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Landscape-oriented approaches in archaeology have moved beyond site-based research to interpret how people have engaged with, modified, and constructed the environment and how the legacies of these activities continue to influence land use. In the Maya Lowlands, landscape archaeology is related to the analysis of settlement patterns, households, agricultural intensification, and water management. The increasing availability of LiDAR data has revolutionized the mapping of archaeological landscapes under vegetation, especially in tropical environments like the Maya Lowlands, but researchers still emphasize site-oriented settlement densities and infrastructure. Furthermore, the accessibility of drone-based LiDAR platforms has the potential to collect data across several seasons or years to facilitate change detection. In this paper, we compare three LiDAR datasets collected from 2018 to 2023, using both occupied and unoccupied airborne systems. The landscape surrounding the archaeological site of El Infiernito, Chiapas, Mexico near the Classic period (AD 250–800) dynastic capital of Piedras Negras, Guatemala was selected to compare these LiDAR datasets in the context of prior, extensive ground-based fieldwork. These data were used to interpret the built environment, land use, hydrology, landscapes of movement, and other infrastructure constructed and modified by several communities beginning in the Late Preclassic period (400 BC–AD 250) to the present. When used alongside systematic survey and ground verification, the combination of several LiDAR platforms to collect data across different seasons at El Infiernito enhanced the understanding of the spatial distribution of archaeological sites and features across the karst landscape.

The frequency and intensity of flood events are increasing year by year as a result of climate change. This poses significant threats to human settlements and adversely affects biodiversity, agriculture, and infrastructure. One of the most prominent and traditional flood evacuation approaches is through the use of boats. Nonetheless, serious challenges exist with respect to determining the optimal deployment locations, routes, and timing. Given research advances in the Unmanned Aerial Vehicles (UAVs) sector—and their ability to offer real-time data and aerial monitoring services—we argue that their applications could help enhance boat-supported flood evacuation operations. In this opinion piece, we explore new opportunities for disaster management and underscore the advantages of integrating UAVs into flood evacuation methodologies, including areas of rapid field assessment, optimal route planning, and improved coordination between rescue boats. Notwithstanding the potential of UAVs, we emphasize several gaps to be explored in terms of large-scale data management/processing, regulatory limitations, and technological know-how. Furthermore, we provide recommendations for bolstering boat deployment protocols, disaster preparedness training programs, policy frameworks, and emergency response systems, which could maximize their efficacy in flood evacuation scenarios.

Hurricane incidents have become increasingly frequent along the coastal United States and have had a negative impact on the mangrove forests and their ecosystem services across the southeastern region. Mangroves play a key role in providing coastal protection during hurricanes by attenuating storm surges and reducing erosion. However, their resilience is being increasingly compromised due to climate change through sea level rises and the greater intensity of storms. This article examines the role of remote sensing tools in studying the impacts of hurricanes on mangrove forests in the coastal United States. Our results show that various remote sensing tools including satellite imagery, Light detection and ranging (LiDAR) and unmanned aerial vehicles (UAVs) have been used to detect mangrove damage, monitor their recovery and analyze their 3D structural changes. Landsat 8 OLI (14%) has been particularly useful in long-term assessments, followed by Landsat 5 TM (9%) and NASA G-LiHT LiDAR (8%). Random forest (24%) and linear regression (24%) models were the most common modeling techniques, with the former being the most frequently used method for classifying satellite images. Some studies have shown significant mangrove canopy loss after major hurricanes, and damage was seen to vary spatially based on factors such as proximity to oceans, elevation and canopy structure, with taller mangroves typically experiencing greater damage. Recovery rates after hurricane-induced damage also vary, as some areas were seen to show rapid regrowth within months while others remained impacted after many years. The current challenges include capturing fine-scale changes owing to the dearth of remote sensing data with high temporal and spatial resolution. This review provides insights into the current remote sensing applications used in hurricane-prone mangrove habitats and is intended to guide future research directions, inform coastal management strategies and support conservation efforts.

Lianas are a key growth form in tropical forests. Their lack of self-supporting tissues and their vertical position on top of the canopy make them strong competitors of resources. A few pioneer studies have shown that liana optical traits differ on average from those of colocated trees. Those trait discrepancies were hypothesized to be responsible for the competitive advantage of lianas over trees. Yet, in the absence of reliable modelling tools, it is impossible to unravel their impact on the forest energy balance, light competition, and on the liana success in Neotropical forests. To bridge this gap, we performed a meta-analysis of the literature to gather all published liana leaf optical spectra, as well as all canopy spectra measured over different levels of liana infestation. We then used a Bayesian data assimilation framework applied to two radiative transfer models (RTMs) covering the leaf and canopy scales to derive tropical tree and liana trait distributions, which finally informed a full dynamic vegetation model. According to the RTMs inversion, lianas grew thinner, more horizontal leaves with lower pigment concentrations. Those traits made the lianas very efficient at light interception and significantly modified the forest energy balance and its carbon cycle. While forest albedo increased by 14% in the shortwave, light availability was reduced in the understorey (-30% of the PAR radiation) and soil temperature decreased by 0.5°C. Those liana-specific traits were also responsible for a significant reduction of tree (-19%) and ecosystem (-7%) gross primary productivity (GPP) while lianas benefited from them (their GPP increased by +27%). This study provides a novel mechanistic explanation to the increase in liana abundance, new evidence of the impact of lianas on forest functioning, and paves the way for the evaluation of the large-scale impacts of lianas on forest biogeochemical cycles.

The ability to analyse aspects of visual culture--works of art, maps or plans, graphs, tables and X-rays--quickly and efficiently is critical in decision-making in a broad range of disciplines. Eye tracking is a technology that can record how long someone dwells on a particular detail in an image, where the eye moves from one part of the image to the other, and the sequence the viewer uses to interpret visual information. These MP4 recordings can be played back and graphically enhanced with coloured dots and lines to point out this natural and fluent eye behaviour to learners. These recordings can form effective pedagogical tools for learning how to look at images through the eyes of experts by mimicking the patterns and rhythms of expert eye behaviour. This paper provides a meta-analysis of studies of this kind and also provides the results of a cross-disciplinary project which involved five different subject areas. The consensus arising from our meta-analysis reveals an emerging field with broad concerns in need of more integrated research. None of the studies cited in this article are interdisciplinary across the sciences and arts and, while some of them address higher education in medicine and computing, there are no interdisciplinary studies of how eye tracking is important for teaching in arts and science subjects at undergraduate and postgraduate levels. In addition, none of the studies address how learning practitioners find these eye recordings useful for their own understanding of learning processes. This establishes the unique contribution of this project.

Background: Cellulose is an organic carbon source that can be used as a sustainable alternative for energy, materials, and chemicals. However, the substantial challenge of converting it into soluble sugars remains a major obstacle in its use as a biofuel and chemical feedstock. A new class of enzymes knowns as copper-dependent polysaccharide monooxygenases (PMOs) or lytic polysaccharide monooxygenases (LPMOs) can break down polysaccharides such as cellulose, chitin, and starch through oxidation. This process enhances the efficiency of cellulose degradation by cellulase. Results: The genome of the fungus Magnaporthe oryzae, the causal agent of rice blast disease, contains the MGG_00245 gene, which encodes a putative PMO referred to as MoAA16. MoAA16 has been found to be highly expressed in planta during the early stages of fungal infection. The gene was optimized for heterologous expression in Pichia pastoris, and its oxidative cleavage activity on cellulose was characterized by analyzing soluble oligosaccharide products using highperformance anion exchange chromatography (HPAEC-PAD). The reaction catalyzed by MoAA16 requires 2 electrons from an electron donor, such as ascorbic acid, and aerobic conditions. It primarily produces Glc1 to Glc4 oligosaccharides, as well as oxidized cellobionic and cellotrionic acids. MoAA16 has been observed to enhance cellulase hydrolysis on phosphoric acid swollen cellulose (PASC) substrate, resulting in the production of more monosaccharide products. Conclusions: Our findings reveal the successful heterologous expression of MoAA16 in P. pastoris and its cellulose-active PMO properties. These results highlight the potential of MoAA16 as a promising candidate for applications in biofuel production and chemical synthesis.How to cite: Nguyen HM, Le LQ, Sella L, et al. Heterologous expression and characterization of a MoAA16 polysaccharide monooxygenase from the rice blast fungus Magnaporthe oryzae. Electron J Biotechnol 2023. https://doi.org/10.1016/j.ejbt.2023.06.002.

The possibility that our universe was initiated intentionally is a compelling philosophical and scientific question that can be evaluated probabilistically based on four primary considerations: finetuning in our universe, hypotheses about the multiverse, the likelihood that intelligent life may be able to initiate a universe, and the possibility that we live in a simulation. This paper offers an equation analogous to the noteworthy Drake equation that is intended to be used as a structured thought experiment to help identify factors related to the initiation of our universe and to facilitate examining each in terms of what we know, do not know, and potentially could know about them.

Abstract Background Paramedics convey a high proportion of seizure patients with no clinical need to emergency departments (EDs). In a landmark study, only 27% of UK paramedics reported being “Very…”/ “Extremely confident” making seizure conveyance decisions. Improved pre-registration education on seizures for paramedics is proposed. Clarity is needed on its potential given recent changes to how UK paramedics train (namely, degree, rather than brief vocational course). This study sought to describe UK student paramedics’ perceived readiness to manage seizures and educational needs; compare this to what they report for other presentations; and, explore subgroup differences. Methods Six hundred thirty-eight students, in year 2 or beyond of their pre-registration programme completed a cross-sectional survey. They rated perceived confidence, knowledge, ability to care for, and educational needs for seizures, breathing problems and, headache. Primary measure was conveyance decision confidence. Results For seizures, 45.3% (95% CI 41.4–49.2) said they were “Very…”/“Extremely confident” to make conveyance decisions. This was similar to breathing problems, but higher than for headache (25.9%, 95% CI 22.6–29.5). Two hundred and thirty-nine participants (37.9%, 95% CI 34.1–41.8) said more seizure education was required – lower than for headache, but higher than for breathing problems. Subgroup differences included students on university-based programmes reporting more confidence for conveyance decisions than those completing degree level apprenticeships. Conclusions Student paramedics report relatively high perceived readiness for managing seizures. Magnitude of benefit from enhancements to pre-registration education may be more limited than anticipated. Additional factors need attention if a sizeable reduction to unnecessary conveyances for seizures is to happen.

Purpose: The extent to which acute exercise improves executive function (EF) remains indeterminate. The purpose of this systematic review and meta-analysis was to determine the effect of acute ergometer cycling exercise on executive function (EF), including the potential moderating effects of exercise intensity and duration, EF task type, and EF task onset. Methods: We searched seven electronic research databases using cycling- and cognition-related terms. All 17 studies included were published in the last 10 years and comprised healthy participants aged 18–35 years who completed tasks assessing a variety of EFs before and after cycling exercise lasting 10–60 min. We analyzed 293 effect sizes obtained from 494 individuals (mean age = 22.07 ± 2.46 yrs). Additional analyses were performed, using averaged effect sizes for each separate study to examine the omnibus effect across studies. Results: There was a positive effect of acute ergometer cycling exercise on response time (RT) in 16 of 17 studies reviewed and a positive effect for response accuracy (RA) in 8 of 14 studies; three studies did not report RA data. Hedges’ g effect sizes [95% CI] for RT ranged from 0.06 [-0.45, 0.56] to 1.50 [0.58, 2.43] and for RA from −1.94 [-2.61, −1.28] to 1.03 [0.88, 1.19].Bouts of cycling completed at moderate intensities appear to have the greatest effect on RT (Hedges' g = 1.03 [0.88, 1.19]) but no significant effect on RA; bouts with durations of 21–30 min appear to offer the greatest benefits for both RT (Hedges' g = 0.77 [0.41, 1.13]) and RA (Hedges' g = 0.92 [0.31, 1.52]). Effect sizes were greatest for RT in inhibitory control tasks (Hedges' g = 0.91 [0.80, 1.03]) and for RT when EF tasks were completed immediately post-exercise (Hedges’ g = 1.11 [0.88, 1.33]). Findings were similar in the omnibus analyses: moderate-intensity bouts had the greatest effect on RT, SMD = 0.79 (95% CI [0.49, 1.08]), z = 5.20, p

Abstract Left ventricular fibrosis can be identified by late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) in some veteran athletes. We aimed to investigate prevalence of ventricular fibrosis in veteran athletes and associations with cardiac arrhythmia. 50 asymptomatic male endurance athletes were recruited. They underwent CMR imaging including volumetric analysis, bright blood (BB) and dark blood (DB) LGE, motion corrected (MOCO) quantitative stress and rest perfusion and T1/T2/extracellular volume mapping. Athletes underwent 12-lead electrocardiogram (ECG) and 24-h ECG. Myocardial fibrosis was identified in 24/50 (48%) athletes. All fibrosis was mid-myocardial in the basal-lateral left ventricular wall. Blood pressure was reduced in athletes without fibrosis compared to controls, but not athletes with fibrosis. Fibrotic areas had longer T2 time (44 ± 4 vs. 40 ± 2 ms, p

Introduction In the UK, mental disorders are one of the most common reasons for claiming a benefit relating to unemployment, income, sickness and disability. Limited information exists regarding the demographic characteristics and psychiatric profiles of working age individuals claiming benefits in London. Until recently, detailed data on both mental disorders and benefit receipt were unavailable. Objectives To establish and describe a cohort of working age adults accessing secondary mental health services and benefits related to unemployment, income, sickness, and disability. Methods Using a novel data linkage containing electronic secondary mental health records from the South London and Maudsley (SLaM) NHS Foundation Trust and benefits data from the Department for Work and Pensions (DWP), we present descriptive statistics on sociodemographics, psychiatric diagnoses, and benefits received among a cohort of working age adults. The DWP benefits data window covers the period January 2007-June 2020, the SLaM data window covers the period January 2007-June 2019. Results We identified n = 150,348 patients (18-65 years), who had attended SLaM secondary mental health services, 78.3% of which had received a benefit relating to unemployment, income, sickness and disability. Of this group, 68% had a recorded primary psychiatric diagnosis. We found that a much higher percentage of those with a primary psychiatric diagnosis received more than one benefit (69.4%) compared to those who had not received a primary psychiatric diagnosis (30.6%). Almost 70% of claimants who obtained more than one benefit were identified as living within the two quintiles representing the highest levels of deprivation in the South-east London boroughs served by SLaM. Conclusions We showed types of benefits received among working age adults accessing secondary mental health services. This cohort will be further examined to explore trajectories of mental health care and benefit receipt and provide evidence that will help to inform both DWP policies and mental health care delivery.