Comparing reflective and formative measures : new insights from relevant simulations

Previous simulations comparing formative and reflective models specify formative population models as the only correct model for a given construct, and compare them with various mis-specified reflective models. However, this approach does not generalize to situations where both reflective and formative specifications can work well to assess constructs. To address this limitation, this study presents simulations in which both formative and reflective specifications fit the underlying population data equally well. The results show that reflective specifications generate less biased and more powerful results than formative specifications, and make a strong case for considering standardized rather than unstandardized coefficients for both specifications. Therefore, conceptual and empirical consequences of using reflective models for constructs that could also be modeled as formative are less dire than past research has suggested

When Do Organizations Behave Opportunistically? The Effects Of Collectivistic Organizational Culture

Transaction cost theory posits that firms behave opportunistically if they are given the chance. In reality, however, some firms act opportunistically, whereas others do not. This raises the question of under what circumstances firms tend to behave opportunistically. Previous studies provided no clear explanation of when opportunism occurs and what its antecedents are. This study identifies the circumstances under which firms behave opportunistically by empirically testing the following two causal factors in opportunistic behaviors: transaction-specific investment (TSI) and collectivistic organizational culture. The survey results indicate that a firm’s TSI is an important factor influencing opportunistic behaviors and that collectivism moderates the relationship between TSI and opportunism

Nature of Infrared Sources in 11 micron Selected Sample from Early Data of the AKARI North Ecliptic Pole Deep Survey

We present the properties of 11 $\mu$m selected sources detected in the early data of the North Ecliptic Pole Deep (NEP-Deep) Survey of AKARI. The data set covers 6 wavelength bands from 2.5 to 11 $\mu$m, with the exposure time of 10 ~ 20 minutes. This field lies within the CFHT survey with four filter bands ($g', r', i',z'), enabling us to establish nearly continuous spectral energy distributions (SEDs) for wavelengths ranging from 0.4 to 11$\mu$m. The main sample studied here consists of 71 sources whose 11$\mu$m AB magnitudes are equal to or brighter than 18.5 (251$\mu$Jy), which is complete to more than 90$\mu$m band has an advantage of sampling star forming galaxies with low to medium redshifts since the prominent PAH feature shifts into this band. As expected, we find that the majority (~68$\mu$m bright sources are star forming galaxies at 0.2 < z < 0.7 with$L_{IR} ~ 10^{10}$--$10^{12} L_{\odot}$ based on the detailed modelling of SEDs. We also find four AGNs lying at various redshifts in the main sample. In addition, we discuss a few sources which have non-typical SEDs of the main sample, including a brown dwarf candidate, a steep power-law source, flat spectrum object, and an early-type galaxy at moderate redshift.Comment: 22 pages, 10 figure

A Robust Longitudinal Co-culture of Obligate Anaerobic Gut Microbiome With Human Intestinal Epithelium in an Anoxic-Oxic Interface-on-a-Chip

The majority of human gut microbiome is comprised of obligate anaerobic bacteria that exert essential metabolic functions in the human colon. These anaerobic gut bacteria constantly crosstalk with the colonic epithelium in a mucosal anoxic-oxic interface (AOI). However, in vitro recreation of the metabolically mismatched colonic AOI has been technically challenging. Furthermore, stable co-culture of the obligate anaerobic commensal microbiome and epithelial cells in a mechanically dynamic condition is essential for demonstrating the host-gut microbiome crosstalk. Here, we developed an anoxic-oxic interface-on-a-chip (AOI Chip) by leveraging a modified human gut-on-a-chip to demonstrate a controlled oxygen gradient in the lumen-capillary transepithelial interface by flowing anoxic and oxic culture medium at various physiological milieus. Computational simulation and experimental results revealed that the presence of the epithelial cell layer and the flow-dependent conditioning in the lumen microchannel is necessary and sufficient to create the steady-state vertical oxygen gradient in the AOI Chip. We confirmed that the created AOI does not compromise the viability, barrier function, mucin production, and the expression and localization of tight junction proteins in the 3D intestinal epithelial layer. Two obligate anaerobic commensal gut microbiome, Bifidobacterium adolescentis and Eubacterium hallii, that exert metabolic cross-feeding in vivo, were independently co-cultured with epithelial cells in the AOI Chip for up to a week without compromising any cell viability. Our new protocol for creating an AOI in a microfluidic gut-on-a-chip may enable to demonstrate the key physiological interactions of obligate anaerobic gut microbiome with the host cells associated with intestinal metabolism, homeostasis, and immune regulation

Novel next generation sequencing panel method for the multiple detection and identification of foodborne pathogens in agricultural wastewater

Detecting and identifying the origins of foodborne pathogen outbreaks is a challenging. The Next-Generation Sequencing (NGS) panel method offers a potential solution by enabling efficient screening and identification of various bacteria in one reaction. In this study, new NGS panel primer sets that target 18 specific virulence factor genes from six target pathogens (Bacillus cereus, Yersinia enterocolitica, Staphylococcus aureus, Vibrio cholerae, Vibrio parahaemolyticus, and Vibrio vulnificus) were developed and optimized. The primer sets were validated for specificity and selectivity through singleplex PCR, confirming the expected amplicon size. Crosscheck and multiplex PCR showed no interference in the primer set or pathogenic DNA mixture. The NGS panel analysis of spiked water samples detected all 18 target genes in a single reaction, with pathogen concentrations ranging from 108 to 105 colony-forming units (CFUs) per target pathogen. Notably, the total sequence read counts from the virulence factor genes showed a positive association with the CFUs per target pathogen. However, the method exhibited relatively low sensitivity and occasional false positive results at low pathogen concentrations of 105 CFUs. To validate the detection and identification results, two sets of quantitative real-time PCR (qPCR) analyses were independently performed on the same spiked water samples, yielding almost the same efficiency and specificity compared to the NGS panel analysis. Comparative statistical analysis and Spearman correlation analysis further supported the similarity of the results by showing a negative association between the NGS panel sequence read counts and qPCR cycle threshold (Ct) values. To enhance NGS panel analysis for better detection, optimization of primer sets and real-time NGS sequencing technology are essential. Nonetheless, this study provides valuable insights into applying NGS panel analysis for multiple foodborne pathogen detection, emphasizing its potential in ensuring food safety

Investing in Clinical Trials for Older Adults: The Value and Challenges of Older Adult-Specific Clinical Trials

Thesis (Ph.D.)--University of Washington, 2022Conducting clinical trials for older adults can address the long-standing issue of the underrepresentation of older adults and the lack of clinical evidence for them. Examining the challenges and the value of such trials could facilitate discussion among trial sponsors on the investment in and the prioritization of older adult-specific trials. This dissertation examines the risk of failure and the real-world value of older adult-specific clinical trials. In Chapter 1, we developed a model that predicts the risk of failure of older adult-specific cancer clinical trials, using trial-level factors. The best-performing machine learning model had an acceptable performance and included nine trial-level factors that can be measured using the trial protocol. The model can aid in the design and prioritization of future older adult-specific clinical trials. Future works examining the causal relationship between the important factors the trial failure can help develop strategies to reduce the risk of failure of cancer trials for older adults. In Chapter 2, we estimated the impact of cumulative evidence from older adult-specific trials on the prescribing patterns, using phase 3 clinical trials for post-lumpectomy irradiation in early-stage breast cancer (ESBC) as a case study. The difference-in-differences analysis showed that older adult-specific trial results led to a significant decrease in irradiation use over time among older adults and the rate of decrease was significantly accelerated by longer-term follow-up results. These findings confirm the potential of new evidence for older adults to make a substantial change in providers’ prescription patterns and the importance of evidence accumulation in driving their behavioral change. Chapter 3 builds on this analysis to quantify the downstream clinical and economic benefits of older adult-specific trial results, using a health-transition model. We found that the older adult-specific trial results on the post-lumpectomy irradiation in ESBC resulted in a substantial cost-saving in the US society, without significantly changing clinical outcomes. These results can inform the discussion around whether to invest in older adult-specific clinical trials. More case studies for trials with different types of results are warranted to have a more comprehensive understanding of how different types of older adult-specific trials generate value

Effect of Gravity and Various Operating Conditions on Proton Exchange Membrane Water Electrolysis Cell Performance

Water electrolysis is an eco-friendly method for the utilization of renewable energy sources which provide intermittent power supply. Proton exchange membrane water electrolysis (PEMWE) has a high efficiency in this regard. However, the two-phase flow of water and oxygen at the anode side causes performance degradation, and various operating conditions affect the performance of PEMWE. In this study, the effects of four control parameters (operating temperature, flow rate, cell orientation, and pattern of the channel) on the performance of PEMWE were investigated. The effects of the operating conditions on its performance were examined using a 25 cm2 single-cell. Evaluation tests were conducted using in situ methods such as polarization curves and electrochemical impedance spectroscopy. The results demonstrated that a high operating temperature and low flow rate reduce the activation and ohmic losses, and thereby enhance the performance of PEMWE. Additionally, the cell orientation affects the performance of PEMWE owing to the variation in the two-phase flow regime. It was observed that the slope of specific sections in the polarization curve rapidly increases at a specific cell voltage

Performance Comparison of Proton Exchange Membrane Water Electrolysis Cell Using Channel and PTL Flow Fields through Three-Dimensional Two-Phase Flow Simulation

Water electrolysis technology is required to overcome the intermittency of renewable energy sources. Among various water electrolysis methods, the proton exchange membrane water electrolysis (PEMWE) cell has the advantages of a fast response and high current density. However, high capital costs have hindered the commercialization of PEMWE; therefore, it is important to lower the price of bipolar plates, which make PEMWE expensive. In addition, since the flow field inscribed in the bipolar plate significantly influences the performance, it is necessary to design the enhanced pattern. A three-dimensional two-phase flow model was used to analyze the two-phase flow and electrochemical reactions of the PEMWE anode. In order to compare the experimental results with the simulation, experiments were conducted according to the flow rate, and the results were in good agreement. First, as a result of comparing the performance of the channel and PTL (porous transport layer) flow fields, the channel flow field showed better performance than the PTL flow field. For the channel flow field, the higher the ratio of the channel width-to-rib width and the permeability of PTL, the performance got better. In the case of the PTL flow field, with the increased capillary pressure, the performance improved even if the PTL permeability decreased. Next, the direction of gravity affected the performance only when the channel flow field was used, and the X+ and Z+ directions were optimal for the performance. Finally, increasing the inlet flow rate could reduce the difference in performance between the channel and PTL flow fields, but the pressure drop gradually increased

The FUTUREPAIN study: Validating a questionnaire to predict the probability of having chronic pain 7-10 years into the future.

ObjectivesThe FUTUREPAIN study develops a short general-purpose questionnaire, based on the biopsychosocial model, to predict the probability of developing or maintaining moderate-to-severe chronic pain 7-10 years into the future.MethodsThis is a retrospective cohort study. Two-thirds of participants in the National Survey of Midlife Development in the United States were randomly assigned to a training cohort used to train a predictive machine learning model based on the least absolute shrinkage and selection operator (LASSO) algorithm, which produces a model with minimal covariates. Out-of-sample predictions from this model were then estimated using the remaining one-third testing cohort to determine the area under the receiver operating characteristic curve (AUROC). An optimal cut-point that maximized sensitivity and specificity was determined.ResultsThe LASSO model using 82 variables in the training cohort, yielded an 18-variable model with an out-of-sample AUROC of 0.85 (95% Confidence Interval (CI): 0.80, 0.91) in the testing cohort. The sum of sensitivity (0.88) and specificity (0.76) was maximized at a cut-point of 17 (95% CI: 15, 18) on a 0-100 scale where the AUROC was 0.82.DiscussionWe developed a short general-purpose questionnaire that predicts the probability of an adult having moderate-to-severe chronic pain in 7-to-10 years. It has diagnostic ability greater than 80% and can be used regardless of whether a patient is currently experiencing chronic pain. Knowing which patients are likely to have moderate-to-severe chronic pain in the future allows clinicians to target preventive treatment