Unknown Source Research Articles

Robust bilinear tracking control of a parabolic trough solar collector via saturation

This paper investigates the problem of robust tracking control of heat transport in a Parabolic Trough Solar Collector (PTSC), where the output has to track a desired reference trajectory. In this work, the PTSC is modeled by state-space bilinear dynamics. The manipulated variable is the pump volumetric flow rate, and the source term, i.e., solar irradiance, is assumed to be unmeasured. In addition, the actuator’s physical constraints induce saturation bounds on the manipulated variable and need to be considered explicitly in the controller design. To deal with these challenges, we first propose a saturated state-feedback law that meets the control objectives. Then, we reconstruct the unknown time-varying source term using an adaptive estimator. Later, through Lyapunov stability analysis, we prove that the closed-loop system and the output tracking error are uniformly ultimately stable. Numerical simulations attest to the performance of the proposed control strategy.

A spatial matrix factorization method to characterize ecological assemblages as a mixture of unobserved sources: An application to fish eDNA surveys

Abstract Understanding how ecological assemblages vary in space and time is essential for advancing our knowledge of biodiversity dynamics and ecosystem functioning. Metabarcoding of environmental DNA (eDNA) is an efficient method for documenting biodiversity changes in both marine and terrestrial ecosystems. However, current methods fail to detect and display the biodiversity structure within and between eDNA samples limiting ecological and biogeographical interpretations. We present a spatial matrix factorization method that identifies optimal eDNA sample assemblages—called pools—assuming that taxonomic unit composition is based on a fixed number of unknown sources. These sources, in turn, represent taxonomic units sharing similar habitat properties or characteristics. The method aims to reduce the multi‐taxa composition structure into a low number of dimensions defined by these sources. This method is inspired by admixture analysis in population genetics. Using a marine fish eDNA survey on 263 sampling stations detecting 2888 molecular operational taxonomic units (MOTUs), we apply this method to analyse the biogeography and mixing patterns of fish assemblages at regional and large scales. At large scale, our analysis reveals six primary pools of fish samples characterized by distinct biogeographic patterns, with some mixtures between these pools. We identify pools composed of unique sources, corresponding to distinct and more isolated regions such as the Mediterranean and Scotia Seas. We also identify pools composed of a greater mix of sources, corresponding to geographically connected areas, such as tropical regions. Additionally, we identify the taxa underpinning the formation of each pool. In the regional analysis of Mediterranean eDNA samples, our method successfully identifies different pools, allowing the detection of not only geographic gradients but also human‐induced gradients corresponding to protection levels. Spatial matrix factorization adds a new method in community ecology, where each sample is considered as a mixture of K unobserved sources, to assess the dissimilarity of ecological assemblages revealing environmental and human‐induced gradients. Beyond the study of fish eDNA samples, this method has the potential to shed new light on any biodiversity survey and provide new bioindicators of global change.

Phenomenon of Screen Dance in the Context of Dialogism of Choreographic and Audiovisual Arts

The purpose of the article is to reveal the peculiarities of the phenomenon of screen dance in the context of dialogism of choreographic and audiovisual art. Research methodology. The method of analysis and synthesis was applied (to study the scientific literature on the research topic and identify the main concepts of screen dance), the terminological method (to clarify the concept of "screen dance"); the typological method and the method of historical and cultural analysis (to identify the peculiarities of the interaction of choreographic and audiovisual art in historical retrospect), the method of generalisation. Scientific novelty. The phenomenon of screen dance is studied in the context of dialogism of choreographic and audiovisual art in historical retrospect; the concept of "screen dance" has been clarified; the properties of screen dance are understood, the points of common influence and mutual exchange between film and dance are considered, which define it as an autonomous practice; little-known and unknown sources, as well as the results of research by modern foreign scientists, were introduced into scientific circulation. Conclusions. The study found that there are no strict criteria for defining screen dance in the scientific literature. During the historical development, this art form was usually denoted by a number of terms limited by indications of materiality (video dance, film dance, dance film), but it is screen dance that formulates the common denominator between them. Within the problematics of dialogism of choreographic and audiovisual art, screen dance can be considered as a form of research that studies the relationships between composition, choreographic language, and the meanings of body, movement, space, and time in the context of contemporary debates about cultural practices. Screen dance can take many forms and features and cross genres, with no limits on how it can be produced, filmed, edited and distributed. The coexistence of choreographic and audiovisual in the concept of screen dance is characterised by a constant dynamic interaction, the specifics of which are determined by innovative technological inventions and trends in the socio-cultural space.

Study of a non-linear Volterra integro-differential equation with a non-linear unknown source term

In this paper, we propose a new class of integro-differential nonlinear Volterra equations with a non-linear unknown source term. Our study focuses on both theoretical analysis and numerical approximation of solutions to these equations. In the theoretical analysis partition, we define the specific assumptions on the integral kernel's characteristics, on the source term function and also on the derivative of the solutions of equations, under which the Krasnoselskii's fixed point theorem can be applied and in order to ensures the existence and uniqueness of solutions to the proposed integro-differential equations. In the numerical approximation partition, we use a well-known numerical technique for solving integral equations called Nyström method. This method allows us to get an approximate solutions of the proposed equations. Furthermore, we provide some illustrative examples and according to the numerical method described in this paper we approach them, where the comparison results between the exact and approximate solutions of these examples confirm the effectiveness of the numerical Nyström method for approaching the solutions of this class of integro-differential equations.

Dynamic event-triggered integrated task and motion planning for process-aware source seeking

The process-aware source seeking (PASS) problem in flow fields aims to find an informative trajectory to reach an unknown source location while taking the energy consumption in the flow fields into consideration. Taking advantage of the dynamic flow field partition technique, this paper formulates this problem as a task and motion planning (TAMP) problem and proposes a bi-level hierarchical planning framework to decouple the planning of inter-region transition and inner-region trajectory by introducing inter-region junctions. An integrated strategy is developed to enable efficient upper-level planning by investigating the optimal solution of the lower-level planner. In order to leverage the information acquisition and computational burden, a dynamic event-triggered mechanism is introduced to enable asynchronized estimation, region partitioning and re-plans. The proposed algorithm provides guaranteed convergence of the trajectory, and achieves automatic trade-offs of both exploration-exploitation and accuracy-efficiency. Simulations in a highly complicated and realistic ocean surface flow field validate the merits of the proposed algorithm, which demonstrates a significant reduction in computational burden without compromising planning optimality.

Gaussian process-based online sensor selection for source localization

This paper addresses the sensor selection problem for source localization within cyber–physical systems (CPSs). While recent machine learning and reinforcement learning approaches aim to optimize sensor selection and placement within the Area of Interest (AoI), their need for intensive data collection and training precludes online operation. Furthermore, these methods often require prior knowledge of the unknown source’s characteristics and lack adaptability to the dynamic nature of CPSs, leading to inefficiencies in unseen environments. This paper addresses these shortcomings using Gaussian process Optimization coupled with an active sensor selection mechanism to locate the unknown source within the AoI. The proposed approach first builds a probabilistic model of the environment, which is discretized into a grid, without prior training using a Gaussian Process surrogate model. Next, the model iteratively and systematically learns the underlying spatial phenomenon using Gaussian Process optimization. Concurrently, the approach selects a subset of sensors by optimizing a fitness function that advocates selecting informative and energy-efficient sensors. Next, the probabilistic model, having accurately learned the environment, directs the algorithm to the unknown source by identifying the cell with the highest likelihood of containing it. Finally, a peak refinement step is performed, which computes the exact location of the source within the designated cell. The proposed method’s efficacy is validated through experiments in radioactive source localization, validation studies, and adaptability assessments across various environments. In terms of quality of localization (QoL), it outperforms recent localization benchmarks, such as a reinforcement learning-based approach and DANS, by around 18% and 100%, respectively.

Major Holocene cryptotephras layers identified from Jeju Island, Republic of Korea: Implications for regional volcanic eruptions and environmental changes

Cryptotephras recorded in sediments are valuable isochrons with which to reconstruct volcanic eruptive history and synchronize environmental changes across large regions. Here we identify four cryptotephras from Jeju Island, Republic of Korea, that constitute tie-points linking palaeoenvironmental records of tropical to mid-latitude east Asia. A cryptotephra of unknown source with trachytic glass compositions at around 2700 cal a BP (named M263a) can be correlated with the HGY263 recorded in the Huguangyan Maar lake in southern China, and SG14–0433 recorded in Suigetsu lake in central Japan. Another population of glass shards with basaltic andesitic to trachybasaltic composition (named M263b) represents the first cryptotephra record of a Jeju eruption. A rhyolitic cryptotephra at ∼7384 cal a BP (H53) can be correlated with the ∼7.3 ka Kikai-Akahoya eruption (specifically, the K-Ah tephra) from Kikai caldera, southern Kyushu, Japan. The cryptotephra coincides with a marked change in aquatic algae communities in Jeju sediments, possibly signifying a climate response to the eruption. Additionally, cryptotephra layers at ∼6948 cal a BP (H22) in the Hanon Maar Lake and ∼ 1030 cal a BP (M125) in Mulyoungari wetland exhibit similar glass compositions to those of the K-Ah tephra, which suggests they are the product of unknown eruptions from Kikai or a neighboring volcano. Given the widespread distributions of K-Ah and M263a tephra across east Asia, Jeju sediments can be precisely synchronized with those high-resolution sediments from southern China and Japan, providing two Holocene marker horizons for palaeoenvironmental comparisons across east Asia. Our work shows great promise for the improved chronological constraints and inter-site linkages for palaeoenvironmental sequences in the region through the application of tephrochronology.

Optimization of an active device for global control of low-frequency wall reflections in a semi-anechoic room

An active device has been designed and built at LMA to control low-frequency reflections on the absorbing walls of a semi-anechoic room: the sound pressure reflected by the walls in the presence of an unknown source is estimated by linear filtering of the total sound pressure near the walls, then neutralized using acoustic sources placed on the walls. Here, we present 2D numerical simulations, involving monopole sources and series of damped analytic modes, which have enabled us to optimize the active device, in particular to (i) deal with resonance frequencies at which cancelling the diffracted pressure near the walls is not sufficient to cancel it inside the room, (ii) minimize the number of the total pressure measurement points required to estimate the pressure diffracted by the walls at each location, and (iii) select the strategy for minimizing the virtual signals corresponding to the diffracted pressure. Simulations show that with the optimized device, the control remains efficient up to frequencies corresponding to one wall source per wavelength and a little less than two pressure sensors per wavelength. Experiments are underway to compare measurements with simulations.

A-307 Clinical utility of serum calprotectin in febrile infants presenting to the Emergency Department

Abstract Background Antimicrobial stewardship involves a delicate balance between the risk of undertreating individuals and the potential societal burden of overprescribing antimicrobials. However, early and accurate diagnosis of bacterial infections in critically ill patients is challenging, as the clinical manifestation is non-specific. Furthermore, the results from microbial cultures may be delayed, resulting in delayed antibiotic treatment, which is associated with increased mortality. Neutrophil activation is a major response to bacterial infection and calprotectin is the most abundant protein in the cytosolic fraction of neutrophils, shown as an early marker for neutrophil activation. The objective of this study was to evaluate the clinical performance of serum calprotectin in identifying bacterial infection in febrile infants presenting to an Emergency Department (ED) relative to other common biomarkers of infection. Methods 141 infants aged 28-90 days with suspected infectious disease presenting to the ED at The Hospital for Sick Children in Toronto, were included in this non-interventional investigation. All biomarkers except calprotectin were used in the routine clinical adjudication of the final diagnosis. Residual serum specimens collected as part of the standard care pathway were stored at -80°C prior to analysis of serum calprotectin using GCAL® assay (Gentian AS, Norway). Chart review was completed for key variables including, age (days), sex, chief complaint and temperature at ED presentation, and available laboratory test results (i.e., C-reactive protein and procalcitonin (Architect, Abbott Diagnostics), WBC count and neutrophil count (XN3000, Sysmex Europe GmbH), urinary leukocytes and nitrates, blood and/or urine bacterial culture). Final diagnosis, admission status, and antibiotic prescription at ED discharge were also extracted. Results Final discharge diagnosis in patient population included bacterial infection (n=23), viral infection (n=22), fever of unknown source (n=54) and other/unknown diagnosis (n=42). Antibiotics were prescribed in 36 cases, although bacterial infection could only be confirmed in 23 cases when final diagnosis was made. Statistically significant differences were observed in serum calprotectin (p<0.001), procalcitonin (p<0.001), and CRP (p<0.001) in patients with bacterial infections compared to patients with other discharge diagnoses. ROC curve analysis was performed for the identification of bacterial infections in the entire clinical cohort (n=141) and in only patients with laboratory confirmed bacterial or viral infection (n=41). Calprotectin and procalcitonin showed higher specificity than CRP and WBC count for differentiation between bacterial and viral infection in both cohorts. Performance of calprotectin in detection of bacterial infections was comparable to the performance of CRP, slightly better than performance of procalcitonin and superior to WBC count. Conclusions In this cohort, one third of the children that were prescribed antibiotics did not have confirmed bacterial infection. Hence, there is a need for adequate diagnostic tools to help discriminate between various kinds of infections. This study confirms serum calprotectin as a valuable biomarker for differentiation between types of infection and estimation of disease severity in febrile infants. Access to fast and accurate analysis of circulating calprotectin, combined with good clinical performance has the potential to make this biomarker a valuable complement to the current diagnostics of patients with bacterial infections and sepsis.

Association of the IceCube neutrinos with blazars in the CGRaBS sample

The origin of high-energy (HE) astrophysical neutrinos has remained an elusive hot topic in the field of HE astrophysics for the past decade. Apart from a handful of individual associations, the vast majority of HE neutrinos arise from unknown sources. While there are theoretically motivated candidate populations, such as blazars – a subclass of active galactic nuclei with jets pointed toward our line of sight – they have not been convincingly linked to HE neutrino production yet. Here, we perform a spatio-temporal association analysis between a sample of blazars (from the CGRaBS catalog) in the radio and optical bands and the most up-to-date IceCube HE neutrino catalog. We find that if the IceCube error regions are enlarged by 1° in quadrature, to account for unknown systematic errors at a maximal level, a spatio-temporal correlation between the multiwavelength light curves of the CGRaBS blazars and the IceCube HE neutrinos is hinted at, least at a 2.17σ significance level. On the other hand, when the IceCube error regions are taken as their published values, we do not find any significant correlations. A discrepancy in the blazar-neutrino correlation strengths, when using such minimal and enlarged error region scenarios, was also obtained in a recent study by the IceCube collaboration. In our study, this difference arises because several flaring blazars – coinciding with a neutrino arrival time – happen to narrowly miss the published 90%-likelihood error region of the nearest neutrino event. For all of the associations driving our most significant correlations, the flaring blazar is much less than 1° away from the published error regions. Therefore, our results indicate that the question of the blazar-neutrino connection is highly sensitive to the reconstruction of the neutrino error regions, whose reliability is expected to improve with the next generation of neutrino observatories.

Data-driven batch detection enhances single-cell omics data analysis

In single-cell omics studies, data are typically collected across multiple batches, resulting in batch effects: technical confounders that introduce noise and distort data distribution. Correcting these effects is challenging due to their unknown sources, nonlinear distortions, and the difficulty of accurately assigning data to batches that are optimal for integration methods.

Cortical Responses to Mother's Voice in Comparison with Unfamiliar Voice in the First Trimester of Life: A fNIRS Study.

Introduction The use of functional near-infrared light spectroscopy (fNIRS) may be applied to study cortical responses in children and could offer insight into auditory and speech perception during the early stages of life. Some literature suggests that babies are already able to identify familiar voices at birth, and fNIRS is a non-invasive technique that can be used to study this population. Objective To characterize the cortical responses of infants during their first trimester of life to infant-directed speech using near-infrared light spectroscopy and to verify whether there is a difference in responses when infant-directed speech is performed by their mother compared with an unknown person. Methods Twenty-three children between 0 and 3 months, healthy, without risk indicators for hearing loss, and with results considered normal in the audiological evaluation were tested with near-infrared spectroscopy using infant-directed speech as an auditory stimulus produced by their own mother and by an unknown source. Results Bilateral cortical activation was observed. The responses were present in the temporal, frontal, and parietal regions. Regarding the familiarity aspect, no significant difference was observed for the mother's voice compared with an unknown voice. Conclusion Infant-directed speech has prosodic characteristics capable of activating several cortical regions in the infant's first trimester of life, especially the temporal region. The familiarity effect needs to be better defined for this type of stimulus during this period.

Patent Foramen Ovale and Other Cardiopathies as Causes of Embolic Stroke With Unknown Source.

In patients with stroke caused by cardiac embolism, the responsible heart diseases include atrial fibrillation, acute myocardial infarction, sick sinus syndrome, valvular disease, and significant heart failure. When there is no clear source of the embolism, the condition is referred to as "embolic stroke with unknown source (ESUS)." Recent studies have shown that the most common cause of ESUS is a right-to-left cardiac shunt through a patent foramen ovale (PFO). However, considering that PFOs are found in up to 25% of the general population, their presence does not necessarily indicate causality. In patients with ESUS associated with a PFO, either anticoagulants or antiplatelets are used for the prevention of future strokes or transient ischemic attacks. However, it currently remains unclear which treatment is superior. Nevertheless, recent randomized clinical trials have shown that percutaneous closure of the PFO more effectively reduces the incidence of recurrent strokes compared to medical therapy alone in patients with PFO-related strokes. This benefit is especially significant when the PFO carries high-risk features, such as a large shunt or the presence of an atrial septal aneurysm. Furthermore, the effectiveness of PFO closure has been well documented in young patients (<60 years) with a high-risk PFO development. In other cases, the therapeutic decision should be made through discussion among neurologists, cardiologists, and patients. Notably, in ESUS patients without a PFO, the underlying heart condition itself may be the source of embolism, with left atrial enlargement being the most important factor. Theoretically, anticoagulants such as non-vitamin K antagonist oral anticoagulants (NOACs) would be an effective therapy in these cases. However, recent trials have failed to show that NOACs are superior to antiplatelets in preventing further strokes in these patients. This may be due to the still uncertain definition of emboligenic cardiopathy and the presence of other potential embolic sources, such as mild but emboligenic arterial diseases. Overall, further research is needed to elucidate the source of embolism and to determine an effective management strategy for patients with ESUS.

Enhancing Full Waveform Inversion of Field GPR Data: A Source-Independent Approach with Dynamic Reference Selection via SE-Wave-U-Net

Ground Penetrating Radar (GPR) is a widely-utilized non-destructive detection tool. Full Waveform Inversion (FWI) offers a reliable algorithm for accurately imaging GPR data. Despite its potential, FWI's effectiveness is often compromised by unknown excitation sources, which can lead to computational failures and/or diminished imaging accuracy. Addressing this challenge, this paper introduces a convolution-type objective function designed to mitigate the detrimental effects of these unknown excitation sources on FWI imaging. Critical to the success of this function is the precise selection of reference traces. Further refining the capability for signal separation, we have integrated Squeeze-and-Excitation (SE) modules into the traditional Wave-U-Net architecture, culminating in the development of the SE-Wave-U-Net framework. This framework is adept at dynamically extracting accurate reference traces from field GPR data, which are essential for the accurate FWI imaging. The efficacy, accuracy, and practical applicability of proposed methods are validated through extensive analysis of numerical, laboratory experiments, and field GPR data. The proposed algorithm not only establishes a high-precision computational framework for FWI but also enhances the reliability of GPR imaging in complex environments.

A stable difference scheme for the solution of a source identification problem for telegraph-parabolic equations

In the present paper, we construct a first order of accuracy difference scheme for the approximate solution of the inverse problem for telegraph-parabolic equations with an unknown spacewise dependent source term. The unique solvability of constructed difference scheme and the stability estimates for its solution were obtained. The proofs are based on the spectral representation of the self-adjoint positive definite operator in a Hilbert space.

Greedy selection of optimal location of sensors for uncertainty reduction in seismic moment tensor inversion

We address an optimal sensor placement problem through Bayesian experimental design for seismic full waveform inversion for the recovery of the associated moment tensor. The objective is that of optimally choosing the location of the sensors (stations) from which to collect the observed data. The Shannon expected information gain is used as the objective function to search for the optimal network of sensors. A closed form for such objective is available due to the linear structure of the forward problem, as well as the Gaussian modeling of the observational errors and prior distribution. The resulting problem being inherently combinatorial, a greedy algorithm is deployed to sequentially select the sensor locations that form the best network for learning the moment tensor. Numerical results are presented to display the optimal network of sensors and how the uncertainty in the inferred seismic moment tensor contracts. The scenario of full three-dimensional velocity models or unknown earthquake source locations is treated as nuisance uncertainty, contributing to the overall uncertainty without being the focus of the inversion. This is addressed using a consensus approach over a set of realizations of the nuisance parameter. We analyzed the resulting network of stations for the moment tensor inversion under model misspecification, which reflects realistic data-generating processes.

Automated detection of regions with persistently enhanced methane concentrations using Sentinel-5 Precursor satellite data

Abstract. Methane (CH4) is an important anthropogenic greenhouse gas, and its rising concentration in the atmosphere contributes significantly to global warming. A comparatively small number of highly emitting persistent methane sources are responsible for a large share of global methane emissions. The identification and quantification of these sources, which often show large uncertainties regarding their emissions or locations, are important to support mitigating climate change. Daily global column-averaged dry air mole fractions of atmospheric methane (XCH4) are retrieved from radiance measurements of the TROPOspheric Monitoring Instrument (TROPOMI) on board on the Sentinel-5 Precursor (S5P) satellite with a moderately high spatial resolution, enabling the detection and quantification of localized methane sources. We developed a fully automated algorithm to detect regions with persistent methane enhancement and to quantify their emissions using a monthly TROPOMI XCH4 dataset from the years 2018–2021. We detect 217 potential persistent source regions (PPSRs), which account for approximately 20 % of the total bottom-up emissions. By comparing the PPSRs in a spatial analysis with anthropogenic and natural emission databases, we conclude that 7.8 % of the detected source regions are dominated by coal, 7.8 % by oil and gas, 30.4 % by other anthropogenic sources like landfills or agriculture, 7.3 % by wetlands, and 46.5 % by unknown sources. Many of the identified PPSRs are in well-known source regions, like the Permian Basin in the USA, which is a large production area for oil and gas; the Bowen Basin coal mining area in Australia; or the Pantanal Wetlands in Brazil. We perform a detailed analysis of the PPSRs with the 10 highest emission estimates, including the Sudd Wetland in South Sudan, an oil- and gas-dominated area on the west coast in Turkmenistan, and one of the largest coal production areas in the world, the Kuznetsk Basin in Russia. The calculated emission estimates of these source regions are in agreement within the uncertainties in results from other studies but are in most of the cases higher than the emissions reported by emission databases. We demonstrate that our algorithm is able to automatically detect and quantify persistent localized methane sources of different source type and shape, including larger-scale enhancements such as wetlands or extensive oil- and gas-production basins.

Vertical transfer of gut microbiota from dam to neonate calf in the early of life

The aim of this study was to investigate the vertical transfer of microbiota from dams to the offspring. We studied a pair of 20 dams and its offspring. Maternal sources (colostrum, feces and vaginal secretion) and newborn fecal samples were analyzed using 16S rDNA amplicon sequencing on days 1, 3, 7, 14 and 28. Overall, newborns were maintained healthy and did not receive antimicrobial therapy. The Source Tracker analysis indicated that the newborn fecal microbiota was similar to colostrum and vaginal secretion from day 1 up to 7. However, an unknown source (probably from the environment) showed a gradual increase in its similarity with fecal samples from calves measured from day 3 to 28. The most abundant bacteria groups on meconium (day 1) and calf fecal samples on day 3 were Escherichia-Shigella and Clostridium, respectively. On day 7, the predominant genus were Bifidobacterium and Lactobacillus, while Fusobacterium was the most abundant genus on day 14, coinciding with the diarrhea peak. Faecalibacterium showed a gradual increase throughout the neonatal period. Maternal sources contribute to the neonatal microbiota, however other unknown sources (probably environment) had a strong influence on development of the gut microbiota later in the neonate period.

Bayesian approaches to assigning the source of an odour detected by an electronic nose

After a brief review of electronic nose technology, the use of an Australian electronic nose to identify an unknown odour out of a set of known odours is described. Multivariate supervised learning is accomplished by applying Bayes’ theorem to data from metal oxide semiconductor sensors responding to each of a number of target odours. An odour from an unknown source is then assigned a probability of membership of each of the training sets by applying either a Naïve Bayes algorithm to the deemed independent data from each sensor, or to a multinormal distribution of the data. A flat prior (equal probabilities of each outcome) is usually adopted, but for particular situations where one odour is known to predominate, then suitably weighted priors can be used. A source ‘none of the above’, which has a small likelihood covering the space of the possible sensor responses, is included for completeness. This also avoids the assignment to a source that has an extremely small probability but which is greater than that of any other source. Examples are given of a single source (detecting diabetes from a patient’s breath), and three sources of unpleasant odours in a meat processing plant.

Chemical classification of spherules recovered from the Pacific Ocean site of the CNEOS 2014-01-08 (IM1) bolide

We have conducted an extensive towed-magnetic-sled survey during the period of June 14–28, 2023, over the seafloor about 85 km north of Manus Island, Papua New Guinea, centered around the calculated path of the bolide CNEOS 2014-01-08 (IM1). We found about 850 spherules of diameter 0.1–1.3 mm in our samples. The samples were analyzed by micro-XRF, Electron Probe Microanalyzer and ICP Mass spectrometry. Here we report major and trace element compositions of the samples and classify spherules based on that analysis. We identified 78 % of the spherules as primitive, in that their compositions have not been affected by planetary differentiation. We divided these into four groups, three of which correspond to previously described cosmic spherule types. Spherules in the fourth group, comprising 22 % of the collection, appear to all reflect planetary igneous differentiation and are all different from previously described spherules. We call them D-type spherules. At least five of the D-type spherules are suggested to be terrestrial in origin, although many spherules exhibit elemental ratios that are distinct from known planetary bodies and their origins are undetermined. A subset of the D-spherules show an excess of Be, La and U, by up to three orders of magnitude relative to the solar system standard of CI chondrites. Detailed mass spectrometry of 12 of these “BeLaU”-type spherules, the population of which may constitute up to ∼10 % of our entire collected sample, suggests that they are derived from material formed by planetary igneous fractionation. Their chemical composition is unlike any known solar system material. We compare these compositions to known differentiated bodies in the solar system and find them similar to those of evolved planetary materials–with lunar KREEP the closest in terms of its trace element enrichment pattern, but unusual in terms of their elevated CI-normalized incompatible elements. The “BeLaU”-type spherules reflect a highly differentiated, extremely evolved composition of an unknown source.