Negative Outliers Research Articles

The Catalysis Mechanism of E. coli Nitroreductase A, a Candidate for Gene-Directed Prodrug Therapy: Potentiometric and Substrate Specificity Studies.

E. coli nitroreductase A (NfsA) is a candidate for gene-directed prodrug cancer therapy using bioreductively activated nitroaromatic compounds (ArNO2). In this work, we determined the standard redox potential of FMN of NfsA to be -215 ± 5 mV at pH 7.0. FMN semiquinone was not formed during 5-deazaflavin-sensitized NfsA photoreduction. This determines the two-electron character of the reduction of ArNO2 and quinones (Q). In parallel, we characterized the oxidant specificity of NfsA with an emphasis on its structure. Except for negative outliers nitracrine and SN-36506, the reactivity of ArNO2 increases with their electron affinity (single-electron reduction potential, E17) and is unaffected by their lipophilicity and Van der Waals volume up to 386 Å. The reactivity of quinoidal oxidants is not clearly dependent on E17, but 2-hydroxy-1,4-naphthoquinones were identified as positive outliers and a number of compounds with diverse structures as negative outliers. 2-Hydroxy-1,4-naphthoquinones are characterized by the most positive reaction activation entropy and the negative outlier tetramethyl-1,4-benzoquinone by the most negative. Computer modelling data showed that the formation of H bonds with Arg15, Arg133, and Ser40, plays a major role in the binding of oxidants to reduced NfsA, while the role of the π-π interaction of their aromatic structures is less significant. Typically, the calculated hydride-transfer distances during ArNO2 reduction are smallwer than for Q. This explains the lower reactivity of quinones. Another factor that slows down the reduction is the presence of positively charged aliphatic substituents.

Achieving optimal cord management: a multidisciplinary quality improvement initiative

Optimal cord management (OCM), defined as waiting at least 60 seconds (s) before clamping the umbilical cord after birth, is an evidence-based intervention that improves outcomes for both term and...

Autonomous closed-loop mechanistic investigation of molecular electrochemistry via automation

Electrochemical research often requires stringent combinations of experimental parameters that are demanding to manually locate. Recent advances in automated instrumentation and machine-learning algorithms unlock the possibility for accelerated studies of electrochemical fundamentals via high-throughput, online decision-making. Here we report an autonomous electrochemical platform that implements an adaptive, closed-loop workflow for mechanistic investigation of molecular electrochemistry. As a proof-of-concept, this platform autonomously identifies and investigates an EC mechanism, an interfacial electron transfer (E step) followed by a solution reaction (C step), for cobalt tetraphenylporphyrin exposed to a library of organohalide electrophiles. The generally applicable workflow accurately discerns the EC mechanism’s presence amid negative controls and outliers, adaptively designs desired experimental conditions, and quantitatively extracts kinetic information of the C step spanning over 7 orders of magnitude, from which mechanistic insights into oxidative addition pathways are gained. This work opens opportunities for autonomous mechanistic discoveries in self-driving electrochemistry laboratories without manual intervention.

Safe and Effective Is Not Always Acceptable: The Case for PASS Scores in Foot and Ankle Orthopaedic Surgery

Category: Other Introduction/Purpose: Determining the success of a clinical intervention can be challenging even with modern patient-reported outcomes. Traditionally studies have used the Minimum Clinically Important Difference (MCID), the smallest difference in an outcome that is felt to have clinical significance. More recently some authors have emphasized the alternative model of the Patient Acceptable Symptomatic State (PASS), the threshold of a PRO defining where patients consider their overall status to be acceptable. PASS scores have not yet seen wide use in the foot and ankle literature, but may add insight to surgical outcomes beyond simply measuring the minimal changes implied by the MCID. Methods: The most universal patient-reported outcome in the foot and ankle literature is the simple Visual Analog Pain Scale (VAS), in which a patient rates their pain along an analog scale between 0 to 10 cm. Articles in Foot and Ankle International from December 2020 to August 2022 that reported VAS pain scores and variance following an intervention were included. Although specific PASS thresholds for VAS scores in many conditions in the foot and ankle have not been determined analytically, values ranging from 2.0 to 3.0 are typical for orthopaedic conditions, corresponding to the intuitive statement “I would like my pain to be less than 2 or 3 out of 10.” A PASS threshold of 2.0 has been used previously in the foot and ankle literature. The studies were therefore analyzed against PASS thresholds for the VAS of 2.0, 2.5, and 3.0. Results: Twenty-one studies were included. Five had multiple internal groups, yielding a total of 27 total sets of VAS scores.All 27 (100%) showed improvements well beyond the MCID and were considered successful. 17 (81%) of the 21 studies subjectively described their intervention as “reliable”, “good”, “effective” or “satisfactory”. Despite this, 8 (38%) of the 21 studies reported final mean VAS scores for all internal groups above a PASS threshold of 2.0. An analytically calculated weighted average final VAS pain score for all studies was 1.78 +/-1.89. Based upon this, the expected percentages of patients included in FAI studies whose results failed to meet VAS PASS thresholds were 45% for a threshold of 2.0, 35% for a threshold of 2.5, and 26% for a threshold of 3.0. Conclusion: Studies in the foot and ankle literature almost universally report positive results, both subjectively in their discussions and by statistically demonstrating improvement of patient-reported outcomes beyond the MCID. PASS threshold analysis yields a much less positive interpretation and emphasizes the number of negative outliers in the population who do not find their outcome acceptable. A fuller picture of the outcome of foot and ankle procedures and overall patient satisfaction can be gained from reporting both changes in the mean and comparing final outcomes to PASS thresholds.

Utilization of Maternal Healthcare Services Among Tribal Women in Empowered Action Group States in India

Maternal and Child Health (MCH) care services mainly focus on the utilization among tribal women in Empowered Action Group (EAG) states in India. For this study, the NFHS-4 (2015–2016) data were used. Analysis was performed on 54,448 women aged between 15–49, who have a child below 5 years of age, by using bivariate logistics regression, chi-squared test and the Moran-I (Univariate) statistical techniques. Results show that only 11% of tribal women accessed full Antenatal Care (ANC), and 54% of women received Postnatal Care (PNC) in EAG states. More than one-third (34%) of tribal women delivered in their homes compared to institutional delivery (66%). Women with higher education are significantly more likely to utilize ANC and have institutional delivery compared to the women with no-education. Also, mothers from the most abundant wealth status are significantly more likely to receive ANC and PNC and have institutional delivery compared to women with poorest wealth quintile. Considering the inter-EAG states comparison, state like Bihar, Jharkhand, Madhya Pradesh, Rajasthan, Uttar Pradesh and Uttarakhand are performing poorly. Hence, out of all EAG states districts almost 3–7 districts from (low–high) and 8–11 districts from (high–low) groups show negative autocorrelation or outliers to received MCH care services. Despite continuous and improving efforts of the government, the utilization of MCH services is very low among tribal women in the EAG states of India.

Extremal quantiles and stock price crashes

We employ extreme value theory to identify stock price crashes, featuring low-probability events that produce large, idiosyncratic negative outliers in the conditional distribution. Traditional methods employ approximations under Gaussian assumptions and central moments. This is inherently imprecise and susceptible to misspecifications, especially for tail events. We instead propose new definitions and measures for crash risk based on conditional extremal quantiles (CEQ) of idiosyncratic stock returns. CEQ provide information on quantile-specific impact of covariates, and shed light on prior empirical puzzles and shortcomings in identifying crashes. Additionally, to capture the magnitude of crashes, we provide an expected shortfall analysis of the losses due to crash. Our findings have important implications for a burgeoning literature in financial economics that relies on traditional approximations.

Dynamic link between central bank reserves, credit default swap spreads, and foreign exchange rates: Evidence from Turkey by time series econometrics

In this study, dynamic links between central bank reserves (CBR), credit default swap (CDS) spreads, and foreign exchange (FX) rates are investigated. So, Turkey, which is a negative outlier country among other peer emerging countries, is examined by considering recent developments on these indicators. In doing so, the study covers relatively high frequency (i.e., weekly) data from January 2, 2004 to November 12, 2021, performs various econometric approaches as Wavelet Coherence (WC), Quantile-on-Quantile Regression (QQR), and Granger Causality in Quantiles (GCQ) as main models, and applies Toda-Yamamoto (TY) causality and Quantile Regression (QR) for the robustness. The results show that (i) there is a time-frequency dependency between the CBR, CDS spreads, and FX rates; (ii) a bidirectional link exists between the CBR and FX rates; between the FX rates and CDS spreads; and between the CDS spreads and CBR; (iii) the link exists in most quantiles except for some lower and middle quantiles for some indicators; (iv) explanatory effect of the indicators on each other varies based on quantiles; (v) the robustness of the results are validated by the TY causality test for the WC model and by the QR approach for the QQR model. The results suggest the significance of the CBR for the FX rates, the FX rates for the CDS spreads, and the CDS spreads for the CBR.

On the Statistics of Mechanical Failure in Flame-Sprayed Self-Supporting Components

The objective of this study was to investigate the variability of flexural strength for flame-sprayed ceramic components and to determine which two-parametric distribution function was best suited to represent the experimental data. Moreover, the influence of the number of tested specimens was addressed. The stochastic nature of the flame-spraying process causes a pronounced variation in the properties of potential components, making it crucial to characterise the fracture statistics. To achieve this, this study used two large data sets consisting of 1000 flame-sprayed specimens each. In addition to the standard Weibull approach, the study examined the quality of representing the experimental data using other two-parametric distribution functions (Normal, Log-Normal, and Gamma). To evaluate the accuracy of the distribution functions and their characteristic parameters, random subsamples were generated by resampling of the experimental data, and the results were assessed based on the sampling size. It was found that the experimental data were best represented by either the Weibull or Gamma distribution, and the quality of the fit was correlated with the number of positive and negative outliers. The Weibull fit was more sensitive to positive outliers, whereas the Gamma fit was more sensitive to negative outliers.

Abstract LB058: A transcriptome-wide gene expression outlier analysis pinpoints therapeutic vulnerabilities in colorectal cancer

Abstract The number of effective therapies approved for metastatic colorectal cancer (mCRC) is still limited and multiple strategies are continuously explored to expand the drug target repertoire. Among these, the identification of overexpressed genes has prompted the discovery of actionable oncogenic dependencies in multiple tumour types. Starting from RNA sequencing data, we identified transcriptome-wide gene expression outliers, defined as samples showing abnormal expression for a particular gene, across 226 CRC cell lines, considering both overexpression and underexpression events as positive or negative outliers. Then, the distance of each outlier from gene-specific reference points, absolute expression values and differential expression values were considered in a multi-filter strategy to select extreme gene expression outliers, with the hypothesis that they are more likely to be functionally relevant in cancer cells. We also profiled genetic and epigenetic features of CRC cell lines based on whole exome sequencing and DNA methylation microarray data. Extreme positive and negative gene expression outliers were found for 3,533 and 965 genes, respectively, and only some of them were associated with underlying genetic and epigenetic alterations. Gene expression alterations with known therapeutic or diagnostic value in CRC were pinpointed as extreme positive and negative outliers thus confirming the validity of the approach. Annotation of overexpressed enzyme genes according to the Target Development Level (TDL) classification revealed numerous enzymes for which inhibitors are already available. We next explored underexpression events to identify potential synthetic lethal targets. Intriguingly, we found that CRC models lacking expression of the MTAP gene were sensitive to treatment with an inhibitor of the PRMT5:MTA complex currently under clinical development. We found that mapping extreme and transcriptome-wide positive and negative gene expression outliers in CRC cell lines is an effective strategy to identify putative drug targets and biomarkers, independently from the underlying genetic or epigenetic alterations. We indeed present a comprehensive atlas of CRC extreme gene expression outliers which includes events with diagnostic or therapeutic relevance. This resource could also serve as a reference for further discoveries in CRC and other tumour types. Citation Format: Gaia Grasso, Elisa Marriella, Martina Miotto, Kristi Buzo, Nicole M. Reilly, Pietro Andrei, Pietro P. Vitiello, Giovanni Crisafulli, Sabrina Arena, Giuseppe Rospo, Giorgio Corti, Annalisa Lorenzato, Carlotta Cancelliere, Ludovic Barault, Giulia Gionfriddo, Michael Linnebacher, Mariangela Russo, Federica Di Nicolantonio, Alberto Bardelli. A transcriptome-wide gene expression outlier analysis pinpoints therapeutic vulnerabilities in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB058.

Where is the distribution tail threshold? A tale on tail and copulas in financial risk measurement

Estimating the market risk is conditioned by the fat tail of the distribution of returns. But the tail index depends on the threshold of this distribution fat tail. We propose a methodology based on the decomposition of the series into positive outliers, Gaussian central part and negative outliers and uses the latter to estimate this cutoff point. Additionally, from this decomposition, we estimate extreme dependence correlation matrix which is used in the measurement of portfolio risk. For a sample consisting of six assets (Bitcoin, Gold, Brent, Standard&Poor-500, Nasdaq and Real Estate index), we find that our methodology presents better results, in terms of normality and volatility of the tail index, than the Kolmogorov–Smirnov distance, and its unnecessary capital consumption is lower. Also, in the measurement of the risk of a portfolio, the results of our proposal improve those of a t-Student copula and allow us to estimate the extreme dependence and the corresponding indexes avoiding the implicit restrictions of the elliptic and Archimedean copulas.

Development and validation of automated electronic health record data reuse for a multidisciplinary quality dashboard.

To describe the development and validation of automated electronic health record data reuse for a multidisciplinary quality dashboard. Comparative study analyzing a manually extracted and an automatically extracted dataset with 262 patients treated for HNC cancer in a tertiary oncology center in the Netherlands in 2020. The primary outcome measures were the percentage of agreement on data elements required for calculating quality indicators and the difference between indicators results calculated using manually collected and indicators that used automatically extracted data. The results of this study demonstrate high agreement between manual and automatically collected variables, reaching up to 99.0% agreement. However, some variables demonstrate lower levels of agreement, with one variable showing only a 20.0% agreement rate. The indicator results obtained through manual collection and automatic extraction show high agreement in most cases, with discrepancy rates ranging from 0.3% to 3.5%. One indicator is identified as a negative outlier, with a discrepancy rate of nearly 25%. This study shows that it is possible to use routinely collected structured data to reliably measure the quality of care in real-time, which could render manual data collection for quality measurement obsolete. To achieve reliable data reuse, it is important that relevant data is recorded as structured data during the care process. Furthermore, the results also imply that data validation is conditional to development of a reliable dashboard.

Optimal Demodulation Band Extraction Method for Bearing Faults Diagnosis Based on Weighted Geometric Cyclic Relative Entropy

Optimal demodulation band extraction is a significant step in rolling bearing fault analysis. However, existing methods, primarily based on global indexes and neglecting negative local outliers, cannot identify compound faults in intense noise environments. To address this problem, a novel demodulation band extraction method based on weighted geometric cyclic relative entropy (WGCRE) is proposed. WGCRE is defined on the cyclic sub-bands model of the logarithmic envelope spectrum (LES) to fully consider the bearing characteristic frequency of pseudo-cyclostationarity. In detail, local and global thresholds are separately set by the white noise parameter and harmonic-to-noise ratio to exclude the exogenous noise outliers. On this basis, the WGCRE is defined as a geometrically weighted index of several different fault types to avoid harmonic interference and improve the identification of composite faults. WGCRE–gram, similar to fast kurtogram (FK), is then constructed by replacing kurtosis with WGCRE to extract the optimal demodulation band. Compared with FK and another LES-based method, logarithmic-cycligram, the proposed method is more robust for accurately identifying single and compound faults under external noise. The effectiveness of this method is verified through simulations and actual tests. Simulation experiments of different kinds and intensities of exogenous noise interference preliminarily determine the superior robustness of WGCRE in the face of solid noise. The inner ring, outer ring, and composite fault experiments further confirmed the robust adaptability of WGCRE in the face of complex working conditions.

Puppeteer: A Random Forest Based Manager for Hardware Prefetchers Across the Memory Hierarchy

Over the years, processor throughput has steadily increased. However, the memory throughput has not increased at the same rate, which has led to the memory wall problem in turn increasing the gap between effective and theoretical peak processor performance. To cope with this, there has been an abundance of work in the area of data/instruction prefetcher designs. Broadly, prefetchers predict future data/instruction address accesses and proactively fetch data/instructions in the memory hierarchy with the goal of lowering data/instruction access latency. To this end, one or more prefetchers are deployed at each level of the memory hierarchy, but typically, each prefetcher gets designed in isolation without comprehensively accounting for other prefetchers in the system. As a result, individual prefetchers do not always complement each other, and that leads to lower average performance gains and/or many negative outliers. In this work, we propose Puppeteer, which is a hardware prefetcher manager that uses a suite of random forest regressors to determine at runtime which prefetcher should be ON at each level in the memory hierarchy, such that the prefetchers complement each other and we reduce the data/instruction access latency. Compared to a design with no prefetchers, using Puppeteer we improve IPC by 46.0% in 1 one-core, 25.8% in four-core, and 11.9% in eight-core processors on average across traces generated from SPEC2017, SPEC2006, and Cloud suites with ~11-KB overhead. Moreover, we also reduce the number of negative outliers by more than 89%, and the performance loss of the worst-case negative outlier from 25% to only 5% compared to the state of the art.

The need for metrics to measure progress on racial equity in global public health and medicine

The need for metrics to measure progress on racial equity in global public health and medicine

Msplit Estimation Approach to Modeling Vertical Terrain Displacement from TLS Data Disturbed by Outliers

Terrestrial laser scanning (TLS) is a modern measurement technique that provides a point cloud in a relatively short time. TLS data are usually processed using different methods in order to obtain the final result (infrastructure or terrain models). Msplit estimation is a modern method successfully applied for such a purpose. This paper addresses the possible application of the method in processing TLS data from two different epochs to model a vertical displacement of terrain resulting, for example, from landslides or mining damages. Msplit estimation can be performed in two variants (the squared or absolute method) and two scenarios (two point clouds or one combined point cloud). One should understand that point clouds usually contain outliers of different origins. Therefore, this paper considers the contamination of TLS data by positive or/and negative outliers. The results based on simulated data prove that absolute Msplit estimation provides better results and overperforms conventional estimation methods (least-squares or robust M-estimation). In practice, the processing of point clouds separately seems to be a better option. This paper proved that Msplit estimation is a compelling alternative to conventional methods, as it can be applied to process TLS data disturbed by outliers of different types.

Robust Asymmetric Safety Kalman Filter for MIMO Radar Resisting Temporary Outliers

This study presents a novel concept of robust Kalman filtering, especially dealing with outliers when detecting human hand intrusion using multiple-input–multiple-output radar. Outliers that severely deviate from the normal value for a certain period have not been sufficiently discussed from the viewpoint of safety and can seriously hamper the performance of the Kalman filter. Therefore, two types of outliers were intensively discussed: the temporary outlier that originated in misdetection and the additive outlier that is generated by heavy-tailed error distribution noise. Moreover, an asymmetric outlier processing strategy was proposed depending on positive and negative outliers. The result shows that the proposed method can resist the additive and temporary outliers.

Is There a Doctors' Effect on Patients' Physical Health, Beyond the Intervention and All Known Factors? A Systematic Review.

PurposeDespite billions of doctor visits worldwide each year, little is known on whether doctors themselves affect patients’ physical health after accounting for intervention and confounders such as patients’ and doctors’ data, hospital effects, nor how strong that doctors’ effect is. Knowledge of surgeons’ and psychotherapists’ effects exists, but not for 102 other medical specialties notwithstanding the importance of such knowledge.MethodsEligibility Criteria: Randomized controlled trials (RCTs), case-control, and cohort studies including medical doctors except surgeons for any intervention, reporting the proportion of variance in patients’ outcomes owing to the doctors (random effects), or the fixed effects of grading doctors by outcomes, after multivariate adjustment. Exclusions: studies of <15 doctors or solely reporting doctors’ effects for known variables.SourcesMedline, Embase, PsycINFO, inception to June 2020. Manual search for papers referring/referred to by resulting studies.Risk of BiasUsing Newcastle–Ottawa scale.ResultsDespite all medical interventions bar surgery being eligible, only thirty cohort papers were found, covering 36,239 doctors, with 10 specialties, 21 interventions, 60 outcomes (17 unique). Studies reported doctors’ effects by grading doctors from best to worst, or by diversely calculating the doctor-attributed percentage of patients’ outcome variation, ie the intra-class correlation coefficient (ICC). Sixteen studies presented fixed effects, 18 random effects, and 3 another approach. No RCTs found. Thirteen studies reported exceptionally good and/or poor performers with confidence intervals wholly outside the average performance. ICC range 0 to 33%, mean 3.9%. Highly diverse reporting, meta-analysis therefore not applicable.ConclusionDoctors, on their own, can affect patients’ physical health for many interventions and outcomes. Effects range from negligible to substantial, even after accounting for all known variables. Many published cohorts may reveal valuable information by reanalyzing their data for doctors’ effects. Positive and negative doctor outliers appear regularly. Therefore, it can matter which doctor is chosen.

Mineral Element Insiders and Outliers Play Crucial Roles in Biological Evolution.

The geosphere of primitive Earth was the source of life’s essential building blocks, and the geochemical interactions among chemical elements can inform the origins of biological roles of each element. Minerals provide a record of the fundamental properties that each chemical element contributes to crustal composition, evolution, and subsequent biological utilization. In this study, we investigate correlations between the mineral species and bulk crustal composition of each chemical element. There are statistically significant correlations between the number of elements that each element forms minerals with (#-mineral-elements) and the log of the number of mineral species that each element occurs in, and between #-mineral-elements and the log of the number of mineral localities of that element. There is a lesser correlation between the log of the crustal percentage of each element and #-mineral-elements. In the crustal percentage vs. #-mineral-elements plot, positive outliers have either important biological roles (S, Cu) or toxic biological impacts (Pb, As), while negative outliers have no biological importance (Sc, Ga, Br, Yb). In particular, S is an important bridge element between organic (e.g., amino acids) and inorganic (metal cofactors) biological components. While C and N rarely form minerals together, the two elements commonly form minerals with H, which coincides with the role of H as an electron donor/carrier in biological nitrogen and carbon fixation. Both abundant crustal percentage vs. #-mineral-elements insiders (elements that follow the correlation) and less abundant outsiders (positive outliers from the correlation) have important biological functions as essential structural elements and catalytic cofactors.

TIME AND FREQUENCY DEPENDENCY OF FOREIGN EXCHANGE RATES AND COUNTRY RISK: EVIDENCE FROM TURKEY

This study examines the time and frequency dependency nexus between foreign exchange (FX) rates and country risk in Turkey. We considered Turkey because it is a negative outlier country in terms of the progress of these indicators. Using quarterly data from 1990/Q1 to 2018/Q4 and the Wavelet Coherence approach, we find that an increase in the country risk causes an increase in the FX rates at different frequencies, especially in the medium and long term and different periods. The results highlight the significance of country risk for the progress of the FX rates. Policy implications are discussed.

Quantitative performance assessment of Asian stellar cities by a DEA cascade system: a capability interpretation

Asia hosts several mega-cities with great economic power, which are often in a mutual competitive relationship. Despite smart specialisation and heterogeneity on national and global markets, they are often in pursuit of the highest possible socio-economic outcome so as to outperform their peers in this dynamic region. The present study seeks to present an operational comparative framework for judging the complex performance of several (12) large urban agglomerations in Asia. In the framework of this paper, these cities are called ‘stellar cities’. Two particular research challenges are addressed: (i) the development and application of a new Data Envelopment Analysis (DEA) approach, culminating—after a cascade of sequential analytical steps—in an Autoconfiguration Target Model which serves as a quantitative statistical tool for evaluating the (relative) multidimensional goal-oriented performance of the cities concerned; and (ii) a new functional interpretation of the DEA slack space for the possible improvement of inefficiently operating cities on the basis of Amartya Sen’s capability theory. In the paper, we use an extensive database on 12 Asian stellar cities, extracted from the annual Global Power City Index (GPCI) system which contains more than 60 urban performance indicators, which has been constructed by the Institute of Urban Strategies (Tokyo). We find that the performance ranking of these Asian mega-cities shows the ‘winners’, but also a high variability, with several positive and negative outliers. We conclude that there is clearly scope (‘capability’) for further improvement of the efficiency of most Asian cities in various specific policy domains, as shown by the DEA results.