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Accurate quantification of model uncertainty has long been recognized as a fundamental requirement for trusted AI. In regression tasks, uncertainty is typically quantified using prediction intervals calibrated to an ad-hoc operating point, making evaluation and comparison across different studies relatively difficult. Our work leverages: (1) the concept of operating characteristics curves and (2) the notion of a gain over a null reference, to derive a novel operating point agnostic assessment methodology for prediction intervals. The paper defines the Uncertainty Characteristics Curve and demonstrates its utility in selected scenarios. We argue that the proposed method addresses the current need for comprehensive assessment of prediction intervals and thus represents a valuable addition to the uncertainty quantification toolbox., Comment: Published at Workshop on Distribution-Free Uncertainty Quantification, International Conference on Machine Learning (ICML), July 2022. arXiv admin note: substantial text overlap with arXiv:2106.00858

BACKGROUND: End-stage renal disease is associated with a high risk of cardiovascular events. It is unknown, however, whether mild-to-moderate kidney dysfunction is causally related to coronary heart disease (CHD) and stroke. METHODS: Observational analyses were conducted using individual-level data from 4 population data sources (Emerging Risk Factors Collaboration, EPIC-CVD [European Prospective Investigation into Cancer and Nutrition-Cardiovascular Disease Study], Million Veteran Program, and UK Biobank), comprising 648 135 participants with no history of cardiovascular disease or diabetes at baseline, yielding 42 858 and 15 693 incident CHD and stroke events, respectively, during 6.8 million person-years of follow-up. Using a genetic risk score of 218 variants for estimated glomerular filtration rate (eGFR), we conducted Mendelian randomization analyses involving 413 718 participants (25 917 CHD and 8622 strokes) in EPIC-CVD, Million Veteran Program, and UK Biobank. RESULTS: There were U-shaped observational associations of creatinine-based eGFR with CHD and stroke, with higher risk in participants with eGFR values <60 or >105 mL·min-1·1.73 m-2, compared with those with eGFR between 60 and 105 mL·min-1·1.73 m-2. Mendelian randomization analyses for CHD showed an association among participants with eGFR <60 mL·min-1·1.73 m-2, with a 14% (95% CI, 3%-27%) higher CHD risk per 5 mL·min-1·1.73 m-2 lower genetically predicted eGFR, but not for those with eGFR >105 mL·min-1·1.73 m-2. Results were not materially different after adjustment for factors associated with the eGFR genetic risk score, such as lipoprotein(a), triglycerides, hemoglobin A1c, and blood pressure. Mendelian randomization results for stroke were nonsignificant but broadly similar to those for CHD. CONCLUSIONS: In people without manifest cardiovascular disease or diabetes, mild-to-moderate kidney dysfunction is causally related to risk of CHD, highlighting the potential value of preventive a

Background: End-stage renal disease is associated with a high risk of cardiovascular events. It is unknown, however, whether mild-to-moderate kidney dysfunction is causally related to coronary heart disease (CHD) and stroke. Methods: Observational analyses were conducted using individual-level data from 4 population data sources (Emerging Risk Factors Collaboration, EPIC-CVD [European Prospective Investigation into Cancer and Nutrition-Cardiovascular Disease Study], Million Veteran Program, and UK Biobank), comprising 648 135 participants with no history of cardiovascular disease or diabetes at baseline, yielding 42 858 and 15 693 incident CHD and stroke events, respectively, during 6.8 million person-years of follow-up. Using a genetic risk score of 218 variants for estimated glomerular filtration rate (eGFR), we conducted Mendelian randomization analyses involving 413 718 participants (25 917 CHD and 8622 strokes) in EPIC-CVD, Million Veteran Program, and UK Biobank. Results: There were U-shaped observational associations of creatinine-based eGFR with CHD and stroke, with higher risk in participants with eGFR values <60 or >105 mL·min-1·1.73 m-2, compared with those with eGFR between 60 and 105 mL·min-1·1.73 m-2. Mendelian randomization analyses for CHD showed an association among participants with eGFR <60 mL·min-1·1.73 m-2, with a 14% (95% CI, 3%-27%) higher CHD risk per 5 mL·min-1·1.73 m-2 lower genetically predicted eGFR, but not for those with eGFR >105 mL·min-1·1.73 m-2. Results were not materially different after adjustment for factors associated with the eGFR genetic risk score, such as lipoprotein(a), triglycerides, hemoglobin A1c, and blood pressure. Mendelian randomization results for stroke were nonsignificant but broadly similar to those for CHD. Conclusions: In people without manifest cardiovascular disease or diabetes, mild-to-moderate kidney dysfunction is causally related to risk of CHD, highlighting the potential value of preventiv

Background: Randomised trials of vitamin D supplementation for cardiovascular disease and all-cause mortality have generally reported null findings. However, generalisability of results to individuals with low vitamin D status is unclear. We aimed to characterise dose-response relationships between 25-hydroxyvitamin D (25[OH]D) concentrations and risk of coronary heart disease, stroke, and all-cause mortality in observational and Mendelian randomisation frameworks. Methods: Observational analyses were undertaken using data from 33 prospective studies comprising 500 962 individuals with no known history of coronary heart disease or stroke at baseline. Mendelian randomisation analyses were performed in four population-based cohort studies (UK Biobank, EPIC-CVD, and two Copenhagen population-based studies) comprising 386 406 middle-aged individuals of European ancestries, including 33 546 people who developed coronary heart disease, 18 166 people who had a stroke, and 27 885 people who died. Primary outcomes were coronary heart disease, defined as fatal ischaemic heart disease (International Classification of Diseases 10th revision code I20-I25) or non-fatal myocardial infarction (I21-I23); stroke, defined as any cerebrovascular disease (I60-I69); and all-cause mortality. Findings: Observational analyses suggested inverse associations between incident coronary heart disease, stroke, and all-cause mortality outcomes with 25(OH)D concentration at low 25(OH)D concentrations. In population-wide genetic analyses, there were no associations of genetically-predicted 25(OH)D with coronary heart disease, stroke, or all-cause mortality. However, for the participants with vitamin D deficiency (25[OH]D concentration <25 nmol/L), genetic analyses provided strong evidence for an inverse association with all-cause mortality (odds ratio [OR] per 10 nmol/L increase in genetically-predicted 25[OH]D concentration 0·69 [95% CI 0·59–0·80]; p<0·0001) and non-significant inverse ass

Accurate quantification of model uncertainty has long been recognized as a fundamental requirement for trusted AI. In regression tasks, uncertainty is typically quantified using prediction intervals calibrated to a specific operating point, making evaluation and comparison across different studies difficult. Our work leverages: (1) the concept of operating characteristics curves and (2) the notion of a gain over a simple reference, to derive a novel operating point agnostic assessment methodology for prediction intervals. The paper describes the corresponding algorithm, provides a theoretical analysis, and demonstrates its utility in multiple scenarios. We argue that the proposed method addresses the current need for comprehensive assessment of prediction intervals and thus represents a valuable addition to the uncertainty quantification toolbox., Comment: 10 pages main paper, 9 pages appendix

Building and maintaining high-quality test sets remains a laborious and expensive task. As a result, test sets in the real world are often not properly kept up to date and drift from the production traffic they are supposed to represent. The frequency and severity of this drift raises serious concerns over the value of manually labeled test sets in the QA process. This paper proposes a simple but effective technique that drastically reduces the effort needed to construct and maintain a high-quality test set (reducing labeling effort by 80-100% across a range of practical scenarios). This result encourages a fundamental rethinking of the testing process by both practitioners, who can use these techniques immediately to improve their testing, and researchers who can help address many of the open questions raised by this new approach., Comment: International Workshop on Challenges in Deploying and Monitoring Machine Learning Systems in Conjunction with ICML 2020

Generating high quality uncertainty estimates for sequential regression, particularly deep recurrent networks, remains a challenging and open problem. Existing approaches often make restrictive assumptions (such as stationarity) yet still perform poorly in practice, particularly in presence of real world non-stationary signals and drift. This paper describes a flexible method that can generate symmetric and asymmetric uncertainty estimates, makes no assumptions about stationarity, and outperforms competitive baselines on both drift and non drift scenarios. This work helps make sequential regression more effective and practical for use in real-world applications, and is a powerful new addition to the modeling toolbox for sequential uncertainty quantification in general.

Today's AI deployments often require significant human involvement and skill in the operational stages of the model lifecycle, including pre-release testing, monitoring, problem diagnosis and model improvements. We present a set of enabling technologies that can be used to increase the level of automation in AI operations, thus lowering the human effort required. Since a common source of human involvement is the need to assess the performance of deployed models, we focus on technologies for performance prediction and KPI analysis and show how they can be used to improve automation in the key stages of a typical AI operations pipeline.

Understanding model performance on unlabeled data is a fundamental challenge of developing, deploying, and maintaining AI systems. Model performance is typically evaluated using test sets or periodic manual quality assessments, both of which require laborious manual data labeling. Automated performance prediction techniques aim to mitigate this burden, but potential inaccuracy and a lack of trust in their predictions has prevented their widespread adoption. We address this core problem of performance prediction uncertainty with a method to compute prediction intervals for model performance. Our methodology uses transfer learning to train an uncertainty model to estimate the uncertainty of model performance predictions. We evaluate our approach across a wide range of drift conditions and show substantial improvement over competitive baselines. We believe this result makes prediction intervals, and performance prediction in general, significantly more practical for real-world use., Comment: 7+6 pages, 5 figures, AAAI 2021

A novel approach to significantly enhance and comprehensively assess the level of nanochannel ordering in self-assembled nanoporous membranes is proposed and tested. An advanced technique based on a two-step anodization and two-step chemical treatment was used to prepare the perfect through membranes by opening channels from the bottom via electrochemical enlargement, and chemical removal of a residual metal and barrier alumina layer. The influence of the process parameters on the self-assembled ordering was studied, and various methods of order assessment were proposed and tested, such as distributions of equivalent disc radii, 2D Fourier transformations, autocorrelation, Hough transformations, Minkowski connectivity, and distributions of nanochannel centre positions. We have demonstrated that self-assembled ordering in nanoscaled membranes could be efficiently tuned by the process parameters, and different assessment methods should be used to comprehensively characterize the order of nanochannels in the nanoporous membranes. To demonstrate the potential of this technique, we show simulations of the narrowing of plasmon spectra in these materials. The proposed fabrication and assessment methods could be used to drastically enhance the properties of nanoporous membranes for nanoelectronics, filters, sensors, bio-active devices and other advanced emerging applications. Finally, our approach could be used for enhancing and tailoring other self-assembled systems and devices of considerable complexity.

Accuracy is an important concern for suppliers of artificial intelligence (AI) services, but considerations beyond accuracy, such as safety (which includes fairness and explainability), security, and provenance, are also critical elements to engender consumers' trust in a service. Many industries use transparent, standardized, but often not legally required documents called supplier's declarations of conformity (SDoCs) to describe the lineage of a product along with the safety and performance testing it has undergone. SDoCs may be considered multi-dimensional fact sheets that capture and quantify various aspects of the product and its development to make it worthy of consumers' trust. Inspired by this practice, we propose FactSheets to help increase trust in AI services. We envision such documents to contain purpose, performance, safety, security, and provenance information to be completed by AI service providers for examination by consumers. We suggest a comprehensive set of declaration items tailored to AI and provide examples for two fictitious AI services in the appendix of the paper., Comment: 31 pages

Software has spent the bounty of Moore's law by solving harder problems and exploiting abstractions, such as highlevel languages, virtual machine technology, binary rewriting, and dynamic analysis. Abstractions make programmers more productive and programs more portable, but usually slow them down. Since Moore's law is now delivering multiple cores instead of faster processors, future systems must either bear a relatively higher cost for abstractions or use some cores to help tolerate abstraction costs. This paper presents the design, implementation, and evaluation of a novel concurrent, configurable dynamic analysis framework that efficiently utilizes multicore cache architectures. It introduces Cache-friendly Asymmetric Buffering (CAB), a lock-free ring-buffer that implements efficient communication between application and analysis threads. We guide the design and implementation of our framework with a model of dynamic analysis overheads. The framework implements exhaustive and sampling event processing and is analysis-neutral. We evaluate the framework with five popular and diverse analyses, and show performance improvements even for lightweight, low-overhead analyses. Efficient inter-core communication is central to high performance parallel systems and we believe the CAB design gives insight into the subtleties and difficulties of attaining it for dynamic analysis and other parallel software.

[Abstract]: The problem of a footing near slope is encountered regularly in engineering practice, with some noteworthy examples being bridge abutments and the basement construction of high rise buildings. This study demonstrates the use of a computer model to analyse the interaction between the slope and the footing. FLAC (Fast Lagrangian Analysis of Continua) is a program which uses explicit finite difference techniques to solve the footing near slope problem and its effectiveness will be demonstrated in this study. Design charts will be presented using non-dimensional parameters to highlight what effects material and geometrical properties have on the normalised bearing capacity of a footing near slope. The parameters comprehensively analysed in this study include dimensionless strength ratio, soil friction angle, slope angle, slope height ratio and footing distance ratio. Initial studies into further footing near slope conditions will also be presented in this paper. This include dimensionless surcharge loading and dilation angle. These parameters will be investigated using a two-dimensional model within the FLAC program.

Microtubules are critically important cytoskeletal elements. Together with microtubule associated proteins (MAPs), they form the latticework on which eukaryotic life exists. Simply put, microtubules are polymers of tubulin heterodimers, which are composed of the globular proteins alpha and beta tubulin. In vivo, these monomers associate with one another to form heterodimers, which then polymerize to form microtubules. In mammals, microtubule polymerization is a temperature-dependent process with an optimum of 37°C (Detrich et al., 2000). If temperatures exceed this optimal temperature by even a few degrees, the microtubule will begin to dissemble due to denaturation of the tubulin subunit and permanent loss of both shape and function will occur. This thermal barrier seems to be consistent in most eukaryotic organisms. Two exceptions are the thermophilic red algae, Cyanidium caldarium and Cyanidioschyzon merolae. These thermophilic acidophiles have been discovered in volcanic vents around the globe from Yellow Stone Park to Italy and grow at optimal temperatures of around 55°C. These organisms have been primarily studied in the context of evolutionary biology because of their primitive characteristics. Very little is known about the molecular biology of these organisms, and certainly nothing is known about how the biochemistry of these organisms brings about the ability to survive the harsh conditions of their environment. Currently, my hypothesis concerning the thermostable tubulin expressed within these organisms is that there may be key amino acid differences in the tubulin's primary structure that confer enhanced thermostability. I am testing this hypothesis by sequencing the alpha and beta tubulin genes of Cyanidium caldarium and Cyanidioschyzon merolae, generating homology models of the tubulin dimers, and comparing these models to a known mesophilic tubulin heterodimer structure in order to identify potential structural differences.

" This expansive and carefully crafted reader brings together many of the classic texts that help to define culture as a tool of resistance. With illuminating introductions throughout, it presents a range of theoretical and historical writings that have influenced contemporary debate, providing tools for the reader's own interventions. " -- Publisher's website.

English Poetry Database, (acc.no) 3.2524, (dlps) ArnolWorks, (c) 1992 Chadwyck-Healey. Do not export or print from this database without checking the Copyright Conditions to see what is permitted.

English Poetry Database, (acc.no) 3.2513, (dlps) ArnoMPoems, (c) 1992 Chadwyck-Healey. Do not export or print from this database without checking the Copyright Conditions to see what is permitted.

xliii p., 1 L., 364 p. ; 19 cm., "Printed in Great Britain.", (dlps) ABR5348.0001.001, http://name.umdl.umich.edu/ABR5348.0001.001, http://quod.lib.umich.edu/t/text/accesspolicy.html

xxxv, 187, [1] p. front. (port.) 19 cm., At head of title: Arnold., (dlps) ABS3480.0001.001, (lccallno) 828 A757 1939, http://quod.lib.umich.edu/t/text/accesspolicy.html

3 p. L., [3]-487 p. front. (port.) 20 cm., At head of title: Oxford edition., (dlps) ABR5201.0001.001, (lccallno) 828 A757e 1914, http://quod.lib.umich.edu/t/text/accesspolicy.html

English Poetry Database, (acc.no) 3.2446, (dlps) ArnoMAlari, (c) 1992 Chadwyck-Healey. Do not export or print from this database without checking the Copyright Conditions to see what is permitted.

Appletons' journal: a magazine of general literature. / Volume 10, Issue 59, Page(s) 413-420, (dlps) volume: acw8433.2-10.059, (dlps) article: acw8433.2-10.059:3, http://quod.lib.umich.edu/t/text/accesspolicy.html

Appletons' journal: a magazine of general literature. / Volume 10, Issue 57, Page(s) 280-281, (dlps) volume: acw8433.2-10.057, (dlps) article: acw8433.2-10.057:11, http://quod.lib.umich.edu/t/text/accesspolicy.html

Appletons' journal: a magazine of general literature. / Volume 7, Issue 2, Page(s) 138-146, (dlps) volume: acw8433.2-07.002, (dlps) article: acw8433.2-07.002:6, http://quod.lib.umich.edu/t/text/accesspolicy.html

English Poetry Database, (acc.no) 3.2446, (dlps) ArnoMAlari, (c) 1992 Chadwyck-Healey. Do not export or print from this database without checking the Copyright Conditions to see what is permitted.

Full limp calf; sweet pea design in brown on covers, gilt title and ornamental border on front cover, repeated on back in brown, signed "MA", i.e. Margaret Armstrong; spine lettered in gilt; t.e.g., untrimmed; bluish-green coated endpapers with gold marble pattern. In box, with publisher's label: "Ariel booklets" listing 25 titles. H: 14.5 cm.; W: 10 cm.; D: 1 cm.

Yeves Andrés, Juan Antonio. La España Moderna: catálogo de la editorial, índice de las revistas. Madrid 2002. P. 67, da como fecha probable de publicación para esta ed. ca. 1893, NUC lo supone impreso en 1893

The function of criticism at the present time -- The literary influence of academies -- Maurice de Guérin -- Eugénie de Guérin -- Heinrich Heine -- Pagan and mediæval religious sentiment -- Joubert -- Spinoza -- Marcus Aurelius -- On translating Homer: three lectures -- On translating Homer: last words -- A French Eton., by Matthew Arnold., First series, with the addition of On translating Homer and A French Eton., Publisher's advertisements: p. [1]-21 (2nd group)., Publisher's device on t.p.

For much of the past seventy-plus years since its independence, Myanmar, often known as Burma, was an isolated military dictatorship plagued by seemingly perpetual civil war. Myanmar’s evolution from military dictatorship began in 2010 when a wide-ranging reform process began. While much has changed in the years since, much has not. Myanmar’s transition can best be understood as a “search for normalcy.” Since 2010, the sheer extent of the country’s dysfunction after decades of military dictatorship has overshadowed prospects for change as has the mass exodus of Rohingya in 2017 after a brutal campaign by the military. Amid these quandaries, it is useful to focus on what is feasible for the country in terms of transitioning to what can be understood as “normal”, or at least on a trajectory towards “normalization”. Framing Myanmar’s domestic prospects is also the reality that the last decade has been distinctly abnormal for the whole world. Reform in Myanmar means working methodically to untangle the messy, convoluted knot that is Myanmar’s governance, politics, and economics and being patient throughout the process. All things considered, Myanmar is progressing in important ways that should neither be taken for granted nor forgotten.