In 2023, the U.S. Office of Management and Budget (OMB) issued guidance documents that specified new procedures for assessing prospective government regulations (Circular A-4) and economic policies more generally (Circular A-94). These revisions to long-standing guidance were not minor updates but shifted policy analyses from an efficiency-oriented perspective to a redistributive approach. OMB broadened the guidelines for reporting distributional consequences of policies and also specified how policy impacts on different income groups should be weighted. The weights assume that the social welfare function is governed by the sum of identical individual utility functions, each of which exhibits a substantial rate of diminishing marginal utility of income. The resulting weights provide a premium for households below the median-income level and a considerable penalty for those at higher-income levels. Application of the weights to property losses creates potentially substantial inefficiencies. If based on current empirical evidence on the income elasticity of the value of a statistical life rather than assuming that there is a complete offset of the weights, application of the weights to mortality risk valuation would generate inequities in protection.

Labor historians, particularly in the United States, have given unique attention to the International Longshore and Warehouse Union (ILWU). Emerging out of a series of tumultuous strikes on the West Coast during the early Depression years, the ILWU won trend-setting employment contracts, survived Second Red Scare-era persecution despite keeping avowedly leftwing leadership, and maintained its presence on the docks even after containerization dramatically reshaped the longshore industry. This review examines multiple recent works on the ILWU, noting new interventions—both in ILWU history and labor history, more broadly. All three reviewed works offer invaluable insight for how contemporary unions can adapt to technological changes in the workplace, foster internal democracy, and build labor power while fighting for social justice. The review concludes by offering potential avenues for further scholarly research, particularly on the nature of leftwing unionism and labor-generated alternatives to deindustrialization and workforce displacement.

In this paper, we study the approximate minimization problem of weighted finite automata (WFAs): to compute the best possible approximation of a WFA given a bound on the number of states. By reformulating the problem in terms of Hankel matrices, we leverage classical results on the approximation of Hankel operators, namely the celebrated Adamyan-Arov-Krein (AAK) theory. We solve the optimal spectral-norm approximate minimization problem for irredundant WFAs with real weights, defined over a one-letter alphabet. We present a theoretical analysis based on AAK theory and bounds on the quality of the approximation in the spectral norm and $\ell ^2$ norm. Moreover, we provide a closed-form solution, and an algorithm, to compute the optimal approximation of a given size in polynomial time.

Classical approaches for flood prediction apply numerical methods for the solution of partial differential equations that capture the physics of inundation processes (e.g., the 2D Shallow Water equations). However, traditional inundation models are still unable to satisfy the requirements of many relevant applications, including early-warning systems, high-resolution (or large spatial domain) simulations, and robust inference over distributions of inputs (e.g., rainfall events). Machine learning (ML) approaches are a promising alternative to physics-based models due to their ability to efficiently capture correlations between relevant inputs and outputs in a data-driven fashion. In particular, once trained, ML models can be tested/deployed much more efficiently than classical approaches. Yet, few ML-based solutions for spatio-temporal flood prediction have been developed, and their reliability/accuracy is poorly understood. In this paper, we propose FloodGNN-GRU, a spatio-temporal flood prediction model that combines a graph neural network (GNN) and a gated recurrent unit (GRU) architecture. Compared to existing approaches, FloodGNN-GRU (i) employs a graph-based model (GNN); (ii) operates on both spatial and temporal dimensions; and (iii) processes the water flow velocities as vector features, instead of scalar features. We evaluate FloodGNN-GRU using a LISFLOOD-FP simulation of Hurricane Harvey (2017) in Houston, Texas. Our results, based on several metrics, show that FloodGNN-GRU outperforms several data-driven alternatives in terms of accuracy. Moreover, our approach can be trained 100x faster and tested 1000x faster than the time required to run a comparable simulation. These findings illustrate the potential of ML-based methods to efficiently emulate physics-based inundation models, especially for short-term predictions.

This article examines the complex phenomenon of self-harm, exploring its motivations, theoretical underpinnings and the intricate transference and countertransference reactions that arise in clinical settings. It aims to integrate psychiatric understanding with contemporary theories of the impact of trauma on both the body and the mind, to deepen the knowledge of self-harm and increase the effectiveness of treatment approaches. The article argues for a nuanced view of self-harm and emphasises the need for compassionate, well-informed care. By addressing the psychodynamics of self-harm, the article seeks to improve therapeutic outcomes and foster an empathetic and effective clinical response. Fictitious case studies are used to illustrate these concepts, demonstrating the critical role of early attachment experiences and the challenges faced by healthcare providers in management.

I formulate a compatibilism that is distinctively responsive to skeptical worries about the justification of punishment and other moral responsibility practices. I begin with an evolutionary story explaining why backward-looking reactive attitudes are “given” in human society. Cooperative society plausibly could not be sustained without such practices. The necessary accountability practices have complex internal standards. These internal standards may fully ground the appropriateness of reactive attitudes. Following a recent analogy, we can similarly hold that there are no external standards for what is funny; the norms of comedy are complex, but funny is funny. However, this is compatible with moral reasons to change the practices themselves, and therefore change what is fitting within them: in the first instance, a moralistic “that's not funny” is ill-fitting, but “that shouldn't be funny” can be apt. The analogous reformist position prescribes practices constituting the minimal responsibility norms necessary for cooperative society.

The plastic pollution crisis has resulted in the establishment of many voluntary plastic waste initiatives in Southeast Asia, where most of the plastic leakage occurs. This study aims to assess the sustainability of four types of voluntary, partly or fully externally funded plastic waste initiatives within Indonesia’s current waste management system and anticipate challenges that can arise in the future. The research used the qualitative approach of Strengths, Weaknesses, Opportunities and Threats and Internal and External Factors Analysis framework to evaluate the initiatives’ techno-economic, socio-cultural, legislative and environmental sustainability. The results showed that three out of four types of plastic waste initiatives were in the diversification quadrant, and one type was in the survival quadrant. The unfavoured position of the initiatives in the quadrant is mainly due to important regulatory gaps in Indonesia and the lack of a stable funding mechanism. The appropriate strategy for the voluntary plastic waste initiatives to be self-sustainable and a catalyst for sustainable national waste management is to exert pressure on the government to establish an institutionalised and legislated waste management system and endorse a mandatory implementation of the polluter pays principle. Otherwise, improving waste management systems in Indonesia at the macro level could be challenging to achieve.

The cable-driven parallel mechanism (CDPM) is known as an interesting application in industry to pick and place objects owing to its advantages such as large workspaces. In addition to the advantages of this mechanism, there are some challenges to improving performance by considering constraints in different components, such as the behavior of cables, shape, size of the end effector and base, and model of pulleys and actuators. Moreover, the impact of online geometry reconfiguration must be analyzed. This paper demonstrates the impact of these constraints on the performance of reconfigurable CDPM. The methodology is based on the systematic review and meta-analysis guidelines to report the results. The databases used to find the papers are extracted from Scopus and Google Scholar, using related keywords. As a result, the impact of physical constraints on system performance is discussed. A total of 90 and 37 articles are selected, respectively. After removing duplicates and unrelated papers, 88 studies that met the inclusion criteria are selected for review. Even when considering the physical constraints in modeling the mechanism, simplifications in designing a model for the reconfigurable CDPM generate errors. There is a gap in designing high-performance controllers to track desired trajectories while reconfiguring the geometry, and the satisfaction of physical constraints needs to be satisfied. In conclusion, this review presents several constraints in designing a controller to track desired trajectories and improve performance in future work. This paper presents an integrated controller architecture that includes physical constraints and predictive control.

We derive an asymptotic expansion for the critical percolation density of the random connection model as the dimension of the encapsulating space tends to infinity. We calculate rigorously the first expansion terms for the Gilbert disk model, the hyper-cubic model, the Gaussian connection kernel, and a coordinate-wise Cauchy kernel.

Understanding gender disparities in home-based self-employment (HBS) and their links to homeownership and socioeconomic factors is crucial for advancing sustainable development goals (SDGs) in Sub-Saharan Africa, especially Nigeria. This study uses data from the 2010/2011, 2012/13, 2015/16, and 2018/19 waves of the Nigerian General Household Survey (GHS). It employs random effect probit regression, the LASSO method for identifying predictors, and the Blinder–Oaxaca decomposition technique to analyse gender differences in nonlinear binary outcomes. The results show that female business owners are more likely to engage in HBS compared to males, highlighting the importance of gender equality (SDG 5) and decent work (SDG 8). While male entrepreneurs are mainly driven by profit, females prioritise balancing paid and unpaid work, reflecting motivations beyond profit within heterodox economics. Significant gender-differentiated impacts are observed in relation to monthly rent, post-secondary education, dwelling space, energy, and regional locations. Notably, the presence of children significantly increases female involvement in HBS, a trend not seen among males. Marriage also influences female participation, suggesting that marital circumstances and economic benefits play a role. These findings highlight the need for policies addressing gender-specific constraints, challenging traditional gender roles, and promoting inclusive human development within the SDG framework.

Research on the language acquisition of deaf individuals who are exposed to accessible linguistic input at a variety of ages has provided evidence for a sensitive period of first language acquisition. Recent studies have shown that deaf individuals who first learn language after early childhood, late first-language learners (LL1), do not comprehend reversible Subject-Verb-Object (SVO) sentences. The present study analyzed 478 signed productions elicited with pictures depicting simple events with one or two arguments by 28 signers. The argument order patterns of native signers converged with one another and the word order patterns of American Sign Language (ASL). By contrast, the ordering patterns of the LL1 signers did not converge with one another or with the patterns of the native signers. This indicates that early childhood is a period of heightened sensitivity to basic word order and may help explain why complex structures are difficult for LL1 signers to learn.