Auswahl der wissenschaftlichen Literatur zum Thema „PUF Statistics“

The internet payment system, which is a widespread cybercrime, is a major issue nowadays. Attackers concentrate on point of sale (POS) systems, the point at which a bank or merchant initially obtains customer information, with the goal of stealing confidential customer information. Effective computer systems with a card reader and specialised software are POS architectures. In this situation, the attacker might utilise malicious software (MS) to steal card statistics. If the customer and the supplier are consistently cut off from the network in, no online payment is practical. If the community fails, attacker's side will attempt to steal the password from the users throughout the price, therefore a safe online transaction price may not be achievable. Due to the PoS information breaches, we recommend an offline micro-fee solution that is secure and protects privacy for the persistent attackers in our paper. We use the FRoDO protocol to make the payment simple and secure from attackers. This protocol not only checks the client's coins but also confirms the client's identity by using identification details. This protocol increases flexibility and security and boosts the device's efficiency by infusing a comfortable micro-charge between the client and carrier.

The flower buds of three Panax species (PGF: P. ginseng; PQF: P. quinquefolius; PNF: P. notoginseng) widely consumed as health tea are easily confused in market circulation. We aimed to develop a green, fast, and easy analysis strategy to distinguish PGF, PQF, and PNF. In this work, fast gas chromatography electronic nose (fast GC e-nose), headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), and headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) were utilized to comprehensively analyze the volatile organic components (VOCs) of three flowers. Meanwhile, a principal component analysis (PCA) and heatmap were applied to distinguish the VOCs identified in PGF, PQF, and PNF. A random forest (RF) analysis was used to screen key factors affecting the discrimination. As a result, 39, 68, and 78 VOCs were identified in three flowers using fast GC e-nose, HS-GC-IMS, and HS-SPME-GC-MS. Nine VOCs were selected as potential chemical markers based on a model of RF for distinguishing these three species. Conclusively, a complete VOC analysis strategy was created to provide a methodological reference for the rapid, simple, and environmentally friendly detection and identification of food products (tea, oil, honey, etc.) and herbs with flavor characteristics and to provide a basis for further specification of their quality and base sources.

Abstract. Long-term monitoring of regulated organic chemicals, such as legacy persistent organic pollutants (POPs) and polycyclic aromatic hydrocarbons (PAHs), in ambient air provides valuable information about the compounds' environmental fate as well as temporal and spatial trends. This is the foundation to evaluate the effectiveness of national and international regulations for priority pollutants. Extracts of high-volume air samples, collected on glass fibre filters (GFF for particle phase) and polyurethane foam plugs (PUF for gaseous phase), for targeted analyses of legacy POPs are commonly cleaned by treatment with concentrated sulfuric acid, resulting in extracts clean from most interfering compounds and matrices that are suitable for multi-quantitative trace analysis. Such standardised methods, however, severely restrict the number of analytes for quantification and are not applicable when targeting new and emerging compounds as some may be less stable under acid treatment. Recently developed suspect and non-target screening analytical strategies (SUS and NTS, respectively) are shown to be effective evaluation tools aimed at identifying a high number of compounds of emerging concern. These strategies, combining highly sophisticated analytical technology with extensive data interpretation and statistics, are already widely accepted in environmental sciences for investigations of various environmental matrices, but their application to air samples is still very limited. In order to apply SUS and NTS for the identification of organic contaminants in air samples, an adapted and more wide-scope sample clean-up method is needed compared to the traditional method, which uses concentrated sulfuric acid. Analysis of raw air sample extracts without clean-up would generate extensive contamination of the analytical system, especially with PUF matrix-based compounds, and thus highly interfered mass spectra and detection limits which are unacceptable high for trace analysis in air samples. In this study, a novel wide-scope sample clean-up method for high-volume air samples has been developed and applied to real high-volume air samples, which facilitates simultaneous target, suspect and non-target analyses. The scope and efficiency of the method were quantitatively evaluated with organic compounds covering a wide range of polarities (logP 2–11), including legacy POPs, brominated flame retardants (BFRs), chlorinated pesticides and currently used pesticides (CUPs). In addition, data reduction and selection strategies for SUS and NTS were developed for comprehensive two-dimensional gas chromatography separation with low-resolution time-of-flight mass spectrometric detection (GC × GC-LRMS) data and applied to real high-volume air samples. Combination of the newly developed clean-up procedure and data treatment strategy enabled the prioritisation of over 600 compounds of interest in the particle phase (on GFF) and over 850 compounds in the gas phase (on PUF) out of over 25 000 chemical features detected in the raw dataset. Of these, 50 individual compounds were identified and confirmed with reference standards, 80 compounds were identified with a probable structure, and 774 compounds were assigned to various compound classes. In the dataset available here, 11 hitherto unknown halogenated compounds were detected. These unknown compounds were not yet listed in the available mass spectral libraries.

Probability Mass Function (PMF) and Probability Density Function (PDF) are fundamental concepts in probability theory and statistics that play a crucial role in describing the probability distribution of random variables. This abstract provides a comprehensive overview of these concepts, highlighting their definitions, characteristics, and applications. The Probability Mass Function is a concept primarily associated with discrete random variables. It defines the probability of a specific outcome occurring. The PMF assigns probabilities to individual values in the sample space, providing a clear picture of the likelihood of each possible outcome. Commonly denoted as P(X=x), where X is the random variable and x is a specific value, the PMF must satisfy two essential properties: non-negativity and the sum of probabilities over all possible outcomes equals one. On the other hand, the Probability Density Function is a concept applied to continuous random variables. Unlike the PMF, which deals with specific values, the PDF deals with ranges of values. The PDF represents the probability that a continuous random variable falls within a given interval. Denoted as f(x), it is essential to note that the probability of any specific point is zero, and instead, probabilities are defined for intervals. The area under the PDF curve over a given interval corresponds to the probability of the random variable falling within that interval. Understanding the differences and similarities between PMF and PDF is crucial for statistical analysis. While PMF is discrete and deals with specific values, PDF is continuous and provides probabilities for intervals. Both functions are integral to the calculation of various statistical measures, including expected values, variance, and standard deviation. This abstract concludes with a discussion of practical applications in diverse fields, such as finance, engineering, and natural sciences, where a deep understanding of PMF and PDF is essential for making informed decisions and drawing meaningful conclusions from data. The integration of these concepts into statistical models and analyses enhances the accuracy and reliability of predictions, making PMF and PDF indispensable tools in the field of probability and statistics

40 Background: Occupational and Physical therapies (OT/PT) are effective treatments to decrease disability and functional status. Few studies have examined the variations in the cost of outpatient OT/PT. For adults with cancer, the added financial burden of cancer rehabilitation is unknown. The study objectives were to (1) describe the variation in patient financial burden for the most commonly used OT/PT services by the provider type (either OT or PT) and State; and (2) determine the impact of therapy caps on the price of service provided among Medicare beneficiaries. Methods: This retrospective, population-based study used the Medicare Provider Utilization and Payment Data Public Use File (PUF), released in April 2014 by the Center for Medicare and Medicaid Services (CMS) to examine variations in care by level of insurance (uninsured, insured and reimbursed), between providers and across states with descriptive statistics. We also examined the impact of the therapy cap on number of visits allowed and the proposed reduction of the therapy cap dollar amount on services use and patient out-of-pocket liability. Results: 3,663 (9.2%) OT’s and 36,247 (90.8%) PT’s were included. Differences between provider’s charges were minimal. Wisconsin, Illinois, Tennessee and Texas had the most inflated charges, respectively, for OT and PT. 12-14 visits plus evaluation are covered under 2012 therapy cap, and the amount of visits would be cut to 7-9 with the MedPAC cap. Conclusions: This study suggests there is wide variation between the potential patient liability for the price of OT/PT based on service provided, state received and insurance coverage. For older adults with cancer who need OT/PT services, this will be an additional cost to their care. Patients without insurance pay a premium for OT/PT services.

A lifted hydrogen/nitrogen turbulent jet flame issuing into a vitiated coflow is investigated using the conditional moment closure (CMC) supplemented by the presumed mapping function (PMF) approach for the modelling of conditional mixing and velocity statistics. Using a prescribed reference field, the PMF approach yields a presumed probability density function (PDF) for the mixture fraction, which is then used in closing the conditional scalar dissipation rate (CSDR) and conditional velocity in a fully consistent manner. These closures are applied to a lifted flame and the findings are compared to previous results obtained usingβ-PDF-based closures over a range of coflow temperatures (Tc). The PMF results are in line with those of theβ-PDF and compare well to measurements. The transport budgets in mixture fraction and physical spaces and the radical history ahead of the stabilisation height indicate that the stabilisation mechanism is susceptible toTc. As in the previousβ-PDF calculations, autoignition around the “most reactive” mixture fraction remains the controlling mechanism for sufficiently highTc. Departure from theβ-PDF predictions is observed whenTcis decreased as PMF predicts stabilisation by means of premixed flame propagation. This conclusion is based on the observation that lean mixtures are heated by downstream burning mixtures in a preheat zone developing ahead of the stabilization height. The spurious sources, which stem from inconsistent CSDR modelling, are further investigated. The findings reveal that their effect is small but nonnegligible, most notably within the flame zone.

This study examined effects of online marketing and consumer buying behaviour of electronic products in the north central zone of Nigeria. The population of this study comprised online marketers and online consumers in the seven states in north central zone of Nigeria. Because the population is infinite, a sample of 385 respondents were taken from marketers and the online consumers. Information was obtained from the respondents using a structured questionnaire. The data collected were analyzed using descriptive statistics such as frequency, simple percentage and the relationship between the variables of the model was tested using multiple linear regression analysis. The result of the regression analysis indicates that a negative relationship exist between perceived risk on consumer (PRK) and consumer buying behavior of electronic products in the north central zone of Nigeria (CBHV) and the relationship is not statistically significant (p>0.05). A positive relationship exist between perceived enjoyment (PEN) and consumer buying behavior of electronic products in the north central zone of Nigeria (CBHV) and the relationship is statistically significant (p<0.05). Perceived ease of use (PEU) was positively related to consumer buying behavior of electronic products in the north central zone of Nigeria (CBHV) and the relationship is statistically significant (p<0.05). Perceived usefulness (PUF) was negatively related to consumer buying behavior of electronic products in the north central zone of Nigeria (CBHV) and the relationship is not statistically significant (p>0.05). A positive relationship exist between perceived convenience (PCN) and consumer buying behavior of electronic products in the north central zone of Nigeria (CBHV) and the relationship is statistically significant (p<0.05). It was concluded that majority of the respondents whopatronize online shopping adopt that because of the convenience and time saving factor they obtain from it. It was recommended among others that owners of online marketing platform should ensure that they make their website dynamic and user friendly so as to attract customerswho will derive comfort and satisfaction transacting from the comfort of their homes.

Les Fonctions Physiques Non-Clonables (PUFs) représentent une alternative prometteuse aux méthodes cryptographiques conventionnelles pour sécuriser les données sensibles dans les circuits modernes en générant des secrets uniques à la volée, en tirant parti de la variabilité inhérente des processus et en éliminant le besoin de stockage des données. Les PUF basées sur les oscillateurs en anneau et la SRAM sont particulièrement étudiées en raison de leur simplicité et de leur prévalence dans les systèmes sur puce (SoC).Lors des simulations paramétriques pour l'évaluation des PUF, plusieurs limitations des logiciels commerciaux de conception électronique assistée par ordinateur (EDA) ont été identifiées. Pour répondre à ces défis, une série d'outils open-source ont été développés, tels que Monaco et NIMPHEL, pour simplifier et accélérer le processus de conception et d'évaluation par des méthodologies de simulation.Pour valider les résultats des simulations, une plateforme open-source, SRAMPlatform, a été créée pour recueillir des données étendues de SRAM et des lectures de capteurs provenant de microcontrôleurs. La plateforme collecte des données de 84 microcontrôleurs STM32, avec des mises à jour hebdomadaires stockées dans une base de données en libre accès, répondant ainsi à la rareté des ensembles de données accessibles sur les PUF. De plus, un ensemble de données complet fourni par Infineon a offert des informations précieuses pour valider les hypothèses de simulation et explorer de nouvelles conceptions de PUF.En outre, des limitations significatives dans les métriques de performance standard des PUF ont été notées et plusieurs solutions et nouvelles métriques alternatives pour une évaluation plus robuste sont proposées. Les données réelles provenant de la plateforme SRAM ont montré des biais extrêmes et des effets de corrélation que les métriques canoniques n'ont pas mis en évidence, soulignant la nécessité de méthodologies de test plus robustes pour identifier avec précision ces effets. Une attention particulière a été portée sur la relation entre l'entropie et la fiabilité des PUF, conduisant au développement d'une méthodologie basée sur la simulation pour établir des seuils de fiabilité basés sur les différences de fréquence. Par la suite, un modèle mathématique holistique prenant en compte la variabilité des processus a été créé pour optimiser les conceptions de RO-PUF, et une nouvelle méthodologie de conception, "Split PUF", a été introduite pour maximiser le rendement en entropie et la fiabilité.La modélisation mathématique des PUFs, un domaine moins exploré, est également investiguée, en proposant des méthodologies statistiques et numériques pour améliorer la compréhension des conceptions de PUF basées sur RO et SRAM. Des méthodes statistiques pour l'extrapolation des métriques sont introduites, réduisant le temps et le coût nécessaires pour évaluer les PUFs. En outre, des jumeaux numériques de PUFs sont proposés, facilitant le test et l'évaluation des algorithmes. Ces modèles offrent une méthodologie robuste et rentable pour évaluer les performances des PUF et aider à leur évaluation de sécurité.Ces avancées améliorent les méthodologies d'évaluation des PUF, en répondant aux limitations des outils et des métriques actuels, et en fournissant de nouveaux cadres et modèles pour la recherche future. Les travaux futurs incluent le développement d'un cadre de test unifié pour toutes les familles de PUF, la validation des modèles statistiques sur un spectre plus large de familles de PUF, le raffinement des modèles de jumeaux numériques, et l'extension du concept de Split PUF à de nouvelles familles de PUF. Ces orientations de recherche visent à accélérer l'adoption mondiale des technologies PUF en améliorant les méthodologies d'évaluation, en répondant aux limitations actuelles des outils et des métriques, et en fournissant de nouveaux cadres et modèles pour la recherche future
Physical Unclonable Functions (PUFs) are a promising alternative to conventional cryptographic methods for securing sensitive data in modern circuits by generating unique secrets on the fly, leveraging inherent process variability and eliminating the need for data storage. Ring Oscillator and SRAM-based PUFs are particularly studied due to their simplicity and prevalence in System-on-Chips (SOCs).During the parametric simulations for PUF evaluation, several limitations in available commercial Electronic Design Automation (EDA) software were identified. To address these challenges, a series of open-source tools were developed, such as Monaco and NIMPHEL, to simplify and accelerate the design process and evaluation through simulation methodologies.To validate the simulation results, an open-source platform, SRAMPlatform, was created to gather extensive SRAM data and sensor readings from microcontrollers. The platform gathers data from 84 STM32 microcontrollers, with weekly updates stored in an open-access database, addressing the scarcity of accessible PUF datasets. Additionally, a comprehensive dataset from Infineon provided valuable insights for validating simulation hypotheses and exploring new PUF designs.Furthermore, significant limitations in standard PUF performance metrics are noted and several mitigations and new alternative metrics for more robust evaluation are proposed. Real-world data from the SRAM platform showed extreme bias and correlation effects that the canonical metrics failed to highlight, underscoring the need for more robust testing methodologies to accurately identify these effects. A major focus was placed on the relationship between entropy and reliability in PUFs, leading to the development of a simulation-based methodology for setting reliability thresholds based on frequency differences. Subsequently, a holistic mathematical model accounting for process variability was created to optimize RO-PUF designs, and a new design methodology, "Split PUF," is introduced to maximize entropy yield and reliability.The mathematical modeling of PUFs, a less-explored area is also investigated, by proposing statistical and numerical methodologies to improve understanding of RO and SRAM-based PUF designs. Statistical methods for metric extrapolation are introduced, reducing the time and cost needed to evaluate PUFs. Furthermore, digital twins of PUFs are proposed, facilitating algorithm testing and evaluation. These models provide a robust and cost-effective methodology for assessing PUF performance and aid in their security assessment.These advancements enhance PUF assessment methodologies, addressing limitations in current tools and metrics, and providing new frameworks and models for future research. Future work includes developing a unified testing framework for all PUF families, validating statistical models across a wider spectrum of PUF families, refining the digital twin models, extending the concept of Split PUFs to new PUF families. These research directions aim to accelerate the worldwide adoption of PUF technologies by enhancing assessment methodologies, addressing current tool and metric limitations, and providing new frameworks and models for future research

A causa del crescente interesse per la protezione dell’ambiente, sta aumentando la quantità di dati disponibili relativi al monitoraggio ambientale. Man mano che le dimensioni e la complessità dei data set ambientali continuano a crescere, si apre un sempre più ampio ventaglio di possibilità per l'implementazione di data science nel campo delle scienze ambientali. Il focus del presente progetto di dottorato è la risoluzione di diverse problematiche idrogeologiche tramite tecniche data-driven. Più specificatamente, il presente progetto di dottorato mira a identificare e applicare tecniche data-driven adatte a dataset idrogeologici, in base alla struttura del problema e dei dati disponibili e alle condizioni sito specifiche. Nell'ambito del presente progetto di dottorato due problemi idrologici principali sono stati affrontati parallelamente, riguardanti i due aspetti principali della gestione delle risorse sotterranee: a) la qualità delle acque sotterranee e b) la quantità delle acque sotterranee. Ognuno di questi due task è stato affrontato in due fasi successive. La prima fase consiste in un'analisi esplorativa dei dati disponibili, volta a raggiungere una migliore comprensione del sistema, del problema e delle informazioni disponibili. La seconda fase consiste nell’uso di tecniche data - driven per indagare sulla loro efficacia in campo idrogeologico. L'analisi dei dati sulla qualità delle acque sotterranee comporta l'applicazione di tecniche di analisi statistica multivariata, normalmente utilizzate per l’identificazione delle sorgenti, a un dataset relativo ai dati chimici di acque superficiali e sotterranee. Lo scopo di questo task è determinare l’efficacia di queste tecniche nell'identificare i fenomeni che contribuiscono alla concentrazione di diversi composti in un campione. Nell’ambito di questo task sono state implementate Factor Analysis, Cluster Analysis e Positive Matrix Factorization. Per quanto riguarda la quantità delle risorse idriche sotterranee, l'analisi delle serie temporali di livelli piezometrici si basa su modelli in grado di ricostruire dati storici ed elaborare scenari futuri; in questo task sono state utilizzate autocorrelazione, autocorrelazione parziale e impulse response e sono stati sviluppati modelli lineari e non lineari (reti neurali). Questo lavoro ha evidenziato che le tecniche data-driven possono essere considerate uno strumento utile a supporto della gestione delle risorse idriche sotterranee.
Due to the constantly growing interest toward environment protection, the amount of available data concerning environmental monitoring is increasing. As the size and complexity of environmental datasets continue to grow, there is a wide variety of possibility for implementation of data science in the environmental sciences field. The focus of the present PhD work is the resolution different hydrogeological issues by means of data science. More specifically, the present PhD project aims at identifying and applying data-driven techniques suitable for hydrogeological datasets, based on the structure of the problem and the available data and on site-specific conditions. In the scope of this PhD work two main hydrological problems were addressed parallelly, concerning the two main aspects of groundwater resource management: a) groundwater quality and b) groundwater quantity. Each task was tackled in two successive phases. The first phase consisted in an exploratory analysis of the available data, aimed at reaching a better understanding of the system, the problem and the available information. The second phase involved the application of specific data driven techniques to investigate their effectiveness in the hydrogeological field. The groundwater quality data analysis involves the application of multivariate techniques, normally used for the source apportionment, to a dataset concerning chemical data of surface water and groundwater aiming at determining their effectiveness in identifying the phenomena that contribute to the concentration of several compounds in a sample. In this task Factor Analysis, Cluster Analysis and Positive Matrix Factorization were implemented. As regards the groundwater quantity, the analysis of groundwater level time series uses models able to reconstruct historical data and applicable to forecast scenarios; in this task autocorrelation, partial autocorrelation and impulse response were used and linear and nonlinear neural networks models

The growing interest in the Internet of Things (IoT) has led to predictions claiming that by 2020 we can expect to be surrounded by 50 billion Internet connected devices. With more entry points to a network, adversaries can potentially use IoT devices as a stepping stone for attacking other devices connected to the network or the network itself. Information security relies on cryptographic primitives that, in turn, depend on secret keys. Furthermore, the issue of Intellectual property (IP) theft in the field of Integrated circuit (IC) design can be tackled with the help of unique device identifiers. Physical unclonable functions (PUFs) provide a tamper-resilient solution for secure key storage and fingerprinting hardware. PUFs use intrinsic manufacturing differences of ICs to assign unique identities to hardware. Arbiter PUFs utilise the differences in delays of identically designed paths, giving rise to an unpredictable response unique to a given IC. This thesis explores the statistical properties of Boolean functions induced by arbiter PUFs. In particular, this empirical study looks into the distribution of induced functions. The data gathered shows that only 3% of all possible 4-variable functions can be induced by a single 4 stage arbiter PUF. Furthermore, some individual functions are more than 5 times more likely than others. Hence, the distribution is non-uniform. We also evaluate alternate PUF designs, improving the coverage vastly, resulting in one particular implementation inducing all 65,536 4-variable functions. We hypothesise the need for n XORed PUFs to induce all 22n possible n-variable Boolean functions.

Monte Carlo path simulations are common in mathematical and computational finance as a way of estimating the expected values of a quantity such as a European put option, which is functional to the solution of a stochastic differential equation (SDE). The computational complexity of the standard Monte Carlo (MC) method grows quite large quickly, so in this thesis we focus on the Multilevel Monte Carlo (MLMC) method by Giles, which uses multigrid ideas to reduce the computational complexity. We use a Euler-Maruyama time discretisation for the approximation of the SDE and investigate how the convergence rate of the MLMC method improves the computational times and cost in comparison with the standard MC method. We perform a numerical analysis on the computational times and costs in order to achieve the desired accuracy and present our findings on the performance of the MLMC method on a European put option compared to the standard MC method.

The performance of lasercom systems operating in the atmosphere is reduced by optical turbulence, which causes irradiance fluctuations in the received signal. The result is a randomly fading signal. Fade statistics for lasercom systems are determined from the probability density function (PDF) of the irradiance fluctuations. The expected number of fades per second and their mean fade time require the joint PDF of the fluctuating irradiance and its time derivative. Theoretical integral expressions, as well as closed form, analytical approximations, were developed for the joint PDF of a gamma-gamma distributed irradiance and its time derivative, and the corresponding expression for the expected number of fades per second. The new approximation for the conditional PDF of the time derivative of a gamma-gamma irradiance is a zero mean Gaussian distribution, with a complicated irradiance depending variance. Fade statistics obtained from experimental data were compared to theoretical predictions based on the lognormal and gamma-gamma distributions. A Gaussian beam wave was propagated through the atmosphere along a horizontal path, near ground, in the moderate-to-strong optical turbulence. To characterize the propagation path, a new method that infers atmospheric propagation parameters was developed. Scintillation theory combined with a numerical scheme was used to infer the structure constant, Cn2, the inner scale and the outer scale from the optical measurements. The inferred parameters were used in calculations for the theoretical PDFs. It was found that fade predictions made by the gamma-gamma and lognormal distributions provide an upper and lower bound, respectively, for the probability of fade and the number of fades per second for irradiance data collected in the moderate-to-strong fluctuation regime. Aperture averaging effects on the PDF of the irradiance fluctuations were investigated by comparing the irradiance distributions for the three receiver apertures at two different values of the structure parameter and, hence, different values of the coherence radius. For the moderate-to-strong fluctuation regime, the gamma-gamma distribution provides a good fit to the irradiance fluctuations collected by finite-sized apertures that are significantly smaller than the coherence radius. For apertures larger than or equal to the coherence radius, the irradiance fluctuations appear to be lognormally distributed.
Ph.D.
Department of Mathematics
Sciences
Mathematics

Students in the sciences, economics, social sciences, and medicine take an introductory statistics course. And yet statistics can be notoriously difficult for instructors to teach and for students to learn. To help overcome these challenges, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, activities, examples and projects that involve active student participation. Part I of the book presents a large selection of activities for introductory statistics courses and has chapters such as ‘First week of class’- with exercises to break the ice and get students talking; then descriptive statistics, graphics, linear regression, data collection (sampling and experimentation), probability, inference, and statistical communication. Part II gives tips on what works and what doesn’t, how to set up effective demonstrations, how to encourage students to participate in class and to work effectively in group projects. Course plans for introductory statistics, statistics for social scientists, and communication and graphics are provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics, sampling, and data science.

AbstractBroadly stated, this book makes the case for a different way of thinking about how to measure and manage person-centered outcomes in health care. The basic contrast is between statistical and metrological definitions of measurement. The mainstream statistical tradition focuses attention on numbers in centrally planned and executed data analyses, while metrology focuses on distributing meaningfully interpretable instruments throughout networks of end users. The former approaches impose group-level statistics from the top down in homogenizing ways. The latter tracks emergent patterns from the bottom up, feeding them back to end users in custom tailored applications, whose decisions and behaviors are coordinated by means of shared languages. New forms of information and knowledge necessitate new forms of social organization to create them and put them to use. The chapters in this book describe the analytic, design, and organizational methods that have the potential to open up exciting new possibilities for systematic and broad scale improvements in health care outcomes.

AbstractFor GinUE matrices the (complex) Schur decomposition underpinned our ability to compute the eigenvalue PDF. This has a real analogue, although it is necessary to condition on the number of real eigenvalues. Consequently, the eigenvalue PDF is no longer absolutely continuous, but rather breaks up into sectors depending on the number of real eigenvalues. Nonetheless, as for real symmetric GOE matrices, structures giving rise to a Pfaffian point process result, the further development of which requires identifying particular skew-orthogonal polynomials. Questions relating to the distribution of real eigenvalues have a rich content, the development of which is facilitated by the identification of a simpler determinantal structure for the generating function, which permits the establishment of a local central limit theorem.

There are far reaching changes occurring in the information industry, including the world of official statistics. The Australian Bureau of Statistics (ABS) is planning to put the user at the centre by giving to them a chance to speak directly with our data. Our catch cry has become ‘freedom to share data will make data more valuable – but only if it’s managed differently.’ The ABS mission is “We assist and encourage informed decision-making, research and discussion within governments and the community, by providing a high quality, objective and responsive national statistical service.” Informed decision making presupposes a level of statistical ability which we know needs development within the Australian community. The ABS has an important leadership role in improving the statistical capability and literacy of our current and future customers. Our statistical output and communication strategy is vital to achieve the aspirational goal of a citizenry that uses statistics to make sensible, informed decisions, whatever their job, community or situation. This paper outlines some aspects of the ABS output and communication strategy, how it has changed and how the strategy increasingly supports a diverse range of customers and their requirements. The paper finishes by examining a range of innovative ABS outputs that have a stronger focus on building statistical capability in communities with lower statistical literacy, such as our youth community.

Since the start of the 2002 academic year, the Department of Sciences of Education of the University of Lyon2, in partnership with the University of Rouen and the CNED (Centre National d'Enseignement à Distance ) of Poitiers (France), has put forward a pedagogical plan of action allowing students to prepare a B.SC degree in Sciences of Education. The goal of this article is the presentation of the problematic of the teaching - learning of the Statistics in this context. Key-words: guidance, e-learning, statistical education, teaching and learning of statistics . A long French version of this article is accessible to URL : ftp://nte.univ-lyon2.fr/users/regnier/public/IASE/BERLIN/.

The degree to which statistics teaching focuses on rules or on critical thinking depends on teachers’ perceptions of and knowledge of statistics, along with their pedagogical content knowledge. This paper reports findings from a brief study with 27 pre-service primary teachers. The teachers completed a survey and planned a lesson for a grade six class, based on a resource that offered rich data and opportunities for addressing issues of statistical literacy. The survey responses and teaching plans analysis reveal an ambivalent attitude towards statistics and an inability or unwillingness to engage deeply with the resource. Most teaching plans focused on correct graphs and rules for presentation or calculation of statistics but put little if any emphasis on understanding the data source or its implications. This simple task provided insight into the pre-service teachers’ knowledge and perceptions, as well as their priorities for their students.

"Objectives—Linking national survey data with administrative data sources enables researchers to conduct analyses that would not be possible with each data source alone. Recently, the Data Linkage Program at the National Center for Health Statistics (NCHS) released updated Linked Mortality Files, including the National Health and Nutrition Examination Survey data linked to the National Death Index mortality files. Two versions of the files were released: restricted-use files available through NCHS and Federal Statistical Research Data Centers and public-use files. To reduce the reidentification risk, statistical disclosure limitation methods were applied to the public-use files before they were released. This included limiting the amount of mortality information available and perturbing cause of death and follow-up time for select records. Methods—To assess the comparability of the restricted-use and public-use files, relative hazard ratios for all-cause and cause-specific mortality using Cox proportional hazards models were estimated and compared. Results—The comparative analysis found that the two data files yield similar descriptive and model results. Suggested citation: Mirel LB, Zhang C, Cox CS, Ye Y, El Burai Félix S, Golden C. Comparative analysis of the National Health and Nutrition Examination Survey public-use and restricted-use linked mortality files. National Health Statistics Reports; no 155. Hyattsville, MD: National Center for Health Statistics. 2021. DOI: https://doi.org/10.15620/cdc:104744. CS323656 nhsr155-508.pdf"

This report documents the acquisition of source data and calculation of land cover summary statistics datasets for 12 National Park Service Pacific Island Network park units: Ala Kahakai National Historic Trail, American Memorial Park, Haleakal? National Park, Hawai?i Volcanoes National Park, Honouliuli National Monument, Kalaupapa National Historical Park, Kaloko-Honok?hau National Historical Park, National Park of American Samoa, Pu?uhonua o H?naunau National Historical Park, Pu?ukohol? Heiau National Historic Site, War in the Pacific National Historical Park, and Pearl Harbor National Memorial, and nine custom areas of analysis. The source data and land cover calculations are available for use within the National Park Service (NPS) Inventory and Monitoring Program. Land cover summary statistics datasets can be calculated for all geographic regions within the extent of the NPS; this report includes statistics calculated for U.S. Pacific Islands. The land cover summary statistics datasets are calculated from the National Oceanic and Atmospheric Administration Office of Coastal Management product Coastal Change Analysis Program (C-CAP) data. These summary statistics calculate land cover at up to two classification scales: modified Anderson Level 2, and Natural versus Converted land cover. The output land cover summary statistics datasets produced here for the 12 Pacific Island Network park units and nine custom areas of analysis utilize the most recent versions of the source datasets (C-CAP). These land cover summary statistics datasets are used in the NPS Inventory and Monitoring Program, including the NPS Environmental Settings Monitoring Protocol, and may be used by networks and parks for additional efforts.

This report consists of climate statistics for air pressure, temperature, relative humidity, precipitation, snow depth, wind, sunshine and global radiation for the normal period covering the years 1991–2020. In addition for the first time oceanographic statistics for sea water level, sea water temperature and sea ice are included. Based on the station and gridded data the new 1991–2020 normal period is approximately 0.6 °C warmer in Finland compared to the previous 1981–2010 period. The new normal period is approximately 1.3 °C warmer when compared to the 1961–1990 period. Climate and oceanographic statistics can be used for example when anomalies for current conditions need to be calculated and put in a historical context. In addition they help in decision-making when it is needed to approximate conditions months into the future. And lastly normal periods provide a way to monitor the progression of climate change. The calculation of the normal period statistics have been carried out following the World Meteorological Organization (WMO) guidelines. Like with previous normal periods, some stricter guidelines were followed nationally, for example in the way missing observations were handled. The period 1991–2020 is both nationally and internationally the official normal period before the next one covering 2001–2030 is taken into use.

This report provides methodologies and processes of data enrichment and enhanced accessibility of Waterborne Commerce and Statistics Center (WCSC) maintained databases. These databases house tabular and statistical data that reports on The U.S. Army Corps of Engineers (USACE) Civil Works Division National Waterway Network (NWN), which geospatially represents approximately 1,000 harbors and 25,000 miles of channels and waterways. WCSC is a division of The Institute for Water Resources (IWR). They have been tasked with the international collection, maintenance, and archival of all records involving commercial movements and commerce that occur on federal waterways. The current records structure is a large, tabular dataset and limited to the systems and processes put in place prior to the computing standards and capabilities available today. Methods have been tested and utilized to bring the tabular datasets into an optimized, modern geospatial network and expanded upon to create a higher resolution than previously maintained by the WCSC. This report will expand upon the applied methodologies to optimize data queries and the overall enhancement of the data system to allow for linkages to various other sources of information for commerce data enhancement for decision support assistance.

SMA is to be designed based on SMA volumetric properties in terms of air voids content (Va), voids in the mineral aggregate (VMA), and adequate stone-on-stone contact. For construction quality assurance (QA) purposes, INDOT currently accepts SMAs based on aggregate gradation and asphalt binder content. Thus, there is a discrepancy between SMA design criteria and construction acceptance. To better align design and construction, it is necessary to consider SMA volumetric properties in the use of QA. For HMA mixtures, INDOT has already transitioned from volumetric QA acceptance procedures to PWL. Today, SMA still uses adjustment points not based on robust statistics for QA acceptance. SMA QA samples and QA data sets were collected from projects constructed in 2019 and tested in the laboratory. The Hamburg Wheel Track Test (HWTT) was performed on the 2019 QA samples to evaluate SMA rutting performance. Additionally, the PWL for HMA was applied to the 2019 SMA QA data to see if the HMA PWL method would work for SMA. Possible SMA QA measurements were compared to past QA data and HMA QA measurements. In addition, Voids in the Coarse Aggregate (VCA) was evaluated as a possible SMA QA measurement. Finally, using the suitable QA measurements for SMA, a PWL parameter study was performed to find PWL that provides a Pay Factor (PF) equivalent to the current SMA Adjustment Point (AP) PF. The current SMA QA measurements (binder content, gradation, and density) are recommended for Indiana's SMA PWL. Based on the results of applying PWL to SMA QA data for the last four years, SMA PWL specification limits are recommended. Also, the SMA PF equations are suggested to get the SMA PWL to have PF equivalent to the current AP PF.

Under the current legal paradigm, the rights to privacy and data protection provide natural persons with subjective rights to protect their private interests, such as related to human dignity, individual autonomy and personal freedom. In principle, when data processing is based on non-personal or aggregated data or when such data pro- cesses have an impact on societal, rather than individual interests, citizens cannot rely on these rights. Although this legal paradigm has worked well for decades, it is increasingly put under pressure because Big Data processes are typically based indis- criminate rather than targeted data collection, because the high volumes of data are processed on an aggregated rather than a personal level and because the policies and decisions based on the statistical correlations found through algorithmic analytics are mostly addressed at large groups or society as a whole rather than specific individuals. This means that large parts of the data-driven environment are currently left unregu- lated and that individuals are often unable to rely on their fundamental rights when addressing the more systemic effects of Big Data processes. This article will discuss how this tension might be relieved by turning to the notion ‘quality of life’, which has the potential of becoming the new standard for the European Court of Human Rights (ECtHR) when dealing with privacy related cases.

Background: The tens of thousands of academic journal websites that are on the Internet today often do not have a clear organizational structure for their website. If most of them are convenient enough for readers (if the journal is open access), then many have problems informing authors about the conditions, the process of submitting and reviewing the manuscript. The Editorial Offices empirically populate the journal's website with content that can change dramatically (both in terms of website design and content) as the journal develops. Aim of Study: To develop a website model for an academic journal that takes into account the basic requirements for the preparation, publication, and archiving of high quality scientific manuscripts. Material and Methods: The academic journal website model is based on a structural-functional approach. The website content consists of text and integrated applications. This model takes into account the basic requirements for the preparation, publication, and archiving of high-quality open access scientific manuscripts, as well as the indexing of journal articles by leading indexing agencies. Results: The academic journal website model is structured with the following menu and submenu elements: 1. HOME: 1.1. Journal information; 1.2. From the editorial office; 1.3. Databases, Indexing; 2. EDITORIAL BOARD: 2.1. Editorial board; 2.2. Reviewers; 2.3. Editing and reviewing process; 3. EDITORIAL POLICIES: 3.1. Editorial policies; 3.2. Plagiarism policy; 3.3. Open access policy; 3.4. The ethics codex of scientific publications; 3.5. Disclaimer; 3.6. License terms; 3.7. Terms of publications (fee); 4. ARCHIV: 4.1. Previous issues; 4.2. Current issue; 4.3. Articles online first; 5. INSTRUCTIONS FOR AUTHORS: 5.1. General recommendations; 5.2. Manuscript templates; 5.3. Supplemental materials; 6. STATISTICS: 6.1. Publications; 6.2. Authors; 6.3. Readers; 7. CONTACTS: 7.1. Contact; 7.2. Subscriptions; 7.3. Search. Conclusions: This academic journal website model was implemented for the International Journal of Science Annals (IJSA). Authors and readers of IJSA noted the advantages of the model proposed by the author, including: a convenient and understandable website interface, the availability of the necessary hyperlinks to the pages of the journal's website and external media (sites of indexed agencies, library archives, etc.), convenient search for information on the website and published in the journal articles (by author, publication, text of the article), availability of integrated applications (online submission of manuscripts, filing appeals against the decision of reviewers and complaints about published articles, viewing the interactive printed version of the journal, etc.), availability of templates (for authors, reviewers), availability of multiple formats for archiving articles (PDF, DOAJ, XML, TXT), the ability to choose the style of citing the article and the website language (English, Ukrainian), etc. Keywords: journal, model, website, academic, indexing

This report describes activity conducted in several lines of research associated with field-scale water and solute processes. A major effort was put forth developing a stochastic continuum analysis for an important class of problems involving flow of reactive and non reactive chemicals under steady unsaturated flow. The field-scale velocity covariance tensor has been derived from local soil properties and their variability, producing a large-scale description of the medium that embodies all of the local variability in a statistical sense. Special cases of anisotropic medium properties not aligned along the flow direction of spatially variable solute sorption were analysed in detail, revealing a dependence of solute spreading on subtle features of the variability of the medium, such as cross-correlations between sorption and conductivity. A novel method was developed and tested for measuring hydraulic conductivity at the scale of observation through the interpretation of a solute transport outflow curve as a stochastic-convective process. This undertaking provided a host of new K(q) relationships for existing solute experiments and also laid the foundation for future work developing a self-consistent description of flow and transport under these conditions. Numerical codes were developed for calculating K(q) functions for a variety of solute pulse outflow shapes, including lognormal, Fickian, Mobile-Immobile water, and bimodal. Testing of this new approach against conventional methodology was mixed, and agreed most closely when the assumptions of the new method were met. We conclude that this procedure offers a valuable alternative to conventional methods of measuring K(q), particularly when the application of the method is at a scale (e.g. and agricultural field) that is large compared to the common scale at which conventional K(q) devices operate. The same problem was approached from a numerical perspective, by studying the feasibility of inverting a solute outflow signal to yield the hydraulic parameters of the medium that housed the experiment. We found that the inverse problem was solvable under certain conditions, depending on the amount of noise in the signal and the degree of heterogeneity in the medium. A realistic three dimensional model of transient water and solute movement in a heterogeneous medium that contains plant roots was developed and tested. The approach taken was to generate a single realization of this complex flow event, and examine the results to see whether features were present that might be overlooked in less sophisticated model efforts. One such feature revealed is transverse dispersion, which is a critically important component in the development of macrodispersion in the longitudinal direction. The lateral mixing that was observed greatly exceeded that predicted from simpler approaches, suggesting that at least part of the important physics of the mixing process is embedded in the complexity of three dimensional flow. Another important finding was the observation that variability can produce a pseudo-kinetic behavior for solute adsorption, even when the local models used are equilibrium.

1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lower than estimates from January’s Monetary Policy Report (-7.2%). High-frequency indicators suggest that economic performance was significantly more dynamic than expected in January, despite mobility restrictions and quarantine measures. This has also come amid declines in total and core inflation, the latter of which was below January projections if controlling for certain relative price changes. This suggests that the unexpected strength of recent growth contains elements of demand, and that excess capacity, while significant, could be lower than previously estimated. Nevertheless, uncertainty over the measurement of excess capacity continues to be unusually high and marked both by variations in the way different economic sectors and spending components have been affected by the pandemic, and by uneven price behavior. The size of excess capacity, and in particular the evolution of the pandemic in forthcoming quarters, constitute substantial risks to the macroeconomic forecast presented in this report. Despite the unexpected strength of the recovery, the technical staff continues to project ample excess capacity that is expected to remain on the forecast horizon, alongside core inflation that will likely remain below the target. Domestic demand remains below 2019 levels amid unusually significant uncertainty over the size of excess capacity in the economy. High national unemployment (14.6% for February 2021) reflects a loose labor market, while observed total and core inflation continue to be below 2%. Inflationary pressures from the exchange rate are expected to continue to be low, with relatively little pass-through on inflation. This would be compatible with a negative output gap. Excess productive capacity and the expectation of core inflation below the 3% target on the forecast horizon provide a basis for an expansive monetary policy posture. The technical staff’s assessment of certain shocks and their expected effects on the economy, as well as the presence of several sources of uncertainty and related assumptions about their potential macroeconomic impacts, remain a feature of this report. The coronavirus pandemic, in particular, continues to affect the public health environment, and the reopening of Colombia’s economy remains incomplete. The technical staff’s assessment is that the COVID-19 shock has affected both aggregate demand and supply, but that the impact on demand has been deeper and more persistent. Given this persistence, the central forecast accounts for a gradual tightening of the output gap in the absence of new waves of contagion, and as vaccination campaigns progress. The central forecast continues to include an expected increase of total and core inflation rates in the second quarter of 2021, alongside the lapse of the temporary price relief measures put in place in 2020. Additional COVID-19 outbreaks (of uncertain duration and intensity) represent a significant risk factor that could affect these projections. Additionally, the forecast continues to include an upward trend in sovereign risk premiums, reflected by higher levels of public debt that in the wake of the pandemic are likely to persist on the forecast horizon, even in the context of a fiscal adjustment. At the same time, the projection accounts for the shortterm effects on private domestic demand from a fiscal adjustment along the lines of the one currently being proposed by the national government. This would be compatible with a gradual recovery of private domestic demand in 2022. The size and characteristics of the fiscal adjustment that is ultimately implemented, as well as the corresponding market response, represent another source of forecast uncertainty. Newly available information offers evidence of the potential for significant changes to the macroeconomic scenario, though without altering the general diagnosis described above. The most recent data on inflation, growth, fiscal policy, and international financial conditions suggests a more dynamic economy than previously expected. However, a third wave of the pandemic has delayed the re-opening of Colombia’s economy and brought with it a deceleration in economic activity. Detailed descriptions of these considerations and subsequent changes to the macroeconomic forecast are presented below. The expected annual decline in GDP (-0.3%) in the first quarter of 2021 appears to have been less pronounced than projected in January (-4.8%). Partial closures in January to address a second wave of COVID-19 appear to have had a less significant negative impact on the economy than previously estimated. This is reflected in figures related to mobility, energy demand, industry and retail sales, foreign trade, commercial transactions from selected banks, and the national statistics agency’s (DANE) economic tracking indicator (ISE). Output is now expected to have declined annually in the first quarter by 0.3%. Private consumption likely continued to recover, registering levels somewhat above those from the previous year, while public consumption likely increased significantly. While a recovery in investment in both housing and in other buildings and structures is expected, overall investment levels in this case likely continued to be low, and gross fixed capital formation is expected to continue to show significant annual declines. Imports likely recovered to again outpace exports, though both are expected to register significant annual declines. Economic activity that outpaced projections, an increase in oil prices and other export products, and an expected increase in public spending this year account for the upward revision to the 2021 growth forecast (from 4.6% with a range between 2% and 6% in January, to 6.0% with a range between 3% and 7% in April). As a result, the output gap is expected to be smaller and to tighten more rapidly than projected in the previous report, though it is still expected to remain in negative territory on the forecast horizon. Wide forecast intervals reflect the fact that the future evolution of the COVID-19 pandemic remains a significant source of uncertainty on these projections. The delay in the recovery of economic activity as a result of the resurgence of COVID-19 in the first quarter appears to have been less significant than projected in the January report. The central forecast scenario expects this improved performance to continue in 2021 alongside increased consumer and business confidence. Low real interest rates and an active credit supply would also support this dynamic, and the overall conditions would be expected to spur a recovery in consumption and investment. Increased growth in public spending and public works based on the national government’s spending plan (Plan Financiero del Gobierno) are other factors to consider. Additionally, an expected recovery in global demand and higher projected prices for oil and coffee would further contribute to improved external revenues and would favor investment, in particular in the oil sector. Given the above, the technical staff’s 2021 growth forecast has been revised upward from 4.6% in January (range from 2% to 6%) to 6.0% in April (range from 3% to 7%). These projections account for the potential for the third wave of COVID-19 to have a larger and more persistent effect on the economy than the previous wave, while also supposing that there will not be any additional significant waves of the pandemic and that mobility restrictions will be relaxed as a result. Economic growth in 2022 is expected to be 3%, with a range between 1% and 5%. This figure would be lower than projected in the January report (3.6% with a range between 2% and 6%), due to a higher base of comparison given the upward revision to expected GDP in 2021. This forecast also takes into account the likely effects on private demand of a fiscal adjustment of the size currently being proposed by the national government, and which would come into effect in 2022. Excess in productive capacity is now expected to be lower than estimated in January but continues to be significant and affected by high levels of uncertainty, as reflected in the wide forecast intervals. The possibility of new waves of the virus (of uncertain intensity and duration) represents a significant downward risk to projected GDP growth, and is signaled by the lower limits of the ranges provided in this report. Inflation (1.51%) and inflation excluding food and regulated items (0.94%) declined in March compared to December, continuing below the 3% target. The decline in inflation in this period was below projections, explained in large part by unanticipated increases in the costs of certain foods (3.92%) and regulated items (1.52%). An increase in international food and shipping prices, increased foreign demand for beef, and specific upward pressures on perishable food supplies appear to explain a lower-than-expected deceleration in the consumer price index (CPI) for foods. An unexpected increase in regulated items prices came amid unanticipated increases in international fuel prices, on some utilities rates, and for regulated education prices. The decline in annual inflation excluding food and regulated items between December and March was in line with projections from January, though this included downward pressure from a significant reduction in telecommunications rates due to the imminent entry of a new operator. When controlling for the effects of this relative price change, inflation excluding food and regulated items exceeds levels forecast in the previous report. Within this indicator of core inflation, the CPI for goods (1.05%) accelerated due to a reversion of the effects of the VAT-free day in November, which was largely accounted for in February, and possibly by the transmission of a recent depreciation of the peso on domestic prices for certain items (electric and household appliances). For their part, services prices decelerated and showed the lowest rate of annual growth (0.89%) among the large consumer baskets in the CPI. Within the services basket, the annual change in rental prices continued to decline, while those services that continue to experience the most significant restrictions on returning to normal operations (tourism, cinemas, nightlife, etc.) continued to register significant price declines. As previously mentioned, telephone rates also fell significantly due to increased competition in the market. Total inflation is expected to continue to be affected by ample excesses in productive capacity for the remainder of 2021 and 2022, though less so than projected in January. As a result, convergence to the inflation target is now expected to be somewhat faster than estimated in the previous report, assuming the absence of significant additional outbreaks of COVID-19. The technical staff’s year-end inflation projections for 2021 and 2022 have increased, suggesting figures around 3% due largely to variation in food and regulated items prices. The projection for inflation excluding food and regulated items also increased, but remains below 3%. Price relief measures on indirect taxes implemented in 2020 are expected to lapse in the second quarter of 2021, generating a one-off effect on prices and temporarily affecting inflation excluding food and regulated items. However, indexation to low levels of past inflation, weak demand, and ample excess productive capacity are expected to keep core inflation below the target, near 2.3% at the end of 2021 (previously 2.1%). The reversion in 2021 of the effects of some price relief measures on utility rates from 2020 should lead to an increase in the CPI for regulated items in the second half of this year. Annual price changes are now expected to be higher than estimated in the January report due to an increased expected path for fuel prices and unanticipated increases in regulated education prices. The projection for the CPI for foods has increased compared to the previous report, taking into account certain factors that were not anticipated in January (a less favorable agricultural cycle, increased pressure from international prices, and transport costs). Given the above, year-end annual inflation for 2021 and 2022 is now expected to be 3% and 2.8%, respectively, which would be above projections from January (2.3% and 2,7%). For its part, expected inflation based on analyst surveys suggests year-end inflation in 2021 and 2022 of 2.8% and 3.1%, respectively. There remains significant uncertainty surrounding the inflation forecasts included in this report due to several factors: 1) the evolution of the pandemic; 2) the difficulty in evaluating the size and persistence of excess productive capacity; 3) the timing and manner in which price relief measures will lapse; and 4) the future behavior of food prices. Projected 2021 growth in foreign demand (4.4% to 5.2%) and the supposed average oil price (USD 53 to USD 61 per Brent benchmark barrel) were both revised upward. An increase in long-term international interest rates has been reflected in a depreciation of the peso and could result in relatively tighter external financial conditions for emerging market economies, including Colombia. Average growth among Colombia’s trade partners was greater than expected in the fourth quarter of 2020. This, together with a sizable fiscal stimulus approved in the United States and the onset of a massive global vaccination campaign, largely explains the projected increase in foreign demand growth in 2021. The resilience of the goods market in the face of global crisis and an expected normalization in international trade are additional factors. These considerations and the expected continuation of a gradual reduction of mobility restrictions abroad suggest that Colombia’s trade partners could grow on average by 5.2% in 2021 and around 3.4% in 2022. The improved prospects for global economic growth have led to an increase in current and expected oil prices. Production interruptions due to a heavy winter, reduced inventories, and increased supply restrictions instituted by producing countries have also contributed to the increase. Meanwhile, market forecasts and recent Federal Reserve pronouncements suggest that the benchmark interest rate in the U.S. will remain stable for the next two years. Nevertheless, a significant increase in public spending in the country has fostered expectations for greater growth and inflation, as well as increased uncertainty over the moment in which a normalization of monetary policy might begin. This has been reflected in an increase in long-term interest rates. In this context, emerging market economies in the region, including Colombia, have registered increases in sovereign risk premiums and long-term domestic interest rates, and a depreciation of local currencies against the dollar. Recent outbreaks of COVID-19 in several of these economies; limits on vaccine supply and the slow pace of immunization campaigns in some countries; a significant increase in public debt; and tensions between the United States and China, among other factors, all add to a high level of uncertainty surrounding interest rate spreads, external financing conditions, and the future performance of risk premiums. The impact that this environment could have on the exchange rate and on domestic financing conditions represent risks to the macroeconomic and monetary policy forecasts. Domestic financial conditions continue to favor recovery in economic activity. The transmission of reductions to the policy interest rate on credit rates has been significant. The banking portfolio continues to recover amid circumstances that have affected both the supply and demand for loans, and in which some credit risks have materialized. Preferential and ordinary commercial interest rates have fallen to a similar degree as the benchmark interest rate. As is generally the case, this transmission has come at a slower pace for consumer credit rates, and has been further delayed in the case of mortgage rates. Commercial credit levels stabilized above pre-pandemic levels in March, following an increase resulting from significant liquidity requirements for businesses in the second quarter of 2020. The consumer credit portfolio continued to recover and has now surpassed February 2020 levels, though overall growth in the portfolio remains low. At the same time, portfolio projections and default indicators have increased, and credit establishment earnings have come down. Despite this, credit disbursements continue to recover and solvency indicators remain well above regulatory minimums. 1.2 Monetary policy decision In its meetings in March and April the BDBR left the benchmark interest rate unchanged at 1.75%.

"The Updated Tables, March 2021) presents nationally representative, cumulative biomonitoring data gathered from 1999–2000 through 2015–2016. It includes all the data from each of the previous National Reports on Human Exposure to Environmental Chemicals and each of the previous Updated Tables (collectively, the Report and Updated Tables). In each survey period, the reported chemicals or their metabolites were measured in blood, serum, and urine samples from random subsamples of the National Health and Nutrition Examination Survey (NHANES). These subsamples typically consisted of about 2,500 participants – exact numbers are included in the tables. Survey data and samples are collected by the Centers for Disease Control and Prevention (CDC) National Center for Health Statistics. CDC’s Environmental Health Laboratory (Division of Laboratory Sciences (DLS), National Center for Environmental Health) used mass spectrometry methods to obtain the blood, serum, and urine exposure measurements presented in the Report and Updated Tables. Volume One (1999-2010) and Volume Two (2011-2016) contain data tables for chemicals measured in the general U.S. population Volume Two: NHANES 2011-2016 provides data on the general U.S. population from NHANES 2011-2012, 2013–2014, and 2015-2016. CS272983-A FourthReport_UpdatedTables_Volume2_Mar2021-508.pdf"