Standard Case Research Articles

Nonlinear evolution of disturbances in higher time-derivative theories

We investigate the evolution of localized initial value profiles when propagated in integrable versions of higher time-derivative theories. In contrast to the standard cases in nonlinear integrable systems, where these profiles evolve into a specific number of N-soliton solutions as dictated by the conservation laws, in the higher time-derivative theories the theoretical prediction is that the initial profiles can settle into either two-soliton solutions or into any number of N-soliton solutions. In the latter case this implies that the solutions exhibit oscillations that spread in time but remain finite. We confirm these analytical predictions by explicitly solving the associated Cauchy problem numerically with multiple initial profiles for various higher time-derivative versions of integrable modified Korteweg-de Vries equations. In the case with the theoretical possibility of a decay into two-soliton solutions, the emergence of underlying singularities may prevent the profiles from fully developing or may be accompanied by oscillatory, chargeless standing waves at the origin.

No evidence that reversibility affects causal judgments in late-preemption cases

ABSTRACT Recently, Ross and Woodward (2022) argued that the reversibility of an outcome – that is, whether the outcome can be undone – affects causal judgments. One prediction of their account is that reversibility affects causal judgments in late-preemption scenarios, where people typically judge that events that produce the outcome earlier are more causal than preempted alternative events that would have otherwise produced the outcome. Ross and Woodward’s account predicts that when the outcome is reversible, people would judge these events similarly – as in standard overdetermination cases. In three experiments, we found no evidence that reversibility affects causal judgments in late-preemption cases. We discuss how these results affect the experimental philosophy and cognitive science of causation, causal modeling, and experimental jurisprudence.

Fast and accurate local ancestry inference with Recomb-Mix.

The availability of large genotyped cohorts brings new opportunities for revealing the high-resolution genetic structure of admixed populations via local ancestry inference (LAI), the process of identifying the ancestry of each segment of an individual haplotype. Though current methods achieve high accuracy in standard cases, LAI is still challenging when reference populations are more similar (e.g., intra-continental), when the number of reference populations is too numerous, or when the admixture events are deep in time, all of which are increasingly unavoidable in large biobanks. Here, we present a new LAI method, Recomb-Mix. Recomb-Mix integrates the elements of existing methods of the site-based Li and Stephens model and introduces a new graph collapsing trick to simplify counting paths with the same ancestry label readout. Through comprehensive benchmarking on various simulated datasets, we show that Recomb-Mix is more accurate than existing methods in diverse sets of scenarios while being competitive in terms of resource efficiency. We expect that Recomb-Mix will be a useful method for advancing genetics studies of admixed populations.

Stochastic block hypergraph model.

The stochastic block model is widely used to generate graphs with a community structure, but no simple alternative currently exists for hypergraphs, in which more than two nodes can be connected together through a hyperedge. We discuss here such a hypergraph generalization, based on the clustering connection probability P_{ij} between nodes of communities i and j, and that uses an explicit and modulable hyperedge formation process. We focus on the standard case where P_{ij}=pδ_{ij}+q(1-δ_{ij}) when 0≤q≤p (δ_{ij} is the Kronecker symbol). We propose a simple model that satisfies three criteria: it should be as simple as possible, when p=q the model should be equivalent to the standard hypergraph random model, and it should use an explicit and modulable hyperedge formation process so that the model is intuitive and can easily express different real-world formation processes. We first show that for such a model the degree distribution and hyperedge size distribution can be approximated by binomial distributions with effective parameters that depend on the number of communities and q/p. Also, the composition of hyperedges goes for q=0 from 'pure' hyperedges (comprising nodes belonging to the same community) to 'mixed' hyperedges that comprise nodes from different communities for q=p. We test various formation processes and our results suggest that when they depend on the composition of the hyperedge, they tend to favor the dominant community and lead to hyperedges with a smaller diversity. In contrast, for formation processes that are independent from the hyperedge structure, we obtain hyperedges comprising a larger diversity of communities. The advantages of the model proposed here are its simplicity and flexibility that make it a good candidate for testing community-related problems, such as their detection, impact on various dynamics, and visualization.

Hopf bifurcation and stability analysis for a delayed equation with φ-Laplacian

A formal framework for the analysis of Hopf bifurcations for a kind of delayed equation with $\varphi$-Laplacian and with a discrete time delay is presented, thus generalizing known results for the sunflower equation given by Somolinos in 1978. Also, under appropriate assumptions we prove the gradient-like behavior of the equation which, in turn, implies the non-existence of nonconstant periodic solutions. Our conditions improve previous results known in the literature for the standard case $\varphi(x)=x$.

Unit commitment of power systems considering system inertia constraints and uncertainties

AbstractLarge‐scale integration of renewable energy into the power grid results in a lack of system inertia, posing challenges to the optimal operation and scheduling of systems considering frequency stability. This article proposes a unit commitment model that considers both inertia constraints and the uncertainty of load and renewable energy. First, the time‐domain expression of the system frequency response is calculated based on the aggregated System Frequency Response (SFR) model, considering the system's maximum frequency deviation and the maximum Rate of Change of Frequency (RoCoF) limit. This calculation determines the minimum inertia requirement for the system. Furthermore, inertia constraints suitable for mixed‐integer programming model are derived to address the nonlinearity of conventional frequency constraints. Second, considering the uncertainties of load and wind energy from renewable sources, a unit commitment model with inertia constraints is constructed, and a robust method is used to solve the uncertainties. Finally, the accuracy of the proposed inertia constraints and unit commitment model is validated using case study of IEEE standard test cases and a provincial power grid in China.

Monkeypox pandemic in Sudan, surveillance epidemiologic report, 2022

BackgroundMpox, is a zoonosis that is known to be endemic in several Central and West African countries. Recently, in 2022, it has emerged in Europe and United States, what raised the alarm to be declared in late June 2024 as a public health event of international concern. This study aimed to give insight about the recent spread of mpox in Sudan, and documents the epidemiologic situation.MethodsThrough a cross-sectional design, Sudan mpox data was extracted from the disease surveillance line-list at the national level at Sudan Federal Ministry of Health. the data was customized and then analyzed using Epi Info7 software. Analysis was done using frequencies and percentages and the results presented in tables and figures. Permission and ethical approval were obtained from the Health Emergency and Epidemic Control Directorate at the Federal Ministry of Health.ResultsThe outbreak of mpox was confirmed after testing of initial specimens outside Sudan with positivity rate of 72%. Later the cases continued to be reported based on the clinical diagnosis and standard case definition. Out of 375 reported cases, 54.4% were males, while 45.6% were females. The age of cases ranged from one month to 78 years with majority (41.1%) of the cases were children under 5 years of age. Regarding the reported symptoms, all cases had the characteristic skin rash and 74.1% of them had fever. Other symptoms included, headache (31.5%), sore throat (30.9%) and lymphadenopathy (26.1%). For occupation, 35.7% were preschool and 10.4% were school children, 9% of cases were prisoners. Around 22 (5.8%) reported contact history with a confirmed case, while (5.6%) of the cases were imported cases. Cases were reported from 17 states with 42 affected localities (districts) with an overall attack rate of 2.36/ 100,000. The highest number of cases was reported from Gadaref (45.3%), West Darfur (25.9%), Khartoum (13.3%) and north Darfur (3.5%). In Gadaref, 146 (85.8%) of the cases were from a refugees’ camp. Started in epi week 19, the outbreak peaked in week 38 and last in week 42.ConclusionMpox was confirmed in the new Sudan for the first time with cases reported in most of states. Although importation of the virus is hypothesized, internal hidden circulation is possible and more in-depth investigation is highly recommended. The higher rate of infection among preschool, school children and refugees, highlights the need to strengthen the prevention and control measures in schools and camps. More focus on the data completeness is required for better understanding of the disease and can be ensured by the surveillance directorate through training of staff and updating of reporting forms. Strengthening the lab capacity inside the country is a necessity to ensure testing of all the clinically diagnosed cases.

Feasibility of Using Simulation to Evaluate Implementation Fidelity in an Advance Care Planning Pragmatic Trial.

Background and Objectives: Traditional methods of fidelity monitoring are not possible in pragmatic trials in real-world clinical settings. We describe our approach to monitoring and reinforcing the fidelity to ACP conversations for a hard-to-reach subpopulation by using standardized patients in a pragmatic trial. Research Design and Methods: We developed standardized patient scenarios grounded in the Respecting Choices First Steps™ Advance Care Planning curriculum to provide an opportunity to reinforce and assess ACP facilitator competency. Scenarios represented one-on-one encounters. The first case was a standardized patient with cognitive impairment and the second case involved a standardized patient with dementia and their care partner. A previously validated fidelity checklist was used to score skills and behaviors observed during simulations including encounter set-up, ACP topics, and general communication. Simulations involved voice teleconferencing to align primary modality of ACP in the pragmatic trial. Results: Six facilitators completed two standardized patient cases each. Overall fidelity scores were moderately high (78.8% ± 11.7; 63.4 - 95.6) for the case with cognitive impairment and for the case with the patient with dementia and care partner (76.2% ± 13.0; 54.4 - 91.5). Discussion and Implications: Simulation using standardized patients supported fidelity monitoring and provided coachable feedback to support facilitator competency. Our study can help inform future research and training related to advance care planning in older adults living with Alzheimer's disease and related disorders.

An improved high-order low dissipation weighted compact nonlinear scheme for compressible flow simulations

Recently, Zhang developed a low-dissipation high-order scheme that employs Fu's targeted essentially non-oscillatory approach. this method incorporates an essentially non-oscillatory-like stencil selection strategy within the framework of the weighted compact nonlinear scheme proposed by Deng. Although this new scheme, termed targeted compact nonlinear scheme (TCNS), can recover ideal weights in smooth regions, it reduces accuracy at the discontinuities by discarding less smooth sub-stencils. Acker et al. showed in a recent study that increasing the weight of less smooth sub-stencils on a relatively coarse grid can further improve the wave resolution. Luo further improved Acker's scheme to fully exploit its potential in spectral characteristics. By following this idea, the less smooth stencil weights were incorporated to overcome problems of classical TCNS and to further improve the scheme's ability to resolve high-frequency waves. Moreover, by introducing an adaptive factor, we further optimized the spectral properties to improve the TCNS. A series of standard cases were used to measure the resolution of the new method for multiscale structures and the ability to suppress nonphysical oscillations at shock waves. The new scheme was applied to three cases involving complex configurations and multiscale flows, demonstrating that its low dissipation characteristics offer advantages in solving real-life problems.

VJY02 Robot-assisted sacrocolpopexy: Step-by-step technique for standard cases and complex situations management

VJY02 Robot-assisted sacrocolpopexy: Step-by-step technique for standard cases and complex situations management

Antibiotic Usage Pattern against COVID-19 in Patients of a Tertiary Care Hospital

The coronavirus disease of 2019 (COVID-19) emerged as a pandemic at the end of 2019. The clinical presentation of COVID-19 was comparable to bacterial infections, and due to the ambiguity of an effective treatment method, the healthcare professionals routinely used antibiotics to treat the patients. So, this study evaluated the antibiotic usage patterns at our hospitals among COVID-19 patients, considering the World Health Organization (WHO) AWaRe (Access, Watch, and Reserve) classification. The present study was a retrospective observational hospital record-based study on COVID-19 patients admitted from March-August 2020. A total of 256 COVID-19 patients were enrolled, considering inclusion and exclusion criteria. Data collection utilizing a standardized case record form to capture all information methodically based on age, sex, comorbidities, duration, and nature of the symptoms. Drug data, for example antibiotic usage patterns were collected with detailed prescription analysis, including route, dose, frequency and number of antibiotics used. A structured proforma was used to analyze data, and descriptive statistical analysis was performed and presented as Histograms. The WHO AWaRe antibiotic classification was used to determine the antibiotics’ suitability for empirical therapy. The mean age of the participants was 40.00 ± 15.46 years with male predominance, 188 (73.43%) in number, compared to females, with 68 (26.56%). Almost all the current study participants received one or more antibiotics during their hospital stay, and a maximum of the patients 126 (49.22%) received 2 antibiotics during treatment, 78 (30.47%) subjects who were managed with 3 antibiotics, and the rest, 52 (20.31%) participants received only 1 antibiotic during their hospital stay. To treat moderate to severely ill patients, the most used antibiotic was doxycycline, followed by meropenem and piperacillin/tazobactam. The findings of this study will provide baseline data that will help to generate strategies to reduce antibiotic prescriptions for the formulation of better antibiotic stewardship programs (ASP) and institutional policies to fight against any infection in a better way in the near future.

A new local and explicit kinetic method for linear and non-linear convection-diffusion problems with finite kinetic speeds: II. Multi-dimensional case

We extend to multi-dimensions the work of [1], where new fully explicit kinetic methods were built for the approximation of linear and non-linear convection-diffusion problems. The fundamental principles from the earlier work are retained: (1) rather than aiming for the desired equations in the strict limit of a vanishing relaxation parameter, as is commonly done in the diffusion limit of kinetic methods, diffusion terms are sought as a first-order correction of this limit in a Chapman-Enskog expansion, (2) introducing a coupling between the conserved variables within the relaxation process by a specifically designed collision matrix makes it possible to systematically match a desired diffusion. Extending this strategy to multi-dimensions cannot, however, be achieved through simple directional splitting, as diffusion is likely to couple space directions with each other, such as with shear viscosity in the Navier-Stokes equations. In this work, we show how rewriting the collision matrix in terms of moments can address this issue, regardless of the number of kinetic waves, while ensuring conservation systematically. This rewriting allows for introducing a new class of kinetic models called regularized models, simplifying the numerical methods and establishing connections with Jin-Xin models. Subsequently, new explicit arbitrary high-order kinetic schemes are formulated and validated on standard two-dimensional cases from the literature. Excellent results are obtained in the simulation of a shock-boundary layer interaction, validating their ability to approximate the Navier-Stokes equations with kinetic speeds obeying nothing but a subcharacteristic condition along with a hyperbolic constraint on the time step.

Multiview Multistatic vs. Multimonostatic Three-Dimensional Ground-Penetrating Radar Imaging: A Comparison

The availability of multichannel ground-penetrating radar systems capable of gathering multiview, multistatic, multifrequency data provides novel chances to improve subsurface imaging results. However, customized data processing techniques and smart choices of the measurement setup are needed to find a trade-off between image quality and acquisition time. In this paper, we adopt a Born Approximation-based full 3D approach, which can manage multiview-multistatic, multifrequency data and faces the imaging as a linear inverse scattering problem. The inverse problem is solved by exploiting the truncated singular value decomposition as a regularization scheme. The paper presents a theoretical study aimed at assessing how the reconstruction capabilities of the imaging approach depend on the adopted measurement configuration. In detail, the performance achievable in the standard case of multimonostatic, multifrequency data is compared with that provided by a multiview-multistatic, multifrequency configuration, where the data are gathered by considering a progressively increasing number of transmitting antennas. The comparison of the achievable imaging performance is carried out by exploiting the spectral content and the point spread function, which are general tools to foresee the achievable reconstruction capabilities. Reconstruction results related to a numerical experiment based on full-wave data are also provided.

Utility of large language models for creating clinical assessment items.

To compare student performance, examiner perceptions and cost of GPT-assisted (generative pretrained transformer-assisted) clinical and professional skills assessment (CPSAs) items against items created using standard methods. We conducted a prospective, controlled, double-blinded comparison of CPSA items developed using GPT-assistance with those created through standard methods. Two sets of six practical cases were developed for a formative assessment sat by final year medical students. One clinical case in each set was created with GPT-assistance. Students were assigned to one of the two sets. The results of 239 participants were analysed in the study. There was no statistically significant difference in item difficulty, or discriminative ability between GPT-assisted and standard items. One hundred percent (n=15) of respondents to an examiner feedback questionnaire felt GPT-assisted cases were appropriately difficult and realistic. GPT-assistance resulted in significant labour cost savings, with a mean reduction of 57% (880 GBP) in labour cost per case when compared to standard case drafting methods. GPT-assistance can create CPSA items of comparable quality with significantly less cost when compared to standard methods. Future studies could evaluate GPT's ability to create CPSA material in other areas of clinical practice, aiming to validate the generalisability of these findings.

A human centered design approach to define and measure documentation quality using an EHR virtual simulation.

Electronic health record (EHR) documentation serves multiple functions, including recording patient health status, enabling interprofessional communication, supporting billing, and providing data to support the quality infrastructure of a Learning Healthcare System. There is no definition and standardized method to assess documentation quality in EHRs. Using a human-centered design (HCD) approach, we define and describe a method to measure documentation quality. Documentation quality was defined as timely, accurate, user-centered, and efficient. Measurement of quality used a virtual simulated standardized patient visit via an EHR vendor platform. By observing and recording documentation efforts, nurse practitioners (NPs) (N = 12) documented the delivery of an Age-Friendly Health System (AFHS) 4Ms (what Matters, Medication, Mentation, and Mobility) clinic visit using a standardized case. Results for timely documentation indicated considerable variability in completion times of documenting the 4Ms. Accuracy varied, as there were many types of episodes of erroneous documentation and extra time in seconds in documenting the 4Ms. The type and frequency of erroneous documentation efforts were related to navigation burden when navigating to different documentation tabs. The evaluated system demonstrated poor usability, with most participants scoring between 60 and 70 on the System Usability Scale (SUS). Efficiency, measured as click burden (the number of clicks used to navigate through a software system), revealed significant variability in the number of clicks required, with the NPs averaging approximately 13 clicks above the minimum requirement. The HCD methodology used in this study to assess the documentation quality proved feasible and provided valuable information on the quality of documentation. By assessing the quality of documentation, the gathered data can be leveraged to enhance documentation, optimize user experience, and elevate the quality of data within a Learning Healthcare System.

Augmenting intensive care unit nursing practice with generative AI: A formative study of diagnostic synergies using simulation-based clinical cases.

As generative artificial intelligence (GenAI) tools continue advancing, rigorous evaluations are needed to understand their capabilities relative to experienced clinicians and nurses. The aim of this study was to objectively compare the diagnostic accuracy and response formats of ICU nurses versus various GenAI models, with a qualitative interpretation of the quantitative results. This formative study utilized four written clinical scenarios representative of real ICU patient cases to simulate diagnostic challenges. The scenarios were developed by expert nurses and underwent validation against current literature. Seventy-four ICU nurses participated in a simulation-based assessment involving four written clinical scenarios. Simultaneously, we asked ChatGPT-4 and Claude-2.0 to provide initial assessments and treatment recommendations for the same scenarios. The responses from ChatGPT-4 and Claude-2.0 were then scored by certified ICU nurses for accuracy, completeness and response. Nurses consistently achieved higher diagnostic accuracy than AI across open-ended scenarios, though certain models matched or exceeded human performance on standardized cases. Reaction times also diverged substantially. Qualitative response format differences emerged such as concision versus verbosity. Variations in GenAI models system performance across cases highlighted generalizability challenges. While GenAI demonstrated valuable skills, experienced nurses outperformed in open-ended domains requiring holistic judgement. Continued development to strengthen generalized decision-making abilities is warranted before autonomous clinical integration. Response format interfaces should consider leveraging distinct strengths. Rigorous mixed methods research involving diverse stakeholders can help iteratively inform safe, beneficial human-GenAI partnerships centred on experience-guided care augmentation. This mixed-methods simulation study provides formative insights into optimizing collaborative models of GenAI and nursing knowledge to support patient assessment and decision-making in intensive care. The findings can help guide development of explainable GenAI decision support tailored for critical care environments. Patients or public were not involved in the design and implementation of the study or the analysis and interpretation of the data.

Epidemiological profile of malaria in a rural community in the Amazon, Mato Grosso State, Brazil, 2011

BackgroundMore than 95% of malaria transmission in Brazil occurs in the Legal Amazon Region, which in 2010 recorded around 333,429 cases reported in the Epidemiological Surveillance Information System-Malaria (Sivep_malaria), presenting an annual parasitic incidence (IPA) of 13.1 cases/1000 inhabitants.MethodsThis was a descriptive study that measured the community prevalence of Plasmodium infection and its relationship with land use in Três Fronteiras District, Colniza Municipality, Mato Grosso State. Data were collected during household visits in July 2011, with blood collection from finger pricks for the preparation of thick smear slides, and completion of a standardized case notification form. A georeferenced database was analysed, with land use evaluated as categorical variables. A kernel density map was built to show the density of cases and their location.ResultsOf the 621 respondents, 68(11%) had Plasmodium infection: 39 (57.4%) with Plasmodium vivax, 27(39.7%) with Plasmodium falciparum and two (2.9%) with mixed infections. Among infected individuals, 49 (72.1%) were men. Cases of malaria were distributed over the district, with greater occurrence of cases per household in open areas close to the mining company and artisanal mining sites. The was a greater density of cases located in the gold mining region.ConclusionTransmission of malaria in Três Fronteiras District has a heterogeneous distribution. Individuals residing in mining and timber extraction sites have increased occurrence of Plasmodium infection.

Gridder-HO: Rapid and efficient parallel software for high-order curvilinear mesh generation

The advancement in high-order computational methods is reshaping the landscape of mesh generation in Computational Fluid Dynamics (CFD), steering the focus towards curvilinear mesh techniques to meet the escalating accuracy demands. Gridder-HO, the software designed to generate high-order curvilinear mesh efficiently and rapidly, has been developed. Gridder-HO supports the elevation of meshes to P2 (quadratic-order) or P3 (cubic-order). It features a layered architecture and utilizes the concurrent hash table and the Alternating Digital Tree (ADT) data structure, supporting thread-level parallelism to convert straight-edge mesh into high-order curvilinear mesh seamlessly. Gridder-HO utilizes the projection method based on a thread pool to precisely preserve geometry, and employs a novel localized RBF method with ADT for volume node interpolation to untangle the mesh, which aims to achieve a satisfactory balance between efficiency and accuracy. Validated through CFD simulations using the GPU-accelerated Python Flux Reconstruction (PyFR) solver, the practicality of Gridder-HO is demonstrated across various Reynolds numbers in typical cases such as sphere, cylinder, and SD7003 airfoil. These results confirm the high-order curvilinear meshes generated by Gridder-HO meet the high-order requirements of emerging computational methods. Moreover, Gridder-HO exemplifies its effectiveness in generating large-scale, high-order curvilinear meshes for the DLR-F6 transport aircraft configuration standard test cases. It elevates a mesh with 5 million elements to P2 in 3 min 39 sec at 68% parallel efficiency on 16 threads, and another with 14 million elements to P3 in 52 min 39 sec at 60% efficiency, illustrating its efficiency and potential in satisfying the demands of complex geometries in engineering applications.

A Comparison of ChatGPT and Multidisciplinary Team Meeting Treatment Recommendations in 10 Consecutive Cervical Cancer Patients.

Background The preparation of multidisciplinary team (MDT) meetings can be time-consuming. In additionto the clinical data being available digitally in subsystems, the preparation of more complex cases requires literature research. Several expert systems have been developed to support this process. However, the interaction with these systems has to be trained. Current development enables linguistic interaction with such artificial intelligence (AI) systems. To the best of our knowledge, these have not been tested as premedical screening tools for MDT. Methods This is a retrospective consecutive case series of 10 cervical cancer cases comparing the medical recommendations of the MDT and artificial intelligence (AI) on a low level (i.e., surgery, systemic treatment, and radiotherapy). Results The clinical cases ranged from primary diagnosis via suspected recurrence to palliative settings. The AI repeatedly stated that medical professionals need to be consulted before treatment decisions. The AI answers ranged from no agreement to overachievement by mentioning treatment options for preexisting risk factors (such as obesity). In standard cases, the AI answer matched well with the expert recommendations. In some cases, the AI answers were contrary to our treatment recommendation. Conclusion The interaction with current language AIs is temptingly easy, and the replies are very understandable. Despite the AI warning regarding medical recommendations in the majority of our cases, there was a good match with the MDT recommendations. However, in some cases, the medical evidence behind the answers was missing or in the worst case fictional. In our case series, the AI did not meet the requirements to support a clinical MDT meeting by prescreening the therapeutic options. However, it did exceed the expectations regarding the risk factors of the patients.

Quantum Big-Bounce as a phenomenology of RQM in the Mini-superspace

We investigate the emergence of a quantum Big-Bounce in the context of an isotropic Universe, filled by a self-interacting scalar field, which plays the role of a physical clock. The bouncing cosmology is the result of a scattering process, driven by the scalar field potential, which presence breaks down the frequency separation of the Wheeler-DeWitt equation, treated in strict analogy to a relativistic quantum system. Differently from previous analyses, we consider a really perturbative self-interaction potential, affecting the dynamics in a finite range of the time labeled by the scalar clock (and in particular we remove the divergent character previously allowed). The main result of the present analysis is that, when the Relativistic Quantum Mechanics formalism is properly implemented in the Mini-superspace analogy, the probability amplitude for the bounce is, both in the standard and polymerized case, characterized by a maximum in correspondence of the quasi-classical condition of a Universe minimum volume.