This paper presents an artificial neural network (ANN)-based nonlinear model predictive visual servoing method for mobile robots. The ANN model is developed for state predictions to mitigate the unknown dynamics and parameter uncertainty issues of the physics-based (PB) model. To enhance both the model generalization and accuracy for control, a two-stage ANN training process is proposed. In a pretraining stage, highly diversified data accommodating broad operating ranges is generated by a PB kinematics model and used to train an ANN model first. In the second stage, the test data collected from the actual system, which is limited in both the diversity and the volume, are employed to further finetune the ANN weights. Path-following experiments are conducted to compare the effects of various ANN models on nonlinear model predictive control and visual servoing performance. The results confirm that the pretraining stage is necessary for improving model generalization. Without pretraining (i.e., model trained only with the test data), the robot fails to follow the entire track. Weight finetuning with the captured data further improves the tracking accuracy by 0.07–0.15 cm on average.

This study documents several correlations observed during the first run of the plasma wakefield acceleration experiment E300 conducted at FACET-II, using a single drive electron bunch. The established correlations include those between the measured maximum energy loss of the drive electron beam and the integrated betatron X-ray signal, the calculated total beam energy deposited in the plasma and the integrated X-ray signal, among three visible light emission measuring cameras and between the visible plasma light and X-ray signal. The integrated X-ray signal correlates almost linearly with both the maximum energy loss of the drive beam and the energy deposited into the plasma, demonstrating its usability as a measure of energy transfer from the drive beam to the plasma. Visible plasma light is found to be a useful indicator of the presence of a wake at three locations that overall are two metres apart. Despite the complex dynamics and vastly different time scales, the X-ray radiation from the drive bunch and visible light emission from the plasma may prove to be effective non-invasive diagnostics for monitoring the energy transfer from the beam to the plasma in future high-repetition-rate experiments.

Physical vapor deposited (PVD) molybdenum disulfide (nominal composition MoS2) is employed as a thin film solid lubricant for extreme environments where liquid lubricants are not viable. The tribological properties of MoS2 are highly dependent on morphological attributes such as film thickness, orientation, crystallinity, film density, and stoichiometry. These structural characteristics are controlled by tuning the PVD process parameters, yet undesirable alterations in the structure often occur due to process variations between deposition runs. Nondestructive film diagnostics can enable improved yield and serve as a means of tuning a deposition process, thus enabling quality control and materials exploration. Grazing incidence X-ray diffraction (GIXRD) for MoS2 film characterization provides valuable information about film density and grain orientation (texture). However, the determination of film stoichiometry can only be indirectly inferred via GIXRD. The combination of density and microstructure via GIXRD with chemical composition via grazing incidence X-ray fluorescence (GIXRF) enables the isolation and decoupling of film density, composition, and microstructure and their ultimate impact on film layer thickness, thereby improving coating thickness predictions via X-ray fluorescence. We have augmented an existing GIXRD instrument with an additional X-ray detector for the simultaneous measurement of energy-dispersive X-ray fluorescence spectra during the GIXRD analysis. This combined GIXRD/GIXRF analysis has proven synergetic for correlating chemical composition to the structural aspects of MoS2 films provided by GIXRD. We present the usefulness of the combined diagnostic technique via exemplar MoS2 film samples and provide a discussion regarding data extraction techniques of grazing angle series measurements.

Introducing soybean cultivars resistant to 2,4-D and dicamba allowed for postemergence applications of these herbicides. These herbicides pose a high risk for off-target movement, and the potential influence on crops such as hemp is unknown. Two studies were conducted from 2020 through 2022 in controlled environments to evaluate hemp response to rates simulating off-target events of 2,4-D and dicamba. The objectives of this study were to: 1) determine the effects of herbicide (2,4-D and dicamba) and rate (1x to 1/100,000x labeled rate) on visible injury, height, and branching, and 2) determine the effect of 2,4-D rate (1x to 1/100,000x labeled rate) on visible injury, height, branching, and reproductive parameters. Herbicides were applied in the early vegetative stage, and evaluations took place 14 and 28 days after treatment (DAT) and at trial termination (42 DAT in the greenhouse trial and at harvest in the growth chamber trial). In the greenhouse trial, 2,4-D and dicamba at the 1x rate and the 1/10x rate caused 68, 78, and 20% injury 28 DAT, respectively. At the time of trial termination 42 DAT, plants treated with 1x rates of 2,4-D and dicamba or 1/10x dicamba were 19, 25, and 9 cm shorter than the nontreated control, respectively. At trial termination, simulated off-target rates of 2,4-D and dicamba did not influence branching or plant weight. In the growth chamber study, the 1x and 1/10x rates of 2,4-D caused 82% and 2% injury 28 DAT, respectively. Plant height, fresh weight, and cannabidiol (CBD) levels of plants treated with simulated off-target rates of 2,4-D were not different from the nontreated control. These studies suggest that hemp grown for CBD exposed to off-target rates of 2,4-D or dicamba in early vegetative stages may not have distinguishable effects 42 DAT or at harvest.

Geoarchaeological research as part of the AHRC funded Living with Monuments (LwM) project investigated the upper Kennet river system across the Avebury World Heritage landscape. The results demonstrate that in the early–mid-Holocene (c. 9500–1000 bc) there was very low erosion of disturbed soils into the floodplain, with floodplain deposits confined to a naturally forming bedload fluvial deposit aggrading in a shallow channel of inter-linked deeper pools. At the time of the Neolithic monument building in the 4th–early 3rd millennium bc, the river was wide and shallow with areas of presumed braid plain. Between c. 4000 and 1000 bc, a human induced signature of soil erosion became a minor component of fluvial sedimentation in the Kennet palaeo-channel but it was small scale and localised. This strongly suggests that there is little evidence of widespread woodland removal associated with Neolithic farming and monument building, despite the evidently large timber requirements for Neolithic sites like the West Kennet palisade enclosures. Consequently, there was relatively light human disturbance of the hinterland and valley slopes over the longue durée until the later Bronze Age/Early Iron Age, with a predominance of pasture over arable land. Rather than large Neolithic monument complexes being constructed within woodland clearings, representing ancestral and sacred spaces, the substantially much more open landscape provided a suitable landscape with areas of sarsen spreads potentially easily visible. During the period c. 3000–1000 bc, the sediment load within the channel slowly increased with alluvial deposition of increasingly humic silty clays across the valley floor. However, this only represents small-scale landscape disturbance. It is from the Late Bronze Age–Early Iron Age when the anthropogenic signal of human driven alluviation becomes dominant and overtakes the bedload fluvial signal across the floodplain, with localised colluvial deposits on the floodplain margins. Subsequently, the alluvial archive describes more extensive human impact across this landscape, including the disturbance of loessic-rich soils in the catchment. The deposition of floodplain wide alluvium continues throughout the Roman, medieval, and post-medieval periods, correlating with the development of a low-flow, single channel, with alluvial sediments describing a decreasing energy in the depositional environment.

Members of the genus Scaphanocephalus mature in accipitrids, particularly osprey, Pandion haliaetus, with metacercaria causing Black Spot Syndrome in reef fishes. In most of the world, only the type species, Scaphanocephalus expansus (Creplin, 1842) has been reported. Recent molecular studies in the Western Atlantic, Mediterranean and Persian Gulf reveal multiple species of Scaphanocephalus, but have relied on 28S rDNA, mainly from metacercariae, which limits both morphological identification and resolution of closely related species. Here we combine nuclear rDNA with mitochondrial sequences from adult worms collected in osprey across North America and the Caribbean to describe species and elucidate life cycles in Scaphanocephalus. A new species described herein can be distinguished from S. expansus based on overall body shape and size. Phylogenetic analysis of the whole mitochondrial genome of Scaphanocephalus indicates a close relationship with Cryptocotyle. We conclude that at least 3 species of Scaphanocephalus are present in the Americas and 2 others are in the Old World. Specimens in the Americas have similar or identical 28S to those in the Mediterranean and Persian Gulf, but amphi-Atlantic species are unlikely in light of divergence in cytochrome c oxidase I and the lack of amphi-Atlantic avian and fish hosts. Our results provide insight into the geographic distribution and taxonomy of a little-studied trematode recently linked to an emerging pathology in ecologically important reef fishes.

In this paper, we show how to represent a non-Archimedean preference over a set of random quantities by a nonstandard utility function. Non-Archimedean preferences arise when some random quantities have no fair price. Two common situations give rise to non-Archimedean preferences: random quantities whose values must be greater than every real number, and strict preferences between random quantities that are deemed closer in value than every positive real number. We also show how to extend a non-Archimedean preference to a larger set of random quantities. The random quantities that we consider include real-valued random variables, horse lotteries, and acts in the theory of Savage. In addition, we weaken the state-independent utility assumptions made by the existing theories and give conditions under which the utility that represents preference is the expected value of a state-dependent utility with respect to a probability over states.

Animals under human care are exposed to a potentially large range of both familiar and unfamiliar humans. Human-animal interactions vary across settings, and individuals, with the nature of the interaction being affected by a suite of different intrinsic and extrinsic factors. These interactions can be described as positive, negative or neutral. Across some industries, there has been a move towards the development of technologies to support or replace human interactions with animals. Whilst this has many benefits, there can also be challenges associated with increased technology use. A day-long Animal Welfare Research Network workshop was hosted at Harper Adams University, UK, with the aim of bringing together stakeholders and researchers (n = 38) from the companion, farm and zoo animal fields, to discuss benefits, challenges and limitations of human-animal interactions and machine-animal interactions for animals under human care and create a list of future research priorities. The workshop consisted of four talks from experts within these areas, followed by break-out room discussions. This work is the outcome of that workshop. The key recommendations are that approaches to advancing the scientific discipline of machine-animal interactions in animals under human care should focus on: (1) interdisciplinary collaboration; (2) development of validated methods; (3) incorporation of an animal-centred perspective; (4) a focus on promotion of positive animal welfare states (not just avoidance of negative states); and (5) an exploration of ways that machines can support a reduction in the exposure of animals to negative human-animal interactions to reduce negative, and increase positive, experiences for animals.

This study aimed to parse between-person heterogeneity in growth of impulsivity across childhood and adolescence among participants enrolled in five childhood preventive intervention trials targeting conduct problems. In addition, we aimed to test profile membership in relation to adult psychopathologies. Measurement items representing impulsive behavior across grades 2, 4, 5, 7, 8, and 10, and aggression, substance use, suicidal ideation/attempts, and anxiety/depression in adulthood were integrated from the five trials (N = 4,975). We applied latent class growth analysis to this sample, as well as samples separated into nonintervention (n = 2,492) and intervention (n = 2,483) participants. Across all samples, profiles were characterized by high, moderate, low, and low-increasing impulsive levels. Regarding adult outcomes, in all samples, the high, moderate, and low profiles endorsed greater levels of aggression compared to the low-increasing profile. There were nuanced differences across samples and profiles on suicidal ideation/attempts and anxiety/depression. Across samples, there were no significant differences between profiles on substance use. Overall, our study helps to inform understanding of the developmental course and prognosis of impulsivity, as well as adding to collaborative efforts linking data across multiple studies to better inform understanding of developmental processes.