Analysis of pion-helium scattering for the pion charge form factor.
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The successful application of photographic, optical-mechanical scanning, and other sensing techniques to vegetation must be based on an understanding of the biological and physical principles involved. The objective is to review the biological and optical characteristics of vegetation and to discuss how knowledge of them can support operational programs by aiding in wavelength selection, timing of missions, and discriminations between vegetation types as well as between healthy and stressed plants of the same type. Both laboratory situations, in which relatively pure spectral data are obtained, and field situations are considered. In the latter, sensor performance and background variables affect data quality.
Four concepts for on-orbit spacesuit donning, doffing, servicing, check-out, egress and ingress are presented. These are: the Space Transportation System (STS) Type (shuttle system enlarged), the Transit Airlock (Shuttle Airlock with suit servicing removed from the pump-down chamber), the Suitport (a rear-entry suit mates to a port in the airlock wall), and the Crewlock (a small, individual, conformal airlock). Each of these four concepts is compared through a series of seven steps representing a typical Extra Vehicular Activity (EVA) mission: (1) Predonning suit preparation; (2) Portable Life Support System (PLSS) preparation; (3) Suit Donning and Final Check; (4) Egress/Ingress; (5) Mid-EVA rest period; (6) Post-EVA Securing; (7) Non-Routine Maintenance. The different characteristics of each concept are articulated through this step-by-step approach. Recommendations concerning an approach for further evaluations of airlock geometry, anthropometrics, ergonomics, and functional efficiency are made. The key recommendation is that before any particular airlock can be designed, the full range of spacesuit servicing functions must be considered, including timelines that are most supportive of EVA human productivity.
This study analyzed the risk factors for patients with COVID-19 developing severe illnesses and explored the value of applying the logistic model combined with ROC curve analysis to predict the risk of severe illnesses at COVID-19 patients’ admissions. The clinical data of 1046 COVID-19 patients admitted to a designated hospital in a certain city from July to September 2020 were retrospectively analyzed, the clinical characteristics of the patients were collected, and a multivariate unconditional logistic regression analysis was used to determine the risk factors for severe illnesses in COVID-19 patients during hospitalization. Based on the analysis results, a prediction model for severe conditions and the ROC curve were constructed, and the predictive value of the model was assessed. Logistic regression analysis showed that age (OR = 3.257, 95% CI 10.466–18.584), complications with chronic obstructive pulmonary disease (OR = 7.337, 95% CI 0.227–87.021), cough (OR = 5517, 95% CI 0.258–65.024), and venous thrombosis (OR = 7322, 95% CI 0.278–95.020) were risk factors for COVID-19 patients developing severe conditions during hospitalization. When complications were not taken into consideration, COVID-19 patients’ ages, number of diseases, and underlying diseases were risk factors influencing the development of severe illnesses. The ROC curve analysis results showed that the AUC that predicted the severity of COVID-19 patients at admission was 0.943, the optimal threshold was −3.24, and the specificity was 0.824, while the sensitivity was 0.827. The changes in the condition of severe COVID-19 patients are related to many factors such as age, clinical symptoms, and underlying diseases. This study has a certain value in predicting COVID-19 patients that develop from mild to severe conditions, and this prediction model is a useful tool in the quick prediction of the changes in patients’ conditions and providing early intervention for those with risk factors.
The interdisciplinary optimization of engineering systems is discussed from the standpoint of the computational alternatives available to the designer. The analysis of such systems typically requires the solution of coupled systems of nonlinear algebraic equations. The solution procedure is necessarily iterative in nature. It is shown that the system can be solved by fixed point iteration, by Newton's method, or by a combination of the two. However, the need for sensitivity analysis may affect the choice of analysis solution method. Similarly, the optimization of the system can be formulated in several ways that are discussed in the paper. It is shown that the effect of the topology of the interaction between disciplines is a key factor in the choice of analysis, sensitivity and optimization methods. Several examples are presented to illustrate the discussion.
Factors external to the aircraft are often a significant causal factor in loss of control (LOC) accidents. In today s aviation world, very few accidents stem from a single cause and typically have a number of causal factors that culminate in a LOC accident. Very often the "trigger" that initiates an accident sequence is an external environment factor. In a recent NASA statistical analysis of LOC accidents, aircraft icing was shown to be the most common external environmental LOC causal factor for scheduled operations. When investigating LOC accident or incidents aircraft icing causal factors can be categorized into groups of 1) in-flight encounter with super-cooled liquid water clouds, 2) take-off with ice contamination, or 3) in-flight encounter with high concentrations of ice crystals. As with other flight hazards, icing induced LOC accidents can be prevented through avoidance, detection, and recovery mitigations. For icing hazards, avoidance can take the form of avoiding flight into icing conditions or avoiding the hazard of icing by making the aircraft tolerant to icing conditions. Icing detection mitigations can take the form of detecting icing conditions or detecting early performance degradation caused by icing. Recovery from icing induced LOC requires flight crew or automated systems capable of accounting for reduced aircraft performance and degraded control authority during the recovery maneuvers. In this report we review the icing induced LOC accident mitigations defined in a recent LOC study and for each mitigation describe a research topic required to enable or strengthen the mitigation. Many of these research topics are already included in ongoing or planned NASA icing research activities or are being addressed by members of the icing research community. These research activities are described and the status of the ongoing or planned research to address the technology needs is discussed
The structural frame used for conducting large structural tests was replaced by the ACME (Applied Combined Mechanical Environments) Lab in Building 860 of Sandia National Laboratories in Albuquerque, NM. This new design required simulation and analysis to verify maximum loads and corresponding factors of safety. Two major assemblies which are part of the ACME Lab, the Modular Wall and A-Frame, were designed to operate with a multitude of components in various configurations and with varying loads. Simulations of the Modular Wall and A-Frame structures were performed through explicit analysis to determine safety factors for numerous loading scenarios. The Modular Wall had safety factors of 1.1 for the lateral, diagonal, and gusset loading conditions. The A-Frame had safety factors of 2 for all loading conditions simulated.
The Orbital Acceleration Research Experiment (OARE), which has flown on STS-40, STS-50, and STS-58, contains a three-axis accelerometer with a single, nonpendulous, electrostatically suspended proofmass, which can resolve accelerations to the 10(sub -9) g level. The experiment also contains a full calibration station to permit in situ bias and scale-factor calibration. This on-orbit calibration capability eliminates the large uncertainty of ground-based calibrations encountered with accelerometers flown in the past on the Orbiter, and thus provides absolute acceleration measurement accuracy heretofore unachievable. This is the first time accelerometer scale-factor measurements have been performed on orbit. A detailed analysis of the calibration process is given, along with results of the calibration factors from the on-orbit OARE flight measurements on STS-58. In addition, the analysis of OARE flight-maneuver data used to validate the scale-factor measurements in the sensor's most sensitive range are also presented. Estimates on calibration uncertainties are discussed. These uncertainty estimates provides bounds on the STS-58 absolute acceleration measurements for future applications.
Purpose: This study aimed to evaluate the prognostic significance of the modified Glasgow Prognostic Score (mGPS) in patients with non-small cell lung cancer (NSCLC) who received stereotactic body radiation therapy (SBRT). Methods and Materials: Data from 165 patients who underwent SBRT for stage I NSCLC with histologic confirmation from January 1999 to September 2010 were collected retrospectively. Factors, including age, performance status, histology, Charlson comorbidity index, mGPS, and recursive partitioning analysis (RPA) class based on sex and T stage, were evaluated with regard to overall survival (OS) using the Cox proportional hazards model. The impact of the mGPS on cause of death and failure patterns was also analyzed. Results: The 3-year OS was 57.9%, with a median follow-up time of 3.5 years. A higher mGPS correlated significantly with poor OS (P<.001). The 3-year OS of lower mGPS patients was 66.4%, whereas that of higher mGPS patients was 44.5%. On multivariate analysis, mGPS and RPA class were significant factors for OS. A higher mGPS correlated significantly with lung cancer death (P=.019) and distant metastasis (P=.013). Conclusions: The mGPS was a significant predictor of clinical outcomes for SBRT in NSCLC patients.
Highlights: • Microchips are developed for stimulating bone cells and quantifying activity. • A chip permits osteocyte loading and soluble signal analysis. • A chip enables quantification of bone resorption and formation. • This model may remove spatial and temporal limitations of existing systems. • This microfluidic approach shows promise for future discovery in the bone field. Researchers have been using lab-on-a-chip systems to isolate factors for study, simulate laboratory analysis and model cellular, tissue and organ level processes. The technology is increasing rapidly, but the bone field has been slow to keep pace. Novel models are needed that have the power and flexibility to investigate the elegant and synchronous multicellular interactions that occur in normal bone turnover and in disease states in which remodeling is implicated. By removing temporal and spatial limitations and enabling quantification of functional outcomes, the platforms should provide unique environments that are more biomimetic than single cell type systems while minimizing complex systemic effects of in vivo models. This manuscript details the development and characterization of lab-on-a-chip platforms for stimulating osteocytes and quantifying bone remodeling. Our platforms provide the foundation for a model that can be used to investigate remodeling interactions as a whole or as a standard mechanotransduction tool by which isolated activity can be quantified as a function of load.
Analysis was made to determine correlation between number and size of carbide particles and rolling-element fatigue. Correlation was established, and carbide factor was derived that can be used to predict fatigue life more effectively than such variables as heat treatment, chemical composition, and hardening mechanism.
Abstract Aim To assess the teratogenic risk of domperidone by comparing the incidence of major malformation with domperidone to a control. Methods Pregnancy outcome data were obtained for women at two Japanese facilities that provide counseling on drug use during pregnancy between April 1988 and December 2017. The incidence of major malformation was calculated among infants born to women taking domperidone ( n = 519), nonteratogenic drugs (control, n = 1673), or metoclopramide (reference, n = 241) during the first trimester of pregnancy. Using the control group as reference, the crude odds ratio (OR) of the incidence of major malformation in the domperidone and metoclopramide groups was calculated using univariable logistic regression analysis. Adjusted OR was also calculated using multivariable logistic regression analysis adjusted for various other factors. Results The incidence of major malformation was 2.9% (14/485, 95% confidence interval [CI]: 1.6–4.8) in the domperidone group, 1.7% (27/1554, 95%CI: 1.1–2.5) in the control group, and 3.6% (8/224, 95%CI: 1.6–6.9) in the metoclopramide group. The adjusted multivariable logistic regression analysis showed no significant difference in incidence between the control and domperidone groups (adjusted OR: 1.86 [95%CI: 0.73–4.70], p = 0.191) or between the control and metoclopramide groups (adjusted OR: 2.20 [95%CI: 0.69–6.98], p = 0.183). Conclusions This observational cohort study showed that domperidone exposure during the first trimester was not associated with increased risk of major malformation in infants. These results may help alleviate the anxiety of patients who took domperidone during pregnancy.
Gloveboxes are isolation barriers that are used within many different industries such as pharmaceuticals, electronic parts fabrication, nuclear, and biological. The research on glovebox ergonomics is currently limited with few ergonomic professionals that focusing exclusively on glovebox working environments. There is existing documentation on occupational injuries, such as musculoskeletal disorders (MSD), sustained as a direct result of working in gloveboxes. The main elements that pose ergonomic risks to glovebox workers are operational repetition, duration, force, vibration, lifting heavy (more than 15lbs with two hands) objects, and awkward postures. This paper examines a small sample of the potential causal or risk factors that lead to the ergonomic injuries. A meta-analysis utilizing a random effect model is used to examine data from several studies which focus on, dexterity and strength changes as result of glove thickness, and robotic assistive technology as a means to improve postural mechanics. With the meta-analysis technique, similar data sets from different research studies can be coalesced into a single weighted, statistically significant result for subsequent consideration. The results from the analysis show that increased glove thickness results in decreased dexterity for operators thus increasing ergonomic risk factors such as task duration. It is also shown that glove thickness decreases grip strength but a similar decrease in pinch strength is not definitively demonstrated. With decreased grip strength, operators will need to exert more force (a known ergonomic risk factor) on processing tools, etc. during operations thus increasing the risk of ergonomic injury. The use of robotic assistive technology as a means to improve operator posture (risk factor) was also examined. Although it may be intuitively assumed that human-robotic collaboration would be beneficial in reducing risk factors, the result from this study’s analysis was not statistically significant. It is inferred that with additional directed research on this topic another study/analysis could be statistically significant demonstrating the benefits of the technology.
Purpose: The purpose of this study was to evaluate the role of involved-lesion radiation therapy (ILRT) after rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) chemotherapy in limited stage diffuse large B-cell lymphoma (DLBCL) by comparing outcomes of R-CHOP therapy alone with R-CHOP followed by ILRT. Methods and Materials: We identified 198 patients treated with R-CHOP (median, 6 cycles) for pathologically confirmed DLBCL of limited stage from July 2004 to December 2012. Clinical characteristics of these patients were 33% with stage I and 66.7% with stage II; 79.8% were in the low or low-intermediate risk group; 13.6% had B symptoms; 29.8% had bulky tumors (≥7 cm); and 75.3% underwent ≥6 cycles of R-CHOP therapy. RT was given to 43 patients (21.7%) using ILRT technique, which included the prechemotherapy tumor volume with a median margin of 2 cm (median RT dose: 36 Gy). Results: After a median follow-up of 40 months, 3-year progression-free survival (PFS) and overall survival (OS) were 85.8% and 88.9%, respectively. Multivariate analysis showed ≥6 cycles of R-CHOP (PFS, P=.004; OS, P=.004) and ILRT (PFS, P=.021; OS, P=.014) were favorable prognosticators of PFS and OS. A bulky tumor (P=.027) and response to R-CHOP (P=.012) were also found to be independent factors of OS. In subgroup analysis, the effect of ILRT was prominent in patients with a bulky tumor (PFS, P=.014; OS, P=.030) or an elevated level of serum lactate dehydrogenase (LDH; PFS, P=.004; OS, P=.012). Conclusions: Our results suggest that ILRT after R-CHOP therapy improves PFS and OS in patients with limited stage DLBCL, especially in those with bulky disease or an elevated serum LDH level.
This paper introduces an analytical approach, Probability and Confidence Trade-space (PACT), which can be used to assess uncertainty in International Space Station (ISS) hardware sparing necessary to extend the life of the vehicle. There are several key areas under consideration in this research. We investigate what sparing confidence targets may be reasonable to ensure vehicle survivability and for completion of science on the ISS. The results of the analysis will provide a methodological basis for reassessing vehicle subsystem confidence targets. An ongoing annual analysis currently compares the probability of existing spares exceeding the total expected unit demand of the Orbital Replacement Unit (ORU) in functional hierarchies approximating the vehicle subsystems. In cases where the functional hierarchies availability does not meet subsystem confidence targets, the current sparing analysis further identifies which ORUs may require additional spares to extend the life of the ISS. The resulting probability is dependent upon hardware reliability estimates. However, the ISS hardware fleet carries considerable epistemic uncertainty (uncertainty in the knowledge of the true hardware failure rate), which does not currently factor into the annual sparing analysis. The existing confidence targets may be conservative. This paper will also discuss how confidence targets may be relaxed based on the inclusion of epistemic uncertainty for each ORU. The paper will conclude with strengths and limitations for implementing the analytical approach in sustaining the ISS through end of life, 2020 and beyond.
Plant defense responses to pathogens involve massive transcriptional reprogramming. Recently, differential coexpression analysis has been developed to study the rewiring of gene networks through microarray data, which is becoming an important complement to traditional differential expression analysis. Using time-series microarray data of Arabidopsis thaliana infected with Pseudomonas syringae, we analyzed Arabidopsis defense responses to P. syringae through differential coexpression analysis. Overall, we found that differential coexpression was a common phenomenon of plant immunity. Genes that were frequently involved in differential coexpression tend to be related to plant immune responses. Importantly, many of those genes have similar average expression levels between normal plant growth and pathogen infection but have different coexpression partners. By integrating the Arabidopsis regulatory network into our analysis, we identified several transcription factors that may be regulators of differential coexpression during plant immune responses. We also observed extensive differential coexpression between genes within the same metabolic pathways. Several metabolic pathways, such as photosynthesis light reactions, exhibited significant changes in expression correlation between normal growth and pathogen infection. Taken together, differential coexpression analysis provides a new strategy for analyzing transcriptional data related to plant defense responses and new insights into the understanding of plant-pathogen interactions.
The paper is a self-contained discussion of a right factorization approach in the stability analysis of the nonlinear continuous-time or discrete-time, time-invariant or time-varying, well-posed unity-feedback system S1(P, C). It is shown that a well-posed stable feedback system S1(P, C) implies that P and C have right factorizations. In the case where C is stable, P has a normalized right-coprime factorization. The factorization approach is used in stabilization and simultaneous stabilization results.
Current earth system models have a large range of uncertainty, owing to differences in the simulation of feedbacks and insufficient information to constrain model parameters. Parameter disturbance experiment provides a straightforward method to quantify the variation (uncertainty) outputs caused by model inputs. Owing to the software complexity and computational intensity of earth system models, a large-scale simulation framework is needed to support ensemble simulation required by parameter disturbance experiment. This paper presents a parallel framework for the community land model ensemble simulation. After a software structure review of the community land model simulation, a single factor parameter disturbance experiment of a reference computational experiment design is used to demonstrate the software design principles, computational characteristics of individual application, parallel ensemble simulation implementation, as well as the weak scalability of this simulation framework on a high-end computer. Lastly, the paper discusses some preliminary diagnostic analysis results of the single factor parameter disturbance experiments. The framework design considerations and implementation details described in this paper can be beneficial to many other research programmes involving large scale, legacy modelling system.