The present study investigated if/how individual differences in heritage language (HL) experience modulate gender agreement processing among Spanish heritage speakers (HSs). We reanalyzed the data from Luque and colleagues (2023), which reported an aggregate biphasic N400–P600. The present analysis revealed that sensitivity to morphological markedness was positively modulated by HL proficiency and exposure/use. Higher proficiency led to increased P600 across markedness conditions—the typical signature of L1-dominant processing—while increased Spanish exposure/use resulted in increased N400 for Default Errors—a signature attested only in HSs in this domain. Formal instruction led to increased N400 but reduced P600 for Feature Clash Errors. We interpret these results to suggest that the N400 reflects a morphophonological pattern-matching strategy with some HSs relying (more) on this mechanism as Spanish exposure and use increases. Markedness also modulated the relative engagement of pattern-matching (N400) versus automatic grammatical processing (P600), depending on the transparency/saliency of morphophonological patterns.

Contrary to longstanding opinion, it was Luther, not Calvin, who first interpreted Christ’s descent into hell as an event of suffering and feeling forsaken by God. Though Lutheran tradition afterward emphasised a victorious interpretation taken from Luther’s famous ‘Torgau sermon’, a more ambivalent legacy exists in his own writings. Sufficient attention is therefore warranted to view Luther as a forerunner to Calvin’s use of the cry of dereliction to interpret the descensus. Understanding this nuance can smooth the edges of a myopic age-old debate between the two traditions, since the two Reformers have more in common than not on the doctrine.

We examine the distributional impact of domestic carbon pricing in three Sub-Saharan African countries. We combine household expenditure surveys and sectoral carbon intensity data derived from a multi-regional input-output model for Ghana, Nigeria and Uganda. Our findings indicate that domestic carbon pricing is progressive in all three countries. This primarily results from higher budget allocations for direct energy consumption in wealthier households, especially concerning motor vehicles and electrical appliances. Disparities in welfare losses within income groups are primarily due to varying energy consumption patterns. Importantly, we identify low-income households as being disproportionately affected by carbon taxes. Lump-sum transfers could fully compensate most households in the bottom two income quintiles, significantly reducing poverty. Our comparative analysis emphasizes the importance of country-specific differences in energy expenditures and carbon intensities in shaping the distributional outcomes of carbon taxes.

The meta-inductive approach to induction justifies induction by proving its optimality. The argument for the optimality of induction proceeds in two steps. The first “a priori” step intends to show that meta-induction is optimal and the second “a posteriori” step intends to show that meta-induction selects object-induction in our world. I critically evaluate the second-step and raise two problems: the identification problem and the indetermination problem. In light of these problems, I assess the prospects of any meta-inductive approach to induction.

During the years 2005-2018, the US Public Health Service (PHS) deployed teams, known as Rapid Deployment Forces (RDF), as a component of disaster response. One component of the disaster response was for a PHS RDF to establish a Federal Medical Station and work with other federal and civilian partners to provide health care to individuals with chronic medical conditions that routinely required additional support for activities of daily living. These individuals were usually housed in private residences or residential facilities and were displaced by the disaster. The operational model was to gather the target population in a temporary facility, assess the needs of each individual and accompanying caretakers, provide health care and social support, and plan a discharge to either an intermediate facility or return to their original residence, if conditions became appropriate. RDF PHS-1 developed approaches for assessment, tracking, planning, resource utilization, and decision making that were field tested, refined them, and then validated their utility. The experience is shared here to inform other disaster responders who may encounter similar displaced populations and circumstances.

This article presents germanium telluride (GeTe)-based switches for radiofrequency (RF) applications, capable of reversible switching between their ON and OFF states through optical activation by irradiation. Unlike previous studies, the transition is induced by infrared laser pulses at a wavelength of λ = 915 nm, which is highly promising for future integration of laser sources and the proposal of fully integrated optical activation of phase change material (PCM) switches. This represents a novel approach compared to the existing literature, which primarily focuses on the ultra-violet spectrum, less suitable for on-chip optical integration. Our work also provides combined optical and thermal simulations to elucidate the challenges associated with actuating small PCM switches and demonstrates the effectiveness of PCMs at this wavelength. The study achieves bistable switching at high frequencies up to 40 GHz, with a figure of merit of 31.5 fs, despite the low GeTe conductivity of only 1.85·105 S/m. Additionally, significant advancements over the literature have been made by surpassing 30,000 cycles with optical actuation.

For organisations, change is becoming a necessity to adapt to the demands of an ever-shifting external environment. In such an environment, conflicting forces create frictions that organisations must address. This study explores the mechanisms through which organisations activate the path towards strategic agility. A single case study approach is used to develop a framework that traces the path to strategic agility in the context of paradoxical tensions. The work shows that strategic agility is the result of four action dimensions that involve values, decision-making processes, knowledge and data management, and of the interconnection of internal and external structures. Instead of eliminating tensions, strategic agility enables organisations to dynamically navigate them. Our work provides organisations with a useful framework for dealing with paradoxes in order to maintain performance in challenging contexts.

This paper shows how Hegel’s philosophy of psychiatry was established within the framework of the unitary psychosis (Einheitspsychose). This psychiatric position considered that there was only one single mental illness with several distinct species. Due to some editions of Hegel’s works, this interpretative framework is often omitted. However, in this paper it is considered to be the key interpretative framework for understanding Hegel’s psychic nosography and therapeutic approach.

Scholarship on minorities in the inter-war period have largely ignored the Flemish question. One obvious reason is that the Flemish accounted for a majority of Belgium’s population. This article, however, argues that the domestic and international historiography would benefit from considering the Flemish a minority, albeit a peculiar one. I suggest that the Flemish question embodies the contradictions of an age in which the nationality question ‘morphed into the minority question’ (as Holly Case has pointed out) without disappearing altogether. The article traces the evolution of different understandings of Flanders in the Belgo-Dutch-German transnational space and shows how such understandings challenge traditional conceptions of minorities, majorities, nationalities and kin states. The article further contributes to a broader shift in historiographies of nationalism and diversity in inter-war Europe by moving focus from East to West and considering minority questions as a pan-European phenomenon.

To assess the association between dietary consumption patterns of antioxidant and pro-oxidant nutrients with prostate cancer (PC) and its histological differentiation, we analyzed data from 394 histologically confirmed incident cases of PC and 793 age-matched population controls (± 5 years), residents of Mexico City. Cases were classified by Gleason score into well-, moderately-, and poorly differentiated categories. Dietary nutrient intake over the three years preceding diagnosis for cases and before the interview for controls was estimated using a semi-quantitative food frequency questionnaire. Using energy-adjusted residuals and a k-means approach, we identified three consumption patterns: 1) pro-oxidant (PRO), 2) moderate antioxidants/low pro-oxidants (MaLp), and 3) high antioxidants and pro-oxidants (HaHp). Associations were evaluated using independent unconditional logistic regression models; stratified models were analysed based on smoking status. Although proportions differed, the main food contributors to the MaLp and HaHp patterns included green vegetables, corn tortillas, seeds, and fruits. Compared to the PRO pattern, the MaLp (OR: 0.71; 95% CI 0.53–0.97) and HaHp (OR: 0.70; 95% CI 0.50–0.99) patterns were associated with lower odds of having PC. These associations were mainly observed with well-differentiated PC and among ever-smokers. Diets with a higher antioxidant content were associated with a reduced likelihood of PC. Further validation of these findings through prospective studies is needed.

This research introduces a cutting-edge approach to glucose monitoring, which is essential in many applications. The study developed a new non-invasive glucose monitoring system utilizing machine learning techniques. This system examines the reflection coefficient data gathered from glucose solutions using a Vector Network Analyzer. To showcase the system’s accuracy in predicting glucose levels, two distinct datasets were employed. The first dataset comprised glucose solutions with concentrations spanning from 0 to 200 g/L, while the second dataset included solutions ranging from 15 000 to 20 000 mg/L for enhanced precision. The system measured both datasets, and three machine learning algorithms – Decision Tree, Random Forest, and Support Vector Regression – were applied to the collected data. Furthermore, a grid search method was employed to optimize the hyperparameters for each model’s optimal performance. The findings revealed that the Random Forest yielded the best results across both datasets. For gram scale, the R2 value was 0.9995, indicating that 99.95% of the glucose level variance was accounted for, with a low RMSE of 1.1589 mg/dL. Moreover, in milligram scale dataset, the R2 value was 0.9932, and RMSE was 1.1119 mg/dL, confirming the model’s high accuracy. These experimental outcomes demonstrate that the proposed system can effectively predict glucose levels.

Selecting appropriate texts for second language (L2) learners is essential for effective education. However, current text difficulty models often inadequately classify materials for L2 learners by proficiency levels. This study addresses this deficiency by employing the Common European Framework of Reference for Languages (CEFR) as its foundational framework. A cohort of expert English-L2 educators classified 1,181 texts from the CommonLit Ease of Readability corpus into CEFR levels. A random forest model was then trained using 24 linguistic complexity features to predict the CEFR levels of English texts for L2 learners. The model achieved 62.6% exact-level accuracy across the six granular CEFR levels and 82.6% across the three overarching levels, outperforming a baseline model based on three existing readability formulas. Additionally, it identified shared and unique linguistic features across different CEFR levels, highlighting the necessity to adjust text classification models to accommodate the distinct linguistic profiles of low- and high-proficiency readers.

Throughout the history of philosophy, numerous philosophers have formulated theories about the connection between law and freedom. However, few have suggested that freedom and love are inherently connected. According to Hegel, the family and marriage represent the initial tangible manifestation of freedom, embodied in ethical and self-conscious love. This contentious thesis pertains to Hegel’s endorsement of the modern bourgeois family and his assertion regarding a compulsory and heteronormative conception of conjugal love. I analyse Hegel’s family theory in what follows, emphasizing the marital relationship as delineated in Outlines of the Philosophy of Right. I examine the significance and ramifications of his dismissal of the marriage contract to illustrate how this creates a paradox. I propose an alternative interpretation of these passages by emphasizing the relationship between love and law within marital relations. I advocate the importance of law within the family and demonstrate its significance to marriage. I assert that Hegel’s understanding of the family, especially regarding marriage, highlights the tensions present in the complex relationship between the legal aspect of marriage as a contract and the ethical aspect rooted in self-conscious love. To achieve this, I firstly reconstruct Hegel’s conception of the family and explore his understanding of marriage as sexual drive, desire, passion and contract. Secondly, I explore Hegel’s notion of ethical and self-conscious love, examining the relationship between law and love to reveal the paradox of marriage. Third, I discuss Hegel’s views on divorce and marriage settlements to demonstrate why marriage cannot overcome the contract. Finally, I discuss why Hegel’s response to the issues he identifies in the theories of his contemporaries is inadequate and how marriage and conjugal love threaten freedom. My claim is that marriage entails a paradoxical relationship between love and law, which calls into question the suitability of marriage to realize freedom.

What role does racial/ethnic diversity in the American states play in racialized partisan and partisan-ideological sorting? We expand the commonly employed empirical frame of Whites’ partisan and partisan-ideological reactions to minority groups at the national level by leveraging the variation in racial/ethnic populations in the American states and accounting for both out-group and in-group size across White, Black, Latino, and Asian respondents. Using the pooled 2012–22 Congressional Election Study, the results demonstrate that Whites tend toward Republican orientations in states with larger Black and Foreign-Born populations and display stronger partisan-ideological sorting in more diverse states with large Black, Latino, or Asian populations. The analyses also reveal that partisan-ideological sorting is asymmetrical along both racial and partisan identities. White partisan-ideological sorting across state racial/ethnic contexts is driven by both Republican and Democratic identifiers, while Black, Latino, and Asian respondents show few signs of elasticity to state context in partisan identity or partisan-ideological sorting. The asymmetries in both PID and partisan-ideological alignment lead to larger racial/ethnic gaps in attachment and alignment in more diverse state contexts. These are well-understood conditions for greater partisan and factional conflict and polarized party and electoral politics.