Two-class System Research Articles

Stability analysis of a two-class system with constant retrial rate and unreliable server

Stability analysis of a two-class system with constant retrial rate and unreliable server

Second-Class Citizen in the Heliophysics Community

The study of solar energetic particles (SEPs) is an important area of solar research and space weather. An SEP event extends over large regions of the heliosphere, involves energy ranges varying by decades, and evolves over various time and spatial scales and with ion composition, but with SEP observations limited to in situ detections on a few spacecraft for any given event, we are unable to observe these properties synoptically. Solar studies in general are the beneficiaries of imaging and remote sensing observations over practically all wavelengths and timescales from ground and space based detectors that drive increasingly highly sophisticated models. I see this divide as creating a two-class system for researchers, with us SEP researchers as second class members. Following a brief review of my experience with solar imagery and failed ideas on remote imaging of SEP events, I review two remarkable developments that give hope for some new SEP imaging technique. Finally, I discuss two poorly understood questions of impulsive and gradual SEP events that I think can be feasibly approached with current modeling techniques.

Remote Sensing for Palmer Amaranth (Amaranthus palmeri S. Wats.) Detection in Soybean (Glycine max (L.) Merr.)

Field studies were conducted in 2016 and 2017 to determine if multispectral imagery collected from an unmanned aerial vehicle (UAV) equipped with a five-band sensor could successfully identify Palmer amaranth (Amaranthus palmeri) infestations of various densities growing among soybeans (Glycine max [L.] Merr.). The multispectral sensor captures imagery from five wavebands: 475 (blue), 560 (green), 668 (red), 840 (near infrared [NIR]), and 717 nm (red-edge). Image analysis was performed to examine the spectral properties of discrete Palmer amaranth and soybean plants at various weed densities using these wavebands. Additionally, imagery was subjected to supervised classification to evaluate the usefulness of classification as a tool to differentiate the two species in a field setting. Date was a significant factor influencing the spectral reflectance values of the Palmer amaranth densities. The effects of altitude on reflectance were less clear and were dependent on band and density being evaluated. The near infrared (NIR) waveband offered the best resolution in separating Palmer amaranth densities. Spectral separability in the other wavebands was less defined, although low weed densities were consistently able to be discriminated from high densities. Palmer amaranth and soybean were found to be spectrally distinct regardless of imaging date, weed density, or waveband. Soybean exhibited overall lower reflectance intensity than Palmer amaranth across all wavebands. The reflectance of both species within blue, green, red, and red-edge wavebands declined as the season progressed, while reflectance in NIR increased. Near infrared and red-edge wavebands were shown to be the most useful for species discrimination and maintained their utility at most weed densities. Palmer amaranth weed densities were found to be spectrally distinct from one another in all wavebands, with greatest distinction when using the red, NIR and red-edge wavebands. Supervised classification in a two-class system was consistently able to discriminate between Palmer amaranth and soybean with at least 80% overall accuracy. The incorporation of a weed density component into these classifications introduced an error of 65% or greater into these classifications. Reducing the number of classes in a supervised classification system could improve the accuracy of discriminating between Palmer amaranth and soybean.

Automated detection of chronic kidney disease using image fusion and graph embedding techniques with ultrasound images

Chronic Kidney disease (CKD) is a progressive disease affecting more than twenty million individuals in the United States. Disease progression is often characterized by complications such as cardiovascular diseases, anemia, hyperlipidemia and metabolic bone diseases etc., Based on estimated GFR values, the disease is categorized in 5 stages which significantly influence patient outcome. Cardiovascular ultrasound (US) (echocardiography) imagery demonstrate significant hemodynamic alterations that are secondary to CKD in the form of volume/ pressure overload. As the CKD pathology directly impacts cardiovascular disease, the US imaging shows structural and hemodynamic adaptation. Hence, the development of a computer-aided diagnosis (CAD) model to predict CKD would be desirable, and can potentially improve treatment. Several prior studies have utilized kidney features for quantitative analysis. In this paper, acquisition of the four-chamber heart US image is employed to predict CKD stage. The method combines image and feature fusion techniques under a graph embedding framework to characterize heart chamber properties. Moreover, a support vector machine is incorporated to classify heart US images. The proposed method achieved 100 % accuracy for a two-class system, and 99.09 % accuracy for a multi-class categorization scenario. Hence, our proposed CAD tool is deployable in both clinic and hospital settings for computer-aided screening of CKD.

Ultraviolet radiation transmission of soft disposable contact lenses and ISO 18369: claims and compliance

ABSTRACT Clinical relevance This study was carried out to provide advice to eye care practitioners on those soft disposable contact lenses that comply with the Class 1 or Class 2 requirements of the international standard ISO 18369 for ultraviolet radiation protection. Background This study was carried out to provide advice to eye care practitioners on those soft disposable contact lenses that comply with the Class 1 or Class 2 requirements of the international standard ISO 18369 for ultraviolet radiation (UVR) protection and to validate any claims made. It is intended to be used when a patient needs or requests UVR protection. A revised ISO 18369-3 was published in 2017. There is no Australian adoption nor equivalent. Methods The direct spectral transmittance of three specimens of each of the twenty soft disposable contact lens types available in Australia in 2018 was measured in saline in a quartz cuvette with a dual beam spectrophotometer from 200-780 nm. Transmittance values for each material were averaged and scaled according to a single measurement of its transmittance in the visible spectrum (380-780 nm). Based on the ISO 18369-3:2017 criteria, lens materials were denoted as Class 1, Class 2 or non-UVR protectors. This classification was compared with any claim made by the manufacturer. Results All claims of the manufacturers for Class 1 or Class 2 were valid. There were no examples of any missed opportunity to make a claim. Some claims were so general as to be untestable. Some numerical claims appeared to hide that only a Class 2 claim could be made. Conclusions Claims of Class 1 or Class 2 were found to be appropriate. There were no missed opportunities to claim. UV protection claims that were not in the ISO 18369-3 format may be taken as Class 2 compliance but not Class 1 compliance. A two-class system of UV protectors and non-UV protectors may serve practitioners and their patients better.

Does Two-Class Training Extract Real Features? A COVID-19 Case Study

Diagnosis aid systems that use image analysis are currently very useful due to the large workload of health professionals involved in making diagnoses. In recent years, Convolutional Neural Networks (CNNs) have been used to help in these tasks. For this reason, multiple studies that analyze the detection precision for several diseases have been developed. However, many of these works distinguish between only two classes: healthy and with a specific disease. Based on this premise, in this work, we try to answer the questions: When training an image classification system with only two classes (healthy and sick), does this system extract the specific features of this disease, or does it only obtain the features that differentiate it from a healthy patient? Trying to answer these questions, we analyze the particular case of COVID-19 detection. Many works that classify this disease using X-ray images have been published; some of them use two classes (with and without COVID-19), while others include more classes (pneumonia, SARS, influenza, etc.). In this work, we carry out several classification studies with two classes, using test images that do not belong to those classes, in order to try to answer the previous questions. The first studies indicate problems in these two-class systems when using a third class as a test, being classified inconsistently. Deeper studies show that deep learning systems trained with two classes do not correctly extract the characteristics of pathologies, but rather differentiate the classes based on the physical characteristics of the images. After the discussion, we conclude that these two-class trained deep learning systems are not valid if there are other diseases that cause similar symptoms.

РАЗВИТИЕ СИСТЕМЫ ЗАЩИТЫ ОТ НЕДРУЖЕСТВЕННЫХ СДЕЛОК СЛИЯНИЯ И ПОГЛОЩЕНИЯ

The effective development of the economy depends on the level of competition. The development of a system of protection against hostile mergers and acquisitions contributes to the creation of a highly competitive environment, forms more comfortable conditions for business. In this study, the author aims to develop this protection system through the use of a two-class system of a company’s equity capital formation. At present, in the Russian Federation, the two-class system of a company’s equity capital formation using multi-voting shares has been little studied. This allows judging about the theoretical significance of the study, since the obtained results develop the theory and instruments of financial management. The author substantiates the low interest of business angels and venture investors in protecting a young company from mergers and acquisitions, since the latter are one of the main ways for an investor to exit a young business. The author reveals that, for the first time, the element of a company’s equity capital in the form of multi-voting shares acts as an instrument of protection against mergers and acquisitions; this element does not create additional risks for founders to lose control of their business by attracting additional financing of equity capital. In this regard, the author proposes to use multivoting shares held by founders of the business as an additional instrument of protection against hostile mergers and acquisitions of young companies.

Dynamic pricing in a two-class queueing system with arrival and service rate control

Abstract Dynamic pricing in a two-class queueing system with adjustable arrival and service rates is considered. We initially take adjustable rates into account to maximize the long-run average social welfare and further establish matched dynamic prices. For the rate-setting problem, we apply sensitivity-based optimization theory and an iterative algorithm to investigate the optimal arrival and service rates of the two classes of customers. Next, we apply the results obtained from the rate-setting problem to find the expected delay time using a recursive algorithm and explicitly determine formulae for the optimal prices of the two classes of customers. Finally, we carry out numerical experiments to illustrate our findings and the performance between two classes of customers at different levels of the holding cost. It appears that for a low holding cost, the optimal prices for the two classes of customers are monotonically increasing in the number of customers regardless of the class, but for a high holding cost, the optimal prices for the customers who have low waiting cost may drop when the number of the other class rises.

The Evidence Base in Exercise Knowledge of Pregnant Women: A Latent Class Analysis

Exercise has many benefits for women with uncomplicated pregnancies. However, poor exercise knowledge may contribute to problems or barriers that reduce a woman's level of exercise after becoming pregnant. This study was performed to identify pregnancy exercise knowledge among pregnant women using latent class analysis and to examine the relationship between pregnancy exercise knowledge patterns and sociodemographic characteristics. A descriptive, cross-sectional approach was used in this study. Participants were recruited from the prenatal outpatient departments of two hospitals and a certified prenatal center in Taipei, Taiwan. A total of 618 participants completed a pregnancy exercise knowledge test. The data were analyzed using WINMIRA and SPSS 20.0 software. Two latent classes were identified based on exercise knowledge among pregnant women. The Accurate Knowledge group (n=543, 87.9%), which had a higher latent trait for exercise knowledge (M=1.31, SD=0.94), was larger than the Limited Knowledge group (n=75, 12.1%), which had a lower latent trait (M = -0.22, SD=1.14). The principles of exercise for pregnant women, particularly the appropriate intensity and duration, may be difficult items for women in the Limited Knowledge group to understand. Women with Limited Knowledge had significantly lower education levels and greater rates of unemployment, multiparity, and miscarriage than women in the Accurate Knowledge group. A two-class system for interpreting exercise knowledge among pregnant women is statistically supported. We believe that this study has evidence-based potential to help healthcare providers improve pregnant women's exercise knowledge as part of routine prenatal care to promote exercise.

Blinde Menschen unter dem NS-Regime in der „Ostmark“ – Eine Problematisierung

This article presents various aspects of my doctoral thesis “Zwischen Integration,Kooperation und Vernichtung – Blinde Menschen unter dem NS-Regime in der ,Ostmark“. Thisdoctoral thesis presents various aspects of the circumstances of blind people’s lives inthe “Ostmark” under the Nazi regime, such as the economic and social situation.Legal, medical and gender aspects are also taken into consideration. The aim was togain detailed insight into the living conditions of blind people of that time. Under theNazi regime blind people were separated into three main groups: the civilian blind, thewar blinded and blind people of Jewish origin. Even since the time of the First WorldWar there had been a two-class system of the civilian blind and blinded ex-serviceman.Due to the Nazi regime’s anti-Jewish policy, the civilian blind and blinded veterans ofJewish origin were persecuted. In addition to that there was a strong segregationamong blind people under the Nazi regime. This article deals with some mainproblems concerning the research about the life of blind people.

“Current-IPM-Fit”: a new proposal for enhanced efficacy labelling of plant protection products

In the European Union, plant protection products (PPP) undergo an intensive evaluation procedure including toxicology, ecotoxicology, fate and residues for approval of the active substance. On product level, additionally the efficacy against pests and adverse effects on pest antagonists and on the cultivated plant itself, i.e. phytotoxicity, are evaluated. Currently, a development towards a two-class classification system takes place in which PPP with low impact in risk categories (“low-risk products”) can be approved with reduced efficacy requirements. Other parallel registration pathways that include limited or no evaluation of efficacy exist for basic substances and minor-use registrations. Nevertheless, registration of a product does not give information of its efficacy level in many European countries. The situation for the effects of PPP on antagonists of practical relevance in growing systems is similar: up to date, there is a lack of information on relevant antagonists because the evaluation and registration process include mostly information about the standard indicator organisms Typhlodromus pyri and Aphidius rhopalosiphi. As a consequence, information on efficacy levels on target pests and side effect levels on relevant pest antagonists are to date mainly provided by private companies, mainly PPP-producing companies and beneficial organisms-producing companies. Unfortunately, it is not transparent on which observations and experiments these ratings base on, i.e. these ratings do not undergo an independent evaluation process. But verified knowledge on efficacy and side effects on relevant antagonists are vital for successful IPM strategies. Both, efficacy and side effects on pest antagonists must be considered together in order to foresee the outcome of a PPP application in an agricultural system. Therefore, the aim of this opinion paper is to propose a standardized European labelling system that displays efficacy levels and side effect levels on beneficial arthropods other than bees.

An Anomaly Detection Approach to Face Spoofing Detection: A New Formulation and Evaluation Protocol

Face spoofing detection is commonly formulated as a two-class recognition problem where relevant features of both positive (real access) and negative samples (spoofing attempts) are utilized to train the system. However, the diversity of spoofing attacks, any new means of spoofing attackers, may invent (previously unseen by the system) the problem of imaging sensor interoperability, and other environmental factors in addition to the small sample size make the problem quite challenging. Considering these observations, in this paper, a number of propositions in the evaluation scenario, problem formulation, and solving are presented. First of all, a new evaluation protocol to study the effect of occurrence of unseen attack types, where the train and test data are produced by different means, is proposed. The new evaluation protocol better reflects the realistic conditions in spoofing attempts where an attacker may come up with new means for spoofing. Inter-database and intra-database experiments are incorporated into the evaluation scheme to account for the sensor interoperability problem. Second, a new and more realistic formulation of the spoofing detection problem based on the anomaly detection concept is proposed where the training data come from the positive class only. The test data, of course, may come from the positive or negative class. Such a one-class formulation circumvents the need for the availability of negative training samples, which, in an in deal case, should be the representative of all possible spoofing types. Finally, a thorough evaluation and comparison of 20 different one-class and two-class systems on the video sequences of three widely employed databases is performed to investigate the merits of the one-class anomaly detection approaches compared with the common two-class formulations. It is demonstrated that the anomaly-based formulation is not inferior as compared with the conventional two-class approach.

A near-infrared spectroscopy routine for unambiguous identification of cryptic ant species.

Species identification—of importance for most biological disciplines—is not always straightforward as cryptic species hamper traditional identification. Fibre-optic near-infrared spectroscopy (NIRS) is a rapid and inexpensive method of use in various applications, including the identification of species. Despite its efficiency, NIRS has never been tested on a group of more than two cryptic species, and a working routine is still missing. Hence, we tested if the four morphologically highly similar, but genetically distinct ant species Tetramorium alpestre, T. caespitum, T. impurum, and T. sp. B, all four co-occurring above 1,300 m above sea level in the Alps, can be identified unambiguously using NIRS. Furthermore, we evaluated which of our implementations of the three analysis approaches, partial least squares regression (PLS), artificial neural networks (ANN), and random forests (RF), is most efficient in species identification with our data set. We opted for a 100% classification certainty, i.e., a residual risk of misidentification of zero within the available data, at the cost of excluding specimens from identification. Additionally, we examined which strategy among our implementations, one-vs-all, i.e., one species compared with the pooled set of the remaining species, or binary-decision strategies, worked best with our data to reduce a multi-class system to a two-class system, as is necessary for PLS. Our NIRS identification routine, based on a 100% identification certainty, was successful with up to 66.7% of unambiguously identified specimens of a species. In detail, PLS scored best over all species (36.7% of specimens), while RF was much less effective (10.0%) and ANN failed completely (0.0%) with our data and our implementations of the analyses. Moreover, we showed that the one-vs-all strategy is the only acceptable option to reduce multi-class systems because of a minimum expenditure of time. We emphasise our classification routine using fibre-optic NIRS in combination with PLS and the one-vs-all strategy as a highly efficient pre-screening identification method for cryptic ant species and possibly beyond.

Using textons to rank crystallization droplets by the likely presence of crystals.

The visual inspection of crystallization experiments is an important yet time-consuming and subjective step in X-ray crystallography. Previously published studies have focused on automatically classifying crystallization droplets into distinct but ultimately arbitrary experiment outcomes; here, a method is described that instead ranks droplets by their likelihood of containing crystals or microcrystals, thereby prioritizing for visual inspection those images that are most likely to contain useful information. The use of textons is introduced to describe crystallization droplets objectively, allowing them to be scored with the posterior probability of a random forest classifier trained against droplets manually annotated for the presence or absence of crystals or microcrystals. Unlike multi-class classification, this two-class system lends itself naturally to unidirectional ranking, which is most useful for assisting sequential viewing because images can be arranged simply by using these scores: this places droplets with probable crystalline behaviour early in the viewing order. Using this approach, the top ten wells included at least one human-annotated crystal or microcrystal for 94% of the plates in a data set of 196 plates imaged with a Minstrel HT system. The algorithm is robustly transferable to at least one other imaging system: when the parameters trained from Minstrel HT images are applied to a data set imaged by the Rock Imager system, human-annotated crystals ranked in the top ten wells for 90% of the plates. Because rearranging images is fundamental to the approach, a custom viewer was written to seamlessly support such ranked viewing, along with another important output of the algorithm, namely the shape of the curve of scores, which is itself a useful overview of the behaviour of the plate; additional features with known usefulness were adopted from existing viewers. Evidence is presented that such ranked viewing of images allows faster but more accurate evaluation of drops, in particular for the identification of microcrystals.

"Successful aging," gerontological theory and neoliberalism: a qualitative critique.

This article is a critique of the successful aging (SA) paradigm as described in the Rowe and Kahn book, Successful Aging (1998). The major point of this article is that two key ideas in the book may be understood as consonant with neoliberalism, a social perspective that came into international prominence at the same time the SA paradigm was initially promoted. These two key ideas are (a) the emphasis on individual social action applied to the nature of the aging experience and (b) the failure to provide a detailed policy agenda for the social and cultural change being promoted and, particularly, for older adults who may be left behind by the approach to change the book suggests. The article provides no evidence for a direct connection between SA and neoliberalism, but rather shows how similarities in their approaches to social change characterize both of them. In sum, the article shows (a) how the implicit social theory developed in the book, in a manner similar to neoliberalism, elevates the individual as the main source of any changes that must accompany the SA paradigm and (b) the focus on SA as individual action does not provide for those older adults who do not or will not age "successfully." This, we conclude, implicitly sets up a two-class system of older adults, which may not be an optimal means of addressing the needs of all older adults. The article also reviews a number of studies about SA and shows how these, too, may emphasize its similarities to neoliberalism and other issues that the SA paradigm does not adequately address.

How Do Cultural Classes Emerge from Assimilation and Distinction? An Extension of the Cucker-Smale Flocking Model

When cultural tastes are not neutral but hierarchically matched to social status, people assimilate themselves to higher status by consuming cultural goods while distinguishing themselves from lower status by developing new tastes. Extending the Cucker-Smale model for mutual influence among agents, we examine when and how many cultural classes emerge from continuous distributions of tastes and what conditions those classes satisfy, through the assimilation-distinction mechanism. We simulate the models with different initial distributions of tastes (uniform, normal, and chi-square), given various ranges of 2 parameters: (a) the strength and (b) the range of distinction relative to assimilation. Tastes are flocking and cultural classes emerge when the range of assimilation is much larger than that of distinction. The number of classes increases with the strength of distinction, whereas the distance between classes equals the range of distinction. Some properties of emergent classes are mathematically proved. First, in a two-class system, the stronger distinction, the larger the upper class. Second, in a three-class system, the middle class is necessarily larger than the lower class and likely larger than the upper class. Third, a 3-class system cannot emerge if distinction is weaker than assimilation. These properties are universal and do not depend on the initial distribution of cultural tastes. This independence predicts homogeneous cultural classes emerging across different social conditions. Also, the cultural middle class as the largest group may explain why subjective class consciousness is often higher than objective position. Unless assimilating efforts can reach an infinite range, there emerges a cultural outcast at the lowest end of the cultural hierarchy.

INTUITIONISTIC FUZZY REASONING FOR MULTIPLE TWO-CLASS CLASSIFIERS FUSION

Combining outputs of a pool of individual classifiers appropriately, as a hot research topic of pattern classification, can generate statistically significant increase in classification performances. During the last decades, several fusion algorithms were presented, but few of those focus on two-class classification which possesses wide application area such as sentiment classification, cancer differentiation and so on. Thus the main purpose of this paper is to develop a highly effective fusion algorithm, i.e. intuitionistic fuzzy reasoning fusion algorithm, to increase the performance of a multiple two-class classifiers system. The outputs of component classifiers are represented by a set of intuitionistic fuzzy values at first and the fusion process is interpreted as aggregation of intuitionistic fuzzy information. The proposed algorithm includes three versions using the intuitionistic fuzzy arithmetic average operator, intuitionistic fuzzy weighted average operator and induced intuitionistic fuzzy ordered weighted average aggregation operator, respectively. The proposed fusion algorithm can combine both evidences of the hypothesis that a test pattern belongs to a class and evidences of the hypothesis that the test pattern does not belong to the class at the same time. We compare the versions of our algorithm with four other fusion techniques on five open-access datasets. The proposed algorithm exhibits good predictive abilities, compared to the best individual classifiers and other comparable fusion techniques. Further, the experiments show some interesting results about measuring and weighting component classifiers.

Ritual among the Masses: Deconstructing Identity and Class in an Ancient Maya Neighborhood

AbstractEquating a single cultural group to a classificatory scheme has implications for not only how archaeologists develop the concept of cultural identity but how we investigate and theorize about internal social dynamics within that same society. For the ancient Maya, social organization remains largely understood as a two-class system—that of commoner and elite. While these categories reflect the extreme ends of known social strata, they inadequately characterize the reality of day-to-day interactions. This has led to tacit assumptions that commoners did not participate in or comprehend the political and social complexity of the world around them. This paper examines how occupants of a Late Classic Maya neighborhood employed ritual and public practices as a means of social differentiation. Excavations at the Northeast Group, part of the ancient Maya site of Chan, Belize, identified considerable diversity between households, suggesting that occupants shaped status and identity through the control and centralization of ritual. Understanding how people distinguished themselves within the context of a neighborhood provides direct evidence of class complexity, challenging traditional models of commoner behavior and more importantly the role they played in ancient Maya society as a whole.

The impact of aviation checkpoint queues on optimizing security screening effectiveness

Passenger screening at aviation security checkpoints is a critical component in protecting airports and aircraft from terrorist threats. Recent developments in screening device technology have increased the ability to detect these threats; however, the average amount of time it takes to screen a passenger still remains a concern. This paper models the queueing process for a multi-level airport checkpoint security system, where multiple security classes are formed through subsets of specialized screening devices. An optimal static assignment policy is obtained which minimizes the steady-state expected amount of time a passenger spends in the security system. Then, an optimal dynamic assignment policy is obtained through a transient analysis that balances the expected number of true alarms with the expected amount of time a passenger spends in the security system. Performance of a two-class system is compared to that of a selective security system containing primary and secondary levels of screening. The key contribution is that the resulting optimal assignment policies increase security and passenger throughput by efficiently and effectively utilizing available screening resources.

Inequality in health care utilization in Germany? Theoretical and empirical evidence for specialist consultation

In view of increasing concern about a two-class system in the German health care sector, this study investigates the relevance of health insurance schemes and other socioeconomic characteristics to the level of specialist health care provision. Referring to Ronald M. Andersen’s model of health care utilization and more content-based approaches, we implement a negative binomial hurdle regression to estimate the number of specialist visits within the last 12 months. Our data source is the German sample of the first wave of the Survey of Health, Ageing and Retirement in Europe (SHARE) in 2004. The results show that men’s number of specialist visits is markedly sensitive to predisposing and enabling factors, whereas women’s health care utilization depends less on such socioeconomic characteristics. With reference to previous findings concerning general practitioner consultation, the assumption of a bipolar health care system providing general practitioner care primarily to the statutory insured and specialist care to the privately insured is supported empirically as to men. Education, which is considered to be highly correlated with health lifestyles, has a positive effect on medical health care. Every additional year of education increases by about 10% the probability of men seeking specialist consultation. Furthermore, the results indicate an unfavorable situation for the self-employed concerning health care because of their specific employment situation and health insurance coverage. The research results suggest the existence of relevant differences in the amount of specialist consultation according to health insurance and other socioeconomic features. Further research could concentrate on the question of whether these inequalities in utilization levels indicate overprovision or underprovision of ambulant health care. Moreover, we recommend longitudinal research that is particularly suited to detangle age and cohort effects.