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Anti-CRISPR (Acr) proteins are natural inhibitors of CRISPR-Cas immune systems. To date, Acrs inhibiting types I, II, III, V, and VI CRISPR-Cas systems have been characterized. While most known Acrs are derived from bacterial phages and prophages, very few have been characterized in the domain Archaea, despite the nearly ubiquitous presence of CRISPR-Cas in archaeal cells. Here we summarize the discovery and characterization of the archaeal Acrs with the representatives encoded by a model archaeal virus, Sulfolobus islandicus rod-shaped virus 2 (SIRV2). AcrID1 inhibits subtype I-D CRISPR-Cas immunity through direct interaction with the large subunit Cas10d of the effector complex, and AcrIIIB1 inhibits subtype III-B CRISPR-Cas immunity through a mechanism interfering with middle/late gene targeting. Future development of efficient screening methods will be key to uncovering the diversity of archaeal Acrs. Similar to bacterial viruses, archaeal viruses encode anti-CRISPR (Acr) proteins. The known archaeal acrs are found in variable regions of viral genomes and are easily lost in the absence of evolutionary pressure. Two Acrs, AcrID1 and AcrIIIB1, have been identified from SIRV2. AcrID1 interacts with the large subunit of the type I-D effector complex Cas10d. AcrID1 is found in multiple copies of low similarity in individual viruses, up to 12 homologs in SIRV2, a phenomenon that has not been observed with bacterial Acrs. AcrIIIB1 inhibits subtype III-B CRISPR-Cas immunity by interfering with middle/late gene targeting. In correlation to the lower abundance of subtype I-D systems in comparison with the wide distribution of subtype III-B systems in archaea, AcrID1 is restricted to fewer viruses while AcrIIIB1 is more widespread. [ABSTRACT FROM AUTHOR]

• Schools are identified as ideal environments for addressing bias-based aggression, whether dealing with aggressors, victims, or bystanders. • Theory of Mind used to analyze responses to bias-based bullying. • Social Ecological Theory employed to address unique forms of bias-based bullying among sexual and gender minority youth. • Social Identity Theory used to examine racist or bias-based bullying among children. • Schools that implement Gay-Straight Alliances (GSA) lower levels of multiple forms of bias-based bullying compared to schools without GSA. • The communities and schools that LGBTQ-inclusive provide enhanced safeguarding against bias-based bullying. The increasing recognition of diversity has brought about a rise in bias-based aggression, with researchers focusing on its prevalence among youth. This has generated the need for a systematic analysis of the factors associated with this type of behavior. To contextualize bias-based aggression and develop future intervention strategies for young people, it is crucial to appraise published studies. This meta -analytic review aims to identify the most commonly used theories to explain bias-based aggression, significant authors, countries, and institutions in this thematic field, as well as how they interrelate. Furthermore, it explores the most analyzed lines of research by researchers and discusses implications for preventive interventions to address bias-based aggression. This review focuses on English-language literature and utilizes a systematic search strategy in Scopus, yielding 51 publications. Descriptive statistical and bibliometric analyses were conducted using VOSviewer software. The results indicate a leadership role held by US researchers and institutions. Theories of mind and Social Ecological theories are found to be the most frequently employed theoretical frameworks by authors. Schools are identified as ideal environments for addressing bias-based aggression, whether dealing with aggressors, victims, or bystanders. [ABSTRACT FROM AUTHOR]

Emissions from motor vehicles are considered to be one of the main sources of airborne particulate matter in Santiago. International researchers have shown that particulate matter contains metal oxides and magnetic particles, both of which are emitted mainly from vehicles exhaust pipes. On the other hand, trees are effective in reducing such contamination, so that they act as passive collectors of particulate matter. This work presents the results obtained from the first magnetic study of the particulate matter collected in two areas of the city of Santiago de Chile. Magnetic susceptibility and Saturation Isothermic Remanent Magnetization (SIRM) were determined in leaves from abundant urban trees and from urban dust samples. Results indicate that most of the samples contain ferromagnetic minerals with magnetite (Fe 3 O 4 ) as the main carrier. Values of magnetic susceptibility (SI ×10 −6 m 3 /kg) in the range 0.04–0.24 for leaves and in the range 10–45 for urban dust were determinated. In one of the city areas studied, significant correlation between the particulate matter deposited on leaves of Platanus orientalis and measured traffic flows was obtained. In addition, it was possible to estimate that the species Platanus orientalis and Acer negundo have a better ability to capture particulate matter than the species Robinia pseudoacacia. [ABSTRACT FROM AUTHOR]

Prokaryotic adaptation is strongly influenced by the horizontal acquisition of beneficial traits via mobile genetic elements (MGEs), such as viruses/bacteriophages and plasmids. However, MGEs can also impose a fitness cost due to their often parasitic nature and differing evolutionary trajectories. In response, prokaryotes have evolved diverse immune mechanisms against MGEs. Recently, our understanding of the abundance and diversity of prokaryotic immune systems has greatly expanded. These defense systems can degrade the invading genetic material, inhibit genome replication, or trigger abortive infection, leading to population protection. In this review, we highlight these strategies, focusing on the most recent discoveries. The study of prokaryotic defenses not only sheds light on microbial evolution but also uncovers novel enzymatic activities with promising biotechnological applications. Newly discovered bacterial and archaeal defense mechanisms against phages and other mobile genetic elements have revealed the complexity of the prokaryotic immune system. Mayo-Muñoz et al. review and classify these defenses based on common modes of action, focusing on recent advances. [ABSTRACT FROM AUTHOR]

Output analysis methods of steady-state simulations have extensively been subject of study to evaluate the performance when estimating the mean. However, smaller efforts have been placed on performance evaluation of these methods to estimate variance and quantiles. In this paper, we empirically evaluate the performance of output analysis methods based on multiple replications and batches to estimate mean, variance and quantile with the same set of data. The evaluation of the performance of the methods is based on the empirical coverage of the true value using confidence intervals, the average bias, relative error and mean squared error. The methods are applied to estimate the average, variance and quantiles of waiting time in an M / M / 1 queue. The results show that the methods based on non-overlapping batches perform consistently well in all the metrics. The performance of the other methods varies depending on the metric and the parameters of the simulation. In addition, we provide another example of a non-geometric ergodic Markov chain to show that asymptotically valid confidence intervals for quantiles can be obtained using batches and replications. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the effects of actual smart antennas on the Power Doppler Spectrum (PDS) are studied when smart antennas are deployed at the base station (BS), employing a statistical Gaussian Scatter Density Model (GSDM). This proposed approach is general and it can be applied to omnidirectional and sectorized antennas as well, for beam patterns of linear and circular arrays, the results obtained are compared with those for omnidirectional and sectorized antennas. The characterization of PDS is presented for channel scenarios including different motion direction, scatterer spread, and a variety of beam patterns. [Copyright &y& Elsevier]

Abstract: Wine aged for 2 years in cellar conditions and a batch of non aged wine were subjected to biological aging with S. cerevisiae var. capensis under controlled microaeration. Another batch of the non aged wine and 4 year aged wine in cellar conditions were used as control and named initial and final control wines, respectively. Thirty-five aroma compounds were quantified by GC–MS, and grouped in nine odorants series to compare the microaerated wines with the control wines. Fruity, balsamic, floral, herbaceous, fatty and roasty series increases their values, while solvent and phenolic diminishes by the effect of yeast metabolism. Roasty and spicy series show the higher values in wines previously aged in cellar conditions for 2 and 4 years probably due to the contact of the wine with the wood. The roasty series is dependent of compounds such as 2,3-butanedione, 2,3-pentanodione, 4-ethylguaiacol and some lactones, whereas the spicy series is only dependent on 4-ethylguaiacol. The similarity obtained for some odorant series in wines aged under controlled conditions and wines aged for 4 years in cellar, suggest that the biological aging time can be shortened using a first step for wine aging in stainless-steel under controlled and periodic microaerations and a second step in an oak cask under cellar conditions. [Copyright &y& Elsevier]

Compound flood hazard assessment (CFHA) and modeling are prone to various sources of uncertainty including model structure, model parameters, input/forcing data, and those associated with nonlinear interactions among flood drivers. Data assimilation (DA) is an efficient method that helps quantify and reduce uncertainty in many hydrological applications and has proven to be effective in water level (WL) predictions and/or flood forecasts. However, research to date has not yet explored the benefits of DA in coastal to inland transition zones where pluvial, fluvial, and coastal flood drivers interact. Here, we present a DA scheme consisting of the Ensemble Kalman Filter technique and hydrodynamic modeling to provide (i) reliable WL predictions and (ii) accurate (near real-time) flood hazard maps within a 6 h-assimilation cycle. The DA scheme is tested on two well-known compound flood events and study sites in the United States, namely Hurricane Harvey for Galveston Bay and Hurricane Sandy for Delaware Bay. WL predictions and compound flood hazard maps are validated against observational data collected from coastal and inland gauge stations and high-water marks obtained from the U.S. Geological Survey, respectively. We show that DA is an effective method that accounts for all sources of uncertainty, reduces errors in peak WL estimates (up to 0.55 m) and mean absolute bias in CFHA (up to 40%). We conclude that, regardless of the dominant fluvial/pluvial or coastal drivers, DA can improve CFHAs in low-lying areas including coastal to inland transition zones. [Display omitted] • A data assimilation (DA) scheme is presented for reliable water level predictions. • And compound flood hazard assessment (CFHA) within a 6-h assimilation cycle. • The DA scheme can reduce errors in peak water level estimates for hurricane events. • CFHA benefits from DA regardless of the dominant inland or coastal flood driver. • The scheme can generate actionable flood risk information on a near-real time basis. [ABSTRACT FROM AUTHOR]

In this paper we discuss a framework to evaluate the benefits of publicly-funded research that includes scientific impact, impacts on stakeholders (next and end users of research outputs), and economic and environmental values. We apply this framework to evaluate two agricultural greenhouse gas (GHG) mitigation research science projects funded in New Zealand: research looking at mitigation options given by genetic markers for low methane animals, and the identification of emission-reducing management practices. From this analysis we achieve two main findings. First, the prominence of the research combined with the low likelihood of research occurring on this scale without public support suggests strongly that the results would not have been obtained in absence of public funding. Second, the advances reached in some areas have the potential for GHG emission reductions that would be significant in environmental terms, and whose value at likely carbon pricing levels would be in the hundreds of millions of dollars. The results discussed are conditional on several factors such as future domestic and international policy settings and implementation, adoption rates and the practical availability of mitigation options and practices for different farm landscapes. However, the impacts and economic and environmental values attached to these research projects, and mitigation research more generally, cannot be overlooked. The case studies evaluated clearly demonstrate the potential benefits that public investments can make to the development of more sustainable agricultural systems. • A framework to evaluate publicly-funded research is discussed. • We note conceptual and practical considerations to gauge value and impacts. • Two New Zealand agricultural mitigation research projects are evaluated. • With an agricultural ETS, research has potential value of hundreds of millions. [ABSTRACT FROM AUTHOR]

A 62-year-old man was admitted to our hospital with sudden chest pain. CT examination showed the presence of an intimal flap in the aortic root and in the descending aorta, with no intimal flap in the ascending aorta and curvilinear filling defects in the aortic arch, and extension into the left subclavian artery. Surgical treatment consisted of ascending aorta replacement. During the operation, the intimal tear was found to be circumferential with intussusception of the intimal layer. The patient died at surgery. [ABSTRACT FROM AUTHOR]

Triathlon followers increase each year and long-distance events have seen major growth worldwide. In the cycling phase, athletes must maintain an aerodynamic posture on the bike for long periods of time. We report a case of a 38-year-old triathlete with symptoms of an axillary vein thrombosis 48h after a long triathlon competition. After 3days of hospitalization with a treatment consisted on enoxaparin anticoagulant and acenocumarol, the patient was discharged with instructions to continue treatment under home hospitalization with acetaminophen. Four weeks after the process, the patient was asymptomatic and the diameter of his arm was near normality. Due to the growing popularity of events based on endurance exercise, it is necessary more research to determine the etiopathogeny of deep venous thrombosis in athletes. [ABSTRACT FROM AUTHOR]

Population density is a fundamental parameter needed to assess wildlife populations but is difficult to obtain given species are often wide-ranging and elusive. Photographic capture-recapture techniques do not require direct observations and thus, have become a common approach for estimating wildlife densities. To date, however, these studies have typically focused on single species. Our research explores study design- and analytical-based approaches for expanding photographic capture-recapture studies to assess multiple species simultaneously. We developed a hybrid-sampling scheme that varied inter-camera distances and used simulations to test the efficacy of this design versus a systematically spaced grid in estimating densities of species with varied space use. Through simulations we found the hybrid design facilitated density estimates for a wider range of species with little or no cost in accuracy for most species. We implemented a hybrid camera design across a 1154-km2 area in northern Botswana to estimate densities of lions, spotted hyenas, leopards, wild dogs, servals, civets, and aardwolves. We estimated densities of these small- to wide-ranging carnivores, where all or some portion of the population was individually identifiable, using spatially explicit capture-recapture and mark-resight models. Mean estimates ranged from 1.2 (95% CI = 0.72–1.99) lions to 10.1 (95% CI = 8.69–11.63) spotted hyenas/100 km2 and provided empirical information needed for the conservation of these species in Botswana. Our research demonstrates how photographic capture-recapture studies can be expanded to estimate the densities of multiple species versus just a single species within a community, thus increasing the conservation value of this globally implemented approach. • Sample design and analytical choices can maximize efficiency of camera trap surveys. • Spacing cameras at a range of distances facilitates multispecies density estimation. • We used one camera grid to estimate densities of 7 carnivore species in Botswana. • Density estimates ranged from 1.2 lions to 10.1 spotted hyenas per 100 km2. • Knowledge of multiple species' densities will facilitate informed conservation plans. [ABSTRACT FROM AUTHOR]

• Standard reflectance hyperspace vs -log reflectance hyperspace. • Deep learning-based vs linear-based unmixing algorithms. • Unmixing performed in the SWIR range. • Combined metric for pigment identification. • Application to a painting with inscription "Boceto di Pablo Veronese" on the back. Hyperspectral imaging has recently consolidated as a useful technique for pigment mapping and identification, although it is commonly supported by additional non-invasive analytical methods. Since it is relatively rare to find pure pigments in aged paintings, spectral unmixing can be helpful in facilitating pigment identification if suitable mixing models and endmember extraction procedures are chosen. In this study, a subtractive mixing model is assumed, and two approaches are compared for endmember extraction: one based on a linear mixture model, and the other, nonlinear and Deep-Learning based. Two spectral hyperspaces are used: the spectral reflectance (R hyperspace) and the -log(R) hyperspace, for which the subtractive model becomes additive. The performance of unmixing is evaluated by the similarity of the estimated reflectance to the measured data, and pigment identification accuracy. Two spectral ranges (400 to 1000 nm and 900 to 1700 nm) and two objects (a laboratory sample and an aged painting, both on copper) are tested. The main conclusion is that unmixing in the -log(R) hyperspace with a linear mixing model is better than for the non-linear model in R hyperspace, and that pigment identification is generally better in R hyperspace, improving by merging the results in both spectral ranges. [ABSTRACT FROM AUTHOR]

Abstract: The statistical Gaussian scatter density model (GSDM) is used to evaluate the effects on the Doppler power density spectrum (PDS) when a directional antenna at base station (BS) is employed. We derive the angle of arrival (AOA) probability density function (pdf ) of the multipath components at the mobile station (MS). The AOA pdf at the MS and the PDS, are compared with those for the Clarke''s model and the macrocell circular model. We demonstrate that the circular model overestimates the probability of scatterers with AOA near to the line of sight (LoS), resulting in a poorer estimation of the PDS unlike the Gaussian model. [Copyright &y& Elsevier]