Meaningful Adjustment Research Articles

Optimizing feature extraction for tampering image detection using deep learning approaches

Tamper image detection approach using deep learning involves, creating a model that can accurately identify and localize instances of image tampering, by employing advanced feature extraction methods, object detection algorithms, and optimization techniques that could be manipulated on need basis. Enhance the integrity of visual content by automating the detection of unauthorized alterations, to ensure the reliability of digital images across various applications and domains. The problem addressing the optimization feature extraction techniques involves the detection of subtle manipulations, handling diverse tampering techniques, and achieving robust performance across different types of images and scenarios. The proliferation of sophisticated image editing tools makes it challenging to detect tampered regions within images, necessitating proposed techniques for automated tamper image detection. The research work will focus on four different feature extraction algorithms such as non-negative factorization (NNF), singular value decomposition (SVD), explicit semantic analysis (ESA), principal component analysis (PCA), which are outsourced. Detecting tampered images through deep learning necessitates the meaningful selection and adjustment of several parameters to enhance the model's effectiveness. Integrating the feature extraction algorithm with the suggested methods effectively identifies critical features within the dataset, thereby improving the detection capabilities and achieving higher accuracy.

Nursing Home Status Adjustment for Standardized Mortality and Hospitalization in Dialysis Facility Reports

Compared to the original nursing home status (any nursing home stay in the previous calendar year), new nursing home status variables were developed to improve the risk adjustment of Standardized Mortality/Hospitalization Ratio (SMR/SHR) models used in public reporting of dialysis quality of care, such as the Annual Dialysis Facility Report. Retrospective observational study. 625,040 US maintenance dialysis patients with>90 kidney failure days in2019. Nursing home status variables; patient characteristics; comorbid conditions. Mortality/hospitalization. We assigned patients and patient times (SMR/SHR model) to one of 3 mutually exclusive categories: long-term care (≥90 days), short-term care (1-89 days), or non-nursing home, based on nursing home stay during the previous 365 days from the first day of the time period at risk. Nursing home status was derived from the Nursing Home Minimum Data Set. Comparisons of hazard ratios from adjusted models, facility SMR/SHR performance, and model C-statistics between the original/new models were performed. SMR's hazard ratio of original nursing home status (2.09) was lower than both ratios of short-term care (2.38) and long-term care (2.43), whereas SHR's hazard ratio of original nursing home status (1.10) was between the ratios of long-term care (1.01) and short-term care (1.20). There was a difference in hazard ratios between short-term care and long-term care for both measures. Small percentages of facilities changed performance categories: 0.7% for SMR and 0.4% for SHR. The SMR C-statistic improved whereas the SHR C-statistic was relatively unchanged. Limited capture of subacute rehabilitation stays in the nursing home by using a 90-day cutoff for short-term care and long-term care; unable to draw causal inference about nursing home care. Use of a nursing home metric that effectively separates short-term from long-term nursing home utilization results in more meaningful risk adjustment that generally comports with Medicare payment policy, potentially resulting in more interpretable results for dialysis stakeholders.

Visualizing Opioid-Use Variation in a Pediatric Perioperative Dashboard.

Anesthesiologists integrate numerous variables to determine an opioid dose that manages patient nociception and pain while minimizing adverse effects. Clinical dashboards that enable physicians to compare themselves to their peers can reduce unnecessary variation in patient care and improve outcomes. However, due to the complexity of anesthetic dosing decisions, comparative visualizations of opioid-use patterns are complicated by case-mix differences between providers. This single-institution case study describes the development of a pediatric anesthesia dashboard and demonstrates how advanced computational techniques can facilitate nuanced normalization techniques, enabling meaningful comparisons of complex clinical data. We engaged perioperative-care stakeholders at a tertiary care pediatric hospital to determine patient and surgical variables relevant to anesthesia decision-making and to identify end-user requirements for an opioid-use visualization tool. Case data were extracted, aggregated, and standardized. We performed multivariable machine learning to identify and understand key variables. We integrated interview findings and computational algorithms into an interactive dashboard with normalized comparisons, followed by an iterative process of improvement and implementation. The dashboard design process identified two mechanisms-interactive data filtration and machine-learning-based normalization-that enable rigorous monitoring of opioid utilization with meaningful case-mix adjustment. When deployed with real data encompassing 24,332 surgical cases, our dashboard identified both high and low opioid-use outliers with associated clinical outcomes data. A tool that gives anesthesiologists timely data on their practice patterns while adjusting for case-mix differences empowers physicians to track changes and variation in opioid administration over time. Such a tool can successfully trigger conversation amongst stakeholders in support of continuous improvement efforts. Clinical analytics dashboards can enable physicians to better understand their practice and provide motivation to change behavior, ultimately addressing unnecessary variation in high impact medication use and minimizing adverse effects.

Team dynamics feedback for post-secondary student learning teams: introducing the “Bare CARE” assessment and report

Team-based learning is recognized as an important opportunity for teamwork skill development, experiential learning, and learning from peers. However, team-based learning presents many challenges. One important challenge involves the accurate, reliable and valid assessment of team health. With such diagnostics, students could receive formative feedback and engage in meaningful goal setting, adjustment and action planning. Moreover, instructors could identify teams in distress and in need of support. We examine the team CARE assessment, which is a team diagnostic on ITPmetrics.com that assesses communication, adaptability, relationships and education/learning. Although the team CARE assessment has been used extensively in educational contexts, the assessment is lengthy and time-consuming to complete. We offer a shorter version, that we call the Bare CARE assessment, by utilizing psychometric analyses and content validity to eliminate the least useful items. We find that the Bare CARE is reliable and valid when considering correlations with teamwork variables and team performance (i.e. grades). Our sample of 61,549 students working in 14,601 teams offers state-of-the-art validation evidence using a large sample that ensures stable and robust results. We discuss the implications for use in pedagogy and future research.

Simulated Treatment Comparison (STC) of Human Mesenchymal Stromal Cells (Remestemcel-L, REM) and Ruxolitinib (RUX) for Steroid-Refractory Acute Graft-Versus-Host Disease (SR aGVHD) Pediatric Patients

Introduction: Allo-HSCT was performed on 1771 US children in 2016. SR aGVHD is a life-threatening complication of allo-HSCT associated with substantial healthcare costs and significant reductions in pediatric QOL. Grade II-IV aGVHD occurs in 39-59% of allo-HSCT recipients. While steroids are typically used 1st line, there is no formal 2nd line consensus. RUX has been approved in SR aGVHD patients ≥12 yrs based on results of a single-arm P2 REACH 1 trial where the lower limit of the age range was 18 yrs per the FDA label. The 12 yr age limit of FDA approval was based on a bioequivalence study. Indirect comparisons of RUX trial data vs novel late stage investigational therapies with exclusively pediatric trial data can thus inform future coverage decisions and budget assessments. Recently, a single-arm P3 trial reported efficacy and safety outcomes with REM (investigational agent) in pediatric SR aGVHD. As there are no head-to-head studies comparing RUX to REM, we compared efficacy and safety outcomes between treatments in a statistically robust manner to aid clinical and reimbursement decisions. Methods: Following NICE Decision Support Unit STC guidelines, regression techniques were used to adjust individual patient-level data from the REM P3 trial to mutually reported baseline (BL) characteristics from the RUX FDA Package Insert (PI)/REACH 1 trial data (2018 ASH Abstract #601). The stepwise model included adjustment for: ethnicity (white), aGVHD grade, and sex. Outcomes of interest included 28-day ORR, 28-day ORR in patients with grade III-IV aGVHD at baseline (BL) from comparable populations (n=49 RUX FDA PI/ n=55 REM), and TEAEs of any grade mutually reported in RUX published data (REACH 1 )/REM trial data (n=71 RUX REACH 1 /n=54 REM). Since the REM trial was limited to pediatric patients, and the youngest patient was 18 yrs in the RUX trial, statistical adjustment for age was unfeasible. Based on RUX approval in patients ≥12 yrs, we assumed that trial populations were comparable despite age differences. Within the REM study, no statistical association was found between age and 28-day ORR or safety in univariate analysis, further validating this assumption. The lack of statistical adjustment for age is, however, a limitation of this analysis. Further limitations include the small sample size of both trials and the small number of endpoints available in the RUX label for comparison. Results: In the full population set for 28-day ORR, the RR of REM vs. RUX was calculated as 1.21 (95% confidence interval [CI], 0.90-1.63; p=0.21) without any covariate adjustment based on ORRs of 69.1% and 57.1% (n=49 RUX FDA PI), respectively. After multivariate adjustment for baseline characteristics, the RR was 1.13 (95% CI, 0.83-1.54; p=0.45). For the BL grade III-IV aGVHD patient subgroup, the unadjusted RR for 28-day ORR of REM vs RUX was 1.72 (95% CI, 1.12-2.63; p=0.01) based on ORRs of 71.4% and 41.6%, respectively. After multivariate adjustment for baseline characteristics, the RR was 1.58 (95% CI, 1.02-2.44; p=0.04), a statistically significant difference. The most frequently reported TEAEs (all grades) for REM were pyrexia (33.3%), abdominal pain (20.4%) and adenovirus infection (20.4%) and for RUX (n=71 RUX REACH 1) were anemia (64.8%), hypokalemia (49.3%) and platelet count decreased (45.1%). AEs led to treatment discontinuation for 15% of patients on REM and 31% on RUX. For mutually reported TEAEs, unadjusted comparisons were employed, as the number of events was too low to facilitate meaningful covariate adjustment. The rates of TEAEs, as well as RRs (95% CI, p-value), are presented in Table 1. Conclusion: Without direct trial comparison, STC results can be used in cost-effectiveness analyses to aid coverage decisions. STC methods showed significant association of REM with improved 28-day ORR for patients with BL grade III-IV aGVHD (p=0.04) and improved safety outcomes relative to RUX (p<0.05 for RR) for multiple TEAEs, including several hematologic TEAEs (anemia, WBCs, platelets, neutrophils), several lab results (hypokalemia, hypomagnesemia, increased AST), peripheral edema, muscular weakness, nausea, back pain, and fatigue. For all grade 28-day ORR, REM-treated patients experienced relative-but not statistically significant-improvement. Disclosures Westley: Mesoblast: Consultancy. Tomaras:Mesoblast: Consultancy. Strati:Mesoblast: Employment. Skerrett:Mesoblast: Employment. Forsythe:Mesoblast: Consultancy. Tremblay:Mesoblast: Consultancy.

Associations between Socioeconomic Status and Urge Urinary Incontinence: An Analysis of NHANES 2005 to 2016.

Urge urinary incontinence significantly impacts quality of life. We investigated the association between urge urinary incontinence and socioeconomic status in a nationally representative adult population. We analyzed the 2005 to 2016 NHANES (National Health and Nutrition Examination Survey), a United States population based, cross-sectional study. Urge urinary incontinence was determined by self-report of leaking urine before reaching the toilet. Socioeconomic status was represented by the poverty income ratio, which reflects the family income relative to poverty thresholds specific to that year and household size. Survey weighted logistic regression models were used to analyze the relationship between socioeconomic status and the poverty income ratio. Multiplicative terms were applied to test for interaction in prespecified subgroups of interest. A total of 25,553 participants were included in the final analysis, representing 180 million people in the United States. Of the participants 19.4% reported any urge urinary incontinence, 4.2% reported weekly urge urinary incontinence and 1.6% reported daily urge urinary incontinence. In the fully adjusted multivariable models those with a poverty income ratio less than 2.00 showed significantly higher odds of any urge urinary incontinence compared to the group with a poverty income ratio of 2.00 or greater (OR 1.17, 95% CI 1.05-1.30, p=0.003). There was increasing strength of association for weekly and daily urge urinary incontinence (OR 1.31, 95% CI 1.12-1.55, p <0.001, and OR 1.60, 95% CI 1.23-2.09, p=0.001, respectively). Individual interaction analyses revealed no significant effect of female gender, age greater than 50 years, body mass index 30 kg/m2 or greater, or less than a high school education on the association of urge urinary incontinence with the poverty income ratio. This study revealed a significant association between urge urinary incontinence and socioeconomic status after meaningful adjustment for covariates. Health care interventions targeting low socioeconomic status individuals with urge urinary incontinence are needed to address this disparity.

When Two Wrongs Make a Right: Using Conjunctive Enablers to Enhance Evaluations for Extremely Incongruent New Products

Abstract The success of new incongruent products hinges largely on whether consumers can efficiently make sense of the product. One of the most efficient ways that people make sense of new objects is through feature-based association. Such associations often incorporate an enabler (e.g., the color green) to help make sense of a semantically related feature (e.g., vitamin enriched). Evidence from three studies suggests that marketers can strategically incorporate enablers in product design to help consumers make sense of an extremely incongruent feature. As a result, consumers tend to reflect more favorably on the product. Furthermore, the authors find that even if the enabler itself is incongruent and leads to lower evaluations on its own, when combined with an atypical feature the effect can still be positive. Thus, a small but semantically meaningful adjustment in design can help marketers successfully introduce extremely incongruent innovations.

What is interiors? An essay on lining, concealing, and making one’s mark

Theme Journal – What is Interiors? In his 1994 book, What is Architecture? An Essay on Landscapes, Buildings, and Machines, Paul Shepheard draws a distinction between the questions ‘What is Architecture?’ and ‘What Should Architecture Be?’ Through this slight but meaningful adjustment, he tries to get underneath the seemingly distinct categories that define the discipline such as history, design, research, and materials, opening up in this way a discussion of how these categorizations emerged in the first place. What are the underlying conditions, events, and questions that enabled their formation? Resisting singular answers such questioning instead prompts a discourse that expands disciplinary knowledge. The title of the journal, Interiors: Design/Architecture/Culture situates interiors vis-a-vis a triad of terms that hold multiple connotations, suggesting a range of possible relationships that shape our intellectual understanding of interiors. This special theme issue seeks to question presumed disciplinary frameworks, much like Shepeard did, in order to define critical trajectories for new interiors scholarship and practice.

Adjusting variables in constructing composite indices by using principal component analysis: illustrated by Colombo district data

Constructing composite indices, variables have to be reduced and principal component analysis (PCA) is widely used for this purpose. Although, PCA is conducted after standardizing variables to overcome unit and value dependency problems, variables lose their inherent variability. To address that issue, two options were tested. First option was transforming variables by dividing their means, resulting new means and variances becoming one and square of coefficient of variance (CV 2 ) respectively. Second option was making meaningful adjustment to original variables to convert them as unitless. Grama Niladhari (GN) division level data on thirteen variables in Colombo district were used and second option was successful illustrating contribution of first two PCs to total variability by 96.34%. However, in the conventional method, 8 PCs were needed to reach that proportion. Expressing some variables on a per household basis and dividing GN density by total density were two adjustments made and that resulted in meaningful variable reduction in the index.

Achieving Meaningful Retirement Adjustment in Late Career

In an ageing society, achieving good quality of retirement adjustment has become a major challenge for individuals, organizations, and governments. Adopting a retrospective view, this paper explore...

Structure of forecast error covariance in coupled atmosphere–chemistry data assimilation

Abstract. In this study, we examined the structure of an ensemble-based coupled atmosphere–chemistry forecast error covariance. The Weather Research and Forecasting (WRF) model coupled with Chemistry (WRF-Chem), a coupled atmosphere–chemistry model, was used to create an ensemble error covariance. The control variable includes both the dynamical and chemistry model variables. A synthetic single observation experiment was designed in order to evaluate the cross-variable components of a coupled error covariance. The results indicate that the coupled error covariance has important cross-variable components that allow a physically meaningful adjustment of all control variables. The additional benefit of the coupled error covariance is that a cross-component impact is allowed; e.g., atmospheric observations can exert an impact on chemistry analysis, and vice versa. Given the realistic structure of ensemble forecast error covariance produced by the WRF-Chem, we anticipate that the ensemble-based coupled atmosphere–chemistry data assimilation will respond similarly to assimilation of real observations.

Price Corrected Domestic Technology Assumption—A Method To Assess Pollution Embodied in Trade Using Primary Official Statistics Only. With a Case on CO2Emissions Embodied in Imports to Europe

Environmentally extended input output (EE IO) analysis is increasingly used to assess the carbon footprint of final consumption. Official EE IO data are, however, at best available for single countries or regions such as the EU27. This causes problems in assessing pollution embodied in imported products. The popular "domestic technology assumption (DTA)" leads to errors. Improved approaches based on Life Cycle Inventory data, Multiregional EE IO tables, etc. rely on unofficial research data and modeling, making them difficult to implement by statistical offices. The DTA can lead to errors for three main reasons: exporting countries can have higher impact intensities; may use more intermediate inputs for the same output; or may sell the imported products for lower/other prices than those produced domestically. The last factor is relevant for sustainable consumption policies of importing countries, whereas the first factors are mainly a matter of making production in exporting countries more eco-efficient. We elaborated a simple correction for price differences in imports and domestic production using monetary and physical data from official import and export statistics. A case study for the EU27 shows that this "price-adjusted DTA" gives a partial but meaningful adjustment of pollution embodied in trade compared to multiregional EE IO studies.

Can financiers learn from traders?

Over the past three decades, the world trading system has functioned well, while the financial system has stumbled. While the trading system cannot provide a template for redesigning the financial system, it can provide useful lessons. The primary goal of the world trading system has been to liberalize commerce. By contrast, the primary goal of the world financial system has been to stabilize markets. The trading system has nonetheless devised useful means for anticipating and coping with shocks. In the pre-crisis period, the trading system has stressed the articulation of binding agreements as to predictable rules. In the mid-crisis period, the trading system's distinction between external and internal causes has political, but not economic, resonance in financial shocks. In the post-crisis period, effective investigation of business conditions abroad and meaningful adjustment to world markets are both useful lessons. Copyright 1999 by Oxford University Press.

A Unifying Approach to Mind and Brain: Ten Year Perspective

Publisher Summary This chapter focuses on the mind-brain relationship. The approach to the mind-brain relation arose largely out of efforts to explain the seeming unity and/or duality of conscious experience in the bisected brain. The chapter focuses on the interpretation of consciousness as an emergent of brain activity. It interprets the emergent conscious properties in terms of conventional neural circuit theory. A further postulate is added to this discussion in which the subjective conscious effect of a brain process is viewed as a functional or operational derivative. In other words, subjective meaning is conceived to depend primarily on the way a given cerebral process works in the context of brain dynamics. The thing that counts in determining a conscious perceptual effect is the preparation to respond to a perceived outside stimulus in an adaptive, meaningful adjustment, rather than the way in which the brain's neural process happens to copy or correspond with the perceived stimulus with respect to shape, size, unity, texture, timing, etc. Conscious phenomena, thus, conceived as dynamic emergent properties of high order cerebral processes, are not merely products of neural complexity, but are also designed specifically to produce operational subjective effects.

A statistical discussion of P residuals from explosions

abstract Explosions at large distances from the Berkeley seismic array of the University of California have been studied in an attempt to obtain an estimate of a P travel time “adjustment” function for each station in the array relative to a standard P table. The probability distribution of residuals is discussed and some error estimates for station adjustments given. A method is suggested for relocating groups of events occurring in small regions. This problem was suggested by the existence of groups of explosions in small regions which gave rise to widely varying sets of residuals. The probable presence of azimuthally varying source, as well as station, terms makes it advisable to obtain times from world-wide stations for each source area in order to attempt to separate the two terms. In fact, the presence of these terms makes it questionable whether a meaningful adjustment function for a single station can be obtained at all.