Coordinated urban and rural development is crucial for reducing inequality and achieving common prosperity. Using panel data from 57 counties in Zhejiang Province from 2015 to 2019, this study examines the impact of digital economy development on the urban–rural income gap, with particular attention to its role in digital poverty alleviation and the underlying transmission mechanisms. The results show that while digital economy development contributes to poverty alleviation by significantly increasing household income in both urban and rural areas, it simultaneously widens the urban–rural income gap. The analysis of mechanisms reveals that nonagricultural employment (NAE), innovation, and entrepreneurship mediate this relationship, disproportionately benefiting urban areas. The heterogeneity analysis further indicates that human capital (HC) and business environment (BE) disparities amplify the widening effect of digital economy development on the urban–rural income gap, while improved infrastructure reduces barriers to resource flow, mitigating the gap. These findings highlight the dual effects of digital economy development, offering critical policy insights for promoting digital poverty reduction while addressing regional disparities to achieve common prosperity.

Zornia latifolia Sm. (Fabaceae) is a perennial herb, known for reported psychoactive and medicinal properties, with a native range from Argentina to South Texas and some West Indian islands. There is disagreement on the status of Z. latifolia in Florida concerning whether it is a native species, an established non-native species, or a waif (i.e., a non-native species growing outside of cultivation, but not maintaining a viable population). In Florida, there is only one published record of Z. latifolia growing outside cultivation, in Hillsborough County, but multiple records of this species cultivated for research. I observed extensive populations of Z. latifolia in St. Lucie, Martin, Palm Beach, and Orange counties, and confirmed observations posted on-line from Hillsborough County. Based the recentness of its first record of growing outside cultivation in Florida (2015), its substantial persistent populations at multiple locations in peninsular Florida, and its occurrence primarily in and adjacent to mowed areas, Z. latifolia appears to be an established non-native species in the state. Whether it becomes a major invasive species in Florida remains to be seen.

Do voters take into account the deaths of family members and close friends when evaluating the government’s response to the COVID-19 pandemic—particularly when that response is problematic or even negligent—as in the case of Mexico under the Andrés Manuel López Obrador (AMLO) administration? Using data from the 2021 Mexican Election Study, this research shows that opposition partisans who lost close friends or relatives to COVID-19 are more likely to evaluate the government’s response to the pandemic negatively. In contrast, National Regeneration Movement (MORENA) partisans do not hold accountable their co-partisan government. They are no more likely to evaluate the government’s response negatively, even when they experience the same losses. Experimental evidence further shows that MORENA partisans do not lower their evaluations of government performance after being informed about the country’s high COVID-19 mortality. They are also more likely to underestimate the number of COVID-19 deaths in the country, even after being presented with official mortality figures. These findings underscore how partisanship can cloud accountability, leading some voters to dismiss objective information and to judge government performance primarily through the lens of partisan loyalty. Partisanship can distort the accountability mechanism at the core of retrospective voting even during a major health crisis.

Following the proclamation of constitutionalism on 23 July 1908, villagers throughout the Ottoman Empire occupied and reclaimed çiftlik (plantation) lands from which they had previously been dispossessed. This article approaches the Ottoman 1908 Revolution as part of the “global wave of constitutional revolutions” by shifting the historiographical focus of the 1908 revolution from urban to agrarian spaces. It investigates a series of land occupations that emerged across the Ottoman çiftlik geography, conceptualizing them as the “constitutionalism of the dispossessed.” I argue that this constitutionalism of the dispossessed was a response to what I call the “order of dispossession” that emerged in the late nineteenth century: a class project of çiftlik owners reacting to global economic, imperial fiscal, and local ecological crises that aimed to subordinate labor to the circuits of global capital. Furthermore, this article discusses the failure of the constitutionalism of the dispossessed in the face of a social counter-revolution by çiftlik owners, which culminated in the codification of imperial property law. It demonstrates that the post-revolutionary government—having been concerned with the credibility of the empire in European credit markets for new loans to sustain the empire in fiscal crisis—desired the restoration of the order that the çiftlik owners insisted upon, and which the circuits of global capital required. This article ultimately offers a fresh and radical history of the Ottoman 1908 revolution and counter-revolution, suggesting a novel perspective to understand the modes of protest of the dispossessed in response to the imperatives of global capital.

We present a unified construction of perfectoid towers from specific prisms which covers all the previous constructions of (p-torsion-free) perfectoid towers. By virtue of the construction, perfectoid towers can be systematically constructed for a large class of rings with Frobenius lift. Especially, any Frobenius lifting of a reduced $\mathbb {F}_p$-algebra has a perfectoid tower.

A 7-year-old boy with a history of fish bone ingestion presented with a progressively enlarging, painless right-sided neck mass one year after the initial event. Contrast-enhanced CT angiography revealed a giant 5 × 5 cm pseudoaneurysm originating from the right common carotid artery. Surgical treatment consisted of complete excision of the pseudoaneurysm followed by primary end-to-end arterial anastomosis. The patient was extubated on postoperative day one and discharged on day five without neurological deficits. At two-year follow-up, Doppler ultrasonography demonstrated durable patency of the anastomosis with no evidence of recurrence or stenosis. An intraoperative surgical video demonstrating aneurysm excision and primary end-to-end repair is provided as supplementary material. This case highlights the importance of considering vascular injury in children presenting with delayed neck masses after foreign body ingestion and supports primary end-to-end repair as a safe surgical option in selected paediatric patients.

This study analyses 18 years of weekly reported dengue cases (January 2002–December 2020; 988 weeks) from Costa Rica’s Central Valley to examine seasonal and multi-year patterns. To model the spatio-temporal dynamics of dengue, we employ three statistical approaches for case counts: the spatial hurdle integer-valued generalized autoregressive conditional heteroskedasticity (INGARCH) model, the spatial zero-inflated generalized Poisson (ZIGP)-INGARCH model, and the endemic–epidemic (EE) model. Covariates include rainfall and maximum temperature or alternatively seasonal Fourier terms to represent annual seasonality. Using a Bayesian framework, we fit the spatial INGARCH-family models to weekly dengue cases. The EE model and the ZIGP-INGARCH model, both with Fourier seasonal terms, show the best predictive accuracy and provide estimates of seasonal intensity and peak timing relevant for dengue surveillance. Incorporating annual seasonality improves modelling of multivariate weekly dengue cases in Costa Rica’s Central Valley, underscoring the importance of cyclical patterns for strengthening early warning systems and guiding targeted vector control.

This article explores the programs known as Project 100,000 and Project Transition developed within the Johnson administration during the Vietnam War. Viewing them as the intersection between the War on Poverty and the War in Vietnam, this article contends with how these programs were designed to serve the goals both of social uplift and crime prevention through the rehabilitation of low-IQ men via military service. The article analyzes the racialized aspects of these programs, as they were disproportionately composed of Black men, and questions the motivations behind the construction of Project 100,000 and Project Transition as a means of “transporting” America’s racial unrest abroad. At its core, the article argues that these programs were inherently at odds with the intense manpower demands of the Vietnam War and the reluctancies of military officials to properly train Project 100,000 men. The program formed another tragedy of the Vietnam era.

A key output of network meta-analysis (NMA) is the relative ranking of treatments; nevertheless, it has attracted substantial criticism. Existing ranking methods often lack clear interpretability and fail to adequately account for uncertainty, overemphasizing small differences in treatment effects. We propose a novel framework to estimate treatment hierarchies in NMA using a probabilistic model, focusing on a clinically relevant treatment-choice criterion (TCC). Initially, we define a TCC based on smallest worthwhile differences (SWD), converting NMA relative treatment effects into treatment preference format. These data are then synthesized using a probabilistic ranking model, assigning each treatment a latent “ability” parameter, representing its propensity to yield clinically important and beneficial true treatment effects relative to the rest of the treatments in the network. Parameter estimation relies on the maximum likelihood theory, with standard errors derived asymptotically from the Hessian matrix. To facilitate the use of our methods, we launched the R package mtrank. We applied our method to two clinical datasets: one comparing 18 antidepressants for major depression and another comparing 6 antihypertensives for the incidence of diabetes. Our approach provided robust, interpretable treatment hierarchies that account for a concrete TCC. We further examined the agreement between the proposed method and existing ranking metrics in 153 published networks, concluding that the degree of agreement depends on the precision of the NMA estimates. Our framework offers a valuable alternative for NMA treatment ranking, mitigating overinterpretation of minor differences. This enables more reliable and clinically meaningful treatment hierarchies.