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The Fokker–Planck equation describes the evolution of the probability density associated with a stochastic differential equation. As the dimension of the system grows, solving this partial differential equation (PDE) using conventional numerical methods becomes computationally prohibitive. Here, we introduce a fast, scalable, and interpretable method for solving the Fokker–Planck equation which is applicable in higher dimensions. This method approximates the solution as a linear combination of shape-morphing Gaussians with time-dependent means and covariances. These parameters evolve according to the method of reduced-order nonlinear solutions (RONS) which ensures that the approximate solution stays close to the true solution of the PDE for all times. As such, the proposed method approximates the transient dynamics as well as the equilibrium density, when the latter exists. Our approximate solutions can be viewed as an evolution on a finite-dimensional statistical manifold embedded in the space of probability densities. We show that the metric tensor in RONS coincides with the Fisher information matrix on this manifold. We also discuss the interpretation of our method as a shallow neural network with Gaussian activation functions and time-varying parameters. In contrast to existing deep learning methods, our method is interpretable, requires no training, and automatically ensures that the approximate solution satisfies all properties of a probability density. • Develop shape-morphing modes as a fast and interpretable method for solving the Fokker-Planck equation in higher dimensions. • Analysis of the computational complexity of the method. • Connection between shape-morphing modes and Fisher information. • Connection between shape-morphing modes and shallow neural networks. • Application of the proposed method to four numerical examples. [ABSTRACT FROM AUTHOR]

Phase-amplitude coupling (PAC) in which the amplitude of a faster field potential oscillation is coupled to the phase of a slower rhythm, is one of the most well-studied interactions between oscillations at different frequency bands. In a healthy brain, PAC accompanies cognitive functions such as learning and memory, and changes in PAC have been associated with neurological diseases including Parkinson's disease (PD), schizophrenia, obsessive-compulsive disorder, Alzheimer's disease, and epilepsy. /Hypothesis: In PD, normalization of PAC in the motor cortex has been reported in the context of effective treatments such as dopamine replacement therapy and deep brain stimulation (DBS), but the possibility of normalizing PAC through intervention at the cortex has not been shown in humans. Phase-targeted stimulation (PDS) has a strong potential to modulate PAC levels and potentially normalize it. We applied stimulation pulses triggered by specific phases of the beta oscillations, the low frequency oscillations that define phase of gamma amplitude in beta-gamma PAC, to the motor cortex of seven PD patients at rest during DBS lead placement surgery We measured the effect on PAC modulation in the motor cortex relative to stimulation-free periods. We describe a system for phase-targeted stimulation locked to specific phases of a continuously updated slow local field potential oscillation (in this case, beta band oscillations) prediction. Stimulation locked to the phase of the peak of beta oscillations increased beta-gamma coupling both during and after stimulation in the motor cortex, and the opposite phase (trough) stimulation reduced the magnitude of coupling after stimulation. These results demonstrate the capacity of cortical phase-targeted stimulation to modulate PAC without evoking motor activation, which could allow applications in the treatment of neurological disorders associated with abnormal PAC, such as PD. • Phase-amplitude coupling (PAC) has been implicated as a mechanism for coordination of neural signals across brain regions. • Abnormalities in PAC have been associated with neurological diseases. • In Parkinson's disease (PD), motor symptoms are correlated with exaggerated PAC in the motor cortex and basal ganglia.. • Phase-dependent stimulation (PDS) of the motor cortex in PD patients could modulate the magnitude of PAC. • PSD has the potential to provide a closed-loop neuromodulation technique for neurological disorders. [ABSTRACT FROM AUTHOR]

Axillary lymph node clearance (ALNC) continues to play a central role in the management of melanoma. However, what defines an adequate lymphadenectomy remains unclear. We aimed to propose Quality Performance Indicators (QPIs) for ALNC and to determine if the number of lymph nodes (LNs) removed impacts survival. We reviewed patients who underwent ALNC for melanoma at the Waitemata District Health Board and Melanoma Unit between February 2005 and October 2019, performed by two surgeons with standardized technique and surveillance. 105 patients with stage III melanoma were included, of which 73 had clinically evident disease and 32 had clinically occult disease. The mean total number of LNs excised was 29 (SD 10.90, range 10–76). On multivariate analysis, lymph node ratio (HR 4.48, 95% CI 1.55–12.93, p = 0.006), extracapsular spread (HR 2.53, 95% CI 1.06–6.05, p = 0.036) and distant recurrence (HR 11.24, 95% CI 3.79–33.31, p < 0.001) were significant predictors of mortality. The number of LNs removed did not predict survival outcomes, while the lymph node ratio did significantly predict survival outcomes. The regional recurrence rate was 3.8%. We propose that QPIs for ALNC in melanoma include a 90th percentile LN yield of greater than 15, a mean LN yield of 20, a regional recurrence rate of less than 10%, and an overall complication rate of less than 50%. The establishment of QPIs can help ensure that surgical oncology patients receive the highest quality of care. [ABSTRACT FROM AUTHOR]

Purpose: To determine if aztreonam as initial empiric treatment of adult septic shock is associated with increased mortality compared to the use of anti-pseudomonal beta-lactam agents.Methods: This was a multicenter, retrospective cohort study of 582 adult emergency department patients admitted to 12 acute care facilities within a single health system from January 2014 to December 2017 with septic shock receiving either aztreonam or an anti-pseudomonal beta-lactam for empiric treatment and discharged with an infection-related ICD-9 or ICD-10 code. The primary endpoint was in-hospital mortality.Results: Initial exposure to aztreonam was associated with increased hospital mortality compared to treatment with an anti-pseudomonal beta-lactam agent (22.7% vs. 12.9%, OR = 1.98, 95% CI: 1.27-3.11). When adjusted for APACHE II score, the treatment group effect on mortality remained statistically significant (OR = 1.74, 95% CI: 1.08-2.80). Aztreonam use was also associated with increased utilization of aminoglycosides (28.9% vs. 12.4%, p < 0.0001) and fluoroquinolones (50.5% vs. 25.8%, p < 0.01). There was no difference in hospital or intensive care unit length of stay in surviving patients between the two groups.Conclusions: Compared to anti-pseudomonal beta-lactams, empiric treatment with aztreonam is associated with increased mortality and greater antibiotic exposure among patients with acute septic shock. These findings suggest that treatment with anti-pseudomonal beta-lactams should be prioritized over allergy avoidance whenever feasible. [ABSTRACT FROM AUTHOR]

Porous additively-manufactured structures could have a niche in orthopaedic implants, due to their potential to reduce stiffness (stress-shielding), improve bony ingrowth, and potential to house reservoirs of drug-eluting non-structural biomaterials. Computer aided design and finite element (FE) modelling plays an important role in the design of porous structured biomedical implants; however it is important to validate both their static and fatigue behaviours using experimental testing. This study compared the mechanical behaviors of titanium cylindrical gyroid structures of varying porosities using physical testing of additively manufactured prototypes and FE models. There was agreement in the measured and predicted relationships between porosity and apparent modulus of elasticity. As porosity increased (and wall thickness decreased), the structures failed at a lower number of cycles when loaded at the same percentage of their yield strengths. Calibration of the fatigue strength coefficient from a previously published value of 1586.5 MPa–1225 MPa greatly improved the fatigue life prediction accuracy for all the gyroid structures. Nevertheless, differences of up to 54% in the predicted versus experimental fatigue lives remained, which could be attributed to difficulties with how the precise time and location of failure is defined in the simulations, and/or minor differences in nominal and actual porosities. Although further calibration and validation should be explored, this study demonstrates that static and fatigue FE-modelling techniques could be used to aid in the design of porous prosthetics. • Computational modelling of gyroid structures for static and fatigue testing validation. • FEM accurately predicted porosity vs. apparent elastic modulus relationships. • Difficult to predict location of failure on complex gyroid structures. • Calibration of fatigue strength coefficient improved fatigue predictions. [ABSTRACT FROM AUTHOR]

Cognitive control involves flexibly combining multiple sensory inputs with task-dependent goals during decision making. Several tasks involving conflicting sensory inputs and motor outputs have been proposed to examine cognitive control, including the Stroop, Flanker, and multi-source interference task. Because these tasks have been studied independently, it remains unclear whether the neural signatures of cognitive control reflect abstract control mechanisms or specific combinations of sensory and behavioral aspects of each task. To address these questions, we record invasive neurophysiological signals from 16 patients with pharmacologically intractable epilepsy and compare neural responses within and between tasks. Neural signals differ between incongruent and congruent conditions, showing strong modulation by conflicting task demands. These neural signals are mostly specific to each task, generalizing within a task but not across tasks. These results highlight the complex interplay between sensory inputs, motor outputs, and task demands underlying cognitive control processes. [Display omitted] • Neural signals reveal incongruency during multiple cognitive control tasks • The neural circuits that detect conflict generalize within a task • The neural mechanisms underlying cognitive control are not task invariant • Cognitive control relies on specific combinations of sensory inputs and motor outputs Cognitive control involves flexibly routing information according to current goals. Xiao et al. demonstrate that the neural mechanisms underlying cognitive control generalize across different conditions within a task but are not task invariant. Instead, the neural signatures of conflict monitoring reflect task-dependent combinations of sensory inputs and motor outputs. [ABSTRACT FROM AUTHOR]

The resilience and low cost of plastics has made their usage ubiquitous, but is also the cause of their prevalence and longevity as waste. Plastic pollution has become a great concern to the health and wellbeing of ecosystems around the world; microplastics are a particular threat, due to their high mobility, ease of ingestion by wildlife, and ability to adsorb and carry toxic contaminants. Material flow analysis has been widely applied to examine stocks and flows of materials in other industries, and has more recently been applied to plastics to examine areas where waste can reach the environment. However, while much research has gone into the environmental fate of microplastics, degradation strategies have been a lesser focus, and material flow analysis of microplastics has suffered from lack of data. Furthermore, the variety of plastics, their additives, and any contaminants pose a significant challenge in degrading (and not merely fragmenting) microplastic particles. This review discusses the current degradation strategies and solutions for dealing with existing and newly-generated microplastic waste along with examining the status of microplastics-based material flow analysis, which are critical for evaluating the possibility of incorporating microplastic waste into a circular economy. The degradation strategies are critically examined, identifying challenges and current trends, as well as important considerations that are frequently under-reported. An emphasis is placed on identifying missing data or information in both material flow analysis and degradation methods that could prove crucial in improving understanding of microplastic flows, as well as optimizing degradation strategies and minimizing any negative environmental impact. [Display omitted] • Microplastic remediation is trending towards sustainable options. • Challenges arise from variety of plastics, additives, and contaminants. • Completeness of degradation is important, but not often investigated. • Additional reporting of parameters and characterization is needed. • Degradation techniques could be combined to address their respective disadvantages. [ABSTRACT FROM AUTHOR]

Regional economic productivity and growth require a reliable, robust road transportation network to facilitate the movement of freight by trucks. Previous network robustness measures focus on the physical effects of network disruptions, such as travel time delays resulting from disabled links. However, the economic impacts associated with disruptions of freight flows must also be accounted for. This paper presents a methodology for generating industry-specific origin-destination freight demand matrices for the province of Ontario, Canada using truck GPS tracking data and the provincially mandated Commercial Vehicle Survey. Six mutually exclusive industry groups are defined, whose spatial interactions are expected to vary. A cost per shipment is estimated for each industry group and used to examine the value of goods carried on each network link for the 1 pm peak hour. Criticality is explored through the combined impacts on travel time due to link disruption and the value of goods carried on the respective links. As expected, a subset of links belonging to important trade corridors are highlighted as critical. Such characterization of the network provides an in-depth view of the economic activity and criticalities associated with regional trucking networks and can inform planning and mitigation measures to maximize network-wide benefits. • Industry-level freight analysis helps characterize inter-regional economic activity • Industry-level freight demand and shipment values are estimated • Shipment value and time delay are used to assess network criticality • Major freight corridors and border crossings are associated with high criticality • Application to Ontario can inform policies to help mitigate disruption effects [ABSTRACT FROM AUTHOR]

Cognition depends on rapid and robust communication between neural circuits spanning different brain areas. We investigated the mesoscopic network of cortico-cortical interactions in the human brain in an extensive dataset consisting of 6,024 h of intracranial field potential recordings from 4,142 electrodes in 48 subjects. We evaluated communication between brain areas at the network level across different frequency bands. The interaction networks were validated against known anatomical measurements and neurophysiological interactions in humans and monkeys. The resulting human brain interactome is characterized by a broad and spatially specific, dynamic, and extensive network. The physiological interactome reveals small-world properties, which we conjecture might facilitate efficient and reliable information transmission. The interaction dynamics correlate with the brain sleep/awake state. These results constitute initial steps toward understanding how the interactome orchestrates cortical communication and provide a reference for future efforts assessing how dysfunctional interactions may lead to mental disorders. [Display omitted] • Recorded continuous intracranial field potentials for 5 days in 48 human subjects • Characterized functional mesoscopic interactome assessed by pairwise coherence • Validated methods using anatomical and physiological interactions in monkeys • Human functional interactome shows small-world graph and changes with brain state Cognition relies on rapid and robust communication between brain areas. Wang et al. leverage multi-day intracranial field potential recordings to characterize the human mesoscopic functional interactome. They validated the methods using monkey anatomical and physiological data. The human interactome reveals small-world properties and is modulated by sleep versus awake state. [ABSTRACT FROM AUTHOR]

Increased demand for single-use personal protective equipment (PPE) during the COVID-19 pandemic has resulted in a marked increase in the amount of PPE waste and associated environmental pollution. Developing efficient and environmentally safe technologies to manage and dispose of this PPE waste stream is imperative. We designed and evaluated a hydrothermal deconstruction technology to reduce PPE waste by up to 99% in weight. Hydrothermal deconstruction of single-use PPE waste was modelled using experimental data in Aspen Plus. Techno-economic and sensitivity analyses were conducted, and the results showed that plant scale, plant lifetime, discount rate, and labour costs were the key factors affecting overall processing costs. For a 200 kg/batch plant under optimal conditions, the cost of processing PPE waste was found to be 10 NZD/kg (6 USD/kg), which is comparable to the conventional practice of autoclaving followed by landfilling. The potential environmental impacts of this process were found to be negligible; meanwhile, this practice significantly reduced the use of limited landfill space. [ABSTRACT FROM AUTHOR]

Stereoelectroencephalography (SEEG) is a critical tool used in the identification of epileptogenic zones. Although stereotactic frame-based SEEG procedures have been performed traditionally, newer robotic-assisted SEEG procedures have become increasingly common. In this study, we evaluate the accuracy, efficacy of the ExcelsiusGPS robot (Globus Medica, Audubon, PA) in SEEG procedures. Five consecutive adult patients with drug resistant epilepsy were identified as SEEG candidates via a multidisciplinary epilepsy surgery committee. Preoperative scans were merged onto the robot to plan electrode placement. With the use of a camera system, dynamic reference base, and surveillance markers, the robotic arm was used to establish the trajectory of the electrodes. Postoperative computed tomography (CT) scans were merged onto the preoperatively planned trajectory and the radial, depth, and entry errors were calculated. Fiducial registration error was calculated for 4 cases to determine error between the patient and intraoperative CT merge. A total of 59 electrodes were placed. The mean age at surgery was 41.6 ± 15.1 years. Mean operating room time, anesthesia time, and surgical time was 301.6 ± 44.4 min, 261.6 ± 50.2 min, and 155.8 ± 48.8 min, respectively. The overall mean depth, radial, and entry errors were 2.5 ± 1.9 mm, 1.9 ± 1.5 mm, and 1.6 ± 1.2 mm. Mean fiducial registration error retrospectively calculated for 4 of 5 cases was 0.13 ± 0.04 mm. There were no perioperative complications. The initial performance of the ExcelsiusGPS robotic system yielded comparable results to other systems currently in use for adult SEEG procedures. [ABSTRACT FROM AUTHOR]

[Display omitted] • Up to 98% of single-use PPE items was deconstructed. • Up to 547 mg/L ammonia was detected in the resulting reaction mixture. • Volatile fatty acids, primarily acetic acid up to 8974 mg/L was produced. • Carbon dioxide and oxygen were the main gaseous products in the off-gas stream. To minimise the transmission of the SARS-CoV-2 virus, there has been a substantial increase in the production and usage of synthetic personal protective equipment (PPE) globally. Consequently, single-use PPE have been widely adopted without appropriate regulations for their disposal, leading to extensive environmental contamination worldwide. This study investigates the non-catalytic hydrothermal deconstruction of different PPE items, including isolation gowns, gloves, goggles, face shields, surgical masks, and filtering-facepiece respirators. The selected PPE items were subjected to hydrothermal deconstruction for 90 min in the presence of 30-bar initial oxygen pressure, at temperatures ranging between 250 °C and 350 °C. The solid content in form of total suspended solids (TSS) was reduced up to 97.6%. The total chemical oxygen demand (tCOD) and soluble chemical oxygen demand (sCOD) decreased with increasing deconstruction temperature, and at 350 °C the lowest tCOD and sCOD content of 546.6 mg/L and 470 mg/L, respectively, was achieved. Short-chained volatile fatty acids were produced after 90 min of deconstruction, predominantly acetic acid at concentrations up to 8974 mg/L. Ammonia nitrogen content (NH 3 –N) of up to 542.6 mg/L was also detected. Carbon dioxide (CO 2) and unreacted oxygen (O 2) were the main gaseous by-products at up to 15.6% (w/w) and 88.7% (w/w), respectively. The findings suggest that non-catalytic hydrothermal deconstruction is a viable option to process and manage PPE waste. [ABSTRACT FROM AUTHOR]

Rocket engine combustors are prone to transverse instabilities that are characterized by large amplitude high frequency oscillations in the acoustic pressure and the heat release rate. In this work, we study the coupled interaction between the acoustic pressure and the CH* intensity (representative of heat release rate) oscillations in a 2D multi-element self-excited model rocket combustor during the transition from a stable state to thermoacoustic instability through intermittency. We show the emergence of synchronization between these oscillations from desynchronization through intermittent phase synchronization during the onset of thermoacoustic instability. We find substantial evidence that the intensities of the jet flames close to the end wall is higher than that observed near the center of the combustor as a result of its strong coupling to the local acoustic field. Using concepts from recurrence theory, we distinguish the type of synchronization between the acoustic pressure and the CH* intensity oscillations at the end wall and the center of the combustor during thermoacoustic instability. Analyzing the local CH* intensity oscillations, we observe that the longitudinally propagating jet flames experience substantial transverse displacement with flame merging effects during thermoacoustic instability. Furthermore, we differentiate the interaction of the jet flames with the shock wave during intermittency and thermoacoustic instability at both the end wall and the center of the combustor. We also discerned the change from stochastic to deterministic nature in the local CH* intensity oscillations during the transition to thermoacoustic instability. Our results demonstrate that only the first few transverse modes contribute to the generation of acoustic power from the reacting flow, in spite of the pressure oscillations featuring several harmonics. The insights gained from such coupled analysis during the transition from stable state to thermoacoustic instability can be leveraged to aid modeling efforts of thermoacoustic instability in rocket engines with multiple injectors. [ABSTRACT FROM AUTHOR]