Does urban greenery add to happiness?:A research synthesis using an online finding archive

Background: There is a high demand for the greening of urban areas and one of the drivers of this demand is the biophilia theory which holds that we feel better in a green environment.Question: Does the provision of urban greenery really add to the happiness of city dwellers? If so, by how much and does the effect differ across people and situations? Approach: We summarized the available research findings on the relation between happiness and urban greenery considering both outdoor and indoor green spaces.Method: We draw on the Word Database of Happiness, in which we found 38 research findings on the relationship between happiness and urban greenery, reported in 13 publications. These findings are presented in two tabular schemes that include links to further online details.Results: The provision of urban greenery tends to go together with greater happiness of locals. The size of the effect is small. Fear of crime reduces the effect of outdoor greenery on happiness

High-resolution temporal profiling of transcripts during Arabidopsis leaf senescence reveals a distinct chronology of processes and regulation

Leaf senescence is an essential developmental process that impacts dramatically on crop yields and involves altered regulation of thousands of genes and many metabolic and signaling pathways, resulting in major changes in the leaf. The regulation of senescence is complex, and although senescence regulatory genes have been characterized, there is little information on how these function in the global control of the process. We used microarray analysis to obtain a highresolution time-course profile of gene expression during development of a single leaf over a 3-week period to senescence. A complex experimental design approach and a combination of methods were used to extract high-quality replicated data and to identify differentially expressed genes. The multiple time points enable the use of highly informative clustering to reveal distinct time points at which signaling and metabolic pathways change. Analysis of motif enrichment, as well as comparison of transcription factor (TF) families showing altered expression over the time course, identify clear groups of TFs active at different stages of leaf development and senescence. These data enable connection of metabolic processes, signaling pathways, and specific TF activity, which will underpin the development of network models to elucidate the process of senescence

Genome-wide diversity and gene expression profiling of Babesia microti isolates identify polymorphic genes that mediate host-pathogen interactions

Babesia microti, a tick-transmitted, intraerythrocytic protozoan parasite circulating mainly among small mammals, is the primary cause of human babesiosis. While most cases are transmitted by Ixodes ticks, the disease may also be transmitted through blood transfusion and perinatally. A comprehensive analysis of genome composition, genetic diversity, and gene expression profiling of seven B. microti isolates revealed that genetic variation in isolates from the Northeast United States is almost exclusively associated with genes encoding the surface proteome and secretome of the parasite. Furthermore, we found that polymorphism is restricted to a small number of genes, which are highly expressed during infection. In order to identify pathogen-encoded factors involved in host-parasite interactions, we screened a proteome array comprised of 174 B. microti proteins, including several predicted members of the parasite secretome. Using this immuno-proteomic approach we identified several novel antigens that trigger strong host immune responses during the onset of infection. The genomic and immunological data presented herein provide the first insights into the determinants of B. microti interaction with its mammalian hosts and their relevance for understanding the selective pressures acting on parasite evolution

Lineage Abundance Estimation for SARS-CoV-2 in Wastewater Using Transcriptome Quantification Techniques

Effectively monitoring the spread of SARS-CoV-2 mutants is essential to efforts to counter the ongoing pandemic. Predicting lineage abundance from wastewater, however, is technically challenging. We show that by sequencing SARS-CoV-2 RNA in wastewater and applying algorithms initially used for transcriptome quantification, we can estimate lineage abundance in wastewater samples. We find high variability in signal among individual samples, but the overall trends match those observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in mutant prevalence in situations where clinical sequencing is unavailable

Where do stars explode in the ISM? -- The distribution of dense gas around massive stars and supernova remnants in M33

Star formation in galaxies is regulated by turbulence, outflows, gas heating and cloud dispersal -- processes which depend sensitively on the properties of the interstellar medium (ISM) into which supernovae (SNe) explode. Unfortunately, direct measurements of ISM environments around SNe remain scarce, as SNe are rare and often distant. Here we demonstrate a new approach: mapping the ISM around the massive stars that are soon to explode. This provides a much larger census of explosion sites than possible with only SNe, and allows comparison with sensitive, high-resolution maps of the atomic and molecular gas from the Jansky VLA and ALMA. In the well-resolved Local Group spiral M33, we specifically observe the environments of red supergiants (RSGs, progenitors of Type II SNe), Wolf-Rayet stars (WRs, tracing stars $>$30 M$_{\odot}$, and possibly future stripped-envelope SNe), and supernova remnants (SNRs, locations where SNe have exploded). We find that massive stars evolve not only in dense, molecular-dominated gas (with younger stars in denser gas), but also a substantial fraction ($\sim$45\% of WRs; higher for RSGs) evolve in lower-density, atomic-gas-dominated, inter-cloud media. We show that these measurements are consistent with expectations from different stellar-age tracer maps, and can be useful for validating SN feedback models in numerical simulations of galaxies. Along with the discovery of a 20-pc diameter molecular gas cavity around a WR, these findings re-emphasize the importance of pre-SN/correlated-SN feedback evacuating the dense gas around massive stars before explosion, and the need for high-resolution (down to pc-scale) surveys of the multi-phase ISM in nearby galaxies.Comment: 34 pages, 14 figures. Submitted to ApJ. Comments welcome! The density distributions will be made publicly available after journal acceptance of manuscript. Please feel free to contact us in the meantime if you would like to use the

Atlantic Ocean Observing Networks: Cost and feasibility study

Results of a cost and feasibility study of the present and planned integrated Atlantic Ocean Observing System, including assessing the readiness and feasibility of implementation of different observing technologie

Quick, accurate, smart: 3D computer vision technology helps assessing confined animals' behaviour

Mankind directly controls the environment and lifestyles of several domestic species for purposes ranging from production and research to conservation and companionship. These environments and lifestyles may not offer these animals the best quality of life. Behaviour is a direct reflection of how the animal is coping with its environment. Behavioural indicators are thus among the preferred parameters to assess welfare. However, behavioural recording (usually from video) can be very time consuming and the accuracy and reliability of the output rely on the experience and background of the observers. The outburst of new video technology and computer image processing gives the basis for promising solutions. In this pilot study, we present a new prototype software able to automatically infer the behaviour of dogs housed in kennels from 3D visual data and through structured machine learning frameworks. Depth information acquired through 3D features, body part detection and training are the key elements that allow the machine to recognise postures, trajectories inside the kennel and patterns of movement that can be later labelled at convenience. The main innovation of the software is its ability to automatically cluster frequently observed temporal patterns of movement without any pre-set ethogram. Conversely, when common patterns are defined through training, a deviation from normal behaviour in time or between individuals could be assessed. The software accuracy in correctly detecting the dogs' behaviour was checked through a validation process. An automatic behaviour recognition system, independent from human subjectivity, could add scientific knowledge on animals' quality of life in confinement as well as saving time and resources. This 3D framework was designed to be invariant to the dog's shape and size and could be extended to farm, laboratory and zoo quadrupeds in artificial housing. The computer vision technique applied to this software is innovative in non-human animal behaviour science. Further improvements and validation are needed, and future applications and limitations are discussed.</p

Combining genomic and epidemiological data to compare the transmissibility of SARS-CoV-2 variants Alpha and Iota.

SARS-CoV-2 variants shaped the second year of the COVID-19 pandemic and the discourse around effective control measures. Evaluating the threat posed by a new variant is essential for adapting response efforts when community transmission is detected. In this study, we compare the dynamics of two variants, Alpha and Iota, by integrating genomic surveillance data to estimate the effective reproduction number (Rt) of the variants. We use Connecticut, United States, in which Alpha and Iota co-circulated in 2021. We find that the Rt of these variants were up to 50% larger than that of other variants. We then use phylogeography to show that while both variants were introduced into Connecticut at comparable frequencies, clades that resulted from introductions of Alpha were larger than those resulting from Iota introductions. By monitoring the dynamics of individual variants throughout our study period, we demonstrate the importance of routine surveillance in the response to COVID-19