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\"Pulling back the covers on the fascinating, yet often forgotten, history of the bed. Louis XIV ruled France from his bedchamber. Winston Churchill governed Britain from his during World War II. Travelers routinely used to bed down with complete strangers, and whole families shared beds in many preindustrial households. Beds were expensive items--and often for show. Tutankhamun was buried on a golden bed, wealthy Greeks were sent to the afterlife on dining beds, and deceased middle-class Victorians were propped up on beds in their parlor. In this sweeping social history that covers the past seventy thousand years, Brian Fagan and Nadia Durrani look at the endlessly varied role of the bed through time. This was a place for sex, death, childbirth, storytelling, and sociability as well as sleeping. But who did what with whom, why, and how could vary incredibly depending on the time and place. It is only in the modern era that the bed has transformed into a private, hidden zone, and its rich social history has largely been forgotten.\"--Dust jacket.

Microbial community development within an anaerobic trickle bed reactor (TBR) during methanation of syngas (56% H 2 , 30% CO, 14% CO 2 ) was investigated using three different nutrient media: defined nutrient medium (241 days), diluted digestate from a thermophilic co-digestion plant operating with food waste (200 days) and reject water from dewatered digested sewage sludge at a wastewater treatment plant (220 days). Different TBR operating periods showed slightly different performance that was not clearly linked to the nutrient medium, as all proved suitable for the methanation process. During operation, maximum syngas load was 5.33 L per L packed bed volume (pbv) & day and methane (CH 4 ) production was 1.26 L CH 4 /L pbv /d. Microbial community analysis with Illumina Miseq targeting 16S rDNA revealed high relative abundance (20–40%) of several potential syngas and acetate consumers within the genera Sporomusa , Spirochaetaceae , Rikenellaceae and Acetobacterium during the process. These were the dominant taxa except in a period with high flow rate of digestate from the food waste plant. The dominant methanogen in all periods was a member of the genus Methanobacterium , while Methanosarcina was also observed in the carrier community. As in reactor effluent, the dominant bacterial genus in the carrier was Sporomusa . These results show that syngas methanation in TBR can proceed well with different nutrient sources, including undefined medium of different origins. Moreover, the dominant syngas community remained the same over time even when non-sterilised digestates were used as nutrient medium. Key points • Independent of nutrient source, syngas methanation above 1 L/L pbv /D was achieved. • Methanobacterium and Sporomusa were dominant genera throughout the process. • Acetate conversion proceeded via both methanogenesis and syntrophic acetate oxidation. Graphical abstract

Separated from the smelly feet and scratchy wool of a pirate's ship by a great storm, a ship's bed floats in the water, making friends with gulls and dolphins and basking in the sun before realizing that something is missing.

Over the past several decades, metal Additive Manufacturing (AM) has transitioned from a rapid prototyping method to a viable manufacturing tool. AM technologies can produce parts on-demand, repair damaged components, and provide an increased freedom of design not previously attainable by traditional manufacturing techniques. The increasing maturation of metal AM is attracting high-value industries to directly produce components for use in aerospace, automotive, biomedical, and energy fields. Two leading processes for metal part production are Powder Bed Fusion with laser beam (PBF-LB/M) and Directed Energy Deposition with laser beam (DED-LB/M). Despite the many advances made with these technologies, the highly dynamic nature of the process frequently results in the formation of defects. These technologies are also notoriously difficult to control, and the existing machines do not offer closed loop control. In the present work, the application of various Machine Learning (ML) approaches and in-situ monitoring technologies for the purpose of defect detection are reviewed. The potential of these methods for enabling process control implementation is discussed. We provide a critical review of trends in the usage of data structures and ML algorithms and compare the capabilities of different sensing technologies and their application to monitoring tasks in laser metal AM. The future direction of this field is then discussed, and recommendations for further research are provided.

Widely distributed in natural rivers and coasts, vegetation interacts with fluid flows and sediments in a variable and complicated manner. Such interactions make it difficult to predict associated drag forces during sediment transport. This paper investigates the drag coefficient for an emergent vegetated patch area under nonuniform flow and mobile bed conditions, based on an analytical model solving the momentum equation following our previous work (Zhang et al., 2020, https://doi.org/10.1029/2020WR027613). Emergent vegetation was modeled with rigid cylinders arranged in staggered arrays of different vegetation coverage ∅. Laboratory flume tests were conducted to measure variations in both the water and bed surfaces along a vegetated patch on a sand bed. Based on the experimental and theoretical analyses, a dimensionless drag model integrating both terms of flow properties and bed effects is proposed to predict the drag coefficient Cd over a mobile bed. The calculated values of Cd exhibit two different trends, that is, nonmonotonically or monotonically increasing along the streamwise direction, due to the combined effect of water surface gradient and bed slope. The morphodynamic response of the mobile bed to nonuniform flow manifests as an evolution in the bed slope within the vegetated patch. Ongoing scouring directs the flow's energy toward overcoming the rising Cd and bed slope, leading to a relatively stable stage with a low sediment transport rate. This study advances the existing understanding of the drag coefficient's role over a mobile bed within nonuniform flows. It also enhances the applicability of vegetation drag models in riverine restoration. Plain Language Summary The drag exerted by vegetation on a riverbed dictates the sediment transport rate with important implications for river morphological evolution. Predicting vegetation drag in nonuniform flow based on the bed characteristics of mobile sand bed conditions poses both theoretical and practical challenges. The implications of this endeavor include the formulation of predictive models for drag and a deeper understanding of the influence of gradually varied flow conditions in rivers. Through both experimental and theoretical investigations, this paper reveals that the drag coefficient exhibits varying patterns along the streamwise direction within the vegetated patch over a mobile sand bed. These patterns manifest in two distinct forms: a steady increase or a parabolic shape, wherein the coefficient initially rises before subsequently decreasing. This contrasts with prior studies on fixed beds, where the drag coefficient consistently follows a parabolic distribution in the streamwise direction. The discrepancy is attributed to the distinct physical contributions of pressure, advection, and bed friction to the drag coefficient. This study provides valuable insights into the importance of flow nonuniformity on vegetation drag, aiding in the prediction of backwater profiles in vegetated flows over a mobile bed. Furthermore, it facilitates modifications to sediment transport within vegetated patches. Key Points Vegetation drag in nonuniform flow over a mobile sand bed is explored using the momentum equation Drag coefficient in nonuniform flow over a mobile bed exhibits either a parabolic or a monotonic increase along the streamwise direction Water surface gradient and bed slope contribute to the flow nonuniformity, collectively influencing the variability of the drag coefficient

\"A boy and his toy dragon search for the most comfortable bed in this dreamy nighttime adventure\"-- Provided by publisher.

The present study uses results of eddy‐resolving numerical simulations to investigate the open channel flow over large clusters of freshwater mussels (Unio elongatulus) partially buried in a rough, gravel bed. The density of the mussels forming the array varies from 26 to 500 mussels/m2. The flow structure is analyzed at large distances from the leading edge of the mussel bed, where the flow can be considered fully developed. The effects of changing the mussel bed density, the filtering discharge, the burial level and the roughness of the bed surface in which mussels are burrowed, are investigated in terms of flow field, turbulent structures, drag forces, and bed shear stresses. It is found that strong interactions occur between energetic eddies generated by the larger gravels on the exposed bed surface and by the mussel shells. Simulations results show that for a burial depth close to 50% and a ratio between the average gravel size and the mussel protruding height of 0.13, the shell induced turbulence becomes dominant for mussel bed densities around 50 mussels/m2. The influence of the bed roughness becomes less relevant with increasing mussel density, as the generation of energetic eddies is mostly controlled by mussel‐to‐mussel interactions. For fixed bed roughness, burial level and filtering velocity, the mean streamwise drag force and the associated drag coefficient for the exposed part of each mussel decrease with increasing mussel density, even if strong variations are observed for individual mussels. For constant mussel bed density and burial level, the mean streamwise drag force and the mean drag coefficient decrease slightly with increasing bed roughness. Increasing the burial level decreases not only the drag forces but also the drag coefficients because of the more streamlined shape of the top of the mussels. Strong active filtering acts toward decreasing the mean streamwise force and the mean drag coefficient. The spanwise drag forces contribute significantly to the total drag force, especially for high mussel bed densities. Based on smooth bed calculations, bed‐averaged shear stresses are reduced in highly dense clusters. Key Points Mussel‐to‐mussel interactions are important for dense arrays and influence flow structure and turbulence Eddy resolving simulations showed that the effect of bed roughness become less significant with increasing mussel bed density In dense clusters of mussels, forces on the shells and bed shear stresses are reduced thus favoring mussel stability