Depression is underrecognized in primary care, which is a barrier to treatment. For the last decade, Zimbabwe has invested in increasing access to depression treatment within primary healthcare. This study describes depression recognition by nurses and referral to treatment in four primary care clinics in Zimbabwe. Research staff screened 200 patients after they attended a primary care visit at a study clinic. They assessed depression using the PHQ-9 and assessed depression and/or anxiety using the Shona Symptoms Questionnaire (SSQ-14). Medical records were examined for depression and/or anxiety diagnoses. Positive depression and anxiety screens were compared with nurse documentation. 69.5% of participants were women and 56.5% were living with HIV. 6.0% had a PHQ-9 score ≥11, indicative of depression, and 22.0% had an SSQ score ≥9, indicative of depression and/or anxiety. None of the patients who screened positive for probable depression and/or anxiety were recognized by nurses. Nurses who saw the patients in the sample were surveyed. Most had not received formal training on mental health in primary care (mhGAP) prior to patient data collection. Despite efforts to expand depression treatment in Zimbabwe, individuals with probable depression were unrecognized by nurses, though nurses offered some care for other mental health conditions.

The account in Odyssey Book 9 of Odysseus’ safe arrival by ship on ‘Goat Island’ off the coast of the land of the Cyclopes, the elaborate description of the geography of the island itself, and even the specific detail of Odysseus and his shipmates slaughtering with bows and spears 108 + 1 wild goats all work together to serve as an ‘anticipatory doublet’ of the account in the second half of the epic of Odysseus’ safe arrival by ship on the island of Ithaca, the elaborate description of the geography of the island itself, and even the specific detail of Odysseus and his comrades slaughtering with bow and spears the 108 arrogant suitors + 1 treacherous goatherd.

Seed banking is the preferred strategy for the ex situ conservation of Seed Plants, due to its effectiveness in preserving whole organisms and genetic diversity at relatively low cost. However, not all seeds are suitable for long-term storage, particularly those classified as recalcitrant or desiccation-sensitive, which limits the applicability of seed banking for certain species. In Chile, the proportion and identification of recalcitrant species remain largely unknown. In this study, we investigated the storage behaviour of potentially recalcitrant species and evaluated two predictive models of seed recalcitrance based on morphological, ecological and taxonomic variables. One of these models was subsequently employed to estimate the incidence of recalcitrance among Chilean tree species. Most of the species assessed exhibited clear sensitivity to desiccation. The Seed Coat Ratio–Seed Mass model showed the highest precision and recall. Nevertheless, models incorporating ecological and taxonomic variables also performed well at the genus level. Using a Boosted Regression Tree model refined through experimental data and literature review, we estimate that 19% (n = 11) of Chilean tree species possess recalcitrant seeds. Among the tree and shrub species confirmed as recalcitrant in this study (n = 17), 71% are endemic to Chile (n = 12), and 53% are categorized as threatened (n = 9). These findings provide a stronger basis for prioritizing alternative ex situ conservation strategies beyond seed banking for species with recalcitrant seeds.

Surety supervision is one of the most onerous bail conditions imposed on legally innocent people pretrial. Sureties are generally family or friends who promise a sum of money and agree to supervise the accused, enforcing conditions and reporting non-compliance. Drawing on data from 32 in-depth interviews with individuals who have acted as sureties, this paper examines the complex, contradictory, and damaging implications of exploiting personal relationships for the state’s surveillance and monitoring interests. We argue that by placing sureties in such a role, the court stresses the accused’s social relationships by transforming the accused’s support network into an apparatus of state control. Sureties describe exploited relational bonds and ruptured relationships, insisting they will never act as a surety again. We conclude by outlining directions for reform, including changing the nature of surety supervision, decriminalization and developing bail supervision programs.

In recent decades, support for the far right has surged in many countries. One common explanation for this is that far-right support is a backlash against left-wing governments and their policies. We investigate the causal effect of the partisan make-up of governments on the electoral results of far-right parties. Evidence from over-time comparative data and a quasi-experimental analysis based on a regression discontinuity design in Spain indicates that far-right parties benefit electorally when the current government is on the left. In further analyses, we employ a novel regression discontinuity design (RDD)-based sampling strategy to examine original individual-level survey data from Spanish municipalities close to the discontinuity cutoff. These data show that the likely mechanism underlying the backlash effect is an ideological shift to the right among the electorate when left-wing parties govern. Overall, the far right benefits more when the mainstream left governs than when the mainstream right does.

Foundation models are many things and encompass several modalities; they use text, images, sound, and more recently, action or inference units. But all of these forms share one thing in common: the (massive) scale. The “large” in large language models has been well studied by scholars in critical data, AI and archive studies, with several experts pointing at how these models are environmentally harmful, technically opaque and corporationally monopolistic primarily because of their scale. This piece discusses questions of technical and cultural scale – in the material, archival and procedural senses – within the contemporary technical and discursive landscape. At stake here is the role of critical and design studies within academic, artistic and para-academic worlds. It suggests that instead of corporate chatbots that aspire to pass the Turing test through multipurpose, encyclopedic service, we may be better served by playing with local models and reaching for small-scale AI development. This epistemological shift, in fact, may also provide some creative and critical potential that more effectively gets at the strangeness of machine learning systems while consciously and carefully handling the scalar environmental and social impacts of big AI.

Star clusters are well known for their dynamical interactions, an outcome of their high stellar densities; in this paper, we use multiwavelength observations to search for the unique outcomes of these interactions in three nearby Galactic open clusters (OCs): IC 2602 (30 Myr), NGC 2632 (750 Myr), and M67 (4 Gyr). We compared X-ray observations from all-sky surveys like eROSITA, plus archival observations from Chandra X-ray Observatory, survey radio observations from ASKAP’s Evolutionary Map of the Universe survey plus archival VLA observations, in conjunction with new cluster catalogues with Gaia. From X-ray, we found 77 X-ray sources likely associated with IC 2602, 31 X-ray sources in NGC 2632, and 31 near M67’s central regions. We were further able to classify these X-ray sources based on their optical variability and any radio emission. Three IC 2602 X-ray sources had radio counterparts, which are likely all chromospherically active binary stars. We also identified luminous radio and X-ray variability from a spectroscopic triple system in M67, WOCS 3012/S1077, which is either consistent with a quiescent black hole binary, or due to an active binary stellar system. A recent population study of optical variables by Anderson & Hunt (2025) shows that the population of optical variables in OCs clearly changes over cluster age; this pilot study gives evidence that the X-ray population also changes with time and demonstrates the need for a broader multiwavelength study of Galactic OCs.

The design of filters used in waveguides, which are crucial components of high-frequency communication systems, plays a significant role in improving system performance. In this study, the usage of metamaterials is first proposed, the SLA 3D printing method is used to design and fabricate CSRR meta-resonators-based bandpass waveguide filters (WGFs) with different filter orders for C-band (4-7.5 GHz), and simulated and measured filter performances are compared. Since the proposed novel WG structure is modular, it allows the design of C-band WGFs using different thicknesses of substrate materials. Also, the number of unit elements can be increased and any number of meta-resonators can be inserted to design filters of different orders ranging from 1 to 5. The electrical length of the WGF/WG structure can be changed according to the needs of the applications. The resulting WGFs demonstrated superior RF performance, being 50% lighter than comparable models found in the literature. Over the relevant frequency range, the filter exhibited return losses between 31-43 dB, insertion losses from 0.1 to 0.35 dB, FBW ranging from 12% to 16%, and quality factors between 6.23 and 8.28, depending on the filter order. The obtained experimental results align closely with the simulation predictions, confirming the effectiveness of the design.

Regular inspections of civil structures and infrastructure, performed by professional inspectors, are costly and demanding in terms of time and safety requirements. Additionally, the outcome of inspections can be subjective and inaccurate as they rely on the inspector’s expertise. To address these challenges, autonomous inspection systems offer a promising alternative. However, existing robotic inspection systems often lack adaptive positioning capabilities and integrated crack labelling, limiting detection accuracy and their contribution to long-term dataset improvement. This study introduces a fully autonomous framework that combines real-time crack detection with adaptive pose adjustment, automated recording and labelling of defects, and integration of RGB-D and LiDAR sensing for precise navigation. Damage detection is performed using YOLOv5, a widely used detection model, which analyzes the RGB image stream to detect cracks and generates labels for dataset creation. The robot autonomously adjusts its position based on confidence feedback from the detection algorithm, optimizing its vantage point for improved detection accuracy. Experiment inspections showed an average confidence gain of 18% (exceeding 20% for certain crack types), a reduction in size estimation error from 23.31% to 10.09%, and a decrease in the detection failure rate from 20% to 6.66%. While quantitative validation during field testing proved challenging due to dynamic environmental conditions, qualitative observations aligned with these trends, suggesting its potential to reduce manual intervention in inspections. Moreover, the system enables automated recording and labeling of detected cracks, contributing to the continuous improvement of machine learning models for structural health monitoring.