Search

This paper explores the boosting ridge (BR) framework in the extreme learning machine (ELM) community and presents a novel model that trains the base learners as a global ensemble. In the context of Extreme Learning Machine single-hidden-layer networks, the nodes in the hidden layer are preconfigured before training, and the optimisation is performed on the weights in the output layer. The previous implementation of the BR ensemble with ELM (BRELM) as base learners fix the nodes in the hidden layer for all the ELMs. The ensemble learning method generates different output layer coefficients by reducing the residual error of the ensemble sequentially as more base learners are added to the ensemble. As in other ensemble methodologies, base learners are selected until fulfilling ensemble criteria such as size or performance. This paper proposes a global learning method in the BR framework, where base learners are not added step by step, but all are calculated in a single step looking for ensemble performance. This method considers (i) the configurations of the hidden layer are different for each base learner, (ii) the base learners are optimised all at once, not sequentially, thus avoiding saturation, and (iii) the ensemble methodology does not have the disadvantage of working with strong classifiers. Various regression and classification benchmark datasets have been selected to compare this method with the original BRELM implementation and other state-of-the-art algorithms. Particularly, 71 datasets for classification and 52 for regression, have been considered using different metrics and analysing different characteristics of the datasets, such as the size, the number of classes or the imbalanced nature of them. Statistical tests indicate the superiority of the proposed method in both regression and classification problems in all experimental scenarios. [ABSTRACT FROM AUTHOR]

Based on the counted power system emission factors of North China Power Grid, a community carbon emissions sample database is constructed. The support vector regression (SVR) model is trained to forecast the power carbon emissions, which is optimized by genetic algorithm (GA). A community carbon emission warning system is designed according the results. The dynamic emission coefficient curve of the power system is obtained by fitting the annual carbon emission coefficients. The time series SVR carbon emission prediction model is constructed, while the GA is improved to optimize its parameters. Taking Beijing Caochang Community as an example, a carbon emission sample database is generated based on the electricity consumption and emission coefficient curve to train and test the SVR model. The results show that the GA–SVR model fits well with the training set and the testing set, and the prediction accuracy of the testing set reaches 86%. In view of the training model in this paper, the carbon emission trend of community electricity consumption in the next month is predicted. The carbon emission warning system of the community is designed, and the specific strategy of community carbon emission reduction is proposed. [ABSTRACT FROM AUTHOR]

Despite the considerable uncertainty in predicting critical parameters of renewable energy systems, the uncertainty during system design is often marginally addressed and consistently underestimated. Therefore, the resulting designs are fragile, with suboptimal performances when reality deviates significantly from the predicted scenarios. To address this limitation, we propose an antifragile design optimization framework that redefines the indicator to optimize variability and introduces an antifragility indicator. The variability is optimized by favoring upside potential and providing downside protection towards a minimum acceptable performance, while the skewness indicates (anti)fragility. An antifragile design primarily enhances positive outcomes when the uncertainty of the random environment exceeds initial estimations. Hence, it circumvents the issue of underestimating the uncertainty in the operating environment. We applied the methodology to the design of a wind turbine for a community, considering the Levelized Cost Of Electricity (LCOE) as the quantity of interest. The design with optimized variability proves beneficial in 81% of the possible scenarios when compared to the conventional robust design. The antifragile design flourishes (LCOE drops by up to 120%) when the real-world uncertainty is higher than initially estimated in this paper. In conclusion, the framework provides a valid metric for optimizing the variability and detects promising antifragile design alternatives. [ABSTRACT FROM AUTHOR]

The Gumelnița site belongs to the Kodjadermen-Gumelnița-Karanovo VI (KGK VI) communities (c. 4700–3900 cal BC) and comprises the tell-type settlement and its corresponding cemetery. This paper reconstructs the diet and lifeways of the Chalcolithic people in the northeastern Balkans using archaeological remains found at the Gumelnița site (Romania). A multi-bioarchaeological investigation (archaeobotany, zooarchaeology, anthropology) was conducted on vegetal, animal, and human remains, alongside radiocarbon dating and stable isotope analyses (δ13C, δ15N) of humans (n = 33), mammals (n = 38), reptiles (n = 3), fishes (n = 8), freshwater mussels shells (n = 18), and plants (n = 24). According to the results of δ13C and δ15N values and FRUITS, the inhabitants of Gumelnița had a diet based on crops and using natural resources, such as fish, freshwater molluscs and game. Although domestic fauna was occasionally exploited for meat, it had a role in providing secondary products. Crops were heavily manured, and chaff and other crop waste may have been necessary fodder for cattle and sheep. Dogs and pigs fed on human waste, although the diet of the latter is more similar to that of wild boars. Foxes had a diet close to dogs, which may indicate synanthropic behaviour. Radiocarbon dates were calibrated with the percentage of freshwater resources obtained by FRUITS. As a result, the corrected dates for the freshwater reservoir effect (FRE) have a delay of an average of 147 years. According to our data, this agrarian community developed a subsistence strategy under the pressure of some climatic changes that started after 4300 cal BC, corresponding to KGK VI rapid collapse/decline episode tracked recently (that begins around 4350 cal BC). This matching of our data in the two models (climatic and chrono-demographic) allowed us to capture the economic strategies that led to the resilience of those people more than other contemporary KGK VI communities. [ABSTRACT FROM AUTHOR]

Cross-habitat spillover may be the outcome of a process of habitat loss or degradation where the receiving habitat serves as a refuge for organisms. Once surface habitats are lost or degraded, animals can find underground refuge in caves. This paper is focused on testing whether taxonomic order richness inside caves is positively affected by the loss of the native vegetation cover surrounding caves; whether degradation of native vegetation cover predicts cave community composition; and whether there is a pattern of cave community clusters delimited by similarity in the effects of habitat degradation on animal communities. We gathered a comprehensive speleological dataset consisting of occurrence data of thousands of invertebrates and vertebrates sampled in 864 iron caves in the Amazon, to test the effects of both variables measured inside caves and surrounding landscapes on spatial variation in richness and composition of animal communities. We show that caves can work as refuges for the fauna in landscapes where the native vegetation cover surrounding them was degraded, which was evidenced by landcover change increasing the richness of cave communities and clustering caves by similarity in community composition. Therefore, habitat degradation on the surface should be a key variable when characterizing cave ecosystems for conservation prioritization and offset planning. Habitat degradation causing a cross-habitat spillover effect highlights the importance of maintaining the connection between caves by the surface, especially large caves. Our study can help guide industry and stakeholders working on the complex conciliation between land use and biodiversity conservation. [ABSTRACT FROM AUTHOR]

In the study of protected areas, the "Fences & fines" approach is increasingly becoming acknowledged as obsolete and ineffectual, and there is mounting evidence suggesting that the "Community-based conservation" approach is acquiring consideration. It is significant to identify which protection model or factors perform a definitive part in China. Taking the East Dongting Lake National Nature Reserve in China as a survey site, this paper utilizes semi-structured interviews and random questionnaires surveyed 431 households to investigate the relationship between "community-based conservation" approaches such aslegal system, ecological compensation, environmental education, community participation, concessions, livelihoods, job provision, intrinsic motivation and pro-environmental behavior. The regression results declare that intrinsic motivation (β = 0.390) and legal system (β = 0.212) are the most effective factors impacting on pro-environmental behavior; concessions has a negative conflict on preservation;but other "community-based conservation" approaches had insignificant positive impacts on pro-environmental behavior. Further mediating effects analysis indicated that intrinsic motivation (B = 0.3899, t = 11.9694, p < 0.01) mediates between legal system and pro-environmental behavior of community residents, legal system promotes pro-environmental behavior by promoting intrinsic motivation, which is more effective than legal system promoting pro-environmental behavior directly. This demonstrates that "Fence and fine approach" still is an effective management tool which can shape community residents' positive attitude towards conservation and pro-environmental behavior especially protected areas with large communities. And appropriate "community-based conservation" approaches can mitigate conflicts between special groups with the combination of these two approaches, the management of protected areas can be successful. This supplies a valuable real-world case for the current debate on conservation and improved human livelihoods. [ABSTRACT FROM AUTHOR]

Chess is a centuries-old game that continues to be widely played worldwide. Opening Theory is one of the pillars of chess and requires years of study to be mastered. In this paper, we use the games played in an online chess platform to exploit the "wisdom of the crowd" and answer questions traditionally tackled only by chess experts. We first define a relatedness network of chess openings that quantifies how similar two openings are to play. Using this network, we identify communities of nodes corresponding to the most common opening choices and their mutual relationships. Furthermore, we demonstrate how the relatedness network can be used to forecast future openings players will start to play, with back-tested predictions outperforming a random predictor. We then apply the Economic Fitness and Complexity algorithm to measure the difficulty of openings and players' skill levels. Our study not only provides a new perspective on chess analysis but also opens the possibility of suggesting personalized opening recommendations using complex network theory. [ABSTRACT FROM AUTHOR]

Using environmental DNA (eDNA) to monitor biodiversity in aquatic environments is becoming an efficient and cost-effective alternative to other methods such as visual and acoustic identification. Until recently, eDNA sampling was accomplished primarily through manual sampling methods; however, with technological advances, automated samplers are being developed to make sampling easier and more accessible. This paper describes a new eDNA sampler capable of self-cleaning and multi-sample capture and preservation, all within a single unit capable of being deployed by a single person. The first in-field test of this sampler took place in the Bedford Basin, Nova Scotia, Canada alongside parallel samples taken using the typical Niskin bottle collection and post-collection filtration method. Both methods were able to capture the same aquatic microbial community and counts of representative DNA sequences were well correlated between methods with R 2 values ranging from 0.71–0.93. The two collection methods returned the same top 10 families in near identical relative abundance, demonstrating that the sampler was able to capture the same community composition of common microbes as the Niskin. The presented eDNA sampler provides a robust alternative to manual sampling methods, is amenable to autonomous vehicle payload constraints, and will facilitate persistent monitoring of remote and inaccessible sites. [ABSTRACT FROM AUTHOR]

Digital image correlation, deflectometry and digital holography are some of the full-field optical measurement techniques that have matured in recent years. Their use in vibroacoustic applications is gaining attention and there is a need for cataloging their performance in order to provide, to a broad community of users and potential future users, quantitative and qualitative evaluations of these three approaches. This paper presents an experimental comparison of the three optical methods in the context of vibration measurements, along with classical reference measurements provided by an accelerometer and a laser Doppler vibrometer. The study is carried out on two mechanical structures exhibiting various vibration responses when submitted to an impact. [ABSTRACT FROM AUTHOR]

Several Late Viséan-Serpukhovian coral reefs were identified in Langping, Tianlin. They provided an opportunity to investigate paleo-environments suitable for the development of reef-building communities and the construction of coral reefs in Langping. In this paper, part of the reef-building environmental and the ecological characteristics of coral reefs then were elaborated by analyzing the development settings, palaeogeography, sedimentation of reefs, the response to hydrodynamic conditions of reef-building corals, effects of disturbance and non-reef-building organism on reef communities, and the influence of coral morphology on reef development. It is considered that the sedimentary environment of Langping in Late Viséan-Serpukhovian is suitable for the development of benthic communities. The current appearance of reefs is determined by both coral populations ecological characteristics and reef-building environment. [ABSTRACT FROM AUTHOR]

In social networks, users often engage with like-minded peers. This selective exposure to opinions might result in echo chambers, i.e., political fragmentation and social polarization of user interactions. When echo chambers form, opinions have a bimodal distribution with two peaks on opposite sides. In certain issues, where either extreme positions contain a degree of misinformation, neutral consensus is preferable for promoting discourse. In this paper, we use an opinion dynamics model that naturally forms echo chambers in order to find a feedback mechanism that bridges these communities and leads to a neutral consensus. We introduce the random dynamical nudge (RDN), which presents each agent with input from a random selection of other agents' opinions and does not require surveillance of every person's opinions. Our computational results in two different models suggest that the RDN leads to a unimodal distribution of opinions centered around the neutral consensus. Furthermore, the RDN is effective both for preventing the formation of echo chambers and also for depolarizing existing echo chambers. Due to the simple and robust nature of the RDN, social media networks might be able to implement a version of this self-feedback mechanism, when appropriate, to prevent the segregation of online communities on complex social issues. [ABSTRACT FROM AUTHOR]

Drought is a natural disaster that causes much damage to the communities. Recently, water demand has been increasing sharply due to the population growth and the development process. By approaching the amount of water demand to the natural supplies, any decrease in the water supply may lead to a considerable negative socio-economic consequence. In this condition, the sense of drought prevails over the physical drought. Therefore, usual drought indices can not be used for characterizing and monitoring the drought in a basin. In this paper, multivariate standardized drought feeling index (MSDFI) is introduced which represents two dimensions of water management: (1) water supply in terms of precipitation and (2) water demand in terms of population. The MSDFI is calculated and its variation over time is compared to the standardized precipitation index (SPI). According to the results, MSDFI values in the early years were usually higher than SPI values and vice versa in the last years. This situation is highly correlated with the population trend in the basin. Thereafter, intensity of drought index (IDI) was defined as the difference between MSDFI and SPI to show the role of water demand in the drought feeling. Results show that IDI has an increasing trend in the populated areas, generally downstream of the basin, where population growth is high. In contrast, in the sparsely populated areas generally upstream of the basin where population growth is low and even negative due to migration, the IDI does not show any significant sense of drought. [ABSTRACT FROM AUTHOR]

Atoll islands face increasing coastal risks (coastal erosion and marine flooding) due to climate change, especially sea-level rise. To face increasing coastal risks, various adaptation options are considered by atoll countries and territories, including in particular hard protection (preferred option to date), Nature-based Solutions (increasingly used) and island raising (considered a longer-term solution and a potential alternative to international migration, e.g. in the Maldives). Internal relocation within the same atoll island or atoll, which refers to long-term community movement from one threatened island area or island to a safer island area or island, has previously been disregarded by scholars as a potentially relevant climate adaptation strategy. However, in low-lying coastal areas, it offers real potential to address the dual context of increasing climate risks and the shrinking of the solution space. This paper assesses the potential of internal relocation for atolls by applying to Rangiroa Atoll, French Polynesia, Central Pacific, a two-fold assessment framework questioning its physical relevance (are some islands high enough to host settlements in the future?) and its societal feasibility (are the political-institutional and socio-economic conditions in place? Are people willing to relocate?). The findings show that internal relocation is both relevant and feasible on Rangiroa Atoll and should therefore serve as a pillar to develop robust in situ adaptation pathways in this atoll. [ABSTRACT FROM AUTHOR]

Detecting communities in complex networks is of paramount importance, and its wide range of real-life applications in various areas has caused a lot of attention to be paid to it, and many efforts have been made to have efficient and accurate algorithms for this purpose. In this paper, we proposed a non-cooperative game theoretic-based algorithm that is able to detect overlapping communities. In this algorithm, nodes are regarded as players, and communities are assumed to be groups of players with similar strategies. Our two-phase algorithm detects communities and the overlapping nodes in separate phases that, while increasing the accuracy, especially in detecting overlapping nodes, brings about higher algorithm speed. Moreover, there is no need for setting parameters regarding the size or number of communities, and the absence of any stochastic process caused this algorithm to be stable. By appropriately adjusting stop criteria, our algorithm can be categorized among those with linear time complexity, making it highly scalable for large networks. Experiments on synthetic and real-world networks demonstrate our algorithm's good performance compared to similar algorithms in terms of detected overlapping nodes, detected communities size distribution, modularity, and normalized mutual information. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Mobility-control policy is a controversial nonpharmacological approach to pandemic control due to its restriction on people's liberty and economic impacts. Due to the computational complexity of mobility control, it is challenging to assess or compare alternative policies. Here, we develop a pandemic policy assessment system that employs artificial intelligence (AI) to evaluate and analyze mobility-control policies. The system includes three components: (1) a general simulation framework that models different policies to comparable network-flow control problems; (2) a reinforcement-learning (RL) oracle to explore the upper-bound execution results of policies; and (3) comprehensive protocols for converting the RL results to policy-assessment measures, including execution complexity, effectiveness, cost and benefit, and risk. We applied the system to real-world metropolitan data and evaluated three popular policies: city lockdown, community quarantine, and route management. For each policy, we generated mobility-pandemic trade-off frontiers. The results manifest that the smartest policies, such as route management, have high execution complexity but limited additional gain from mobility retention. In contrast, a moderate-level intelligent policy such as community quarantine has acceptable execution complexity but can effectively suppress infections and largely mitigate mobility interventions. The frontiers also show one or two turning points, reflecting the safe threshold of mobility retention when considering policy-execution errors. In addition, we simulated different policy environments and found inspirations for the current policy debates on the zero-COVID policy, vaccination policy, and relaxing restrictions. [ABSTRACT FROM AUTHOR]

Acinetobacter species are widely known opportunistic pathogens causing severe community and healthcare-associated infections. One such emerging pathogen, Acinetobacter colistiniresistens, is known to exhibit intrinsic resistance to colistin. We investigated the molecular characteristics of A. colistiniresistens strain C-214, isolated from the fecal sample of a healthy community member, as part of a cohort study being conducted in Segamat, Malaysia. Comparison of the whole genome sequence of C-214 with other A. colistiniresistens sequences retrieved from the NCBI database showed 95% sequence identity or more with many of the genome sequences representing that species. Use of the Galleria mellonella killing assay showed that C-214 was pathogenic in this model infection system. The strain C-214 had a colistin and polymyxin B MIC of 32 and 16 mg/L, respectively. Besides, it was resistant to cefotaxime, amikacin, and tetracycline and showed moderate biofilm-producing ability. Different genes associated with virulence or resistance to major classes of antibiotics were detected. We observed mutations in lpxA/C/D in C-214 and other A. colistiniresistens strains as probable causes of colistin resistance, but the biological effects of these mutations require further investigation. This study provides genomic insights into A. colistiniresistens, a potentially pathogenic bacterium isolated from a community member and notes the public health threat it may pose. [ABSTRACT FROM AUTHOR]

Respiratory viruses that were suppressed through previous lockdowns during the COVID-19 pandemic have recently started to co-circulate with SARS-CoV-2. Understanding the clinical characteristics and symptomatology of different respiratory viral infections can help address the challenges related to the identification of cases and the understanding of SARS-CoV-2 variants' evolutionary patterns. Flu Watch (2006–2011) and Virus Watch (2020–2022) are household community cohort studies monitoring the epidemiology of influenza, respiratory syncytial virus, rhinovirus, seasonal coronavirus, and SARS-CoV-2, in England and Wales. This study describes and compares the proportion of symptoms reported during illnesses infected by common respiratory viruses. The SARS-CoV-2 symptom profile increasingly resembles that of other respiratory viruses as new strains emerge. Increased cough, sore throat, runny nose, and sneezing are associated with the emergence of the Omicron strains. As SARS-CoV-2 becomes endemic, monitoring the evolution of its symptomatology associated with new variants will be critical for clinical surveillance. [ABSTRACT FROM AUTHOR]

High performance computing has a great potential to provide a range of significant benefits for investigating biological systems. These systems often present large modelling problems with many coupled subsystems, such as when studying colonies of bacteria cells. The aim to understand cell colonies has generated substantial interest as they can have strong economic and societal impacts through their roles in in industrial bioreactors and complex community structures, called biofilms, found in clinical settings. Investigating these communities through realistic models can rapidly exceed the capabilities of current serial software. Here, we introduce BMX, a software system developed for the high performance modelling of large cell communities by utilising GPU acceleration. BMX builds upon the AMRex adaptive mesh refinement package to efficiently model cell colony formation under realistic laboratory conditions. Using simple test scenarios with varying nutrient availability, we show that BMX is capable of correctly reproducing observed behavior of bacterial colonies on realistic time scales demonstrating a potential application of high performance computing to colony modelling. The open source software is available from the zenodo repository https://doi.org/10.5281/zenodo.8084270 under the BSD-2-Clause licence. [ABSTRACT FROM AUTHOR]

Multidisciplinary Design Optimization (MDO) enables one to reach a better solution than by optimizing each discipline independently. In particular, the optimal structure of a drone varies depending on the selected material. The C O 2 footprint of a solar-powered High Altitude Long Endurance (HALE) drone is optimized here, where the structural materials used is one of the design variables. Optimization is performed using a modified version of OpenAeroStruct, a framework based on OpenMDAO. Our EcoHale framework is validated on a classical HALE testcase in the MDO community (FBhale) constructed using high-fidelity codes compared to our low-fidelity approach. The originality of our work is to include two specific disciplines (energy and environment) to adapt to a new problem of C O 2 minimization. The choice of eco-materials is performed in the global MDO loop from a choice of discrete materials. This is achieved through a variable relaxation, enabling the use of continuous optimization algorithms inspired from multimaterial topology optimization. Our results show that, in our specific case of electric drone, the optimal material in terms of C O 2 footprint is also the optimal material in terms of weight. It opens the door to new researches on digital microarchitectured materials that will decrease the C O 2 footprint of the drone. [ABSTRACT FROM AUTHOR]

The incidence of plague has rebounded in the Americas, Asia, and Africa alongside rapid globalization and climate change. Previous studies have shown local climate to have significant nonlinear effects on plague dynamics among rodent communities. We analyzed an 18-year database of plague, spanning 1998 to 2015, in the foci of Mongolia and China to trace the associations between marmot plague and climate factors. Our results suggested a density-dependent effect of precipitation and a geographic location-dependent effect of temperature on marmot plague. That is, a significantly positive relationship was evident between risk of plague and precipitation only when the marmot density exceeded a certain threshold. The geographical heterogeneity of the temperature effect and the contrasting slopes of influence for the Qinghai-Tibet Plateau (QTP) and other regions in the study (nQTP) were primarily related to diversity of climate and landscape types. [ABSTRACT FROM AUTHOR]

Sea level rise (SLR) is projected to impact approximately one billion people by 2100. For many coastal communities, retreat is the most viable long-term option due to exposure risk under SLR and increased coastal hazards. Our research analyzes the costs of retreating coastal development at an iconic beach in Hawaiʻi that is experiencing severe erosion. We assess three retreat approaches: all-at-once, threshold-based, and reactive. Utilizing detailed SLR modeling projected to the year 2100, we estimate the public and private costs of retreat approaches and the amount of increased beach area. We find an all-at-once approach is most costly but maintains the largest beach area over time. In contrast, a reactive approach has the lowest direct costs but offers the least beach area gained over time and incurs the greatest public safety and environmental risk. The threshold-based approach largely mitigates public safety and environmental risks while providing more beach area over time than the reactive approach with similar direct costs. We find that a threshold-based approach should be further explored as a SLR response for coastal communities to maintain their sandy beach areas. Our study informs coastal adaptation research and identifies a new framework to explore the financial costs alongside social and ecological values. [ABSTRACT FROM AUTHOR]

For maritime navigation in the Arctic, sea ice charts are an essential tool, which still to this day is drawn manually by professional ice analysts. The total Sea Ice Concentration (SIC) is the primary descriptor of the charts and indicates the fraction of ice in an ocean surface area. Naturally, automating the SIC chart creation is desired. However, the optimal representation of the corresponding machine-learning task is ambivalent and discussed in the community. In this study, we explore the representation with either regressional or classification objectives, each with two different (weighted) loss functions: Mean Square Error and Binary Cross-Entropy, and Categorical Cross-Entropy and the Earth Mover's Distance, respectively. While all models achieve good results they differ as the regression-based models obtain the highest numerical similarity to the reference charts, whereas the classification-optimised models generate results more visually pleasing and consistent. Rescaling the loss functions with inverse class weights improves the performance for intermediate classes at the expense of open water and fully-covered sea ice areas. [ABSTRACT FROM AUTHOR]

In studying resilience in temporal human networks, relying solely on global network measures would be inadequate; latent sub-structural network mechanisms need to be examined to determine the extent of impact and recovery of these networks during perturbations, such as urban flooding. In this study, we utilize high-resolution aggregated location-based data to construct temporal human mobility networks in Houston in the context of the 2017 Hurricane Harvey. We examine motif distribution, motif persistence, temporal stability, and motif attributes to reveal latent sub-structural mechanisms related to the resilience of human mobility networks during disaster-induced perturbations. The results show that urban flood impacts persist in human mobility networks at the sub-structure level for several weeks. The impact extent and recovery duration are heterogeneous across different network types. Also, while perturbation impacts persist at the sub-structure level, global topological network properties indicate that the network has recovered. The findings highlight the importance of examining the microstructures and their dynamic processes and attributes in understanding the resilience of temporal human mobility networks (and other temporal networks). The findings can also provide disaster managers, public officials, and transportation planners with insights to better evaluate impacts and monitor recovery in affected communities. [ABSTRACT FROM AUTHOR]

Wildfire events are becoming more frequent and severe on a global scale. Rising temperatures, prolonged drought, and the presence of pyrophytic invasive grasses are contributing to the degradation of native vegetation communities. Within the Great Basin region of the western U.S., increasing wildfire frequency is transforming the ecosystem toward a higher degree of homogeneity, one dominated by invasive annual grasses and declining landscape productivity. Greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) are a species of conservation concern that rely on large tracts of structurally and functionally diverse sagebrush (Artemisia spp.) communities. Using a 12-year (2008–2019) telemetry dataset, we documented immediate impacts of wildfire on demographic rates of a population of sage-grouse that were exposed to two large wildfire events (Virginia Mountains Fire Complex—2016; Long Valley Fire—2017) near the border of California and Nevada. Spatiotemporal heterogeneity in demographic rates were accounted for using a Before-After Control-Impact Paired Series (BACIPS) study design. Results revealed a 40% reduction in adult survival and a 79% reduction in nest survival within areas impacted by wildfires. Our results indicate that wildfire has strong and immediate impacts to two key life stages of a sagebrush indicator species and underscores the importance of fire suppression and immediate restoration following wildfire events. [ABSTRACT FROM AUTHOR]

We present an approach (knowledge-and-data-driven, KDD, modeling) that allows us to get closer to understanding the processes that affect the dynamics of plankton communities. This approach, based on the use of time series obtained as a result of ecosystem monitoring, combines the key features of both the knowledge-driven modeling (mechanistic models) and data-driven (DD) modeling. Using a KDD model, we reveal the phytoplankton growth-rate fluctuations in the ecosystem of the Naroch Lakes and determine the degree of phase synchronization between fluctuations in the phytoplankton growth rate and temperature variations. More specifically, we estimate a numerical value of the phase locking index (PLI), which allows us to assess how temperature fluctuations affect the dynamics of phytoplankton growth rates. Since, within the framework of KDD modeling, we directly include the time series obtained as a result of field measurements in the model equations, the dynamics of the phytoplankton growth rate obtained from the KDD model reflect the behavior of the lake ecosystem as a whole, and PLI can be considered as a holistic parameter. [ABSTRACT FROM AUTHOR]

Dog-infecting haemotropic mycoplasmas (haemoplasmas), such as Mycoplasmahaemocanis and Candidatus Mycoplasma haematoparvum are common blood-borne pathogens of canines that can potentially inflict a substantial burden of disease, particularly in immunosuppressed individuals. Nonetheless, the transmission of these pathogens remains debated as more evidence emerges that they may not be transmitted by vectors, but instead use alternative methods such as aggressive interactions and vertical transmission. Here, we treated forty dogs with two different topically-acting ectoparasiticide products able to prevent vector-borne pathogen infections during an 8-month community trial in Cambodia. A total absence of ectoparasites were observed at all time points, and no new infections caused by pathogens confirmed as being vectorially-transmitted were detected, i.e., Babesiavogeli, Ehrlichiacanis, Anaplasmaplatys, and Hepatozooncanis. Conversely, the number of haemoplasma infections in dogs on both ectoparasiticides rose significantly, with an incidence of 26 infections per 100 dogs at risk per year, providing strong evidence of non-vectorial transmission. Over the study period, dog aggression and fighting were frequently observed, highlighting a different potential mode of transmission. This study presents the first robust evidence that canine haemoplasmas may be transmitted without arthropod vectors drawing attention to the need for new methods to prevent their transmission. [ABSTRACT FROM AUTHOR]

Partisan sorting in residential environments is an enduring feature of contemporary American politics, but little research has examined partisan segregation individuals experience in activity spaces through their daily activities. Relying on advances in spatial computation and global positioning system data on everyday mobility flows collected from smartphones, we measure experienced partisan segregation in two ways: place-level partisan segregation based on the partisan composition of its daily visitors and community-level experienced partisan segregation based on the segregation level of places visited by its residents. We find that partisan segregation experienced in places varies across different geographic areas, location types, and time periods. Moreover, partisan segregation is distinct from experienced segregation by race and income. We also find that partisan segregation individuals experience is relatively lower when they visit places beyond their residential areas, but partisan segregation in residential space and activity space is strongly correlated. Residents living in predominantly black, liberal, low-income, non-immigrant, more public transit-dependent, and central city communities tend to experience a higher level of partisan segregation. [ABSTRACT FROM AUTHOR]

Livestock mobility exacerbates infectious disease risks across sub-Saharan Africa, but enables critical access to grazing and water resources, and trade. Identifying locations of high livestock traffic offers opportunities for targeted control. We focus on Tanzanian agropastoral and pastoral communities that account respectively for over 75% and 15% of livestock husbandry in eastern Africa. We construct networks of livestock connectivity based on participatory mapping data on herd movements reported by village livestock keepers as well as data from trading points to understand how seasonal availability of resources, land-use and trade influence the movements of livestock. In communities that practise agropastoralism, inter- and intra-village connectivity through communal livestock resources (e.g. pasture and water) was 1.9 times higher in the dry compared to the wet season suggesting greater livestock traffic and increased contact probability. In contrast, livestock from pastoral communities were 1.6 times more connected at communal locations during the wet season when they also tended to move farther (by 3 km compared to the dry season). Trade-linked movements were twice more likely from rural to urban locations. Urban locations were central to all networks, particularly those with potentially high onward movements, for example to abattoirs, livestock holding grounds, or other markets, including beyond national boundaries. We demonstrate how livestock movement information can be used to devise strategic interventions that target critical livestock aggregation points (i.e. locations of high centrality values) and times (i.e. prior to and after the wet season in pastoral and agropastoral areas, respectively). Such targeted interventions are a cost-effective approach to limit infection without restricting livestock mobility critical to sustainable livelihoods. [ABSTRACT FROM AUTHOR]

Elasmobranchs, which include sharks and batoids, play critical roles in maintaining the integrity and stability of marine food webs. However, these cartilaginous fish are among the most threatened vertebrate lineages due to their widespread depletion. Consequently, understanding dynamics and predicting changes of elasmobranch communities are major research topics in conservation ecology. Here, we leverage long-term catch data from a standardized bottom trawl survey conducted from 1996 to 2019, to evaluate the spatio-temporal dynamics of the elasmobranch community in the heavily exploited Adriatic Sea, where these fish have historically been depleted. We use joint species distribution modeling to quantify the responses of the species to environmental variation while also including important traits such as species age at first maturity, reproductive mode, trophic level, and phylogenetic information. We present spatio-temporal changes in the species community and associated modification of the trait composition, highlighting strong spatial and depth-mediated patterning. We observed an overall increase in the abundance of the dominant elasmobranch species, except for spurdog, which has shown a continued decline. However, our results showed that the present community displays lower age at first maturity and a smaller fraction of viviparous species compared to the earlier observed community due to changes in species' relative abundance. The selected traits contributed considerably to explaining community patterns, suggesting that the integration of trait-based approaches in elasmobranch community analyses can aid efforts to conserve this important lineage of fish. [ABSTRACT FROM AUTHOR]

Figurative depictions in art first occur ca. 50,000 years ago in Europe, Africa, and Southeast Asia. Considered by most as an advanced form of symbolic behavior, they are restricted to our species. Here, we report a piece of ornament interpreted as a phallus-like representation. It was found in a 42,000 ca.-year-old Upper Paleolithic archaeological layer at the open-air archaeological site of Tolbor-21, in Mongolia. Mineralogical, microscopic, and rugosimetric analyses points toward the allochthonous origin of the pendant and a complex functional history. Three-dimensional phallic pendants are unknown in the Paleolithic record, and this discovery predates the earliest known sexed anthropomorphic representation. It attests that hunter-gatherer communities used sex anatomical attributes as symbols at a very early stage of their dispersal in the region. The pendant was produced during a period that overlaps with age estimates for early introgression events between Homo sapiens and Denisovans, and in a region where such encounters are plausible. [ABSTRACT FROM AUTHOR]

Coral reefs are iconic examples of climate change impacts because climate-induced heat stress causes the breakdown of the coral-algal symbiosis leading to a spectacular loss of color, termed 'coral bleaching'. To examine the fine-scale dynamics of this process, we re-sampled 600 individually marked Montipora capitata colonies from across Kāne'ohe Bay, Hawai'i and compared the algal symbiont composition before and after the 2019 bleaching event. The relative proportion of the heat-tolerant symbiont Durusdinium in corals increased in most parts of the bay following the bleaching event. Despite this widespread increase in abundance of Durusdinium, the overall algal symbiont community composition was largely unchanged, and hydrodynamically defined regions of the bay retained their distinct pre-bleaching compositions. We explain ~ 21% of the total variation, of which depth and temperature variability were the most significant environmental drivers of Symbiodiniaceae community composition by site regardless of bleaching intensity or change in relative proportion of Durusdinium. We hypothesize that the plasticity of symbiont composition in corals may be constrained to adaptively match the long-term environmental conditions surrounding the holobiont, despite an individual coral's stress and bleaching response. [ABSTRACT FROM AUTHOR]

Volcanism can cause major impacts, including climate change and mass extinctions. However, the impact of monogenetic volcanism is often considered as limited in volcanological research. This work provides for the first time an interdisciplinary approach to the socio-ecological impact of monogenetic volcanism in a key region, the La Garrotxa Volcanic Field (GVF, Girona, NE Iberia), where intense monogenetic volcanic activity occurred in the past. The analyses of a sedimentary sequence from the GVF enabled identifying previously unknown volcanic eruptions in the time interval 14–8.4 ka cal BP, constrain their volcanic stratigraphy and age, and unfold the effects of environmental change on geomorphology, vegetation, aquatic organisms and humans. Moreover, we reconstruct the major palaeoenvironmental changes caused by the eruptions in terms of fire episodes and subsequent disturbance on vegetation, hydrology and limnological conditions. When put in context with the archaeological record, it appears that the last hunter–gatherer communities were resilient at an extra-local scale, facing episodes of vulnerability due to volcanic activity, suggesting that their flexible nomadic patterns and foraging economies were an efficient source of risk management against the volcanic eruptions and their ecological impacts. [ABSTRACT FROM AUTHOR]

Human microbiome research is helped by the characterization of microbial networks, as these may reveal key microbes that can be targeted for beneficial health effects. Prevailing methods of microbial network characterization are based on measures of association, often applied to limited sampling points in time. Here, we demonstrate the potential of wavelet clustering, a technique that clusters time series based on similarities in their spectral characteristics. We illustrate this technique with synthetic time series and apply wavelet clustering to densely sampled human gut microbiome time series. We compare our results with hierarchical clustering based on temporal correlations in abundance, within and across individuals, and show that the cluster trees obtained by using either method are significantly different in terms of elements clustered together, branching structure and total branch length. By capitalizing on the dynamic nature of the human microbiome, wavelet clustering reveals community structures that remain obscured in correlation-based methods. [ABSTRACT FROM AUTHOR]

Wildfire is a natural disturbance in boreal forest systems that has been predicted to increase in frequency, intensity, and extent due to climate change. Most studies tend to assess the recovery of one component of the community at a time but here we use DNA metabarcoding to simultaneously monitor soil bacteria, fungi, and arthropods along an 85-year chronosequence following wildfire in jack pine-dominated ecosites. We describe soil successional and community assembly processes to better inform sustainable forest management practices. Soil taxa showed different recovery trajectories following wildfire. Bacteria shared a large core community across stand development stages (~ 95–97% of their unique sequences) and appeared to recover relatively quickly by crown closure. By comparison fungi and arthropods shared smaller core communities (64–77% and 68–69%, respectively) and each stage appeared to support unique biodiversity. We show the importance of maintaining a mosaic ecosystem that represents each stand development stage to maintain the full suite of biodiversity in soils following wildfire, especially for fungi and arthropods. These results will provide a useful baseline for comparison when assessing the effects of human disturbance such as harvest or for assessing the effects of more frequent wildfire events due to climate change. [ABSTRACT FROM AUTHOR]

Ultraviolet (UV) disinfection has been incorporated into both drinking water and wastewater treatment processes for several decades; however, it comes with negative environmental consequences such as high energy demands and the use of mercury. Understanding how to scale and build climate responsive technologies is key in fulfilling the intersection of UN Sustainable Development Goals 6 and 13. One technology that addresses the drawbacks of conventional wastewater UV disinfection systems, while providing a climate responsive solution, is UV light emitting diodes (LEDs). The objective of this study was to compare performance of bench-scale 280 nm UV LEDs to bench-scale low pressure (LP) lamps and full-scale UV treated wastewater samples. Results from the study demonstrated that the UV LED system provides a robust treatment that outperformed LP systems at the bench-scale. A comparison of relative energy consumptions of the UV LED system at 20 mJ cm−2 and LP system at 30 and 40 mJ cm−2 was completed. Based on current projections for wall plug efficiencies (WPE) of UV LED it is expected that the energy consumption of LED reactors will be on par or lower compared to the LP systems by 2025. This study determined that, at a WPE of 20%, the equivalent UV LED system would lead to a 24.6% and 43.4% reduction in power consumption for the 30 and 40 mJ cm−2 scenarios, respectively. [ABSTRACT FROM AUTHOR]

Face masks are often recommended in community settings to prevent the airborne transmission of respiratory viruses or bacteria. Our first objective was to develop an experimental bench to assess the viral filtration efficiency (VFE) of a mask with a methodology similar to the normative measurement of bacterial filtration efficiency (BFE) used to determine the filtration performance of medical masks. Then, using three categories of masks of increasing filtration quality (two types of community masks and one type of medical mask), filtration performances measured ranged from 61.4 to 98.8% of BFE and from 65.5 to 99.2% of VFE. A strong correlation (r = 0.983) between bacterial and viral filtration efficiency was observed for all types of masks and for the same droplets size in the 2–3 µm range. This result confirms the relevance of the EN14189:2019 standard using bacterial bioaerosols to evaluate mask filtration, to also extrapolate mask performances whatever their filtration quality against viral bioaerosols. Indeed, it appears that the filtration efficiency of masks (for micrometer droplet sizes and low bioaerosol exposure times) depends mainly on the size of the airborne droplet, rather than on the size of the infectious agent contained in that droplet. [ABSTRACT FROM AUTHOR]

Although methodological advances have been made over the past years, a widely applicable, easily scalable and cost-effective procedure that can be routinely used to isolate specific ribonucleoprotein complexes (RNPs) remains elusive. We describe the "Silica-based Acidic Phase Separation (SAPS)-capture" workflow. This versatile method combines previously described techniques in a cost-effective, optimal and widely applicable protocol. The specific RNP isolation procedure is performed on a pre-purified RNP sample instead of cell lysate. This combination of protocols results in an increased RNP/bead ratio and by consequence a reduced experimental cost. To validate the method, the 18S rRNP of S. cerevisiae was captured and to illustrate its applicability we isolated the complete repertoire of RNPs in A. thaliana. The procedure we describe can provide the community with a powerful tool to advance the study of the ribonome of a specific RNA molecule in any organism or tissue type. [ABSTRACT FROM AUTHOR]

Pastoralists in the Borana zone of southern Ethiopia are grappling with climatic risks and impacts, and their livelihoods appear to be precarious. The long-term changes in precipitation, temperature and extreme events are under-researched aspects of climate risk in the study area. Climate observations, local people's experiences, and memories of weather and drought patterns were analysed in this work to better understand the climate risks in the study region and provide actionable knowledge to facilitate adaptations. In southern Ethiopia, the primary drivers of climate risks are rainfall variabilities, rising temperatures, and drought. The annual rainfall variability observed in the study area (20–35%) is greater than the overall estimate for Eastern Africa (15–25%), indicative of a heightened climate risk in this area. Furthermore, seasonal and intra-seasonal rainfall variabilities are being aggravated by rising temperatures, leading to increased frequency and magnitude of extreme events, particularly in the lowland area. These changes, specifically droughts of different intensities occurring every 2–3 years, erode the livelihood of the pastoralists. The lack of consensus among stakeholders as to the causes and aggravating factors of these climate changes impedes adaptation actions. The authors recommend the importance of initiating a participatory platform that will facilitate discussion on climate change to create a common understanding of the problem and relate it to public policy. The use of gridded precipitation and temperature data is recommended in future research to improve the availability of climate information for climate risk management. In addition, the use of mixed methods and local knowledge, as demonstrated in this study, is highly recommended to better understand climate risks, particularly when there is a limited availability and quality of long-time-series climate data. [ABSTRACT FROM AUTHOR]

Retrospective perceptions of parental bonding may be a protective factor for emotional health. These perceptions are grounded in autobiographical memory, which plays a key role in the onset and maintenance of depressive symptomatology. The aim of the present study was to explore whether the emotional valence of autobiographical memories (positive and negative) and the dimensions of parental bonding (care and protection) have an impact on depressive symptomatology, examining the role of depressive rumination and possible age-related differences. A total of 139 young adults (18–28 years) and 124 older adults (65–88 years) completed the Parental Bonding Instrument, the Beck Depression Inventory (BDI-II), the Autobiographical Memory Test and the Short Depressive Rumination Scale. Our results show that positive autobiographical memories serve as a protective factor for depressive symptoms in both young and older adults. Additionally, in young adults, high paternal care and protection scores are associated with increased negative autobiographical memories, although this association has no effect on depressive symptomatology. In older adults, high maternal protection scores are directly related to greater depressive symptomatology. Depressive rumination significantly increases depressive symptoms in both young and older adults, with an increase in negative autobiographical memories in young adults, and a decrease in such memories in older adults. Our findings progress the understanding of the relationships between parental bonding and autobiographical memory with respect to emotional disorders, which, in turn, will help in the design of effective prevention measures. [ABSTRACT FROM AUTHOR]

Flood nowcasting refers to near-future prediction of flood status as an extreme weather event unfolds to enhance situational awareness. The objective of this study was to adopt and test a novel structured deep-learning model for urban flood nowcasting by integrating physics-based and human-sensed features. We present a new computational modeling framework including an attention-based spatial–temporal graph convolution network (ASTGCN) model and different streams of data that are collected in real-time, preprocessed, and fed into the model to consider spatial and temporal information and dependencies that improve flood nowcasting. The novelty of the computational modeling framework is threefold: first, the model is capable of considering spatial and temporal dependencies in inundation propagation thanks to the spatial and temporal graph convolutional modules; second, it enables capturing the influence of heterogeneous temporal data streams that can signal flooding status, including physics-based features (e.g., rainfall intensity and water elevation) and human-sensed data (e.g., residents' flood reports and fluctuations of human activity) on flood nowcasting. Third, its attention mechanism enables the model to direct its focus to the most influential features that vary dynamically and influence the flood nowcasting. We show the application of the modeling framework in the context of Harris County, Texas, as the study area and 2017 Hurricane Harvey as the flood event. Three categories of features are used for nowcasting the extent of flood inundation in different census tracts: (i) static features that capture spatial characteristics of various locations and influence their flood status similarity, (ii) physics-based dynamic features that capture changes in hydrodynamic variables, and (iii) heterogeneous human-sensed dynamic features that capture various aspects of residents' activities that can provide information regarding flood status. Results indicate that the ASTGCN model provides superior performance for nowcasting of urban flood inundation at the census-tract level, with precision 0.808 and recall 0.891, which shows the model performs better compared with other state-of-the-art models. Moreover, ASTGCN model performance improves when heterogeneous dynamic features are added into the model that solely relies on physics-based features, which demonstrates the promise of using heterogenous human-sensed data for flood nowcasting. Given the results of the comparisons of the models, the proposed modeling framework has the potential to be more investigated when more data of historical events are available in order to develop a predictive tool to provide community responders with an enhanced prediction of the flood inundation during urban flood. [ABSTRACT FROM AUTHOR]

Chronic obstructive pulmonary disease (COPD) is a common disease and among the top causes of mortality worldwide but can be prevented and treated. This study aims to estimate the awareness of COPD among the Syrian population. A cross-sectional anonymous self-administered online survey was conducted by using Google Forms on Social Media platforms. The questionnaire included demographic, smoke-related and COPD-related questions. This study included 1607 participants with 930 (57.8%) females, 40% aging 21–25 years old, more than 90% being university students/graduates and 67.8% living in cities. Around half were either active smokers or had second-hand smoke exposure. After excluding participants in health-related fields who were 950 participants, only 25.4% of the remaining had ever heard of the term COPD. Knowing about COPD was not associated with reported smoking habits. No significant differences in awareness were seen between city and countryside dwellers, governate groups, genders, or age groups. Being in a health-related field was a major factor of being aware of COPD. COPD awareness in Syria is low, even amongst the well-educated group. Moreover, COPD risk factors of smoking and exposure to indoor and outdoor pollutants are common. Raising awareness is crucial in the Syrian community as COPD is highly prevalence. [ABSTRACT FROM AUTHOR]

Ebola virus disease (EVD) is one of the most highly stigmatised diseases in any affected country because of the disease's high infectivity and case fatality rate. Infected individuals and most especially survivors are often stigmatised by their communities for fear of contagion. We propose and analyse a mathematical model to examine the impact of stigmatisation of Ebola survivors on the disease dynamics. The model captures both the internal stigmatisation experienced by infected individuals after witnessing survivors being stigmatised and the external stigmatisation imposed on survivors by their communities. The results obtained from our analysis and simulations show that both internal and external stigma may lead to an increase in the burden of Ebola virus disease by sustaining the number of infected individuals who hide their infection and the number of unsafe burials of deceased Ebola victims. Strategies that seek to put an end to both forms of stigmatisation and promote safe burials will therefore go a long way in averting the EVD burden. [ABSTRACT FROM AUTHOR]

The market for the application of probiotics as a livestock health improvement supplement has increased in recent years. However, most of the available products are quality-controlled using low-resolution techniques and un-curated databases, resulting in misidentification and incorrect product labels. In this work, we deployed two workflows and compared results obtained by full-length 16S rRNA genes (16S) and metagenomic (Meta) data to investigate their reliability for the microbial composition of both liquid and solid forms of animal probiotic products using Oxford Nanopore long-read-only (without short-read). Our result revealed that 16S amplicon data permits to detect the bacterial microbiota even with the low abundance in the samples. Moreover, the 16S approach has the potential to provide species-level resolution for prokaryotes but not for assessing yeast communities. Whereas, Meta data has more power to recover of high-quality metagenome-assembled genomes that enables detailed exploration of both bacterial and yeast populations, as well as antimicrobial resistance genes, and functional genes in the population. Our findings clearly demonstrate that implementing these workflows with long-read-only monitoring could be applied to assessing the quality and safety of probiotic products for animals and evaluating the quality of probiotic products on the market. This would benefit the sustained growth of the livestock probiotic industry. [ABSTRACT FROM AUTHOR]

The morbidity of skin tumors (ST) in China is a great concern as the population ages. No epidemiological survey on ST in elderly communities in China has been reported. A questionnaire survey was conducted among the residents over 60 years old in a community in Shanghai, China from May 1, 2011 to November 30, 2011. The prevalence of cutaneous tumors and associated factors were analyzed. Among 2038 valid cases, a total of 78 (3.8%, 95% CI 3.0–4.7) skin cancers (SC) were confirmed. According to the final multivariate regression analysis, age, gender and previous occupation were the significantly influential factors for SC. Actinic keratosis (AK) accounted for the largest proportion (63, 3.1%) in SC. The head and neck was the physiological site with the highest incidence of SC (64, 82.1%), and AK was the most common (55, 87.3%) in head and neck SC. The common concomitant diseases of SC were hypertension (26, 33.3%) and diabetes mellitus (9, 11.5%). Seborrheic keratosis (SK) was the most common benign skin tumor with a prevalence of 100%. Men and women developed SK in significantly different parts of the body (P < 0.0001). The incidence of ST in the elderly population in Shanghai community increased with age. ST preferred to occur in the head and neck, which might be attributed to excessive ultraviolet (UV) exposure in these areas. Therefore, early diagnosis and sun-protection education are essential interventions for ST in the elderly. [ABSTRACT FROM AUTHOR]

This community-based cross-sectional study was conducted among 1190 randomly selected rural households in northwest Ethiopia to assess hand hygiene practice and associated factors. Frequent handwashing with rubbing agents, drying mechanisms; and condition of fingernails were used to assess hand hygiene practice. Multivariable binary logistic regression analysis was used to identify factors associated with hand hygiene and statistically significant association was declared on the basis of adjusted odds ratio (AOR) with 95% confidence interval (CI) and p-values < 0.05. Results showed that 28.8% (95% CI 26.2, 31.4%) of the households had good hand hygiene practice. Good hand hygiene practice was significantly associated with formal education attended household heads (AOR 1.79, 95% CI 1.33, 2.40), family discussion on sanitation (AOR 1.56, 95% CI 1.08, 2.26), provision of health education (AOR 2.23, 95% CI 1.62, 3.06), and availability of water (AOR 3.51, 95% CI 1.02, 12.05). In conclusion, about one-third of the rural households had good hand hygiene practice and more than two-third had poor hand hygiene practice in the study area, and this may imply that hands in the area may play roles in spreading infections in the community. Therefore, people need to be informed to always keep their hand hygiene good. [ABSTRACT FROM AUTHOR]

Medieval southern Italy is typically viewed as a region where political, religious, and cultural systems coexisted and clashed. Written sources often focus on elites and give an image of a hierarchical feudal society supported by a farming economy. We undertook an interdisciplinary study combining historical and archaeological evidence with Bayesian modelling of multi-isotope data from human (n = 134) and faunal (n = 21) skeletal remains to inform on the socioeconomic organisation, cultural practices, and demographics of medieval communities in Capitanata (southern Italy). Isotopic results show significant dietary differences within local populations supportive of marked socioeconomic hierarchies. Bayesian dietary modelling suggested that cereal production, followed by animal management practices, was the economic basis of the region. However, minor consumption of marine fish, potentially associated with Christian practices, revealed intra-regional trade. At the site of Tertiveri, isotope-based clustering and Bayesian spatial modelling identified migrant individuals likely from the Alpine region plus one Muslim individual from the Mediterranean coastline. Our results align with the prevailing image of Medieval southern Italy but they also showcase how Bayesian methods and multi-isotope data can be used to directly inform on the history of local communities and of the legacy that these left. [ABSTRACT FROM AUTHOR]

Intense volcanic and geothermal activities characterize the Great Rift Valley of East Africa. Ground fissure disasters of the Great Rift Valley have garnered increasing attention in recent years. Through field investigations, trenching, geophysical exploration, gas sampling and analysis, we determined the distribution and origin of 22 ground fissures within the Kedong Basin of the Central Kenya Rift. These ground fissures caused varying degrees of damage to roads, culverts, railways, and communities. Trenching and geophysical exploration have shown that ground fissures in sediments are connected to rock fractures with gas escaping. The gases expelled from the rock fractures contained methane and SO2, which were absent in the normal atmosphere, and 3He/4He ratios in gases measured further indicated that the volatiles were derived from the mantle, suggesting that these rock fractures extended deep into the underlying bedrock. Spatial correlations with rock fractures demonstrate the deep origin of these ground fissures, which are associated with active rifting, plate separation, and volcanism. The ground fissures are formed due to movement on the deeper rock fractures, and then the gas escapes through the fissures. Determining the unusual origin of these ground fissures can not only guide infrastructure development and urban planning but also contribute to the safety of local communities. [ABSTRACT FROM AUTHOR]

Plant microbiomes depend on environmental conditions, stochasticity, host species, and genotype identity. Eelgrass (Zostera marina) is a unique system for plant–microbe interactions as a marine angiosperm growing in a physiologically-challenging environment with anoxic sediment, periodic exposure to air at low tide, and fluctuations in water clarity and flow. We tested the influence of host origin versus environment on eelgrass microbiome composition by transplanting 768 plants among four sites within Bodega Harbor, CA. Over three months following transplantation, we sampled microbial communities monthly on leaves and roots and sequenced the V4–V5 region of the 16S rRNA gene to assess community composition. The main driver of leaf and root microbiome composition was destination site; more modest effects of host origin site did not last longer than one month. Community phylogenetic analyses suggested that environmental filtering structures these communities, but the strength and nature of this filtering varies among sites and over time and roots and leaves show opposing gradients in clustering along a temperature gradient. We demonstrate that local environmental differences create rapid shifts in associated microbial community composition with potential functional implications for rapid host acclimation under shifting environmental conditions. [ABSTRACT FROM AUTHOR]

The Early Iron Age in Italy (end of the tenth to the eighth century BCE) was characterized by profound changes which influenced the subsequent political and cultural scenario in the peninsula. At the end of this period people from the eastern Mediterranean (e.g. Phoenicians and Greek people) settled along the Italian, Sardinian and Sicilian coasts. Among local populations, the so-called Villanovan culture group—mainly located on the Tyrrhenian side of central Italy and in the southern Po plain—stood out since the beginning for the extent of their geographical expansion across the peninsula and their leading position in the interaction with diverse groups. The community of Fermo (ninth–fifth century BCE), related to the Villanovan groups but located in the Picene area (Marche), is a model example of these population dynamics. This study integrates archaeological, osteological, carbon (δ13C), nitrogen (δ15N) (n = 25 human) and strontium (87Sr/86Sr) isotope data (n = 54 human, n = 11 baseline samples) to explore human mobility through Fermo funerary contexts. The combination of these different sources enabled us to confirm the presence of non-local individuals and gain insight into community connectivity dynamics in Early Iron Age Italian frontier sites. This research contributes to one of the leading historical questions of Italian development in the first millennium BCE. [ABSTRACT FROM AUTHOR]