy of the personnel acoustic comfort. Furthermore, the 45 dB (A) pure-noise environment overlaid with 40 dB(A) fast-paced light music effectively improves oceanauts' comfort. Practitioner summary: This study provides a convenient and available method for analysing acoustic comfort in the cabins of deep-sea manned submersibles, including a quantitative prediction model and an effective method for sound environment improvements. These can be used to improve the comfort, task performance, and working efficiency of manned submersibles.

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Background. Chronic obstructive pulmonary disease (COPD) is a multisystemic chronic condition which may induce significant consequences in daily life activities. Preserving activities of daily living in COPD is therefore a common treatment goal among people living with COPD, which leaves ample opportunity for occupational therapy interventions to comprise part of their rehabilitation. However, the question of how exactly occupational therapists can and do contribute to pulmonary rehabilitation remains underexplored. Purpose. To reveal the contribution of occupational therapy intervention in the pulmonary rehabilitation on improving the occupational performance of patients with COPD. Method. A scoping review was performed by selecting articles focusing on occupational therapy in pulmonary rehabilitation for patients with COPD. A total of four databases were surveyed for article selection. Findings. Among nine studies selected, seven studies reported a significant improvement in the occupational performance of patients with occupational therapy. However, two studies did not observe differences between the groups regarding occupational performance. Implications. Occupational therapy in pulmonary rehabilitation seems to contribute to the improvement of occupational performances of patients with COPD. Nevertheless, research focused on this field needs to be further developed to support the positive impact of occupational therapy in COPD management.

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BACKGROUND: The Basic Local Alignment Search Tool (BLAST) is a suite of commonly used algorithms for identifying matches between biological sequences. The user supplies a database file and query file of sequences for BLAST to find identical sequences between the two. The typical millions of database and query sequences make BLAST computationally challenging but also well suited for parallelization on high-performance computing clusters. The efficacy of parallelization depends on the data partitioning, where the optimal data partitioning relies on an accurate performance model. In previous studies, a BLAST job was sped up by 27 times by partitioning the database and query among thousands of processor nodes. However, the optimality of the partitioning method was not studied. Unlike BLAST performance models proposed in the literature that usually have problem size and hardware configuration as the only variables, the execution time of a BLAST job is a function of database size, query size, and hardware capability. In this work, the nucleotide BLAST application BLASTN was profiled using three methods: shell-level profiling with the Unix "time" command, code-level profiling with the built-in "profiler" module, and system-level profiling with the Unix "gprof" program. The runtimes were measured for six node types, using six different database files and 15 query files, on a heterogeneous HPC cluster with 500+ nodes. The empirical measurement data were fitted with quadratic functions to develop performance models that were used to guide the data parallelization for BLASTN jobs. RESULTS: Profiling results showed that BLASTN contains more than 34,500 different functions, but a single function, RunMTBySplitDB, takes 99.12% of the total runtime. Among its 53 child functions, five core functions were identified to make up 92.12% of the overall BLASTN runtime. Based on the performance models, static load balancing algorithms can be applied to the BLASTN input data to minimize the runtime of the longest job on an HPC cluster. Four test cases being run on homogeneous and heterogeneous clusters were tested. Experiment results showed that the runtime can be reduced by 81% on a homogeneous cluster and by 20% on a heterogeneous cluster by re-distributing the workload. DISCUSSION: Optimal data partitioning can improve BLASTN's overall runtime 5.4-fold in comparison with dividing the database and query into the same number of fragments. The proposed methodology can be used in the other applications in the BLAST+ suite or any other application as long as source code is available.

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A gas path analysis approach of dynamic modelling was used to examine the gas turbine performance. This study presents an investigation of the effect of physical faults on the performance of a three-shaft gas turbine at full-load and part-load operation. A nonlinear steady state performance model was developed and validated. The datasheet from the engine manufacturer was used to gather the input and validation data. Some engineering judgement and optimization were used. Following validation of the engine performance model with the engine manufacturer data using physical fault and component health parameter relationships, physical faults were implanted into the performance model to evaluate the performance characteristics of the gas turbine at degradation state at full- and part-load operation. The impact of erosion and fouling on the gas turbine output parameters, component measurement parameters, and the impact of degraded components on another primary component of the engine have been investigated. The simulation results show that the deviation in the output parameters and component isentropic efficiency due to compressor fouling and erosion is linear with the load variation, but it is almost nonlinear for the downstream components. The results are discussed following the plots.

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OBJECTIVE: This study investigated the use of human performance modeling (HPM) approach for prediction of driver behavior and interactions with in-vehicle technology. BACKGROUND: HPM has been applied in numerous human factors domains such as surface transportation as it can quantify and predict human performance; however, there has been no integrated literature review for predicting driver behavior and interactions with in-vehicle technology in terms of the characteristics of methods used and variables explored. METHOD: A systematic literature review was conducted using Compendex, Web of Science, and Google Scholar. As a result, 100 studies met the inclusion criteria and were reviewed by the authors. Model characteristics and variables were summarized to identify the research gaps and to provide a lookup table to select an appropriate method. RESULTS: The findings provided information on how to select an appropriate HPM based on a combination of independent and dependent variables. The review also summarized the characteristics, limitations, applications, modeling tools, and theoretical bases of the major HPMs. CONCLUSION: The study provided a summary of state-of-the-art on the use of HPM to model driver behavior and use of in-vehicle technology. We provided a table that can assist researchers to find an appropriate modeling approach based on the study independent and dependent variables. APPLICATION: The findings of this study can facilitate the use of HPM in surface transportation and reduce the learning time for researchers especially those with limited modeling background.

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Water temperature is the major controlling factor that shapes the physiology, behaviour and, ultimately, survival of aquatic ectotherms. Here we examine temperature effects on the survival of Chinook salmon (Oncorhynchus tshawytscha), a species of high economic and conservation importance. We implement a framework to assess how incremental changes in temperature impact survival across populations that is based on thermal performance models for three freshwater life stages of Chinook salmon. These temperature-dependent models were combined with local spatial distribution and phenology data to translate spatial-temporal stream temperature data into maps of life stage-specific physiological performance in space and time. Specifically, we converted temperature-dependent performance (i.e. energy used by pre-spawned adults, mortality of incubating embryos and juvenile growth rate) into a common currency that measures survival in order to compare thermal effects across life stages. Based on temperature data from two abnormally warm and dry years for three managed rivers in the Central Valley, California, temperature-dependent mortality during pre-spawning holding was higher than embryonic mortality or juvenile mortality prior to smolting. However, we found that local phenology and spatial distribution helped to mitigate negative thermal impacts. In a theoretical application, we showed that high temperatures may inhibit successful reintroduction of threatened Central Valley spring-run Chinook salmon to two rivers where they have been extirpated. To increase Chinook salmon population sizes, especially for the threatened and declining spring-run, our results indicate that adults may need more cold-water holding habitat than currently available in order to reduce pre-spawning mortality stemming from high temperatures. To conclude, our framework is an effective way to calculate thermal impacts on multiple salmonid populations and life stages within a river over time, providing local managers the information to minimize negative thermal impacts on salmonid populations, particularly important during years when cold-water resources are scarce.

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Objective:Build a research index performance model with discipline growth evaluation, to evaluate the scientific research performance level of various disciplines in hospital more objectively, fairly and dynamically.Methods:Take the research projects, papers, patents and achievements as the main evaluation indicators and establish the hierarchical and classified scoring standards, to form the weight index evaluation model for the total score, per capita score and growth of the discipline research.Results:Using the growth research index to evaluate the scientific research performance of departments and individual researcher between January 2018 and December 2020. Excellent departments were selected for the top 10% of the scientific research index, those whose scientific research scores increased by more than 20% compared with the previous year were selected as the progressive departments, and the top 1% of individual scientific research scores were selected as the advanced researchers, which were commended and encouraged. For the departments ranked in the bottom 5% or whose scientific research index significantly declined compared with previous year, early warning, guidance and supervision were implemented. Since the implementation of the evaluation system, the research performance of disciplines has been significantly improved, and many achievements were made.Conclusions:This evaluation mode can stimulate the enthusiasm of the disciplines and scientific researchers for entrepreneurship and innovation to set up the standards and promote the continuous improvement of the research capacity of the whole hospital.

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Strengthening clinical research is an inevitable requirement for expediting the development of the medical and healthcare services, as well as enhancing the capability of the hospitals in China. On the basis of sufficient argumentation of the significance and the internal and external environment of developing clinical research according to structure-conduct-performance analysis model, Henan Cancer Hospital set the aim of transforming from clinical hospital to clinical research hospital. By constructing a high-level phase Ⅰ clinical trials center, establishing the department of clinical research management, promoting the collaborative innovation and cooperation among medical institutions, research institutions, and enterprises, and developing the accessory clinical trial management system, Henan Cancer Hospital has turned abundant patient resources into advantages of clinical research. The quality and quantity of clinical trials have been elevated significantly, which could provide strong impetus for hospital′s discipline construction and high-quality development.

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The Saudi construction industry is among the largest in the region - and, for workers, among the most dangerous industries. The importance of this study is assisting to reduce hazards, sources of risk and perceptions of safety in the construction sector. Using a quantitative survey measure administered to a small (n = 276) sample of individuals, this study aimed to contribute to empirical understandings of safety performance in this unique context. A multivariate safety performance model was developed to ensure compatibility with the structure of the survey measure. The survey data revealed a strong consensus expressing negative views of every safety dimension and variable tested, with only tiny minorities selecting positively valenced responses. To test the descriptive power of the model as a whole, a structural equation modelling technique was used to assess the correspondence between the relationships constituting the model and their significance relative to empirical data.

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A photovoltaic-electrolysis-PEM hybrid model was developed for a feasibility study, and simulations of several scenarios in Korea were performed. The solar irradiance was derived from the University of Arizona solar irradiance based on satellite-Korea Institute of Energy Research model which provides the satellite imagery over the Korean peninsula every 15 min. In Korea, the annual average solar irradiance is 1,310 kWh m-2 with a maximum of 1,440 kWh m-2 in 2017. Electricity load and solar irradiance information were used to test the performance model of the photovoltaic-electrolysis-PEM hybrid system for baseload and several peak load shave runs. When the baseload was set at 4200 MW, the total capacity of the Photovoltaic plants was 58.5 GWp. In contrast, the hybrid system reduced the peak load more efficiently during daytime. In particular, the capacity factor of the Proton Exchange Membrane system increased in winter because the solar irradiance is relatively weak in that season. These results provide useful insights for the development of control logic models for the PV-electrolysis-PEM system in micro-grid setups.

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RESUMO O Aterro Controlado do Jóquei Clube (ACJC), localizado no Distrito Federal, operou como área de disposição final inadequada de resíduos sólidos desde 1960 até o início de 2018. O principal objetivo desta pesquisa consistiu em avaliar o potencial de contaminação desse aterro, em razão da produção de chorume e biogás. Inicialmente, foram identificadas as áreas mais suscetíveis à contaminação nas sub-bacias hidrográficas do Bananal e do Riacho Fundo, onde o aterro está situado, por meio da produção de um mapa de vulnerabilidade natural à contaminação dos aquíferos. Para tanto, utilizou-se a metodologia DRASTIC, que consiste em uma combinação linear ponderada de sete parâmetros hidrogeológicos, com o auxílio da ferramenta de análise multicritério AHP (Análise Hierárquica de Processos) e de algoritmos de álgebra de mapas implementados em ambiente de Sistema de Informação Geográfica (SIG). Esse mapa evidenciou que o ACJC está localizado em áreas de moderada a elevada vulnerabilidade natural à contaminação. Simulou-se também o balanço hídrico no aterro por meio do modelo Hydrologic Evaluation of Landfill Performance (HELP), o qual possibilitou a identificação de áreas com maior potencial de contaminação em razão do maior volume de chorume produzido. Por fim, realizou-se uma análise da temperatura de cobertura do solo na região do aterro, por meio de imagens sazonais do sensor orbital TM/Landsat entre os anos de 1986 e 2016, as quais evidenciaram aumento gradual da temperatura, servindo de possível indicador da distribuição subsuperficial de biogás presente no aterro.

ABSTRACT The Jockey Club Landfill is a solid waste disposal site located at Brazil's Federal District, which operated inadequately from 1960 until the beginning of 2018. The main objective of this paper was to assess the contamination potential of the Jockey Club Landfill due to leachate and biogas production. Initially, the most susceptible areas to contamination were identified within the two hydrographic sub-basins of Bananal and Riacho Fundo, where the landfill is located, by producing a map of the aquifer's natural vulnerability to contamination. This map was produced based on the DRASTIC methodology, which consists in a weighted linear combination of seven important hydrogeological parameters, with support of the multicriteria Analytic Hierarchy Process (AHP) and map algebra tools implemented in a Geographic Information System (GIS) environment. This map evidenced that Jockey Club Landfill is located in areas of moderate to high natural vulnerability to contamination. The water balance throughout the landfill profile was also simulated using the Hydrologic Evaluation of Landfill Performance model (HELP), whose results evidenced that the contamination potential is higher in some portions of the landfill due to greater volumes of leachate produced. Lastly, an analysis of ground cover temperature in the landfill region was undertaken, using TM/Landsat seasonal images between the years 1986 to 2016, which indicated a gradual increase in ground temperature, evidencing a possible occurrence of subsurface biogas distribution in the landfill.

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Seed germination is a critical stage in the life cycle of most plants and is defined by specific tolerance thresholds beyond which rates and success of germination rapidly decline. Previous studies have demonstrated that widespread plant species commonly germinate over a broad range of temperatures and water stress levels, whereas range-restricted species often exhibit a narrower germination window in terms of temperature and moisture. We investigated the relationships of the key germination traits of maximum germination (G max) and time to 50% germination (t 50) in response to temperature (5-35°C) and water stress (-1.5-0 MPa) in four co-occurring Western Australian native Eucalyptus species with widely varying biogeography. Eucalyptus caesia subsp. caesia and E. ornata exhibit a highly localized distribution and a narrow geographical range, being restricted either to granite outcrops or the upper slopes and tops of lateritic rises, respectively. These two species were compared with the two widespread and dominant congenerics E. salmonophloia and E. salubris. There was a distinctive hump-shaped response of t 50 to temperature and an exponential response to water stress, characteristic of rate- and threshold-limited processes, but no consistent pattern in the response of G max. The four species were significantly different in their thermal performance of t 50, with E. caesia and E. ornata displaying narrower thermal tolerance ranges than the two widespread species. In terms of mean final germination percentage, the two range-restricted endemic taxa exhibited higher lability in their response to thermal stress and drought stress compared to the two broadly distributed congenerics. These findings indicate a link between distributional extent, temperature and water stress tolerance and may have implications for identifying ecological filters of rarity and endemism.

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We calibrate the seven parameters of a single-diode model (SDM) for photo-voltaic device performance using current-voltage (I-V) curves measured under controlled laboratory conditions over a matrix of nominal temperature and irradiance combinations. As described in previous modeling work, we do not use a short-circuit temperature coefficient parameter, which depends on the often unknown insolation spectrum and whose validity may be questionable. Alternatively, we employ a rigorous temperature-dependent extension of the spectral mismatch correction. This standard correction is routinely used by calibration laboratories to measure an effective irradiance ratio (i.e., a particular ratio of short-circuit currents) using a calibrated reference device, thereby compensating for spectral effects of the irradiance and for any difference in spectral response between the test device and reference device. The calibrated SDM predicts the device's current at any prescribed voltage, temperature, and effective irradiance, and thus can predicts power and energy production under prescribed conditions. Our approach aligns well with the matched reference cell approach to outdoor I-V curve measurements, while clarifying the requirements of a "matched" condition for the irradiance monitoring device(s). We find evidence for significant model discrepancy in the SDM, suggesting that model improvements and measurement intercomparisons are needed.

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Objective:To establish a calculation model of drug preparation difficulty coefficient for outpatient pharmacy intrave -nous admixture center ( OUIVA) in a children's hospital, and construct the performance model .Methods: All the prescriptions in a week in OUIVA of Shanghai children's medical center were randomly selected .According to the actual difficulty level in the process of outpatient and emergency drug preparation , a basic drug difficulty coefficient and difficulty coefficient addition method was constructed . The difficulty index of every prescription was calculated .All the prescriptions in a week were randomly selected , and according to the difficulty coefficient analysis method , the daily difficulty coefficient of the prescriptions was calculated in order to build a performance model for OUIVA in the hospital .Results:The difficulty coefficient of medicine mainly included four basic difficulty coefficients and nine difficulty addition coefficients .According to the statistics , the average difficulty coefficient of daily prescriptions was (3.83 ± 2.86 )with the highest difficulty coefficient of 35, and the prescription data showed that there was significant difference between outpa -tient and emergency prescriptions and daytime blood tumor prescriptions .Conclusion:A performance model based on the difficulty co-efficient for OUIVA in children ' s hospital is a more scientific reflection to the daily work .