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This report summarizes the statistical analyses of the International Board of Lactation Consultant Examiners 1999 examination for certification as an International Board Certified Lactation Consultant. The summary includes information regarding exam translations and recertification rates. [ABSTRACT FROM AUTHOR]

Substantial guidance is available on undergraduate quantitative training for biologists, including reports focused on biomedical science. Far less attention has been paid to the graduate curriculum and the particular challenges of the diversity of specialization within the life sciences. We propose an innovative approach to quantitative education that goes beyond recommendations of a course or set of courses or activities, derived from analysis of the expectations for students in particular programs. Due to the plethora of quantitative methods, it is infeasible to expect that biomedical PhD students can be exposed to more than a minority of the quantitative concepts and techniques employed in modern biology. We collected key recent papers suggested by the faculty in biomedical science programs, chosen to include important scientific contributions that the faculty consider appropriate for all students in the program to be able to read with confidence. The quantitative concepts and methods inherent in these papers were then analyzed and categorized to provide a rational basis for prioritization of those concepts to be emphasized in the education program. This novel approach to prioritization of quantitative skills and concepts provides an effective method to drive curricular focus based upon program-specific faculty input for science programs of all types. The results of our particular application to biomedical science training highlight the disconnect between typical undergraduate quantitative education for life science students, focused on continuous mathematics, and the concepts and skills in graphics, statistics, and discrete mathematics that arise from priorities established by biomedical science faculty. There was little reference in the key recent papers chosen by faculty to classic mathematical areas such as calculus which make up a large component of the formal undergraduate mathematics training of graduate students in biomedical areas., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Gross et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The ambition and effectiveness of climate policies will be essential in determining greenhouse gas emissions and, as a consequence, the scale of climate change impacts 1,2 . However, the socio-politico-technical processes that will determine climate policy and emissions trajectories are treated as exogenous in almost all climate change modelling 3,4 . Here we identify relevant feedback processes documented across a range of disciplines and connect them in a stylized model of the climate-social system. An analysis of model behaviour reveals the potential for nonlinearities and tipping points that are particularly associated with connections across the individual, community, national and global scales represented. These connections can be decisive for determining policy and emissions outcomes. After partly constraining the model parameter space using observations, we simulate 100,000 possible future policy and emissions trajectories. These fall into 5 clusters with warming in 2100 ranging between 1.8 °C and 3.6 °C above the 1880-1910 average. Public perceptions of climate change, the future cost and effectiveness of mitigation technologies, and the responsiveness of political institutions emerge as important in explaining variation in emissions pathways and therefore the constraints on warming over the twenty-first century., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

In response to the pandemic in early 2020, cities implemented states of emergency and stay at home orders to reduce virus spread. Changes in social dynamics due to local restrictions impacted human behavior and led to a shift in crime dynamics. We analyze shifts in crime types by comparing crimes before the implementation of stay at home orders and the time period shortly after these orders were put in place across three cities. We find consistent changes across Chicago, Baltimore, and Baton Rouge with significant declines in total crimes during the time period immediately following stay at home orders. The starkest differences occurred in Chicago, but in all three cities the crime types contributing to these declines were related to property crime and statutory crime rather than interpersonal crimes., Competing Interests: The authors have declared that no competing interests exist.

We live in a data-rich world with rapidly growing databases with zettabytes of data. Innovation, computation, and technological advances have now tremendously accelerated the pace of discovery, providing driverless cars, robotic devices, expert healthcare systems, precision medicine, and automated discovery to mention a few. Even though the definition of the term data science continues to evolve, the sweeping impact it has already produced on society is undeniable. We are at a point when new discoveries through data science have enormous potential to advance progress but also to be used maliciously, with harmful ethical and social consequences. Perhaps nowhere is this more clearly exemplified than in the biological and medical sciences. The confluence of (1) machine learning, (2) mathematical modeling, (3) computation/simulation, and (4) big data have moved us from the sequencing of genomes to gene editing and individualized medicine; yet, unsettled policies regarding data privacy and ethical norms could potentially open doors for serious negative repercussions. The data science revolution has amplified the urgent need for a paradigm shift in undergraduate biology education. It has reaffirmed that data science education interacts and enhances mathematical education in advancing quantitative conceptual and skill development for the new generation of biologists. These connections encourage us to strive to cultivate a broadly skilled workforce of technologically savvy problem-solvers, skilled at handling the unique challenges pertaining to biological data, and capable of collaborating across various disciplines in the sciences, the humanities, and the social sciences. To accomplish this, we suggest development of open curricula that extend beyond the job certification rhetoric and combine data acumen with modeling, experimental, and computational methods through engaging projects, while also providing awareness and deep exploration of their societal implications. This process would benefit from embracing the pedagogy of experiential learning and involve students in open-ended explorations derived from authentic inquiries and ongoing research. On this foundation, we encourage development of flexible data science initiatives for the education of life science undergraduates within and across existing models.

We describe the development and initial validity assessment of the 20-item BioCalculus Assessment (BCA), with the objective of comparing undergraduate life science students' understanding of calculus concepts in different courses with alternative emphases (with and without focus on biological applications). The development process of the BCA included obtaining input from a large network of scientists and educators as well as students in calculus and biocalculus courses to accumulate evidential support of the instrument's content validity and response processes of test takers. We used the Rasch model to examine the internal structure of scores from students who have experienced calculus instruction in the two methods. The analysis involved three populations (Calculus 1, Calculus 2, and Biocalculus) for which the Calc 1 and Calc 2 students were not exposed to calculus concepts in a life science setting, while the Biocalculus students were presented concepts explicitly with a life science emphasis. Overall, our findings indicate that the BCA has reasonable validity properties, providing a diagnostic tool to assess the relative learning success and calculus comprehension of undergraduate biology majors from alternative methods of instruction that do or do not emphasize life science examples.

If pathogen species, strains, or clones do not interact, intuition suggests the proportion of coinfected hosts should be the product of the individual prevalences. Independence consequently underpins the wide range of methods for detecting pathogen interactions from cross-sectional survey data. However, the very simplest of epidemiological models challenge the underlying assumption of statistical independence. Even if pathogens do not interact, death of coinfected hosts causes net prevalences of individual pathogens to decrease simultaneously. The induced positive correlation between prevalences means the proportion of coinfected hosts is expected to be higher than multiplication would suggest. By modelling the dynamics of multiple noninteracting pathogens causing chronic infections, we develop a pair of novel tests of interaction that properly account for nonindependence between pathogens causing lifelong infection. Our tests allow us to reinterpret data from previous studies including pathogens of humans, plants, and animals. Our work demonstrates how methods to identify interactions between pathogens can be updated using simple epidemic models., Competing Interests: The authors have declared that no competing interests exist.

Maize lethal necrosis (MLN) has emerged as a serious threat to food security in sub-Saharan Africa. MLN is caused by coinfection with two viruses, Maize chlorotic mottle virus and a potyvirus, often Sugarcane mosaic virus. To better understand the dynamics of MLN and to provide insight into disease management, we modeled the spread of the viruses causing MLN within and between growing seasons. The model allows for transmission via vectors, soil, and seed, as well as exogenous sources of infection. Following model parameterization, we predict how management affects disease prevalence and crop performance over multiple seasons. Resource-rich farmers with large holdings can achieve good control by combining clean seed and insect control. However, crop rotation is often required to effect full control. Resource-poor farmers with smaller holdings must rely on rotation and roguing, and achieve more limited control. For both types of farmer, unless management is synchronized over large areas, exogenous sources of infection can thwart control. As well as providing practical guidance, our modeling framework is potentially informative for other cropping systems in which coinfection has devastating effects. Our work also emphasizes how mathematical modeling can inform management of an emerging disease even when epidemiological information remains scanty. [Formula: see text] Copyright © 2017 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap.

We here present a highly efficient and high yielding procedure for the preparation of 2-vinyl tetrahydrofurans starting from α-hydroxymethyl tetrahydrofurans. Best results for this dehydration were achieved using Burgess' reagent in dioxane under microwave irradiation. A range of functional groups as well as different cyclic and bicyclic frameworks were found to be compatible with the reaction conditions. The desired products were obtained within minutes in good to high yields and excellent regioselectivity.

An asymmetric synthesis of the C 11 -homoterpenoid (+)-Greek tobacco lactone is developed starting from readily available (R)-linalool. The synthesis is comprised of four operations and features a diastereoablative epoxidation and an oxidative tetrahydropyran formation using vanadium-, palladium-, and selenium-catalyzed cyclizations.

The direct oxidative cyclization of 1,5-dienes is a valuable synthetic method for the (dia)stereoselective preparation of substituted tetrahydrofurans. Closely related reactions start from 5,6-dihydroxy or 5-hydroxyalkenes to generate similar products in a mechanistically analogous manner. After a brief overview on the history of this group of transformations and a survey on mechanistic and stereochemical aspects, this review article provides a summary on applications in natural product synthesis. Moreover, current limitations and future directions in this area of chemistry are discussed.

This article provides a summary of the ideas discussed at the 2015 Annual Meeting of the Society for Integrative and Comparative Biology society-wide symposium on Leading Students and Faculty to Quantitative Biology through Active Learning. It also includes a brief review of the recent advancements in incorporating active learning approaches into quantitative biology classrooms. We begin with an overview of recent literature that shows that active learning can improve students' outcomes in Science, Technology, Engineering and Math Education disciplines. We then discuss how this approach can be particularly useful when teaching topics in quantitative biology. Next, we describe some of the recent initiatives to develop hands-on activities in quantitative biology at both the graduate and the undergraduate levels. Throughout the article we provide resources for educators who wish to integrate active learning and technology into their classrooms., (© The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.)

Purpose: This US survey aimed to determine (1) relative utilization of the 2 techniques, a gas radiopharmaceutical technique (GRT) versus aerosolized radiopharmaceutical technique (ART), in ventilation-perfusion scintigraphy done for pulmonary embolism indication and (2) radiopharmaceuticals (RFs) used., Patients and Methods: Nuclear medicine physicians and technologists were sent a questionnaire asking which RF(s) their imaging facilities are using for ventilation imaging. Respondents were classified as reporting from academic/teaching facilities (ATFs) or from community-based facilities (CBFs)., Results: Of the 256 surveyed, 78 responded (30.5%), who reported about 158 facilities. Majority (90/158, 57%) were CBFs, whereas the rest (68/158, 43%) were ATFs. Overall, slight majority (92/158, 58%) used ART, 90 using (99m)Tc-DTPA, one using (99m)Tc-sulfur colloid (SC), and one using (99m)Tc-PYP. Minority (66/158, 42%) used GRT (all ¹³³Xe). In the CBFs, a slight majority (55/90, 61%) used ART (including one that used (99m)Tc-PYP), whereas the rest 35 (39%) of 90 used GRT. In the ATFs, a slight majority (37/68, 54.4%) used ART (including 1 facility that used (99m)Tc-SC), whereas the rest (31/68, 45.6%) used GRT. There was no statistically significant difference in ART:GRT ratios between CBFs and ATFs (P = 0.35)., Conclusions: Aerosolized RF technique is overall more common (57%) than GRT, about the same at CBFs and at ATFs, and almost all ART using (99m)Tc-DTPA. Therefore, (99m)Tc-DTPA price increase would have impacted a significant number of the US facilities, which should increase interest in alternatives identified by this survey—(99m)Tc-SC and (99m)Tc-PYP.

Objective: The aim of the study was to examine the association between resource activation and treatment success in in-patient and day-care psychosomatic treatment., Methods: 130 patients were examined at the beginning and at the end of their in-patient or day-care psychosomatic treatment. The change of resource realization (RES[1]) and different measures of therapeutic success (SCL-90-R[2], BDI-II[3], WHO-5-Q[4], GAS[5], retrospective success evaluation [6]) were assessed using standardized questionnaires., Results: The results demonstrated a significant trans-diagnostic change in patients' resource realization, which correlated with different measures of mental health (SCL-90-R, BDI-II, WHO-5-Q). Resource realization at the beginning of the treatment and the process of resource activation (pre-post measure of resource realization) turned out to be relevant for predicting treatment success. Furthermore, mediation analysis shows that initiation of experiences of mastery (BSPR-P[7]) seems to be effective as a mediation process., Conclusion: The results show that resource realization improves during psychosomatic treatment and is associated with treatment success., (© Georg Thieme Verlag KG Stuttgart · New York.)

Use of individual-based models (IBMs) has been expanding in both theoretical and applied ecology. IBMs include details at the level of individuals that may lead to different conclusions from aggregated modeling methods. There has been essentially no guidance available on how to most effectively manage populations when the underlying dynamics are best modeled through IBMs. Using a simple resource-consumer IBM, we investigate whether optimal control theory applied to an aggregated model (AM) can effectively control a harmful species modeled by an IBM or whether interactions between individuals, their spatial distribution, and/or landscape heterogeneities limit the effectiveness of a control derived for the AM. If optimal policies derived from an AM are determined to be generally effective in managing a population modeled with considerably greater complexity, this provides evidence that optimal management strategies may be relatively insensitive to the details of individual behavior and the associated effects on population response. We investigate these issues and find that if there is weak spatial heterogeneity in the resource, the optimal control derived from the AM can be used effectively to control the harmful species in the IBM. The approach is more limited in the case of very strong spatial heterogeneity in the resource. This suggests investigation of a mixture of simplified models in conjunction with detailed simulation models when individual differences affect population processes.

This review summarises theoretical issues and current research on working with clients' resources and strengths in clinical psychology and psychotherapy. Resource activation is considered as an important common factor in psychotherapy. In general, resource activation means an explicit focus on resources, strengths and potentials of the clients. After defining the term resources, considerations with regard to therapeutic attitude, principles of resource activation, approaches to resource diagnostics and different research strategies are presented. Current research focuses especially on the relation between resource activation and process variables in out-patient treatment., (© Georg Thieme Verlag KG Stuttgart · New York.)

We investigate optimal timing of augmentation of an endangered/threatened species population in a target region by moving individuals from a reserve or captive population. This is formulated as a discrete-time optimal control problem in which augmentation occurs once per time period over a fixed number of time periods. The population model assumes the Allee effect growth functions in both target and reserve populations and the control objective is to maximize the target and reserve population sizes over the time horizon while accounting for costs of augmentation. Two possible orders of events are considered for different life histories of the species relative to augmentation time: move individuals either before or after population growth occurs. The control variable is the proportion of the reserve population to be moved to the target population. We develop solutions and illustrate numerical results which indicate circumstances for which optimal augmentation strategies depend upon the order of events.

A system of ordinary differential equations describes the population dynamics of a rabies epidemic in raccoons. The model accounts for the dynamics of a vaccine, including loss of vaccine due to animal consumption and loss from factors other than racoon uptake. A control method to reduce the spread of disease is introduced through temporal distribution of vaccine packets. This work incorporates the effect of the seasonal birth pulse in the racoon population and the attendant increase in new-borns which are susceptible to the diseases, analysing the impact of the timing and length of this pulse on the optimal distribution of vaccine packets. The optimization criterion is to minimize the number of infected raccoons while minimizing the cost of distributing the vaccine. Using an optimal control setting, numerical results illustrate strategies for distributing the vaccine depending on the timing of the infection outbreak with respect to the birth pulse.

Savanna models that are based on recurrent disturbances such as fire result in nonequilibrium savannas, but these models rarely incorporate vegetation feedbacks on fire frequency or include more than two states (grasses and trees). We develop a disturbance model that includes vegetation-fire feedbacks, using a system of differential equations to represent three main components of savannas: grasses, fire-tolerant savanna trees, and fire-intolerant forest trees. We investigate the stability of savannas in the presence of positive feedbacks of fire frequency with (1) grasses, (2) savanna trees, and (3) grasses and savanna trees together while also allowing for negative feedbacks of forest trees on fire frequency. We find that positive feedbacks between fire frequency and savanna trees, alone or together with grasses, can stabilize savannas, blocking the conversion of savannas to forests. Negative feedbacks of forest trees on fire frequency shift the range of parameter space that supports savannas, but they do not generally alter our results. We propose that pyrogenic trees that modify characteristics of fire regimes are ecosystem engineers that facilitate the persistence of savannas, generating both threshold fire frequencies with rapid changes in community composition when these thresholds are crossed and hystereses with bistable community states.

Species augmentation is a method of reducing species loss via augmenting declining or threatened populations with individuals from captive-bred or stable, wild populations. In this paper, we develop a differential equations model and optimal control formulation for a continuous time augmentation of a general declining population. We find a characterization for the optimal control and show numerical results for scenarios of different illustrative parameter sets. The numerical results provide considerably more detail about the exact dynamics of optimal augmentation than can be readily intuited. The work and results presented in this paper are a first step toward building a general theory of population augmentation, which accounts for the complexities inherent in many conservation biology applications.

We consider an SIR metapopulation model for the spread of rabies in raccoons. This system of ordinary differential equations considers subpopulations connected by movement. Vaccine for raccoons is distributed through food baits. We apply optimal control theory to find the best timing for distribution of vaccine in each of the linked subpopulations across the landscape. This strategy is chosen to limit the disease optimally by making the number of infections as small as possible while accounting for the cost of vaccination.

To effectively manage large natural reserves, resource managers must prepare for future contingencies while balancing the often conflicting priorities of different stakeholders. To deal with these issues, managers routinely employ models to project the response of ecosystems to different scenarios that represent alternative management plans or environmental forecasts. Scenario analysis is often used to rank such alternatives to aid the decision making process. However, model projections are subject to uncertainty in assumptions about model structure, parameter values, environmental inputs, and subcomponent interactions. We introduce an approach for testing the robustness of model-based management decisions to the uncertainty inherent in complex ecological models and their inputs. We use relative assessment to quantify the relative impacts of uncertainty on scenario ranking. To illustrate our approach we consider uncertainty in parameter values and uncertainty in input data, with specific examples drawn from the Florida Everglades restoration project. Our examples focus on two alternative 30-year hydrologic management plans that were ranked according to their overall impacts on wildlife habitat potential. We tested the assumption that varying the parameter settings and inputs of habitat index models does not change the rank order of the hydrologic plans. We compared the average projected index of habitat potential for four endemic species and two wading-bird guilds to rank the plans, accounting for variations in parameter settings and water level inputs associated with hypothetical future climates. Indices of habitat potential were based on projections from spatially explicit models that are closely tied to hydrology. For the American alligator, the rank order of the hydrologic plans was unaffected by substantial variation in model parameters. By contrast, simulated major shifts in water levels led to reversals in the ranks of the hydrologic plans in 24.1-30.6% of the projections for the wading bird guilds and several individual species. By exposing the differential effects of uncertainty, relative assessment can help resource managers assess the robustness of scenario choice in model-based policy decisions.

An epidemic model for rabies in raccoons is formulated with discrete time and spatial features. The goal is to analyze the strategies for optimal distribution of vaccine baits to minimize the spread of the disease and the cost of implementing the control. Discrete optimal control techniques are used to derive the optimality system, which is then solved numerically to illustrate various scenarios.

Invasive plant populations typically consist of a large (main) focus and several smaller outlier populations. Management of the spread of invasives requires repeated control measures, constrained by limited funding and effort. Posing this as a control problem, we investigate whether it is best to apply control to the main focus, the outlier populations, or some combination of these. We first formulate and solve a discrete-time optimal control problem to determine where control is best applied over a finite time horizon. However, if limited funds are available for control, this optimal solution may not be feasible. In this case, we add an additional constraint to account for the fixed budget and solve the new optimality system. Our results have a variety of practical implications for invasive species management.

Recent increases in reported outbreaks of tick-borne diseases have led to increased interest in understanding and controlling epidemics involving these transmission vectors. Mathematical disease models typically assume constant population size and spatial homogeneity. For tick-borne diseases, these assumptions are not always valid. The disease model presented here incorporates non-constant population sizes and spatial heterogeneity utilizing a system of differential equations that may be applied to a variety of spatial patches. We present analytical results for the one patch version and find parameter restrictions under which the populations and infected densities reach equilibrium. We then numerically explore disease dynamics when parameters are allowed to vary spatially and temporally and consider the effectiveness of various tick-control strategies.

Recent empirical studies have found evidence of increased biomass production ('overyielding') in species mixtures relative to monoculture, but the interpretation of these results remains controversial, in part, because of the lack of a theoretical expectation. Here, we examined the expected frequency and stability of overyielding species mixtures using Lotka-Volterra models of species dynamics in two- and four-species systems in conjunction with community, population, and specific rate of biomass production (SRP) definitions of overyielding. Overyielding plant mixtures represented > 55% of potential species assemblages under community definitions and approximately 100% of species were either overyielding or underyielding under the population definition. Our species simulations approached their equilibria in 1-2 yr, supporting the relevancy of an equilibrial analysis. The range of parameter space that we explored produced realistic values of plot biomass, supporting their biological relevance. We show that overyielding is expected to be common under community definitions and population definitions. Overyielding, under community or population definitions, does not imply an actual increase in the specific rate of biomass production. In addition, assemblages of overyielding and underyielding species under all three definitions can be stable over time with underyielding species persisting in the presence of overyielding species.

This report summarizes the statistical analyses of the International Board of Lactation Consultant Examiners 1999 examination for certification as an International Board Certified Lactation Consultant. The summary includes information regarding exam translations and recertification rates.

The national certification examination in nurse-midwifery/midwifery was adapted to the Puerto-Rican Spanish language. Specific attention was paid to creating a version of the examination that was both culturally and linguistically relevant, while remaining appropriately representative of national standards of practice. The procedures used in translation and cultural adaptation are described. The process used in review of the examination followed usual and customary practice. This included consideration of item critiques received from candidates (qualitative data) and the computation of standard measures of item performance, including item difficulty indices and the standard error of measurement (quantitative data). Additional analyses conducted for this specific purpose included the calculation of an index of differential item performance between both language versions. All measures of assessment indicated that the adapted language version was of high quality and psychometrically equivalent to the English language version, which was the comparison standard.

It is often impossible to validate cut scores set using judged item review methods due to the fact that many high stakes testing programs attempt to limit the number of common items across consecutively administered forms. However, over time, with a stable item pool, secondary links through other test administrations allow the use of common item equating to test the stability of the judged cut scores. In this study five forms of a basic science examination administered over a three year period in a national board testing program were analyzed to determine the stability of judged cut scores. The stability was determined by comparison of the judged cut scores with the equated cut scores derived by the Rasch common item equating technique. The results indicate cut scores derived from the modified Nedelsky procedure were within equating error of the Rasch equated cut scores over five administrations.

The intracellular polymerization of deoxyhemoglobin S (HbS) into helical fibers is the primary pathological event which gives rise to sickle cell disease. The structure of these fibers has previously been studied by electron microscopy of negatively stained specimens. We are extending these studies with unstained frozen-hydrated HbS fibers (cryo-EM), which afford better visualization of the internal details of the fiber structure than can be achieved by negative staining, but have lower signal-to-noise ratio images. The pitch of the HbS fiber structure varies locally along any given particle. Because rotation about the particle axis thus is partially decoupled from translation along the axis, the pitch and angular rotation of a fiber unit cell cannot be inferred by symmetry (as is the case with constant pitch helices). Image analysis procedures are presented which are capable of explicitly identifying the pitch and angular rotation of individual HbS fiber unit cells having low signal-to-noise ratios. Fiber images are divided into segments one unit cell long (63 A) which are analyzed in two steps. First each unit cell is aligned with constant pitch electron density reference models by cross-correlation. Correlation coefficients are then used to determine angular rotation and pitch. This procedure was tested, and found to be robust, using model images corrupted to simulate experimental problems normally encountered in the analysis of cryo-electron micrographs. The effects of limited resolution, low signal-to-noise ratio, scaling errors, and rotational and axial misalignment are described.