Dynamic Source Research Articles

Exercises to improve directional sound recognition by visually impaired users heading to the workplace

Moving is an integral part of everyday life and applies to accessing the workplace, attending a health centre or meeting friends. Determination of the source of sound may be important when a visually impaired person is moving around. This allows to navigate, but also provides important information about potential danger. Sound exercises have been prepared to support the ability to recognize the direction of sound and to learn about the problems associated with it. The research version of the app was prepared covering 12 situations related to three static and nine dynamic sources of sounds. All 10 participants in the exercises had a significant degree of visual impairment. An extended dataset obtained from three subjects without disabilities was also included. As a result, six exercises qualified for the final set of sound exercises, which allow to gain benefits from their implementation.

A Dynamic Volumetric Heat Source Model for Laser Additive Manufacturing

Melt pool scale models of laser powder bed fusion (LPBF) offer insights into the process-structure-property relationships in additive manufacturing (AM). These models often neglect physical phenomena such as vapor cavity formation and fluid mechanics to reduce computational demands. Instead, volumetric heat source models are used to represent the effects that these phenomena have on the predicted melt pool dimensions. Generally, the dimensions and effective absorption of the volumetric heat source are calibrated to reproduce melt pool dimensions observed in metallographic cross sections taken from single-track experiments on bare plate. However, the transient nature of LPBF often deviates the melt pool dimensions from the assumed steady-state conditions of single-track experiments, motivating the need for a volumetric heat source model that more generally considers the dynamic relationship between melt pool shape and laser-material interactions. Here, we introduce a two-parameter volumetric heat source model that integrates several existing models into a generalized mathematical expression, providing independent control over the radial heat distribution via the parameter k and the volumetric shape of the heat source via the parameter m. This parameterization enables the calibration of melt pool shape predictions through simultaneous adjustment of these parameters, while keeping the radial heat source dimensions consistent with the experimental spot size (D4σ) and constraining the heat source depth and absorption to physically derived expressions for cavities. Consequently, the proposed volumetric heat source model adapts to changes in the local melt pool conditions due to scanning strategy and part geometry by dynamically adjusting the heat source depth and absorption. We demonstrate the capabilities of the proposed model through comparisons with a collection of experiments from the Additive Manufacturing Benchmark (AMBench).

Modeling Method of Meshing Stiffness of High Speed Spur Gears

As one of the most important dynamic excitation sources, the gear time-varying mesh stiffness is the key parameter of gear system dynamic model. So how to calculate the gear mesh stiffness accurately is of great importance. Based on Euler beam theory, this paper proposes a primitive calculation algorithm (PCA) to calculate the time-varying mesh stiffness of spur gears. A simplified gear model is developed based on nonlinear strain-displacement relationships, and a finite element program is used to simulate the gear's meshing stiffness. The rationality of this method was verified through finite element analysis. The results indicate that mesh stiffness plays a crucial role in controlling mesh deformation. In view of this, this study lays a theoretical foundation for further analysis of the vibration and noise of gears.

Three‐Dimensional Numerical Modeling of Coseismic Atmospheric Dynamics and Ionospheric Responses in Slant Total Electron Content Observations

AbstractDespite routine detection of coseismic acoustic‐gravity waves (AGWs) in Global Navigation Satellite System (GNSS) total electron content (TEC) observations, models of the earthquake‐atmosphere‐ionosphere dynamics, essential for validating data‐driven studies, remain limited. We present the results of three‐dimensional numerical simulations encompassing the entire coupling from Earth's interior to the ionosphere during the 7.8 2016 Kaikoura earthquake. Incorporating the impact of data/model uncertainties in estimating the ionospheric state, the results show a good agreement between observed and simulated slant TEC (sTEC) signals, assessed through a set of metrics. The signals exhibit intricate waveforms, resulting from the integrated nature of TEC and phase cancellation effects, emphasizing the significance of direct signal comparisons along realistic line‐of‐sight paths. By comparing simulation results initialized with kinematic and dynamic source models, the study demonstrates the quantifiable sensitivity of sTEC to AGW source specifications, pointing to their utility in the analysis of coupled dynamics.

Solidarity and broadening the practices of action research

We live in a world of runaway global social inequality and immanent planetary ecological collapse and action research is more necessary than ever. Solidarity across countries, regions, classes, and ecosystems is the only way out of these linked crises caused by neoliberal capitalism. Action research is a vibrant and heterogeneous set of democratic practices capable of addressing many of these dilemmas. Action researchers have for generations largely been content to develop their own approaches independently and the attempts to create better integrated global action research networks have yet to show the needed success. This essay argues that the lack of collaboration and solidarity across the whole spectrum of action research is an unaffordable luxury. Living up to our own ethical and political commitments, we need to find ways to treat the diversity among our own practices and political visions as sources of strength and dynamism. Beyond this, together we need to make a concerted effort to link with other groups and networks promoting fairness, democracy, sustainability and solidarity because the future without these collaborations is unsustainable.

Enhancing Smart City Connectivity: A Multi-Metric CNN-LSTM Beamforming Based Approach to Optimize Dynamic Source Routing in 6G Networks for MANETs and VANETs

Enhancing Smart City Connectivity: A Multi-Metric CNN-LSTM Beamforming Based Approach to Optimize Dynamic Source Routing in 6G Networks for MANETs and VANETs

Enhancing heart disease classification with M2MASC and CNN-BiLSTM integration for improved accuracy

Heart disease is a leading cause of death globally; therefore, accurate detection and classification are prominent, and several DL and ML methods have been developed over the last decade. However, the classical approaches may be prone to overfitting and under fitting issues, and the model performance may lag due to the unavailability of annotated datasets. To overcome these issues, the research proposed a model for heart disease detection and classification by integrating blockchain technology with a Modified mixed attention-enabled search optimizer-based CNN-Bidirectional Long Short-Term Memory (M2MASC enabled CNN-BiLSTM) model. The novel model incorporates a pre-trained VGG16 model to enhance feature extraction and improve the overall predictive accuracy. Leveraging the continuous monitoring capabilities of IoT devices, patient data is collected in real-time, providing a dynamic source to the CNN-BiLSTM model. Blockchain integration ensures stored health data’s security, transparency, and immutability, addresses privacy concerns, and promotes trust in the predictive system. The classifier parameters are tuned using the modified mixed attention and search optimization. The M2MASC-enabled CNN-BiLSTM model performs better than traditional methods of accuracy 98.25%, precision 99.57%, and recall 97.53% for TP 80 with the MIT-BIH dataset.

Atmospheric Precursors of Skillful SST Prediction in the Northeast Pacific

Abstract Forecasts of sea surface temperature anomalies (SSTAs) provide essential information to stakeholders of marine resources in coastal ecosystems, such as the California Current Large Marine Ecosystem (CCLME), at management-relevant monthly-to-annual time scales. Diagnosing dynamical sources of predictability and the mechanisms differentiating skill among forecasts is required for verification and improvement in operational forecasting systems. Using retrospective forecasts (1982–2020) from a four-member subset of the North American Multi-Model Ensemble (NMME), we evaluate the conditional skill of SSTA forecasts in the CCLME at monthly resolution for lead times up to 10.5 months. Forecasts from ensemble members with relatively small SSTA errors at shorter lead times retain higher skill at longer lead times, with the most substantial and long-lasting increases for forecasts initialized in the fall and early spring. The “best” low-error SSTA forecasts are characterized by increased skill in the prediction of North Pacific atmospheric circulation [sea level pressure (SLP) and 200-hPa geopotential height] the month prior to the evaluation of SSTA errors in the CCLME and exhibit more realistic progressions of anomalous SLP. The Pacific meridional mode (PMM) emerges as a diagnostic of skillful North Pacific atmosphere–ocean coupling, as forecasts that correctly simulate the PMM and its associated SLP variability increase the SSTA prediction skill in the CCLME in the fall through spring. Predictable coupled ocean–atmosphere modes provide a target for enhancing predictability with early detection of the onset of a deterministic progression emerging from stochastic atmospheric variability. Significance Statement Global forecast systems provide near-term climate predictions that inform the management of marine resources, such as those of the California Current Large Marine Ecosystem. In this study, we probe the processes which lead forecasts to succeed or fail at predicting sea surface temperatures in the California Current at seasonal time scales among retrospective forecasts from the North American Multimodel Ensemble. We demonstrate that forecasts which best simulate sea surface temperatures at the earliest lead times sustain advantages in forecast skill and find that correctly simulating extratropical atmospheric circulation increases the predictive skill of sea surface temperatures in the northeast Pacific in the following lead times. Our results offer North Pacific atmospheric circulation as a target for forecast model improvement that would additionally enhance ocean forecasts.

Computational Models of Dynamic Load Sources for Modeling of Construction Structures Operation Used in Monitoring of Technical Condition of Buildings and Structures

This research aims to develop principles for assessing the impact of mega-cyclic vibrodynamic loads on the reliability of construction structures. The relevance of the reasons for the development and improvement of algorithms for numerical modeling of multicycle dynamic loads on building structures is due to the steadily increasing intensity of such loads on buildings and structures in megacities, as well as the acute practical problem of significant differences in the dynamic characteristics of buildings and structures obtained as a result of mathematical modeling and determined by experimental methods. The article presents research materials on computational equivalent models of dynamic load sources for numerical modeling of the behavior of construction structures under their influence, using the method of vibroacoustic analogies. The article examines models of sources of dynamic impact on construction sites. Algorithms and final formulas for computational modeling of the simplest sources of dynamic load are developed using the method of vibroacoustic analogies. The dynamic properties of the simplest dynamic load sources were analyzed. A significant difference between the computational models of real and ideal dynamic load sources. The article presents research and development results intended for calculating the distribution of dynamic loads on elements of construction structures in industrial and civil engineering projects located in areas with high levels of transport vibrodynamic impacts. An important property of the proposed computational equivalent models of sources of dynamic impact on building structures is the possibility of computational verification of critical elements, points, or nodes of load-bearing structures of buildings and structures under dynamic overloads. The position of these critical elements, points, and nodes of load-bearing structures under dynamic loads can differ significantly from their position determined using static and quasistatic computational modeling methods.

Extended matrix modeling of integrated energy systems considering network dynamic characteristics and source–load uncertainty

A refined and efficient modeling approach is indispensable for enhancing the timeliness of scheduling strategies for the integrated energy system (IES). Non-flowing variables such as pressure and temperature introduced by energy devices, however, worsen the complexity while improving the completeness for models. Nonlinear and uncertain variables associated with network dynamic characteristics and source–load uncertainty in the systems seriously postpone the modeling processes. An extended matrix modeling approach is proposed in this paper to tackle such issues. New nodes, branches, definition rules and topological matrices are first presented to create an extended matrix model that is compatible with both flowing and non-flowing variables. To boost the modeling efficiency, adaptive piecewise linearization (APL) with extended matrix form and modified Taylor expansion are applied to approximate various nonlinear characteristics. The convex approximation based on Kullback–Leibler (KL) divergence and the strong duality theory characterized by Wasserstein distance are adopted to deal with uncertain variables, which adapt to combine with the above matrix model. A linearized matrix modeling framework applicable to highly automated by computers is thus established. The distributionally robust optimization (DRO) scheduling strategy is verified in a standard test system with the proposed modeling. The effect of dynamic characteristics and uncertain factors on the strategy is discussed. The results show that the extended matrix model simulates the response for real physical systems more effectively, which exhibits the better performances in modeling, objectives and scheduling strategies.

Standardized Kalman filtering for dynamical source localization of concurrent subcortical and cortical brain activity

ObjectiveWe introduce standardized Kalman filtering (SKF) as a new spatiotemporal method for tracking brain activity. Via the Kalman filtering scheme, the computational workload is low, and by spatiotemporal standardization, we reduce the depth bias of non-standardized Kalman filtering (KF). MethodsWe describe the standardized KF methodology for spatiotemporal tracking from the Bayesian perspective. We construct a realistic simulation setup that resembles activity due to somatosensory evoked potential (SEP) to validate the proposed methodology before we run our tests using real SEP data. ResultsIn the experiments, SKF was compared with standardized low-resolution brain electromagnetic tomography (sLORETA) and the non-standardized KF. SKF localized the cortical and subcortical SEP originators appropriately and tracked P20/N20 originators for investigated signal-to-noise ratios (25, 15, and 5 dB). sLORETA distinguished those for 25 and 15 dB suppressing the subcortical originators. KF tracked only the evolution of cortical activity but mislocalized it. ConclusionsThe numerical results suggest that SKF inherits the estimation accuracy of sLORETA and traceability of KF while producing focal estimates for SEP originators. SignificanceSKF could help study time-evolving brain activities and localize landmarks with a deep contributor or when there is no prior knowledge of evolution.

Landscape of exosomes to modified exosomes: a state of the art in cancer therapy.

Exosomes are a subpopulation of extracellular vesicles (EVs) that naturally originate from endosomes. They play a significant role in cellular communication. Tumor-secreted exosomes play a crucial role in cancer development and significantly contribute to tumorigenesis, angiogenesis, and metastasis by intracellular communication. Tumor-derived exosomes (TEXs) are a promising biomarker source of cancer detection in the early stages. On the other hand, they offer revolutionary cutting-edge approaches to cancer therapeutics. Exosomes offer a cell-free approach to cancer therapeutics, which overcomes immune cell and stem cell therapeutics-based limitations (complication, toxicity, and cost of treatment). There are multiple sources of therapeutic exosomes present (stem cells, immune cells, plant cells, and synthetic and modified exosomes). This article explores the dynamic source of exosomes (plants, mesenchymal stem cells, and immune cells) and their modification (chimeric, hybrid exosomes, exosome-based CRISPR, and drug delivery) based on cancer therapeutic development. This review also highlights exosomes based clinical trials and the challenges and future orientation of exosome research. We hope that this article will inspire researchers to further explore exosome-based cancer therapeutic platforms for precision oncology.

A New Numerically Improved Transient Technique for Measuring Thermal Properties of Anisotropic Materials

A new transient technique of the thermal conductivity and diffusivity measurement for anisotropic materials is presented and validated. It is based on measuring the through-plane properties using the extended dynamic plane source (EDPS) method and in-plane conductivity employing the transient plane source (TPS) and modified dynamic plane source (MDPS) methods. The key advantage of this technique is that only one pair of specimens is required for measurements. While the EDPS method is implemented on real measurements, the TPS and MDPS are applied to the finite elements method (FEM) simulation of the experiment. The accuracy of the results is enhanced by the application of the FEM and is better than 1% for materials with through-plane conductivity of less than 2 W m−1 K−1 and a specimen thickness of 9 mm.

Classical Dynamical r-matrices for the Chern–Simons Formulation of Generalized 3d Gravity

AbstractClassical dynamical r-matrices arise naturally in the combinatorial description of the phase space of Chern–Simons theories, either through the inclusion of dynamical sources or through a gauge fixing procedure involving two punctures. Here we consider classical dynamical r-matrices for the family of Lie algebras which arise in the Chern–Simons formulation of 3d gravity, for any value of the cosmological constant. We derive differential equations for classical dynamical r-matrices in this case and show that they can be viewed as generalized complexifications, in a sense which we define, of the equations governing dynamical r-matrices for $$\mathfrak {su}(2)$$ su ( 2 ) and $$\mathfrak {sl}(2,{\mathbb {R}})$$ sl ( 2 , R ) . We obtain explicit families of solutions and relate them, via Weierstrass factorization, to solutions found by Feher, Gabor, Marshall, Palla and Pusztai in the context of chiral WZWN models.

An Analysis of Routing Protocol in Mobile Adhoc Networks and its Applications

Each hub in a mobile ad-hoc network (MANET) sends parcels bound for different hubs in the network by means of remote (radio transmission) transmission on a wilful premise, making it a self-beginning, powerful network made up of mobile hubs. Multi-bounce transferring is the essential inspiration for the advancement of ad hoc networking. Remote Ad hoc networks, otherwise called foundation less networks, can be set up rapidly and effectively using radio waves as the network's transmission channel. There is no principal server or referee in an ad hoc network. Every hub in a MANET is fit for playing out its own networking errands, for example, routing and bundle sending, in a decentralized and independent style. Uses of routing protocols like Ad hoc On-request Distance Routing Protocol (AODV), Dynamic Source Routing (DSR), Transiently Requested Routing Calculation (TORA), and Enhanced Connection State Routing (OLSR) are fascinating in light of the fact that routing is the focal issue in MANETs. These routing protocols are simulated using OPNET, and their effectiveness is investigated using various metrics. With the use of metrics, the most efficient channel for data transfer can be determined. The results demonstrate the viability of AODV and TORA for topology-changing in large-scale networks using a variety of criteria.

Provenance Analysis of the Northern Offshore Mud Area of the Shandong Peninsula, China, Spanning the Last 2000 Years

The mud area in the northern offshore of the Shandong Peninsula constitutes a dynamic source–sink system in China’s continental shelf and is a hotspot for research. However, the provenance of the sediments remains controversial, and the depositional environment is not yet fully understood. This paper performed accelerator mass spectrometry 14C dating, grain-size analysis, clay mineralogic analysis, and geochemical analysis of the ZZ04 sediment core. The results showed that this core primarily comprises silt and clay, reflecting weak sedimentary hydrodynamic conditions and stable deposition. The clay mineral assemblage—illite, smectite, chlorite, and kaolinite—indicates strong physical weathering. The provenance of the mud area was mainly from the Yellow River, Shandong Peninsula rivers, and Yangtze River, highlighting its multi-source characteristics. The smectite/(illite + chlorite) ratio in the ZZ04 core serves as a mineralogical indicator of the East Asian summer monsoon (EASM). Eight significant East Asian winter monsoon (EAWM) intensifications were identified, correlating with global cooling events similar to those at 1.89, 1.4, 1.03, and 0.62 thousand years ago. During the EAWM period, the coastal current and the Yellow Sea warm current play crucial roles in the transportation of matter and heat flux in the mud area. In contrast, during the EASM period, the sediments are predominantly sourced from the Shandong Peninsula rivers, contributing terrigenous materials shaped by chemical weathering.

Comparison and application of the far-field identification algorithms for multiple sound sources based on microphone array

Based on the conventional beamforming (CBF), some algorithms for far-field sound source identification have been proposed in the past few decades. Typically, the functional beamforming (FBF) and the deconvolution methods, such as CLEAN, CLEAN with source coherence (CLEAN-SC), CLEAN-SC with compressed grids (CLEAN-SC-CG), CLEAN with cross spectral matrix function (CLEAN-CSM), High-resolution CLEAN-SC (HR-CLEAN-SC), are frequently mentioned and their advantages are widely discussed in the previous literatures. To assess their efficacy and suitability in engineering applications, with a focus on spatial resolution, computational efficiency, and dynamic range, a comparative study by locating two types of sound sources is carried out. The first scenario represents the case where the distance between two sound sources is smaller than the Rayleigh limit, while the second scenario represents the situation involving multiple sound sources, such as four or more complex sound sources. The analysis demonstrates that CBF, CLEAN, and CLEAN-SC cannot surpass the Rayleigh limit. However, FBF, CLEAN-SC-CG, CLEAN-CSM, and HR-CLEAN-SC have the potential to overcome it. In FBF, the grid mismatch results in a compromise between its dynamic range and source strength estimation. Meanwhile, HR-CLEAN-SC requires prior knowledge of the number of sound sources, which is challenging in applications. Because of superiority in the fundamental acoustic image and searching strategy, CLEAN-CSM and CLEAN-SC-CG exhibits superior features compared to the others. By compressing the number of grids, the CLEAN-SC-CG can improve the computational efficiency up to at least 46%. By constructing the cross spectral matrix function related to the real source, CLEAN-CSM uses the power function to simultaneously enhance the spatial resolution, dynamic range and source strength estimation. The conclusions are further validated through sound-source identification experiments involving two loudspeakers and an engine. The findings presented in this paper serve to guide the selection of suitable approaches for multi-sound source identification in engineering applications.

Sequence types of enteroaggregative Escherichia coli strains recovered from human, animal, and environmental sources: India

In the current study, we report whole genome sequencing (WGS) data on EAEC strains from India to identify lineages and different sequence types (STs) in our geographical regions across North India. We performed WGS comparative genomics characterization to examine the diversity of 122 EAEC strains collected from a large geographic area from clinical (Human sources) and non-clinical sources (animal and environmental sources). M-PCR for 21 virulence genes was performed. A triplex PCR detected phylogenetic groups A, B1, B2, and D was done. All strains were genome-sequenced, and bioinformatics analysis was performed. EAEC isolates belonged to 29 sequence types, further clustered into 11 clonal complexes, among which CC38 was the largest, containing 38 isolates mainly belonging to two ST types (ST38 and ST315). CC10 was the most diverse group, comprising 8 STs (ST43, ST2706, ST1286, ST 10, ST167, ST34, ST227, and ST4305). The most frequently detected virulence gene among the 96 clinical EAEC isolates was astA (87.5%), followed by ORF3 (62.5%), and aap (54.1 %). ST131, known for multidrug resistance and causing various diseases, was detected in acute diarrhea cases and animal sources, underscoring its clinical significance. These findings indicate the high diversity of EAEC and different sources of unique ST types of EAEC. The study reinforces the One Health approach, highlighting the interconnection between human health, animal reservoirs, and environmental sources in EAEC transmission dynamics. The identification of EAEC strains in animals suggests the zoonotic potential of these pathogens, necessitating comprehensive surveillance and control measures. The study emphasizes the need for continued surveillance and a One Health approach to address the complex transmission dynamics of EAEC.

Comparing the Upper Mesospheric Temperature Trend and the Response to Solar Activity Derived From the Daily Mean and Nocturnal Na Lidar Observations

AbstractOver the past decades, various experimental and numerical model studies have indicated cooling trend in the mesosphere and lower thermosphere (MLT), while the magnitude of the trend varies noticeably. Previous studies using the lidar observations derived the temperature trends and solar responses solely from the traditional nocturnal measurements. While these archived results are more or less in agreement with modeling studies, one of the main uncertainties in these studies is the potential biases induced by the trends of the diurnal tide forced in the lower atmosphere, and that of the in situ exothermal reactions involving the photolysis. In the MLT, the diurnal tide has significant seasonal variations, considerable amplitude and is one of the dominant dynamic sources. However, its potential effects in the trend studies have rarely been discussed. In this paper, we present and compare the long‐term temperature trends in the upper mesosphere utilizing the daily mean and nightly mean temperature profiles measured by a Sodium (Na) Doppler lidar at midlatitude. The system was operating routinely in full diurnal cycles between 2002 and 2017, obtaining a unique multi‐year temperature data set. A customized multi‐linear regression (MLR) model is applied to determine the linear trends and the other fitting parameters, such as ENSO and solar F10.7 responses in the upper mesosphere. This study indicates the daily mean cooling trend between 84 and 98 km is larger than that of nightly mean trend by ∼−1 K/decade, while differences in the solar response are within the fitting uncertainties.

On the accuracy of idealized sources in CFD simulations of pollutant dispersion in an urban street canyon

Idealized pollutant sources are widely used by the scientific community to replicate traffic emissions in wind tunnel tests and CFD simulations. However, it is unclear to what extent such idealized sources can adequately reproduce the emission and dispersion by cars in idle (static) or moving situations in streets. This study investigates the impact of a static idealized point source (S-IPS) versus an idling or static (S-) and a moving or dynamic (D-) realistic car source (RCS) on the pollutant dispersion in a street canyon. First, 3D steady RANS and LES simulations are performed with a S-IPS and validated by means of wind-tunnel tests. Next, LES simulations are performed to analyze the impact of S-IPS versus S-RCS. Finally, three D-RCS with different car speeds are simulated and compared with S-RCS. The results show that using a S-RCS increases the plane-averaged concentration by 11%–140 % at z/H = 0.03 and by 30%–50 % at y/H = 0, with respect to S-IPS. The comparison of S-RCS and D-RCS shows that car movement can also have a large impact on pollutant dispersion along the canyon.