We give a complete description of Rees quotients of free inverse semigroups given by positive relators that satisfy nontrivial identities, including identities in signature with involution. They are finitely presented in the class of all inverse semigroups. Those that satisfy a nontrivial semigroup identity have polynomial growth and can be given by an irredundant presentation with at most four relators. Those that satisfy a nontrivial identity in signature with involution, but which do not satisfy a nontrivial semigroup identity, have exponential growth and fall within two infinite families of finite presentations with two generators. The first family involves an unbounded number of relators and the other involves presentations with at most four relators of unbounded length. We give a new sufficient condition for which a finite set X of reduced words over an alphabet $A\cup A^{-1}$ freely generates a free inverse subsemigroup of $FI_A$ and use it in our proofs.

Understanding the determinants of malnutrition is pivotal for public health interventions. This study aimed to identify socio-economic, demographic, dietary and maternal determinants of wasting and overweight among Brazilian children between 6 and 59 months. Data from the Brazilian National Survey on Child Nutrition were analysed (n 11 789). Children’s weight-for-height Z-scores were calculated according to the WHO growth standard and classified as wasting (Z < −2), normal weight (–2 ≤ Z ≤ 1), overweight risk (1 < Z ≤ 2) and overweight (Z > 2). Socio-economic, demographic, dietary and maternal covariables were considered. Adjusted multinomial logistic regression (OR and 95 % CI) was employed. The prevalence of overweight and wasting was 9·5 and 2·6 %, respectively. In the adjusted model, younger age (6–23 months: OR: 1·7; 95 % CI: 1·3, 2·2), consumption of ≥ 5 ultra-processed food groups (OR: 1·8; 95 % CI: 1·1, 3·1), maternal underweight (OR: 0·4; 95 % CI: 0·2, 0·9), overweight (OR: 1·5; 95 % CI: 1·2, 1·9) and mild food insecurity (OR: 0·8; 95 % CI: 0·6, 1·0) were associated with child overweight. The Brazilian Northeast (OR: 4·9; 95 % CI: 2·1, 11·3), Southeast (OR: 7·1; 95 % CI: 3·0, 16·6), South (OR: 4·7; 95 % CI: 1·8, 12·1), Midwest regions (OR: 2·7; 95 % CI: 1·2, 6·2) and maternal underweight (OR: 5·4; 95 % CI: 2·7, 10·7) were associated with wasting. Overweight in Brazil is prevalent among children between 6 and 59 months, while wasting is not a major public health problem. The main determinants of these Brazilian children’s nutritional status were age, ultra-processed food consumption and maternal nutritional status.

In institutional design, public policy and for society as a whole, securing freedom of choice for individuals is important. But how much choice should we aim for? Various theorists argue that above some level more choice improves neither wellbeing nor autonomy. Worse still, psychology research seems to suggest that too much choice even makes us worse off. Such reasons suggest the Sufficiency View: increasing choice is only important up to some sufficiency level, a level that is not too far from the level enjoyed by well-off citizens in rich liberal countries today. I argue that we should reject the Sufficiency View and accept Liberal Optimism instead: expanding freedom of choice should remain an important priority even far beyond levels enjoyed in rich liberal countries today. I argue that none of the arguments given for the Sufficiency View work. Neither psychological evidence nor any broader social trends support it. If anything, they support Liberal Optimism instead. I also show why further increases are possible and desirable, and sketch some implications for debates around immigration, economic growth, markets and the value of community.

A common assessment research design is the single-group pre-test/post-test design in which examinees are administered an assessment before instruction and then another assessment after instruction. In this type of study, the primary objective is to measure growth in examinees, individually and collectively. In an item response theory (IRT) framework, longitudinal IRT models can be used to assess growth in examinee ability over time. In a diagnostic classification model (DCM) framework, assessing growth translates to measuring changes in attribute mastery status over time, thereby providing a categorical, criterion-referenced interpretation of growth. This study introduces the Transition Diagnostic Classification Model (TDCM), which combines latent transition analysis with the log-linear cognitive diagnosis model to provide methodology for analyzing growth in a general DCM framework. Simulation study results indicate that the proposed model is flexible, provides accurate and reliable classifications, and is quite robust to violations to measurement invariance over time. The TDCM is used to analyze pre-test/post-test data from a diagnostic mathematics assessment.

Nitrogen (N) is the most significant nutrient affecting crop growth and development for all types of crops, except legumes. The goal of this study was to optimize the N level for cotton grown in a semi-arid environment to enhance growth and development, determine N status, and increase seed cotton yield and biomass. Two independent field experiments each three years in duration were conducted, from 2007 to 2009 (Exp.-I) and 2018 to 2020 (Exp.-II). Experiments were laid out in a randomized complete block design with three replicates. The N treatments in Exp.-I were comprised of 0, 40, 80, 120, 160, 200 and 240 kg N/ha, while treatments in Exp.-II were comprised of 0, 70, 140, 210 and 280 kg N/ha. A wide range of data sets for cotton traits were recorded, including canopy height, leaf area index, the N status of the leaf and stem, seed cotton yield and time-series biomass data. The higher N rates 240 and 280 kg N/ha performed better for all these traits. However, the highest leaf N contents were recorded for 210 kg N/ha. Based on these results, it is suggested that under semi-arid conditions, slightly higher rates than optimum or recommended N rates could be applied as a strategy by cotton growers for a higher seed cotton yield. The findings of this study may also increase profitability in other cotton-growing areas that have similar weather conditions.

Data show that an increase in the Gini coefficient is associated with a falling bottom $p_{B}$% income share and an increasing top $p_{T}$ % income share where, for example $p_{B}$ = 40 and $p_{T}$ = 1. This relationship, which we call the $X$ inequality relationship, is pervasive in the sense that it is observed in many countries, including the US, the UK, France and others. The purpose of this paper is (i) to construct a Schumpeterian growth model to explain the relationship, and (ii) to identify/quantify factors behind it via calibration of the US economy. Our model gives rise to a double-Pareto distribution of income as a result of entrant and incumbent innovations. Its advantage is that it allows us to develop iso-Gini loci and iso-income share schedules in a tractable way. Using a double-Pareto distribution as an approximation of an underlying income distribution, calibration analysis reveals that a declining business dynamism and fiscal policy changes in the past decades played a significant role in generating the $X$ inequality relationship in the US.

In this paper, we construct an elaborate general equilibrium model with a continuum of production fragments for an intermediate good, then incorporate it in a growth model to address the effects of global production fragmentation, vertical specialization, and trade on growth and inequality for a small developing country. Among other things, we show that a small developing economy grows faster than the rest of the world as a result of global fragmentation and trade in intermediates if it is skilled-labor scarce. We further address the effects of such a trade opening on wage inequality.

Politics in environmental education is conspicuous by its absence. This article is a plea to make politics–the study of who gets what, when, and how–central to our field and the keystone of a better way forward.

Early nutritional and growth experiences can impact development, metabolic function, and reproductive outcomes in adulthood, influencing health trajectories in the next generation. The insulin-like growth factor (IGF) axis regulates growth, metabolism, and energetic investment, but whether it plays a role in the pathway linking maternal experience with offspring prenatal development is unclear. To test this, we investigated patterns of maternal developmental weight gain (a proxy of early nutrition), young adult energy stores, age, and parity as predictors of biomarkers of the pregnancy IGF axis (n = 36) using data from the Cebu Longitudinal Health and Nutrition Survey in Metro Cebu, Philippines. We analyzed maternal conditional weight measures at 2, 8, and 22 years of age and leptin at age 22 (a marker of body fat/energy stores) in relation to free IGF-1 and IGFBP-3 in mid/late pregnancy (mean age = 27). Maternal IGF axis measures were also assessed as predictors of offspring fetal growth. Maternal age, parity, and age 22 leptin were associated with pregnancy free IGF-1, offspring birth weight, and offspring skinfold thickness. We find that free IGF-1 levels in pregnancy are more closely related to nutritional status in early adulthood than to preadult developmental nutrition and demonstrate significant effects of young adult leptin on offspring fetal fat mass deposition. We suggest that the previously documented finding that maternal developmental nutrition predicts offspring birth size likely operates through pathways other than the maternal IGF axis, which reflects more recent energy status.

The resurgence of industrial policy is reshaping the global political economy and creating emergent formations that could help create green states. Such green states can seed a world after growth. Growth is often taken for granted as a natural purpose of states and an appropriate basis of public policy. However, it has a recent political-economic and cosmological history. This suggests that an age after growth is not only possible but likely. In the current conjuncture of crises and challenges, industrial strategies that bring together environmental, social justice, and pro-growth coalitions offer the best chance to meet climate goals and improve the prospects for inclusive prosperity globally. In addition, there is evidence that industrial policy is providing a platform to build active states, rebalance state–business relations, forge new systems of calculation, and gather cosmological resources for new action.

The dual language development of dual language immersion (DLI) students, although often examined at the domain level (e.g., listening or reading), remains understudied for more specific skills (e.g., word, sentence, or discourse). This study examines the eleven-month progression of oral language skills in a picture description task in two languages (French and English) for early-elementary (Transitional Kindergarten through first grade) DLI students (N = 42). Using Bayesian methods, which estimate parameters using both the data and prior information, we describe French and English growth patterns as measured by learning progressions whose focus is on language features at the word, sentence, and discourse levels. For French oral language, we found evidence of meaningful positive linear growth for all language features, whereas for English oral language, meaningful linear positive growth was only detected for sophistication of topic vocabulary. Overall, coming from a French-speaking household was associated with steeper French oral language trajectories, but coming from an English-only household did not specifically impact English oral language trajectories. In both languages, grade level influenced the trajectories of some—but not all—features. We conclude with theoretical and practical implications, advocating for a language progression approach in instruction and research on bilingualism.