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The concepts of technology fusion describe the phenomenon of technology overlap. Despite its importance, the evolutionary trajectories of technology fusion are not explored well. The main contributions of this article have two aspects: One is the mathematical modeling of a two-dimensional technology fusion system with technical efficiency and convergence parameters that can determine the evolution trajectories of technology fusion; the other is to reveal the dynamics of the evolution process through robust analysis and improving the stability of technology fusion under external disturbances. A novel technology fusion analysis method is proposed for technology fusion by applying dynamic development scenarios of manufacturing technology and information technology to be robust under external disturbances. In this article, firstly, we introduce technical efficiency and convergence parameters to establish a two-dimensional technology fusion system. Secondly, according to the characteristics of different fusion stages, we select the order parameters at each stage and establish order parameters function to determine the evolution trajectories of technology fusion. Finally, the fixed-point theory and the bifurcation theory are used to analyze the robustness of each stage, and the robust theorem at different technology fusion stages is proposed. The research results show: (1) We find that the characteristics analysis of technology fusion can divide the technology fusion process into three different stages, and the main characteristics of each stage as the order parameter can better reveal the evolution trajectory of technology fusion. (2) We find that the dynamics of technology fusion are caused by competition between the driving force and the dissipating force in the process of technology fusion. (3) We find that the dynamics of the technology fusion process may cause technology fusion to fall into chaos. (4) We find that by reasonably changing the relationship between the driving force and the dissipating force, the technology fusion process can be kept stable.

Introduction: Total joint arthroplasty is projected to expand rapidly by 2030. With large numbers of patients undergoing TJA, the choice of incisional closure has come into question. We compared the 2-Ocyl cyanoacrylate closure system of Dermabond ® Prineo ® with Exofin Fusion ® to compare rates of adverse wound outcomes after total joint arthroplasty. Secondary outcome measures were age, sex, and medical comorbidities between groups.Methods: We retrospectively reviewed adverse wound outcomes with skin closure in TJA in 281 patients (160 Dermabond Prineo and 121 Exofin Fusion). Clinical charts were analyzed out to the 6-week post-op visit.Results: The rate of overall adverse superficial wound outcomes was similar between the two groups with Dermabond Prineo (N=20) and Exofin Fusion (N=19). The rate of cellulitis was significantly higher for Dermabond Prineo when compared to Exofin Fusion (P=0.033). No other significant differences were found for rate of superficial or deep wound complications or for secondary outcomes.Conclusions: The two 2-octyl wound closure systems had similar adverse superficial wound complications. Except for Dermabond Prineo having a higher rate of post-operative cellulitis, there were no statistically significant differences for other superficial or deep adverse wound outcomes or secondary outcomes. A future randomized control trial or prospective cohort study is needed for a more robust analysis.

Purpose The purpose of this study is to propose an integrated model based on expectation-confirmation model (ECM) and technology acceptance model (TAM) to examine whether environmental, human, organizational and technology factors as the antecedents to physicians’ beliefs can affect their satisfaction and continuance intention of the cloud-based hospital information system (HIS). Design/methodology/approach Sample data for this study were collected from physicians at six hospitals in Taiwan. A total of 600 questionnaires were distributed, and 471 (78.5 per cent) usable questionnaires were analyzed using structural equation modeling in this study. Findings This study proposes a solid research model that is based on ECM and TAM, four types of factors, environmental factor, human factor, organizational factors and technology factors, as antecedents to physicians’ continuance intention of the cloud-based HIS have been examined. This study’s results strongly support the research model with all hypothesized links being significant, and control variables have no confounding effects on physicians’ continuance intention of the cloud-based HIS. Originality/value This study contributes to physicians’ continuance intention toward the cloud-based HIS based on ECM, TAM, technology-organization-environment framework and human-organization-technology fit framework, and reveals deep insights into the evaluation of determinants in the field of physicians’ continuance intention of the cloud-based HIS. Accordingly, it is particularly worth mentioning that IS and non-IS determinants are simultaneously evaluated and taken into consideration in this study’s theoretical development of physicians’ continuance intention of the cloud-based HIS to acquire a more comprehensive and robust analysis.

“An excess of everything is bad”. This famous old proverb fits well with the current condition of Australian household debt that is continuously rising. Research in Australia’s household indebtedness is scarce and strategies to control the rising household debt remain contentious. The government of Australia has introduced financial literacy and financial capability measures to help control the rising household debt. Given that the literature highlights the importance of improving financial wellbeing, we analyse if financial wellbeing is a factor, which could be relevant to the reduced household debt. We use the Household, Income and Labour Dynamics in Australia panel survey in our analysis and find that improved financial wellbeing is associated with the reduced debt-taking behaviour of Australians. Our robust analysis confirms our findings. Finally, our empirical results suggest that improving households’ perception of their personal financial situation can bring improvement in their financial decisions, including the decision to take on debt.

Ideally, pharmacological analysis is based on quantitative measurements applied toward unveiling biological mechanisms and guiding medicinal chemistry efforts in drug discovery and basic research. The most robust analysis frameworks generate findings which can be dissociated from the specific experimental setting to provide insights of a broader scope. With insufficient efficacy being the leading cause of drug failures in late-stage clinical trials, more rigorous preclinical definitions might assist in better translation. This chapter details a new method for accessing the Black and Leff operational model of agonism using a stable Flp-In™ T-REx™ HEK293 cell line under tetracycline-dependent control of OTR expression. We cover steps for performing the Gq-coupled HTRF® IP-One assay, curve-fitting data, calculating and statistically representing system-independent drug activity, predicting responses in different sensitivities, and plotting of multivariate analyses.

Background An artificial intelligence vessel segmentation tool, Fully Automated and Robust Analysis Technique for Popliteal Artery Evaluation (FRAPPE), was used to analyze a large databank of popliteal arteries imaged through the OAI (Osteoarthritis Initiative) to study the impact of atherosclerosis risk factors on vessel dimensions and characterize remodeling patterns. Methods and Results Magnetic resonance images from 4668 subjects contributing 9189 popliteal arteries were analyzed using FRAPPE. Age ranged from 45 to 79 years (median, 61), and 58% were women. Mean lumen diameter, mean outer wall diameter, and mean wall thickness (MWT) were measured per artery. Their median values were 5.8 mm (interquartile range, 5.2–6.5 mm), 7.3 mm (interquartile range, 6.7–8.1 mm), and 0.78 mm (interquartile range, 0.73–0.84 mm) respectively. MWT was associated with multiple cardiovascular risk factors, with age (4.2% increase in MWT per 10‐year increase in age; 95% CI, 3.9%–4.5%) and sex (8.6% higher MWT in men than women; 95% CI, 7.7%–9.3%) being predominant. On average, lumen and outer wall diameters increased with increasing MWT until the thickness was 0.92 mm for men and 0.84 mm for women. After this point, lumen diameter decreased steadily, more rapidly in men than women (−7.9% versus −6.1% per 25% increase in MWT; P Conclusions FRAPPE has enabled the analysis of the large OAI knee magnetic resonance imaging data set, successfully showing that popliteal atherosclerosis is predominantly associated with age and sex. The average vessel remodeling pattern consisted of an early phase of compensatory enlargement, followed by a negative remodeling, which is more pronounced in men.

In this article, we have deigned a new mechanism for the construction of confusion component which is one of the most important and integral part of any confidential scheme in secure communication. The privacy of digital information is one of the most vital issues of the digitally advanced world. The proposed nonlinear component which is usually termed as substitution box (S-box) is constructed by utilizing quantum map. Moreover, we have performed the robust analysis for our anticipated nonlinear component and compared it with already existing standards.

With plate-buckling problem still being an active area of research in the field of mechanics of materials, researchers need to validate the proposed solutions and theories, using robust analysis tools such like ANSYS, which is a robust finite element analysis tool. This article investigates modeling and buckling analysis of rectangular plates in ANSYS mechanical APDL through a series of comparative studies conducted on various models and options. Shell and solid models of homogeneous and functionally graded plate (FGP) using various elements are investigated. Expressing boundary conditions on both shell and solid models of plate for buckling analysis is discussed. Procedures of buckling analysis in ANSYS are presented and effects of meshing, boundary conditions and element options are examined though comparative studies. Results obtained from ANSYS are compared to various analytical solutions.

The significance of distributed data warehouses is to initiate the proliferation of various analytical applications. However, with the increase of ubiquitous devices, it is likely that massive volumes of data will be generated, which poses further problems based on the degradation of data quality. The practical reasons for the degradation of data quality in distributed warehouses are identified as heterogeneous data, uncertain inferior data which further affect predictions. The proposed system presents an integrated optimization model to address all the quality degradation problems and to provide a better computational model which effectively incorporates a higher degree of quality assurance. An analytical methodology is adopted in order to develop the proposed quality assurance model for distributed data warehouses.

The purpose of this systematic review is to highlight the salient elements of learning from incidents in the aircraft maintenance and continuing airworthiness management area. This involved the review of more than 1,000 publications reflecting practice in different domains. The cache was eventually distilled to 18 publications of relevance to learning from incidents. The systematic review of the literature was not intended to be exhaustive, but it was deliberately bound by the parameters of predefined search terms. A robust analysis was performed on the 18 distilled publications with the use of the NVivo software. A critical and systematic examination of this body of literature further supported the development of the five codification themes. The analysis of the literature revealed the benefits of a just culture as an enabler of reporting and learning from incidents. Moreover, it identified limitations inherent in the current body of knowledge. The most evident being a paucity of literature relevant to the featured industry segment. Some impediments to learning from incidents are also highlighted. Central to this is the prevalence of lack of effective focus and practice on satisfactory causation of events. Currently, the efforts applied across many featured domains appear to be based upon ineffective legacy linear practices. However, emerging investigative philosophies that look beyond direct cause and effect contain opportunities for practitioners to consider causation through dawning axioms. This systematic review could be used in the European aviation regulatory activities associated with improving learning from incident in aircraft maintenance and continuing airworthiness management.

Unmanned Aircraft Systems (UAS) have become a regular part of military operations and civilian life since the early 2000s. The proliferation of drone technologies has led to reduced costs and increased accessibility for individuals, states, and non-state actors. While extensive research and commentary have been made on the impacts of high-end military drones, the literature is comparatively sparse on the impacts of small UAS. With the regulations for civilian drones set to be finalized shortly, the potential impacts of small UAS on safety, privacy, and security need to be understood to have the right regulatory framework in place. This chapter deals with estimating the projected impacts of small UAS proliferation and increased autonomy on security. A robust analysis is presented by evaluating the disruptive potential of national security in various scenarios by analyzing the current and future trends of drone technologies, regulations, threats, and other important variables. The framework provided lays the groundwork for further studies into the impact of small UAS on security and hopes to inform future usage, perception, and policy surrounding these systems.

1. Quantifying interactive effects of environmental drivers on population dynamics can be critical for a robust analysis of population viability. Fire regimes, among the most widespread disturbances driving population dynamics, are increasingly modified by and interact with human activities. However, viability of fire‐adapted species is typically assessed overlooking disturbance interactions, potentially resulting in suboptimal management actions. 2. We investigated whether increasing human disturbances in fire‐prone ecosystems may pose a threat or an opportunity to improve population viability, using demographic data of the carnivorous, post‐fire recruiting plant Drosophyllum lusitanicum, endemic to heathlands in the southwestern Mediterranean Basin. We built integral projection models and simulated population dynamics under different combinations of two key disturbance types affecting populations: fire and livestock browsing and trampling. We used perturbation analyses to determine potential long‐term consequences of maintaining fundamentally different disturbance types. 3. Despite most populations inhabiting browsed habitats, simulations showed a greater extinction risk in populations under high livestock pressure compared with ones under low or moderate pressures. Extinction risk decreased when fire return intervals shortened in populations under low or moderate livestock pressure; however, the opposite pattern emerged in heavily browsed populations, where short intervals between fires increased extinction. 4. Elasticity analyses showed that decreases in viability under frequent disturbance interactions (heavy browsing and frequent fire) may be explained by selection against seed dormancy in populations with frequent browsing and trampling. This may potentially cause populations to collapse when fires kill above‐ground plants without populations being able to recover from a seed bank. 5. Synthesis and applications. Incorporating disturbance interactions can result in a different assessment of viability of a fire‐adapted species than considering fire regimes alone. In Mediterranean ecosystems, fire management may be more effective when integrating moderate human activities. However, replacing fires by human disturbances, a currently widespread strategy in many fire‐prone ecosystems, is not recommended since it may fundamentally alter population dynamics and selection pressures and decrease viability of fire‐adapted species.

Over the past century much-bruited developments in the physical sciences (and a concomitant physicization of biology, perhaps most prominent in molecular biology) have overshadowed a long-term tendency of the biologization of physics—clearly enunciated already in Alfred North Whitehead’s generalized “science of organisms.” Because such biologization occurs in a context in which science is understood to operate within a broader poetic canvas—a poetic universe, as it were—we should look to the poets for instruction in how to proceed in this tangled state of affairs. In the present essay, I turn to the MacArthur Fellow and Bollingen Prize winner Jay Wright, and the distinctive role modern physics has played in the formulation of his poetics. Ongoing conversations with the philosopher Susanne K. Langer and physicist Niels Bohr (and with Whitehead) inform Wright’s methodological multiculturalism, manifestly including literary and scientific cultures, as well as his robust analysis of “the poet’s primary province, feeling.”

ONCOhabitats is an open online service that provides a fully automatic analysis of tumor vascular heterogeneity in gliomas based on multiparametric MRI. Having a model capable of accurately segment pathological tissues is critical to generate a robust analysis of vascular heterogeneity. In this study we present the segmentation model embedded in ONCOhabitats and its performance obtained on the BRATS 2019 dataset. The model implements an residual-Inception U-Net convolutional neural network, incorporating several pre- and post- processing stages. A relabeling strategy has been applied to improve the segmentation of the necrosis of high-grade gliomas and the non-enhancing tumor of low-grade gliomas. The model was trained using 335 cases from the BraTS 2019 challenge training dataset and evaluated with 125 cases from the validation set and 166 cases from the test set. The results on the validation dataset in terms of the mean/median Dice coefficient are 0.73/0.85 in the enhancing tumor region, 0.90/0.92 in the whole tumor, and 0.78/0.89 in the tumor core. The Dice results obtained in the independent test are 0.78/0.84, 0.88/0.92 and 0.83/0.92 respectively for the same sub-compartments of the lesion.

Highlights • A split target method was proposed in prostate with pelvic lymph nodes irradiation. • Pencil beam scanning (PBS) plans were able to achieve optimal target coverage. • Low to intermediate dose to the organs at risk were reduced in PBS plans. • PBS plans remained robust in simulated setup and range errors analysis., Purpose To evaluate the dosimetric impact and plan robustness of using Pencil Beam Scanning (PBS) in patients that requires prophylactic pelvic lymph nodes (PLNs) irradiation for prostate cancer. Material and methods Five intermediate to high-risk prostate patients previously treated using volumetric modulated arc therapy (VMAT), were selected for this study. Comparative proton radiotherapy plans were generated, where a three-field intensity modulated proton therapy (IMPT) plan was for the phase 1 planning target volume (PTV1) with PLNs. A technique with two posterior oblique fields using single field uniform dose (SFUD) was used for phase 2 (PTV2) volume, that comprises of the prostate and proximal seminal vesicles (Pro + proxSVs). Plan evaluation was performed on PTV coverage and dose to the organs at risk (OARs) using VMAT plans as a baseline (BL). Robust analysis on clinical target volume (CTV) coverage for the PBS plans was simulated with a 3 and 5 mm setup errors and a 3.5% range uncertainty. Results For target coverage, PTV1 and PTV2 showed negligible differences with a comparable homogeneity index (HI) values for both modalities. Proton plans produced a statistically significant lower mean dose to the bladder (32.5 Gy(RBE) vs. 46.5 Gy) and rectum (33.6 Gy(RBE) vs. 42.7 Gy). Dose to the bladder and rectum was equivalent at the high dose region. For the bowel cavity, the mean dose for proton plans were 45% lower compared to VMAT plans. Similarly, proton plans were able to achieve an overall reduction in integral dose for both treatment phase. CTV coverage remained high with all the simulated setup and range errors. Conclusions Proposed beam geometries for PTV1 and PTV2 proton plans presented good treatment accuracy with similar target coverage as the VMAT plans. Better sparing of OARs was achieved at the low-medium dose region for the proton plans.

For the risk, progression, and response to treatment of many complex diseases, it has been increasingly recognized that genetic interactions (including gene-gene and gene-environment interactions) play important roles beyond the main genetic and environmental effects. In practical genetic interaction analyses, model mis-specification and outliers/contaminations in response variables and covariates are not uncommon, and demand robust analysis methods. Compared with their nonrobust counterparts, robust genetic interaction analysis methods are significantly less popular but are gaining attention fast. In this article, we provide a comprehensive review of robust genetic interaction analysis methods, on their methodologies and applications, for both marginal and joint analysis, and for addressing model mis-specification as well as outliers/contaminations in response variables and covariates.

The empirical literature on farmer cooperatives is now fast emerging and developing in the areas of performance, ownership and governance, finance, and member attitude. We discuss 56 peer‐reviewed publications to illustrate the main findings and conclusions while outlining challenges and opportunities for future research. Generally, cooperative membership is found to positively impact price, yield, input adoption, income, and other indicators of member performance, yet there is growing evidence of an uneven distribution of benefits for small and large producers. In terms of structure, evidence of a causal relationship of ownership and governance to performance has been elusive, yet there are now many findings of inherent equity and long‐term debt constraints, often in the context of consolidation to drive scale and scope economies. Further inefficiency is observed to be driven by increased heterogeneity in member attitudes and objectives, in particular in terms of commitment and participation. Thus, overall, empirical work portrays farmer cooperatives as flawed and complex business organizations which nonetheless have a strong positive impact on its members. While applied research may progress in various directions, a general improvement in empirical methodologies is needed to allow robust analysis of mixed objectives in dynamic environments.

The human skin microbiota is essential for maintaining homeostasis and ensuring barrier functions. Over the years, the characterization of its composition and taxonomic diversity has reached outstanding goals, with more than 10 million bacterial genes collected and cataloged. Nevertheless, the study of the skin microbiota presents specific challenges that need to be addressed in study design. Benchmarking procedures and reproducible and robust analysis workflows for increasing comparability among studies are required. For various reasons and because of specific technical problems, these issues have been investigated in gut microbiota studies, but they have been largely overlooked for skin microbiota. After a short description of the skin microbiota, the review tackles methodological aspects and their pitfalls, covering NGS approaches and high throughput culture-based techniques. Recent insights into the “core” and “transient” types of skin microbiota and how the manipulation of these communities can prevent or combat skin diseases are also covered. Finally, this review includes an overview of the main dermatological diseases, the changes in the microbiota composition associated with them, and the recommended skin sampling procedures. The last section focuses on topical and oral probiotics to improve and maintain skin health, considering their possible applications for skin diseases.

We provide a comprehensive and robust analysis of the role of renewable energy consumption and institutions on economic growth and in combating CO2 emissions across the regions and income groups. For our empirical model, we use annual data from 85 developed and developing economies across the world over the period from 1991 to 2012. We employ various econometric techniques from panel estimations to obtain the robust results. Our findings confirm that there is significant heterogeneity across the sub-samples. Overall, results from the system-GMM and fully modified OLS indicate that the growth of renewable energy consumption has a significant positive and negative impact on economic output and CO2 emissions, respectively. Institutions have a positive influence on economic growth and a reducing effect on CO2 emissions. Our findings suggest that both renewable energy deployment and institutions are significant in promoting economic growth and reducing CO2 emissions. Finally, we suggest that institutional alignment is necessary to promote the use of renewable energy across economic activities to ensure sustainable economic development.

In this study, the effects of open innovation practices on enterprise value were discussed based on the supply chain perspective. A nonlinear programming mode was constructed considering the uncertainty of open innovation effect. On this basis, the prototype was analyzed using a robust optimization approach with comprehensive considerations to the infeasible probability of constraint and goal accuracy. Findings show that parameter $$\Gamma $$ could convert the nonlinear programming model with uncertainty into a robust model with a strong stability. Furthermore, $$\Gamma $$ could be used to regulate the preference of the manufacturer to profit and the uncertainties in innovative practices. A small $$\Gamma $$ indicates manufacturers can refer to more information, and the manufacturers are more inclined to a mass production, so the profit is larger. Meanwhile, a high $$\Gamma $$ means that manufacturers can refer to less information, so that they pay more attention to making the product output adapt to the uncertainty of innovative effect. Manufacturers could select the appropriate $$\Gamma $$ value and reasonably arrange the production outputs of different goods according to the technological level of open innovation subject and their preference to profit and uncertainty. These conclusions were verified by a case study. In this work, the uncertainty of the open innovation effect was investigated from the supply chain perspective, which is of important significance to the decision making on optimal supply chain output and innovation risk control under an uncertain environment.

Although the number of studies discerning the impact of climate change on ecological systems continues to increase, there has been relatively little sharing of the lessons learnt when accumulating this evidence. At a recent workshop entitled ‘Using climate data in ecological research’ held at the UK Met Office, ecologists and climate scientists came together to discuss the robust analysis of climate data in ecology. The discussions identified three common pitfalls encountered by ecologists: 1) selection of inappropriate spatial resolutions for analysis; 2) improper use of publically available data or code; and 3) insufficient representation of the uncertainties behind the adopted approach. Here, we discuss how these pitfalls can be avoided, before suggesting ways that both ecology and climate science can move forward. Our main recommendation is that ecologists and climate scientists collaborate more closely, on grant proposals and scientific publications, and informally through online media and workshops. More sharing of data and code (e.g. via online repositories), lessons and guidance would help to reconcile differing approaches to the robust handling of data. We call on ecologists to think critically about which aspects of the climate are relevant to their study system, and to acknowledge and actively explore uncertainty in all types of climate data. And we call on climate scientists to make simple estimates of uncertainty available to the wider research community. Through steps such as these, we will improve our ability to robustly attribute observed ecological changes to climate or other factors, while providing the sort of influential, comprehensive analyses that efforts to mitigate and adapt to climate change so urgently require.

In geodesy and geophysics, continuous GNSS observations have been used globally. As the number of GNSS observing stations increases, GNSS time series analysis software should be developed with more flexible format support, better man---machine interaction, and robust analysis characteristics. To meet this requirement, a new software package called TSAnalyzer was written in Python and was developed for preprocessing and analyzing continuous GNSS position time series individually, as well as with batch processing. This software can read GNSS position time series with different formats, pick epochs of offsets or seismic events interactively, remove outliers, and estimate linear, polynomial, and harmonic signals. It also provides Lomb---Scargle spectrum analysis. Since it is based on Python, it is cross-platform.

This paper investigates the role of Muslim CEOs on the performance of Malaysian Shariah firms. Based on firm-level data from Bursa Malaysia from 2007 to 2013, we find no statistical difference between the performance of Shariah and non-Shariah firms; however, firms with Muslim CEOs do show lower performance levels relative to firms with non-Muslim CEOs. We further examine a sub-sample of the results for firms with widely held shareholder bases and inactive board members and find an obvious increase in the negative effect of Muslim CEOs under these two scenarios. Focusing on Shariah firms, we investigate whether a Muslim owner, Muslim chairman and Muslim-dominated board of directors facilitate the negative effects of Muslim CEOs. No supporting evidence is documented under a return on assets (ROA) model, but a Muslim-dominated board of directors is found to facilitate the negative effects of a Muslim CEO under a stock-return model in a robust analysis. Finally, we investigate whether a degree of the ownership concentration, a degree of board activeness and a degree of board independence moderates the negative effects of Muslim CEOs. We document consistently positive effects of ownership concentration on Muslim CEOs under an ROA as well as all other performance models.

228 p. This thesis studies the nonlinear robust control problems for continuous time parameter-dependent nonlinear systems with polynomial vector fields. Several novel approaches have been proposed to overcome the non-convex nature and numerical difficulty in ro-bust nonlinear system design. Several design problems are addressed, including stability analysis and synthesis, estimation of region of attraction, H^ synthesis, output feedback design, multi-objective reliable control and H^ filter design. DOCTOR OF PHILOSOPHY (EEE)

Automated image analysis tools for Ki67 breast cancer digital pathology images would have significant value if integrated into diagnostic pathology workflows. Such tools would reduce the workload of pathologists, while improving efficiency, and accuracy. Developing tools that are robust and reliable to multicentre data is challenging, however, differences in staining protocols, digitization equipment, staining compounds, and slide preparation can create variabilities in image quality and color across digital pathology datasets. In this work, a novel unsupervised color separation framework based on the IHC color histogram (IHCCH) is proposed for the robust analysis of Ki67 and hematoxylin stained images in multicentre datasets. An “overstaining” threshold is implemented to adjustforbackgroundoverstaining,andanautomatednucleiradiusestimatorisdesigned to improve nuclei detection. Proliferation index and F1 scores were compared between the proposed method and manually labeled ground truth data for 30 TMA cores that have ground truths for Ki67+ and Ki67− nuclei. The method accurately quantified the PI over the dataset, with an average proliferation index difference of 3.25%. To ensure the method generalizes to new, diverse datasets, 50 Ki67 TMAs from the Protein Atlas were used to test the validated approach. As the ground truth for this dataset is PI ranges, the automated result was compared to the PI range. The proposed method correctly classified 74 out of 80 TMA images, resulting in a 92.5% accuracy. In addition to these validations experiments, performance was compared to two color-deconvolution based methods, and to six machine learning classifiers. In all cases, the proposed work maintained more consistent (reproducible) results, and higher PI quantification accuracy.

Introduction: Mometasone furoate (MF), an inhaled corticosteroid (ICS), is approved for the treatment of asthma. Previous studies suggest that MF Twisthaler® doses of 800 and 200 µg and MF Breezhaler® doses of 320 and 80 µg would elicit similar lung function effects, respectively. These MF doses are also used in an indacaterol/MF combination in development for asthma. Since sensitivity to ICS is variable, individual patients’ ICS sensitivity (as measured by FEV1 decline on ICS weaning) was used to build a robust analysis model for the study data. Methods: This was a randomized, double-blind, double-dummy, parallel-group, non-inferiority study of 739 adolescents and adults with asthma. MF was delivered with Breezhaler® at daily doses of 80 and 320 µg and corresponding Twisthaler® doses of 200 and 800 µg. The primary endpoint was trough FEV1 on Day 29 (non-inferiority margin: -90 mL). Models with and without ICS sensitivity at baseline were used to analyze the data. Results: In the model with ICS sensitivity the least squares (LS) mean difference (Δ) in trough FEV1 between MF 80 µg Breezhaler® and MF 200 µg Twisthaler® was 27 mL (95% CI –34, 89); for MF 320 µg Breezhaler® and MF 800 µg Twisthaler® Δ was 0 mL (95% CI –60, 61). In the model without ICS sensitivity Δ between MF 80 μg Breezhaler® and MF 200 μg Twisthaler® patients was 68 mL (0, 137) and 25 mL (-43, 92) between MF 320 μg Breezhaler® and MF 800 μg Twisthaler®. Model diagnostics showed that using ICS sensitivity as a covariate improved the model. Conclusion: MF 80 and 320 μg, delivered via Breezhaler®, is non-inferior to MF at 200 and 800 μg, delivered via Twisthaler®. Including ICS sensitivity in the model improves model robustness.

Sheet metal parts are widely used in automotive, aerospace, ship and consumer goods industries. The final dimensions of a sheet metal assembly result from the parts deformation, which in turn is affected by many variations in material, thickness and single parts dimensions. The tolerance analysis on sheet metal assemblies improve the knowledge about the process. Advanced simulations enable the optimization of product features, GD&T scheme and assembly process. Moreover, Variational Models of both the product and the assembly system enable to assess the sources of 3D error propagation from the different contributors. However, the simulation results are very affected by the modelling approach of critical components, such as the Fixture Systems. The present paper firstly introduces a strategy to model the Fixture System and the assembly process for compliant parts. Then, a robust analysis of the variations in the model with respect to the modelling factors is performed by a Design of Experiments. A case study on an automotive fender is discussed. The results demonstrate that the modelling strategy of the clamping operation have the main effects, while the modelling of locators scheme, spot joints and FEM meshing are less important.

Introduction: Due to the relatively low mutation rate and high frequency of copy number variation, finding actionable genetic drivers of high-grade serous carcinoma (HGSC) is a challenging task. Furthermore, emerging studies show that genetic alterations are frequently poorly represented at the protein level adding a layer of complexity. With improvements in large-scale proteomic technologies, proteomics studies have the potential to provide robust analysis of the pathways driving high HGSC behavior. Areas covered: This review summarizes recent large-scale proteomics findings across adequately sized ovarian cancer sample sets. Key words combined with 'ovarian cancer' including 'proteomics', 'proteogenomic', 'reverse-phase protein array', 'mass spectrometry', and 'adaptive response', were used to search PubMed. Expert opinion: Proteomics analysis of HGSC as well as their adaptive responses to therapy can uncover new therapeutic liabilities, which can reduce the emergence of drug resistance and potentially improve patient outcomes. There is a pressing need to better understand how the genomic and epigenomic heterogeneity intrinsic to ovarian cancer is reflected at the protein level and how this information could be used to improve patient outcomes.

Understanding the changes in diverse molecular pathways underlying the development of breast tumors is critical for improving diagnosis, treatment, and drug development. Here, we used RNA-profiling of canine mammary tumors (CMTs) coupled with a robust analysis framework to model molecular changes in human breast cancer. Our study leveraged a key advantage of the canine model, the frequent presence of multiple naturally occurring tumors at diagnosis, thus providing samples spanning normal tissue and benign and malignant tumors from each patient. We showed human breast cancer signals, at both expression and mutation level, are evident in CMTs. Profiling multiple tumors per patient enabled by the CMT model allowed us to resolve statistically robust transcription patterns and biological pathways specific to malignant tumors versus those arising in benign tumors or shared with normal tissues. We showed that multiple histological samples per patient is necessary to effectively capture these progression-related signatures, and that carcinoma-specific signatures are predictive of survival for human breast cancer patients. To catalyze and support similar analyses and use of the CMT model by other biomedical researchers, we provide FREYA, a robust data processing pipeline and statistical analyses framework.

The robustness of Freight Comprehensive Transportation Networks (FCTNs) refers to the ability that FCTNs can maintain their function or performance tolerating perturbations from uncertainties. To evaluate the robustness of FCTNs, this paper proposes several quantitative indicators including accessibility, delivery, carrying capacity and transferring capacity. Numerical results based on the case of coal comprehensive transportation networks in Shanxi, China show the effectiveness of the proposed method.

If used appropriately, panel data in transportation allow for better decision making for mobility of passengers and supply chain services for freight. Research on transport is constrained by the availability of data. While the trend is to examine questions at a more disaggregate level, often building to the aggregate level through the summation of a multitude of individual data observations (big data), this chapter offers examples of how constraints in data availability can still provide useful and robust analysis.

Compared with life sciences, management consulting is a relatively new field. Nonetheless, leading firms have assumed a central role in the global business economy and command increasing influence as advisors to corporations and organizations in the public and social sectors. Offering robust analysis, independent and expert perspectives, and—in the best cases—valuable creative input, these companies focus on helping clients to improve their performance or more effectively execute their mission. Because the top firms tackle the most complex problems for the most successful organizations in the world, they attract top graduates. But the field is no longer the sole province of those with MBAs. In recent years, the profession has increasingly diversified and now actively recruits candidates with advanced degrees in a range of disciplines—including the life sciences. Those who join the field will find many parallels between the consulting approach and scientific inquiry. As a result, life scientists have many of the intrinsic skills needed to thrive in the industry, which can offer an extraordinary breadth of assignments, global experience, and an accelerated way to learn. At leading firms, the intensive training and development offered can pave the way for partnership, in which consultants counsel senior executives as peers. Many of those who leave become entrepreneurs or join top organizations—sometimes their former clients—at a leadership level.

Nowadays under COVID 2019, e-learning has become a potential prop approach of technology in education that provides contemporary learners with authentic knowledge acquisitions. As a practical contribution, electronic examination (e-exam) is a novel approach in e-learning designed to solve traditional examination issues. It is a combination of assorted questions designed by specialized software to detect an individual’s performance. Despite intensive research in this area, the performance of e-exams faces challenges such as authentication of the examinee’s identity and answered papers. This paper aims to present the experiences of educational organizations in e-exam and e-evaluation as an essential tool of e-learning in various countries. The paper recommends that under the global pandemic COVID 2019 evaluating students using intensive continuous evaluation, including e-exam supported by authentication methods, which may help detect and reduce or even prevent student violations. The results show that the most used LMS tools were the Moodle and proprietary solutions which were 75% both among many other LMS tools i.e., Blackboard and eFront. The least develop countries are prefer to use open source and proprietary due to the zero cost of these solutions. The internet speed, cost and authenticity were the most challenges faced e-exams centers, which were 99%, 82%, and 68%, respectively.

This work represents a combined approach of green chemistry and analytical Quality-by-Design principles for developing sustainable HPLC-DAD methods with high operational flexibility and reliability. Two newly introduced pharmaceutical combinations were analyzed; the first one (mixture I) composed of tamsulosin and tadalafil, while the second (mixture II) was a mixture of alfuzosin and solifenacin. To achieve this goal, monolithic-based C18 column was utilized for its characteristic rapid flow and short analysis time in addition to expressing low back-pressure upon using ethanol as a green organic solvent. Analytical Quality-by-Design approach was conducted by applying quality risk assessment and scouting analysis followed by screening five chromatographic parameters via Placket-Burman design. Critical method parameters were thoroughly identified and then optimized using central composite design and Derringer’s desirability function. The optimized mobile phase was composed of ethanol and phosphate buffer (pH 4.0) in a ratio of 40:60 (v/v) for mixture I and in a ratio of 50:50 (v/v) for mixture II. The flow rate was adjusted at 2.3 mL/min with UV detection at 210 nm for both mixtures. Design space was then assigned to estimate the operating regions that guarantee satisfactory results and robust analysis. The proposed methods were validated as per ICH guidelines with peak purity assessment and careful robustness monitoring around the created design space. Moreover, the methods showed good applicability for determination of the cited drugs in their marketed formulations and evaluating their content uniformity. Finally, environmental impact of the methods was comparatively appraised by three state-of-the-art metrics, namely; National Environmental Methods Index, Analytical Eco-Scale and Green Analytical Procedure Index.

Novel pavement design and size design are important factors to improve the mechanical properties and applicability of composite structures. Based on the multi-coupling of laminates, the universal analytical conditions for multi-coupled laminates are derived. Then four types of laminates with extension-shear coupling capable of forming bending-twisting coupled structure are designed, including three types of multi-coupled laminates. The shape of laminate is no longer limited to rectangular laminate, which is considered as a variable in the design process. Through the combination of theoretical calculation and numerical simulation, the optimal design of trapezoidal laminates with multiple coupling is achieved. The effect of the multi-coupling effect on the stiffness performance has been explored for free-layer laminates, and it has been found that the introduction of the multi-coupling can greatly improve the stiffness performance of laminates. Finally, the hygro-thermal stability performance is verified by numerical simulation and the robust analysis is obtained for stiffness performance.

The objective of this study is to develop a reliable and robust analysis system that can automatically detect motor imagery (MI) based electroencephalogram (EEG) signals for the development of brain–computer interface (BCI) systems. The detection of MI tasks provides an important basis for designing a communication way between brain and computer in creating devices for people with motor disabilities. This paper presents a synthesis approach based on optimum allocation system and Naive Bayes (NB) algorithm for detecting mental states based on EEG signals. In this study, an optimal allocation (OA) is introduced to discover the most effective representatives with minimal variability from a large number of MI based EEG data and the NB classifier is employed on the extracted features for discriminating the MI signals. The feasibility and effectiveness of the proposed method is demonstrated by analyzing the results and its success on two public benchmark datasets. The results indicate that the proposed approach outperforms the most recently reported five methods and achieves 0.64–20.90% improvement on average accuracy. The performances of this proposed approach implies that it can be reliably used to detect EEG based MI activity and can be a promising avenue for EEG based BCI applications.

Most randomised controlled trials (RCTs) are relatively short term and, due to costs and available resources, have limited opportunity to be re-visited or extended. There is no guarantee that effects of treatments remain unchanged beyond the study. Here, we illustrate the feasibility, benefits and cost-effectiveness of enriching standard trial design with electronic follow up. We completed a 5-year electronic follow up of a RCT investigating the impact of probiotics on asthma and eczema in children born 2005–2007, with traditional fieldwork follow up to two years. Participants and trial outcomes were identified and analysed after five years using secure, routine, anonymised, person-based electronic health service databanks. At two years, we identified 93% of participants and compared fieldwork with electronic health records, highlighting areas of agreement and disagreement. Retention of children from lower socio-economic groups was improved, reducing volunteer bias. At 5 years we identified a reduced 82% of participants. These data allowed the trial’s first robust analysis of asthma endpoints. We found no indication that probiotic supplementation to pregnant mothers and infants protected against asthma or eczema at 5 years. Continued longer-term follow up is technically straightforward.

Histopathology deals with the microscopic examination of tissues. The thin tissue specimen is collected from patients' body and converted to slides to make them useful for microscopic examination. Breast cancer histopathological images help pathologists in breast cancer grading and thus earlier prognosis is possible. Nottingham Grading system (NGS) is currently being used in most laboratories for breast cancer grading. Mitosis count plays an important role in the grading process. With the help of whole slide digital scanners, we can get digitized histopathological images. Thus computer-aided image analysis systems can be used to automatically find out breast cancer grade. This paper reviews the existing works on the automatic grading of breast cancer histopathological images. This study also intends to find out the challenges and future scope in order to reach robust analysis and grading.

This paper deals with robust stability and stabilization of linear discrete-time systems subject to uncertainties and network constraints. In network control systems, the control loop is closed over a network, which induces additional dynamics to the original control loop such as delays, sampling, quantization among many others. This paper focuses on networked induced delays due to unreliable network for which packet losses may occur. An equivalent periodic-like representation of the resulting system is proposed. This allows first, to revisit existing results in this framework and second, to take model uncertainties into account by analyzing the closed-loop model by means of a recent method based on robust control for discrete-time time-varying systems. Stability analysis and dynamic state-feedback stabilization are characterized via new conditions, whose conservatism is extensively discussed. Effectiveness of the proposed methodology is illustrated by numerical examples.

This paper argues that the Reducing Emission from Deforestation and Forest Degradation (REDD +) initiatives in Nepal have not adequately understood and considered institutional and political issues around forest tenure and governance challenges. The paper is developed based on reviews of polices, assessments of project activities, interviews with key informants, and observation of ongoing REDD + related public discussions. We found that the REDD + initiatives so far appear to have prioritized technical issues such as carbon assessment, reference scenario, and measurement, reporting and verification of emissions. However, a major policy challenge in Nepal is the substantial deforestation and degradation going on, which leads to substantial challenges of leakage and threatens Nepal's National REDD + policy ambition. The key drivers of deforestation and degradation in Nepal are still poorly identified, analyzed and understood. Inadequate focus of Nepal's present REDD + readiness on the core issues of contested forest tenure and frail governance entails that an unrealistic policy and institutional measures would be developed in addressing these issues of deforestation and degradation. Consequently, it would seriously undermine the prospect of achieving emission reduction — the very goal of REDD +. It is suggested that a robust analysis, collective understanding and broadly agreed policy measures for curbing deforestation must be at the core of REDD + readiness process.

This article describes the current stage in development of the phytomass disintegration apparatus based on the pressure shockwaves. Previous findings confirmed that the batch system provides disintegration to larger extents. However, the time delays connected with filling and discharging of the batch pressure vessel would naturally burden its commercialization. New generation of the continuous prototype that enables to interference the pressure shockwaves was designed. Robust analysis on the biodegradability, microporosity, and the oil yield was carried out. The data shows that this development step outperforms the original batch system. Closer examination of the process economics was conducted. Admittedly, the financial analysis shows that the pilot still apparatus can not compete with the established commercial scale prices. However, under certain assumptions, an assumption that the commercial version will be profitable can be formulated.

Recently, there is growing demand for alternative new heating technology, ohmic heating is an alternative and fast heating method has a large number of actual and potential application exits in food industry, water distillation, waste treatment, chemical processing etc. This paper presents a comprehensive review of ohmic heating current application, design configurations and operation parameters. The review highlights that ohmic heating are prospective alternative new heating technology to meet the demand of industrial and domestic heating utilizing. The recommendations for further research are made to provide more robust analysis in assessing ohmic heating performance.

Summary This R package helps to implement a robust approach to deal with mass spectrometry (MS) data. It is aimed at alleviating reproducibility issues and pernicious effects of deviating signals on both data pre-processing and downstream data analysis. Based on robust statistical methods, it facilitates the identification and filtering of low-quality mass spectra and atypical peak profiles as well as monitoring and data handling through pre-processing, which extends existing computational tools for high-throughput data. Availability and implementation MALDIrppa is implemented as a package for the R environment for data analysis and it is freely available to download from the CRAN repository at https://CRAN.R-project.org/package=MALDIrppa.

Background Dactylitis and enthesitis, hallmark features of psoriatic arthritis (PsA), may be difficult to manage. PALACE 1, 2, and 3 compared the efficacy and safety of apremilast (APR) with placebo (PBO) in patients (pts) with active PsA despite prior conventional DMARDs and/or biologics. Objectives Report the impact of long-term APR 30 mg BID (APR30) treatment on dactylitis and enthesitis in pts with active PsA. Methods Pts were randomized (1:1:1) to PBO, APR30, or APR 20 mg BID (APR20) stratified by baseline (BL) DMARD use (yes/no). After the 24-wk PBO-controlled phase, all pts received APR30 or APR20 and could enroll in long-term follow-up. Data for pts entering the study with pre-existing dactylitis or enthesitis were pooled across PALACE 1–3, as prespecified, to allow for robust analysis. Dactylitis count (number of digits [hands/feet] with dactylitis present [0=absence, 1=presence]; range: 0–20) was used to assess dactylitis improvement. Enthesitis was evaluated based on MASES (range: 0–13), indicating the number of painful entheses out of 13 enthesis sites. Wk 24 analyses used LOCF for missing values and data for early escape pts; Wks 52 and 156 used data as observed. Results Among pts with dactylitis (n=610) or enthesitis (n=915) at BL and ≥1 post-BL value, BL mean dactylitis counts ranged from 3.2 to 3.4 and MASES ranged from 4.4 to 4.8. At Wk 24, mean change in dactylitis count was −1.8 (APR30) vs −1.3 (PBO) ( P =0.0097); more APR30 pts achieved a dactylitis count of 0 vs PBO pts (Table). Mean change in MASES was −1.3 (APR30) vs −0.9 (PBO) ( P =0.0194); more APR30 pts achieved a MASES of 0 vs PBO pts. Significant effect on enthesitis was confirmed in the PSA-006 (ACTIVE) study of APR in pts with a maximum of 1 previous DMARD treatment, in which the Gladman Enthesitis Index was used, focusing on more peripheral sites of activity: significant effect for APR vs PBO was seen as early as Wk 2, and at Wk 24, mean changes were −1.5 vs −0.5 ( P =0.0032, MMRM). Sustained improvements in dactylitis and enthesitis severity were seen in APR pts at Wk 156 in PALACE 1–3 (Table): for dactylitis, 79.6% achieved a count of 0 and the mean percent change was −83.6%; for MASES, 55.0% of APR pts achieved a score of 0 and the mean percent change was −65.2%. Conclusions The majority of pts (63%) in PALACE 1–3 had active enthesitis and 42% had dactylitis at BL. APR30 demonstrated early and long-term benefit (up to 156 wks) in treating dactylitis and enthesitis, including resolution of BL disease in many pts. Disclosure of Interest D. Gladman Grant/research support from: AbbVie, Amgen, BMS, Celgene Corporation, Janssen, Novartis, Pfizer, UCB, Consultant for: AbbVie, Amgen, BMS, Celgene Corporation, Janssen, Novartis, Pfizer, UCB, A. Kavanaugh Grant/research support from: Abbott, Amgen, AstraZeneca, BMS, Celgene Corporation, Centocor-Janssen, Pfizer, Roche, UCB, J. Gomez-Reino Grant/research support from: Roche and Schering-Plough, Consultant for: BMS, Pfizer, Roche, Schering-Plough, UCB, J. Wollenhaupt Grant/research support from: Abbott, BMS, MSD, Pfizer, UCB, Consultant for: Abbott, BMS, MSD, Pfizer, UCB, M. Cutolo Grant/research support from: Actelion, BMS, Sanofi-Aventis, Consultant for: Actelion, BMS, Sanofi-Aventis, G. Schett Grant/research support from: Abbott, Celgene Corporation, Roche, UCB, Consultant for: Abbott, Celgene Corporation, Roche, UCB, E. Lespessailles Grant/research support from: Amgen, Eli Lilly, Novartis, Servier, Speakers bureau: Amgen, Eli Lilly, Novartis, Servier, M. McIlraith Employee of: Celgene Corporation, C. Hu Employee of: Celgene Corporation, C. Edwards Grant/research support from: Celgene Corporation, Pfizer, Roche, Samsung, Consultant for: Celgene Corporation, Pfizer, Roche, Samsung, Speakers bureau: Abbott, GSK, Pfizer, Roche, C. Birbara Grant/research support from: Amgen, BMS, Incyte, Eli Lilly, Merck, Pfizer, P. Mease Grant/research support from: Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Genentech, Janssen, Eli Lilly, Novartis, Pfizer, Roche, UCB, Consultant for: Abbott, Amgen, Biogen Idec, BMS, Celgene Corporation, Genentech, Janssen, Eli Lilly, Novartis, Pfizer, Roche, UCB, Speakers bureau: Abbott, Amgen, Biogen Idec, BMS, Genentech, Janssen, Eli Lilly, Pfizer, UCB

This paper deals with the robustness analysis of an anti-windup predictive current controller applied to a DFIG-based wind turbine in the presence of parameter variation. Experimental results were carried out, under the changing of the rotor speed, power and voltage sags, for a 3.7kW DFIG to verify the robustness of the designed controller.

Several fungi, including plant pathogens and endophytes, produce secondary metabolites with biological activity traits (e.g. antibiotics, insecticides, and mycotoxins). Mycotoxins can cause severe intoxication of livestock and humans who consume food that is contaminated. Over 350 mycotoxins which may impact food safety, have been recognized, and probably many more exist. Awareness of the significant impacts of mycotoxins on animal and human health has led to the development of analytical methods for their identification and surveillance in food and feed. The wide range of crops, commodities and agricultural systems in which mycotoxins can be found, presents a challenge for effective analyses. The reliability of quantitative analysis depends on careful execution of all component steps from sampling through the extraction and cleanup. Traditional methods, such as chromatography, together with new and improved ones, can meet these needs. Sophisticated UHPLC–MS/MS technologies are currently the cutting-edge methodology for simultaneous multi-mycotoxin analysis in a wide range of matrices. A combination of the cutting-edge technology with effective sample preparation, can provide robust and practical answers for mycotoxin detection. On the other hand, rapid, field deployable methods (such as dipsticks and biosensors) are significantly less expensive while still providing acceptable accuracy. These techniques can be applied and adapted for the specific requirements of biosecurity. The likelihood of discovery of yet-unknown mycotoxins, and the specific context of biosecurity, calls for additional improved technologies for rapid and robust analysis.