We present the serendipitous radio-continuum discovery of a likely Galactic supernova remnant (SNR) G305.4–2.2. This object displays a remarkable circular symmetry in shape, making it one of the most circular Galactic SNRs known. Nicknamed Teleios due to its symmetry, it was detected in the new Australian Square Kilometre Array Pathfinder (ASKAP) Evolutionary Map of the Universe (EMU) radio–continuum images with an angular size of 1 320$^{\prime\prime}$$\times$1 260$^{\prime\prime}$ and PA = 0$^\circ$. While there is a hint of possible H$\alpha$ and gamma-ray emission, Teleios is exclusively seen at radio–continuum frequencies. Interestingly, Teleios is not only almost perfectly symmetric, but it also has one of the lowest surface brightnesses discovered among Galactic SNRs and a steep spectral index of $\alpha$=–0.6$\pm$0.3. Our best estimates from Hi studies and the $\Sigma$–D relation place Teleios as a type Ia SNR at a distance of either $\sim$2.2 kpc (near-side) or $\sim$7.7 kpc (far-side). This indicates two possible scenarios, either a young (under 1 000 yr) or a somewhat older SNR (over 10 000 yr). With a corresponding diameter of 14/48 pc, our evolutionary studies place Teleios at the either early or late Sedov phase, depending on the distance/diameter estimate. However, our modelling also predicts X-ray emission, which we do not see in the present generation of eROSITA images. We also explored a type Iax explosion scenario that would point to a much closer distance of $\lt$1 kpc and Teleios size of only $\sim$3.3 pc, which would be similar to the only known type Iax remnant SN1181. Unfortunately, all examined scenarios have their challenges, and no definitive Supernova (SN) origin type can be established at this stage. Remarkably, Teleios has retained its symmetrical shape as it aged even to such a diameter, suggesting expansion into a rarefied and isotropic ambient medium. The low radio surface brightness and the lack of pronounced polarisation can be explained by a high level of ambient rotation measure (RM), with the largest RM being observed at Teleios’s centre.

The establishment of the possible presence of life on Mars (past or present) is based on the study of planetary analogues, which allow in situ analysis of the environments in which living organisms adapt to often extreme conditions. Although Mars has been a candidate for hosting life, based on observations made decades ago, it is thanks to the characteristics identified in environments, mainly volcanic, that it has been possible to calibrate instruments and detail the features of the red planet. In this paper, we present a review of the main characteristics of different planetary analogues, particularly deepening the study of Antarctica, to later expose the factors studied in Deception Island that have contributed to considering it as an analogue of Mars from different perspectives. Although geological and geomorphological studies on the analogies of the island already exist, detailed analyses that present the approach of astrobiological analogues are required, thus allowing further research.

Recent advancements in Earth system science have been marked by the exponential increase in the availability of diverse, multivariate datasets characterised by moderate to high spatio-temporal resolutions. Earth System Data Cubes (ESDCs) have emerged as one suitable solution for transforming this flood of data into a simple yet robust data structure. ESDCs achieve this by organising data into an analysis-ready format aligned with a spatio-temporal grid, facilitating user-friendly analysis and diminishing the need for extensive technical data processing knowledge. Despite these significant benefits, the completion of the entire ESDC life cycle remains a challenging task. Obstacles are not only of a technical nature but also relate to domain-specific problems in Earth system research. There exist barriers to realising the full potential of data collections in light of novel cloud-based technologies, particularly in curating data tailored for specific application domains. These include transforming data to conform to a spatio-temporal grid with minimum distortions and managing complexities such as spatio-temporal autocorrelation issues. Addressing these challenges is pivotal for the effective application of Artificial Intelligence (AI) approaches. Furthermore, adhering to open science principles for data dissemination, reproducibility, visualisation, and reuse is crucial for fostering sustainable research. Overcoming these challenges offers a substantial opportunity to advance data-driven Earth system research, unlocking the full potential of an integrated, multidimensional view of Earth system processes. This is particularly true when such research is coupled with innovative research paradigms and technological progress.

We present a re-discovery of G278.94+1.35a as possibly one of the largest known Galactic supernova remnants (SNRs) – that we name Diprotodon. While previously established as a Galactic SNR, Diprotodon is visible in our new Evolutionary Map of the Universe (EMU) and GaLactic and Extragalactic All-sky MWA (GLEAM) radio continuum images at an angular size of $3{{{{.\!^\circ}}}}33\times3{{{{.\!^\circ}}}}23$, much larger than previously measured. At the previously suggested distance of 2.7 kpc, this implies a diameter of 157$\times$152 pc. This size would qualify Diprotodon as the largest known SNR and pushes our estimates of SNR sizes to the upper limits. We investigate the environment in which the SNR is located and examine various scenarios that might explain such a large and relatively bright SNR appearance. We find that Diprotodon is most likely at a much closer distance of $\sim$1 kpc, implying its diameter is 58$\times$56 pc and it is in the radiative evolutionary phase. We also present a new Fermi-LAT data analysis that confirms the angular extent of the SNR in gamma rays. The origin of the high-energy emission remains somewhat puzzling, and the scenarios we explore reveal new puzzles, given this unexpected and unique observation of a seemingly evolved SNR having a hard GeV spectrum with no breaks. We explore both leptonic and hadronic scenarios, as well as the possibility that the high-energy emission arises from the leftover particle population of a historic pulsar wind nebula.

Visceral leishmaniasis (VL) is a tropical disease that can be fatal if acute and untreated. Diagnosis is difficult, the treatment is toxic and prophylactic vaccines do not exist. Leishmania parasites express hundreds of proteins and several of them are relevant for the host's immune system. In this context, in the present study, 10 specific T-cell epitopes from 5 parasite proteins, which were identified by antibodies in VL patients’ sera, were selected and used to construct a gene codifying the new chimeric protein called rCHI. The rCHI vaccine was developed and thoroughly evaluated for its potential effectiveness against Leishmania infantum infection. We used monophosphoryl lipid A (MPLA) and polymeric micelles (Mic) as adjuvant and/or delivery system. The results demonstrated that both rCHI/MPLA and rCHI/Mic significantly stimulate an antileishmanial Th1-type cellular response, with higher production of IFN-γ, TNF-α, IL-12 and nitrite in vaccinated animals, and this response was sustained after challenge. In addition, these mice significantly reduced the parasitism in internal organs and increased the production of IgG2a isotype antibodies. In vivo and in vitro toxicity showed that rCHI is safe for the mammalians, and the recombinant protein also induced in vitro lymphoproliferative response and production of Th1-type cytokines by human cells, which were collected from healthy subjects and treated VL patients. These data suggest rCHI plus MPLA or micelles could be considered as a vaccine candidate against VL.

Objectives: Despite the increasing number of people with dementia (PWD), detection remains low worldwide. In Brazil, PWD is expected to triple by 2050, and diagnosis can be challenging, contributing to high and growing rates of underdiagnosis. At the moment, there is no national estimate of the under detection or characteristics of its distribution according to gender, age and region. We aimed to estimate the proportion of PWD not diagnosed in relation to the estimated number of PWD.

Methods: The number of diagnosed individuals were estimated based on national records of the prescription of anticholinesterases drugs (AChE) in 2022 for the treatment of mild and moderate stages of Alzheimer’s Disease (AD) held by the Unified Health System (SUS). Data were obtained from ftp://ftp.datasus.gov.br and drugs were dispensed according to the national clinical protocol. Studies from the national literature were consulted to estimate: (i) the number of people currently diagnosed with mild and moderate AD; (ii) the proportion of those who obtain AChE from SUS; (iii) the proportion of those who do not take AChE; and (iv) the proportion of AD related to other dementias. We assumed that the under-detection rate of AD would be similar to other dementias and 70% of the diagnosed AD individuals obtain AChE from SUS.

Results: More than 80% of the PWD 60+ are undetected (88.7%, 95% CI = 88.6–88.7). The poorest regions had higher rates (94.6% 95%, CI = 94.5–94.6) than the richest (84.8%, 95% CI = 84.7–84.8). Men had higher rates (89.8%, 95% CI = 89.7–89.9) than women (87.4%, 95% CI = 87.4–87.5). The youngest age group (60-64) had the highest rate (94.6%, 95% CI = 94.5–94.7) which decreased until 85–89 (84.3%, 95% CI = 84.2–84.4), before increasing again to 91.1% (95% CI = 91.0–91.2) among 90+.

Conclusions: Dementia under detection in Brazil is among the highest in the world. Fast populational aging and the highest rates among the youngest individuals are of concern as it may be related to late diagnosis. Gender and regional disparities also need to be considered when developing health policies.

For any $n<\omega $ we construct an infinite $(n+1)$-generated Heyting algebra whose n-generated subalgebras are of cardinality $\leq m_n$ for some positive integer $m_n$. From this we conclude that for every $n<\omega $ there exists a variety of Heyting algebras which contains an infinite $(n+1)$-generated algebra, but which contains only finite n-generated algebras. For the case $n=2$ this provides a negative answer to a question posed by G. Bezhanishvili and R. Grigolia in [4].

The developmental origins of health and disease hypothesis have highlighted the link between early life environment and long-term health outcomes in offspring. For example, maternal protein restriction during pregnancy and lactation can result in adverse metabolic and cognitive outcomes in offspring postnatal. Hence, in the present study, we assess whether an isocaloric low-protein diet (ILPD) affects the fatty acid profile in breast milk, the hippocampal synaptophysin (Syn) ratio, and the oxidative stress markers in the neonatal stage of male and female offspring. The aim of this work was to assess the effect of an ILPD on the fatty acid profile in breast milk, quantified the hippocampal synaptophysin (Syn) ratio and oxidative stress markers in neonatal stage of male and female offspring. Female Wistar rats were fed with either a control diet or an ILPD during gestation to day 10 of lactation. Oxidative stress markers were assessed in serum and liver. All quantifications were done at postnatal day 10. The results showed: ILPD led to decreases of 38.5% and 17.4% in breast milk volume and polyunsaturated fatty acids content. Significant decreases of hippocampal Syn ratio in male offspring (decreases of 98% in hippocampal CA1 pyramidal and CA1 oriens, 83%, stratum pyramidal in CA3, 80%, stratum lucidum in CA3, and 81% stratum oriens in CA3). Male offspring showed an increase in pro-oxidant status in serum and liver. Thus, the data suggest that male offspring are more vulnerable than females to an ILPD during gestation and lactation.

Design education prepares novice designers to solve complex and challenging problems requiring diverse skill sets and an interdisciplinary approach. Hackathons, for example, offer a hands-on, collaborative learning approach in a limited time frame to gain practical experience and develop problem-solving skills quickly. They enable collaboration, prototyping and testing among interdisciplinary teams. Typically, hackathons strongly focus on the solution, assuming that this will support learning. However, building the best product and achieving a strong learning effect may not be related. This paper presents the results of an empirical study that examines the relationship between product quality, learning effect and effort spent in an academic 2-week hackathon. Thirty teams identified user problems in this course and developed hardware and mechatronic products. This study collected the following data: (1) effort spent during the hackathon through task tracking, (2) learning effect through self-assessment by the participants and (3) product quality after the hackathon by an external jury. The study found that the team effort spent has a statistically significant but moderate correlation with product quality. The correlation between product quality and learning effect is statistically insignificant, suggesting that for this setting, there is no relevant association.

Griffithite, a high Fe content saponite (Griffith Park, California) was pillared with Al polymeric solutions, using different Al/clay ratios. The cation exchange began when Al-polycation solutions were added, being completed during the dialysis of the samples. Pillared solids were obtained by calcination of intercalated precursors at 500 °C. The content of A12O3 increased from 7.35% in the natural griffithite to about 14% in the pillared samples, equivalent to the fixation of about 1.4 mmol Al per g of clay. The surface areas of the pillared griffithite were between 230–300 m2 g-1. The intercalation and pillaring of griffithite were easier than that of a less-crystalline nonferrous saponite.

Particle-size distribution (PSD) is a fundamental soil property usually reported as discrete clay, silt, and sand percentages. Models and methods to effectively generate a continuous PSD from such poor descriptions using another property would be extremely useful to predict and understand in fragmented distributions, which are ubiquitous in nature. Power laws for soil PSDs imply scale invariance (or selfsimilarity), a property which has proven useful in PSD description. This work is based on two novel ideas in modeling PSDs: (1) the concept of selfsimilarity in PSDs; and (2) mathematical tools to calculate fractal distributions for specific soil PSDs using few actual texture data. Based on these ideas, a random, multiplicative cascade model was developed that relies on a regularity of scale invariance called ‘log-selfsimilarity.’ The model allows the estimation of intermediate particle size values from common texture data. Using equivalent inputs, this new modeling approach was checked using soil data and shown to provide greatly improved results in comparison to the selfsimilar model for soil PSD data. The Kolmogorov-Smirnov D-statistic for the log-selfsimilar model was smaller than the selfsimilar model in 92.94% of cases. The average error was 0.74 times that of the selfsimilar model. The proposed method allows measurement of a heterogeneity index, H, defined using Hölder exponents, which facilitates quantitative characterization of soil textural classes. The average H value ranged from 0.381 for silt texture to 0.838 for sandy loam texture, with a variance of <0.034 for all textural classes. The index can also be used to distinguish textures within the same textural class. These results strongly suggest that the model and its parameters might be useful in estimating other soil physical properties and in developing new soil PSD pedotransfer functions. This modeling approach, along with its potential applications, might be extended to fine-grained mineral and material studies.