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Abstract Most soundfield synthesis approaches deal with extensive and regular loudspeaker arrays, which are often not suitable for home audio systems, due to physical space constraints. In this article, we propose a technique for soundfield synthesis through more easily deployable irregular loudspeaker arrays, i.e., where the spacing between loudspeakers is not constant, based on deep learning. The input are the driving signals obtained through a plane wave decomposition-based technique. While the considered driving signals are able to correctly reproduce the soundfield with a regular array, they show degraded performances when using irregular setups. Through a complex-valued convolutional neural network (CNN), we modify the driving signals in order to compensate the errors in the reproduction of the desired soundfield. Since no ground truth driving signals are available for the compensated ones, we train the model by calculating the loss between the desired soundfield at a number of control points and the one obtained through the driving signals estimated by the network. The proposed model must be retrained for each irregular loudspeaker array configuration. Numerical results show better reproduction accuracy with respect to the plane wave decomposition-based technique, pressure-matching approach, and linear optimizers for driving signal compensation.

Bilateral robotic rehabilitation has proven helpful in the recovery of upper limb motor function in patients with stroke, but its effects on the cortical reorganization mechanisms underlying recovery are still unclear. This pilot Randomized Controlled Trial (RCT) aimed to evaluate the effects on the interhemispheric balance of unilateral or bilateral robotic treatments in patients with subacute stroke, using Quantitative Electroencephalography (qEEG). 19 patients with ischemic stroke underwent a 30-session upper limb neurorehabilitation intervention using a bilateral upper limb exoskeleton. Each patient was randomly assigned to the bilateral (BG, n=10) or unilateral treatment group (UG, n=9). EEG evaluations were performed before (T0) and right after (T $0+\text {)}$ the first treatment session, after 30 treatment sessions (T1), and at 1-week follow-up (T2), in both eyes open and eyes closed conditions. From the acquired EEG data, the pairwise-derived Brain Symmetry Index (pdBSI) was computed. In addition, clinical evaluation was performed at T0 and T1 with validated clinical scales. After the treatment, a significant improvement in clinical and EEG evaluations was observed for both groups, but only the BG showed reduced pdBSI in delta and theta bands. In the cluster of sensorimotor channels, there was no significant difference between groups. The observed changes were not maintained at follow-up. No significant changes were observed in the pdBSI after a single rehabilitation session. Results suggest that balancing of interhemispheric symmetry comes along with a clinical improvement in the upper extremity and that the pdBSI can be used to investigate the mechanisms of neuronal plasticity involved in robotic rehabilitation after stroke.

Objective: The objective of this study was to produce a cross-cultural adaptation in Italian of the Agitated Behavior Scale (ABS), originally developed in English, as the first of two stages that also include cross-cultural validation and allow a clinical scale to be used in the proper setting such as rehabilitation units. Methods: In order to adapt the ABS scale to a different cultural environment, five consecutive steps were performed: (1) forward translations (n = 8), (2) synthesis of the 8 forward translations to obtain a first shared italian version (ABS_I_trial), (3) back translations (n = 3), (4) creation of an expert committee to evaluate forward and back translations and finally (5) the cognitive debriefing. Results: After the five steps, including forward translations and back translations, the process of committee verification and judgement and the evaluative step of cognitive debriefing, high comprehensibility of all items was found, resulting in an Italian translation version of ABS suitable for application in a clinical setting. Conclusion: ABS translation was produced by means of a standardized procedure aimed at minimizing cross-cultural gaps. The expert committee evaluated the version produced as highly understandable in Italian. Further steps, such as the subsequent validation of its psychometric properties, are needed to employ this translation in a clinical setting.

Abstract How can an intentional movement be distinguished from the same movement done nonintentionally? How can this distinction be drawn without asking the subject, or in patients who are unable to communicate? Here we address these questions, by focusing on blinking. This is one of the most frequent spontaneous actions in our daily life, but it can also be done intentionally. Furthermore, blinking is often spared in patients with severe brain injuries, and for some, it is the only way to report complex meanings. Using kinematic and EEG-based measures, we found that intentional and spontaneous blinking are preceded by different brain activities, even when they are indistinguishable. Unlike spontaneous ones, intentional blinks are characterized by a slow negative EEG drift, resembling the classic readiness potential. We investigated the theoretical implication of this finding in stochastic decision models as well as the practical significance of using brain-based signals to improve the discrimination between intentional and nonintentional actions. As proof of principle, we considered three brain-injured patients with rare neurological syndromes characterized by motor and communicative impairments. Although further research is needed, our results indicate that brain-based signals can offer a feasible way to infer intentionality even in absence of overt communication.

Abstract In recent years, the adoption of deep learning techniques has allowed to obtain major breakthroughs in the automatic music generation research field, sparking a renewed interest in generative music. A great deal of work has focused on the possibility of conditioning the generation process in order to be able to create music according to human-understandable parameters. In this paper, we propose a technique for generating chord progressions conditioned on harmonic complexity, as grounded in the Western music theory. More specifically, we consider a pre-existing dataset annotated with the related complexity values and we train two variations of Variational Autoencoders (VAE), namely a Conditional-VAE (CVAE) and a Regressor-based VAE (RVAE), in order to condition the latent space depending on the complexity. Through a listening test, we analyze the effectiveness of the proposed techniques.

Abstract Background Disorders of consciousness (DoC) are severe neurological conditions in which consciousness is impaired to various degrees. They are caused by injury or malfunction of neural systems regulating arousal and awareness. Over the last decades, major efforts in improving and individualizing diagnostic and prognostic accuracy for patients affected by DoC have been made, mainly focusing on introducing multimodal assessments to complement behavioral examination. The present EU-funded multicentric research project “PerBrain” is aimed at developing an individualized diagnostic hierarchical pathway guided by both behavior and multimodal neurodiagnostics for DoC patients. Methods In this project, each enrolled patient undergoes repetitive behavioral, clinical, and neurodiagnostic assessments according to a patient-tailored multi-layer workflow. Multimodal diagnostic acquisitions using state-of-the-art techniques at different stages of the patients’ clinical evolution are performed. The techniques applied comprise well-established behavioral scales, innovative neurophysiological techniques (such as quantitative electroencephalography and transcranial magnetic stimulation combined with electroencephalography), structural and resting-state functional magnetic resonance imaging, and measurements of physiological activity (i.e. nasal airflow respiration). In addition, the well-being and treatment decision attitudes of patients’ informal caregivers (primarily family members) are investigated. Patient and caregiver assessments are performed at multiple time points within one year after acquired brain injury, starting at the acute disease phase. Discussion Accurate classification and outcome prediction of DoC are of crucial importance for affected patients as well as their caregivers, as individual rehabilitation strategies and treatment decisions are critically dependent on the latter. The PerBrain project aims at optimizing individual DoC diagnosis and accuracy of outcome prediction by integrating data from the suggested multimodal examination methods into a personalized hierarchical diagnosis and prognosis procedure. Using the parallel tracking of both patients’ neurological status and their caregivers’ mental situation, well-being, and treatment decision attitudes from the acute to the chronic phase of the disease and across different countries, this project aims at significantly contributing to the current clinical routine of DoC patients and their family members. Trial registration ClinicalTrials.gov, NCT04798456 . Registered 15 March 2021 – Retrospectively registered.

Tropical marine ecosystems provide a wide range of provisioning, regulating, supporting and cultural services to millions of people. They also largely contribute to blue carbon sequestration. Mangroves, seaweeds, and seagrass habitats are important because they store large amounts of organic carbon while fish play a fundamental role in the carbon transport to deep waters. Protecting and restoring tropical marine ecosystems is of great value to society because their decline impairs the vital services they provide, such as coastal protection and seafood supplies. In this marine policy paper, we present options for enhancing blue carbon sequestration in tropical coastal areas. In addition, we outline the economic value of four components of coastal ecosystems (mangroves, seagrass beds, seaweed forests and fish) and discuss the economic levers society can apply to ensure the end of the current gross mismanagement of tropical blue carbon ecosystems. Market-based solutions, such as carbon taxes or fines for violations that use the ‘polluter pays' principle, can be very effective in achieving national or international climate agreements. Private investment can also finance the preservation of blue carbon ecosystems. One widely known financing method for blue carbon conservation, particularly of mangroves, is the use of municipal bonds, which can be issued like traditional bonds to finance the day-to-day obligations of cities, states and counties. Non-philanthropic investments can also be used in order to protect these ecosystems, such as debt-for-nature swaps and the improved application of regulatory frameworks. Overall, the protection of tropical marine ecosystems is an ecological imperative and should also be seen as an opportunity for new revenue streams and debt reduction for countries worldwide.

Complexity analysis of electroencephalogram (EEG) signals has emerged as a valuable tool for characterizing Parkinson’s disease (PD). Fractal dimension (FD) is a widely employed method for measuring the complexity of shapes with many applications in neurodegenerative disorders. Nevertheless, very little is known on the fractal characteristics of EEG in PD measured by FD. In this study we performed a spatio-temporal analysis of EEG in PD using FD in four dimensions (4DFD). We analyzed 42 resting-state EEG recordings comprising two groups: 27 PD patients without dementia and 15 healthy control subjects (HC). From the original resting-state EEG we derived the cortical activations defined by a source reconstruction at each time sample, generating point clouds in three dimensions. Then, a sliding window of one second (the fourth dimension) was used to compute the value of 4DFD by means of the box-counting algorithm. Our results showed a significantly higher value of 4DFD in the PD group (p < 0.001). Moreover, as a diagnostic classifier of PD, 4DFD obtained an area under curve value of 0.97 for a receiver operating characteristic curve analysis. These results suggest that 4DFD could be a promising method for characterizing the specific changes in the brain dynamics associated with PD.

The improvement of digital communication networks increased the interest towards Networked Music Performance (NMP) both for entertainment and education. One of the main issues that affects the effectiveness of remote performances is the inherent network latency in the communication chain. In this paper we propose a technique that, to the best of our knowledge, is the first work that explores the use of adaptive metronomes in order to track the tempo of the musicians and help them in coping with the latency. We test our proposal with real experiments in the context of chamber music.

BackgroundDue to continuous advances in intensive care technology and neurosurgical procedures, the number of survivors from severe acquired brain injuries (sABIs) has increased considerably, raising several delicate ethical issues. The heterogeneity and complex nature of the neurological damage of sABIs make the detection of predictive factors of a better outcome very challenging. Identifying the profile of those patients with better prospects of recovery will facilitate clinical and family choices and allow to personalize rehabilitation. This paper describes a multicenter prospective study protocol, to investigate outcomes and baseline predictors or biomarkers of functional recovery, on a large Italian cohort of sABI survivors undergoing postacute rehabilitation.MethodsAll patients with a diagnosis of sABI admitted to four intensive rehabilitation units (IRUs) within 4 months from the acute event, aged above 18, and providing informed consent, will be enrolled. No additional exclusion criteria will be considered. Measures will be taken at admission (T0), at three (T1) and 6 months (T2) from T0, and follow-up at 12 and 24 months from onset, including clinical and functional data, neurophysiological results, and analysis of neurogenetic biomarkers.StatisticsAdvanced machine learning algorithms will be cross validated to achieve data-driven prediction models. To assess the clinical applicability of the solutions obtained, the prediction of recovery milestones will be compared to the evaluation of a multiprofessional, interdisciplinary rehabilitation team, performed within 2 weeks from admission.DiscussionIdentifying the profiles of patients with a favorable prognosis would allow customization of rehabilitation strategies, to provide accurate information to the caregivers and, possibly, to optimize rehabilitation outcomes.ConclusionsThe application and validation of machine learning algorithms on a comprehensive pool of clinical, genetic, and neurophysiological data can pave the way toward the implementation of tools in support of the clinical prognosis for the rehabilitation pathways of patients after sABI.

Multiple-antibiotic-resistant (MAR) extra-intestinal pathogenic Escherichia coli (ExPEC) represents one of the most frequent causes of human nosocomial and community-acquired infections, whose eradication is of major concern for clinicians. ExPECs may inhabit indefinitely as commensal the gut of humans and other animals; from the intestine, they may move to colonize other tissues, where they are responsible for a number of diseases, including recurrent and uncomplicated UTIs, sepsis and neonatal meningitis. In the pre-antibiotic era, heavy metals were largely used as chemotherapeutics and/or as antimicrobials in human and animal healthcare. As with antibiotics, the global incidence of heavy metal tolerance in commensal, as well as in ExPEC, has increased following the ban in several countries of antibiotics as promoters of animal growth. Furthermore, it is believed that extensive bacterial exposure to heavy metals present in soil and water might have favored the increase in heavy-metal-tolerant microorganisms. The isolation of ExPEC strains with combined resistance to both antibiotics and heavy metals has become quite common and, remarkably, it has been recently shown that heavy metal resistance genes may co-select antibiotic-resistance genes. Despite their clinical relevance, the mechanisms underlining the development and spread of heavy metal tolerance have not been fully elucidated. The aim of this review is to present data regarding the development and spread of resistance to first-line antibiotics, such as beta-lactams, as well as tolerance to heavy metals in ExPEC strains.

With the big improvement of digital communication networks, Networked Music Performances (NMP) received a great interest from music live performance and music recording industry. The positive impact of NMP in pedagogical appli- cations, instead, has been only preliminary explored. Within the InterMUSIC project, we aim to investigate NMP from a pedagogical perspective, that has considerable differences with respect to music performances, and to develop tools to improve distance learning experiences. In this paper, we introduce a conceptual framework designed to be the foundation for all the experiments conducted in the project. We also present two preliminary experiments that investigate the sense of presence of geographically-distant musicians in a distance learning scenario. We discuss the comments provided by the musicians as a set of requirements and guidelines for future experiments.

Many brain-injured patients retain large cortical islands that are intact, active and reactive but blocked in a state of low complexity, leading to unconsciousness. Here, the authors show that this loss of complexity is due to the pathological engagement of sleep-like neuronal mechanisms.

The clinical assessment of patients with disorders of consciousness (DoC) relies on the observation of behavioural responses to standardised sensory stimulation. However, several medical comorbidities may directly impair the production of reproducible and appropriate responses, thus reducing the sensitivity of behaviour‐based diagnoses. One such comorbidity is akinetic mutism (AM), a rare neurological syndrome characterised by the inability to initiate volitional motor responses, sometimes associated with clinical presentations that overlap with those of DoC. In this paper, we describe the case of a patient with large bilateral mesial frontal lesions, showing prolonged behavioural unresponsiveness and severe disorganisation of electroencephalographic (EEG) background, compatible with a vegetative state/unresponsive wakefulness syndrome (VS/UWS). By applying an unprecedented multimodal battery of advanced imaging and electrophysiology‐based techniques (AIE) encompassing spontaneous EEG, evoked potentials, event‐related potentials, transcranial magnetic stimulation combined with EEG and structural and functional MRI, we provide the following: (i) a demonstration of the preservation of consciousness despite unresponsiveness in the context of AM, (ii) a plausible neurophysiological explanation for behavioural unresponsiveness and its subsequent recovery during rehabilitation stay and (iii) novel insights into the relationships between DoC, AM and parkinsonism. The present case offers proof‐of‐principle evidence supporting the clinical utility of a multimodal hierarchical workflow that combines AIEs to detect covert signs of consciousness in unresponsive patients. [ABSTRACT FROM AUTHOR]

The analysis of spontaneous electroencephalogram (EEG) is a cornerstone in the assessment of patients with disorders of consciousness (DoC). Although preserved EEG patterns are highly suggestive of consciousness even in unresponsive patients, moderately or severely abnormal patterns are difficult to interpret. Indeed, growing evidence shows that consciousness can be present despite either large delta or reduced alpha activity in spontaneous EEG. Quantifying the complexity of EEG responses to direct cortical perturbations (perturbational complexity index [PCI]) may complement the observational approach and provide a reliable assessment of consciousness even when spontaneous EEG features are inconclusive. To seek empirical evidence of this hypothesis, we compared PCI with EEG spectral measures in the same population of minimally conscious state (MCS) patients (n = 40) hospitalized in rehabilitation facilities. We found a remarkable variability in spontaneous EEG features across MCS patients as compared with healthy controls: in particular, a pattern of predominant delta and highly reduced alpha power—more often observed in vegetative state/unresponsive wakefulness syndrome (VS/UWS) patients—was found in a non‐negligible number of MCS patients. Conversely, PCI values invariably fell above an externally validated empirical cutoff for consciousness in all MCS patients, consistent with the presence of clearly discernible, albeit fleeting, behavioural signs of awareness. These results confirm that, in some MCS patients, spontaneous EEG rhythms may be inconclusive about the actual capacity for consciousness and suggest that a perturbational approach can effectively compensate for this pitfall with practical implications for the individual patient's stratification and tailored rehabilitation. [ABSTRACT FROM AUTHOR]

The limits of the standard, behaviour‐based clinical assessment of patients with disorders of consciousness (DoC) prompted the employment of functional neuroimaging, neurometabolic, neurophysiological and neurostimulation techniques, to detect brain‐based covert markers of awareness. However, uni‐modal approaches, consisting in employing just one of those techniques, are usually not sufficient to provide an exhaustive exploration of the neural underpinnings of residual awareness. This systematic review aimed at collecting the evidence from studies employing a multimodal approach, that is, combining more instruments to complement DoC diagnosis, prognosis and better investigating their neural correlates. Following the PRISMA guidelines, records from PubMed, EMBASE and Scopus were screened to select peer‐review original articles in which a multi‐modal approach was used for the assessment of adult patients with a diagnosis of DoC. Ninety‐two observational studies and 32 case reports or case series met the inclusion criteria. Results highlighted a diagnostic and prognostic advantage of multi‐modal approaches that involve electroencephalography‐based (EEG‐based) measurements together with neuroimaging or neurometabolic data or with neurostimulation. Multimodal assessment deepened the knowledge on the neural networks underlying consciousness, by showing correlations between the integrity of the default mode network and the different clinical diagnosis of DoC. However, except for studies using transcranial magnetic stimulation combined with electroencephalography, the integration of more than one technique in most of the cases occurs without an a priori‐designed multi‐modal diagnostic approach. Our review supports the feasibility and underlines the advantages of a multimodal approach for the diagnosis, prognosis and for the investigation of neural correlates of DoCs. [ABSTRACT FROM AUTHOR]

We present a dataset that combines multimodal biosignals and eye tracking information gathered under a human-computer interaction framework. The dataset was developed in the vein of the MAMEM project that aims to endow people with motor disabilities with the ability to edit and author multimedia content through mental commands and gaze activity. The dataset includes EEG, eye-tracking, and physiological (GSR and Heart rate) signals collected from 34 individuals (18 able-bodied and 16 motor-impaired). Data were collected during the interaction with specifically designed interface for web browsing and multimedia content manipulation and during imaginary movement tasks. The presented dataset will contribute towards the development and evaluation of modern human-computer interaction systems that would foster the integration of people with severe motor impairments back into society.

Abstract Urinary tract infections (UTIs) are among the most common bacterial infections in humans. Although a number of bacteria can cause UTIs, most cases are due to infection by uropathogenic Escherichia coli (UPEC). UPEC are a genetically heterogeneous group that exhibit several virulence factors associated with colonization and persistence of bacteria in the urinary tract. Caenorhabditis elegans is a tiny, free‐living nematode found worldwide. Because many biological pathways are conserved in C. elegans and humans, the nematode has been increasingly used as a model organism to study virulence mechanisms of microbial infections and innate immunity. The virulence of UPEC strains, characterized for antimicrobial resistance, pathogenicity‐related genes associated with virulence and phylogenetic group belonging was evaluated by measuring the survival of C. elegans exposed to pure cultures of these strains. Our results showed that urinary strains can kill the nematode and that the clinical isolate ECP110 was able to efficiently colonize the gut and to inhibit the host oxidative response to infection. Our data support that C. elegans, a free‐living nematode found worldwide, could serve as an in vivo model to distinguish, among uropathogenic E. coli, different virulence behavior.

The difficulties of behavioral evaluation of prolonged disorders of consciousness (DOC) motivate the development of brain-based diagnostic approaches. The perturbational complexity index (PCI), which measures the complexity of electroencephalographic (EEG) responses to transcranial magnetic stimulation (TMS), showed a remarkable sensitivity in detecting minimal signs of consciousness in previous studies. Here, we tested the reliability of PCI in an independently collected sample of 24 severely brain-injured patients, including 11 unresponsive wakefulness syndrome (UWS), 12 minimally conscious state (MCS) patients, and 1 emergence from MCS patient. We found that the individual maximum PCI value across stimulation sites fell within the consciousness range (i.e., was higher than PCI*, which is an empirical cutoff previously validated on a benchmark population) in 11 MCS patients, yielding a sensitivity of 92% that surpassed qualitative evaluation of resting EEG. Most UWS patients (n = 7, 64%) showed a slow and stereotypical TMS-EEG response, associated with low-complexity PCI values (i.e., ≤PCI*). Four UWS patients (36%) provided high-complexity PCI values, which might suggest a covert capacity for consciousness. In conclusion, this study successfully replicated the performance of PCI in discriminating between UWS and MCS patients, further motivating the application of TMS-EEG in the workflow of DOC evaluation.

Complexity analysis of electroencephalogram (EEG) signals has emerged as a valuable tool for characterizing Parkinson's disease (PD). Fractal dimension (FD) is a widely employed method for measuring the complexity of shapes with many applications in neurodegenerative disorders. Nevertheless, very little is known on the fractal characteristics of EEG in PD measured by FD. In this study we performed a spatio-temporal analysis of EEG in PD using FD in four dimensions (4DFD). We analyzed 42 resting-state EEG recordings comprising two groups: 27 PD patients without dementia and 15 healthy control subjects (HC). From the original resting-state EEG we derived the cortical activations defined by a source reconstruction at each time sample, generating point clouds in three dimensions. Then, a sliding window of one second (the fourth dimension) was used to compute the value of 4DFD by means of the box-counting algorithm. Our results showed a significantly higher value of 4DFD in the PD group (p < 0.001). Moreover, as a diagnostic classifier of PD, 4DFD obtained an area under curve value of 0.97 for a receiver operating characteristic curve analysis. These results suggest that 4DFD could be a promising method for characterizing the specific changes in the brain dynamics associated with PD. [ABSTRACT FROM AUTHOR]

It is no overstatement to say that gesture defines the universe of Yorgos Lanthimos’s cinema. Entire sequences in his films portray the characters as they perform complex and arbitrary gestures, or as they enact, through a series of orchestrated movements, a script they have been hired to perform in order to flesh out somebody else’s fantasies or to impersonate someone else’s lost loved one. Language itself is often reduced to gesture – to a superficial, obsessive and empty performance, a movement not only deprived of meaning but of emotion as well. Automatism and repetition further mark this strange universe, calling into question the idea of gesture as something either purely aesthetic or, on the other hand, intrinsically liberating, and affirming instead its entanglement with power and subjection. Characters seem to go through the motions of life, love, and mourning, instead of actually living or giving voice to their feelings. In this sense, their gestures often appear to be not mimetic but automatic, and not only devoid of finality and meaning, but also of intention: not only do the characters seem to touch just to touch, speak just to speak, and move just to move, without any immediate purpose, but, often enough, they touch only because they have been compelled to touch, speak because they have been ordered to speak, and move not through their own will but through their subjection to the will of another. These gestures are not expressive, then, but are rather performed as a bare act of submission. Reading Lanthimos’s work through Giorgio Agamben’s theory of gesture, this article discusses the performative character of agency that corresponds to pure gesture.

Transcranial magnetic stimulation (TMS) of the primary motor cortex (M1) can excite both cortico-cortical and cortico-spinal axons resulting in TMS-evoked potentials (TEPs) and motor-evoked potentials (MEPs), respectively. Despite this remarkable difference with other cortical areas, the influence of motor output and its amplitude on TEPs is largely unknown. Here we studied TEPs resulting from M1 stimulation and assessed whether their waveform and spectral features depend on the MEP amplitude. To this aim, we performed two separate experiments. In experiment 1, single-pulse TMS was applied at the same supra-threshold intensity on primary motor, prefrontal, premotor and parietal cortices and the corresponding TEPs were compared by means of local mean field power and time-frequency spectral analysis. In experiment 2 we stimulated M1 at resting motor threshold in order to elicit MEPs characterized by a wide range of amplitudes. TEPs computed from high-MEP and low-MEP trials were then compared using the same methods applied in experiment 1. In line with previous studies, TMS of M1 produced larger TEPs compared to other cortical stimulations. Notably, we found that only TEPs produced by M1 stimulation were accompanied by a late event-related desynchronization (ERD-peaking at ~300 ms after TMS), whose magnitude was strongly dependent on the amplitude of MEPs. Overall, these results suggest that M1 produces peculiar responses to TMS possibly reflecting specific anatomo-functional properties, such as the re-entry of proprioceptive feedback associated with target muscle activation.

Weed control in different crops affects the chemical, physical, and biological properties of the soil and consequently its structural quality. The objective of this study was to evaluate, using water retention characteristics and the S index, the physical quality of an Oxisol (Red-Yellow Latosol), subjected to weed control during the cultivation of coffee. The following weed control methods were evaluated: harrowing, brushcutting, residue crushing, manual weeding, post-emergence herbicide application, pre-emergence herbicide application, and maintenance of soil cover with peanut forage, Brachiaria grass, and spontaneous vegetation (no weed treatment). The following properties were determined for physical characterization of the soil: bulk density, total porosity, macroporosity, microporosity, water retention, and the S index. The weed control method significantly affected the physical properties and water retention in the subsurface layer of the Oxisol. Soil bulk density, total porosity, macroporosity, and microporosity were significantly correlated with the S index. According to the S index, the physical quality of the soil was classified as very good for the various weed control methods investigated.

O controle de plantas daninhas em cultivos de cafeeiros tem expressivo efeito na qualidade física do solo, influenciando, entre outros atributos, na sua estabilidade estrutural. Neste trabalho, objetivou-se avaliar o estado de agregação das partículas primárias de um Latossolo Vermelho-Amarelo (LVA) cultivado com cafeeiros, quando submetido a diversos métodos de controle de plantas invasoras. Os métodos de controle de plantas invasoras avaliados foram: manutenção da entrelinha coberta com amendoim-forrageiro (Arachis pintoi L.) e capim-braquiária (Brachiaria decumbens); controle mecânico com grade, roçadora, trincha e capina manual; controle químico com herbicidas de pós e pré-emergência; e ausência de controle, mantendo a entrelinha sem capina. O delineamento experimental foi em blocos casualizados em um fatorial 9 × 2 em parcelas subdivididas, sendo nove métodos de controle e duas profundidades do solo (0-15 e 15-30 cm), com três repetições. Determinaram-se a estabilidade dos agregados em água, expressa pelo diâmetro médio geométrico, o potencial dispersivo da fração argila, estimado pelos teores de argila dispersa em água e do índice de floculação, além dos teores de matéria orgânica do solo. Os atributos avaliados foram influenciados pelos diferentes métodos de controle, contudo essa influência não foi dependente da camada de solo amostrada. A utilização contínua de grade e herbicida de pré-emergência no controle de invasoras na cultura do café diminuiu a agregação das partículas do solo, confirmado pelos menores valores de diâmetro médio geométrico. Os métodos biológicos de controle das invasoras mantiveram melhor estado de agregação das partículas do solo. O estado de agregação das partículas não mostrou-se associado à dispersibilidade da fração argila do solo.