Dense Configuration Research Articles

Black hole from entropy maximization

One quantum characterization of a black hole motivated by (local) holography and thermodynamics is that it maximizes thermodynamic entropy for a given surface area. In the context of quantum gravity, this could be more fundamental than the classical characterization by a horizon. As a step, we explore this possibility by solving the 4D semiclassical Einstein equation with many matter fields. For highly excited spherically symmetric static configurations, we apply local typicality and estimate the entropy including self-gravity to derive its upper bound. The saturation condition uniquely determines the entropy-maximized configuration: self-gravitating quanta condensate into a radially uniform dense configuration with no horizon, where the self-gravity and a large quantum pressure induced by the curvatures are balanced and no singularity appears. The interior metric is a self-consistent and nonperturbative solution in Planck’s constant. The maximum entropy, given by the volume integral of the entropy density, agrees with the Bekenstein-Hawking formula through self-gravity, deriving the Bousso bound for thermodynamic entropy. Finally, 10 future prospects are discussed, leading to a speculative view that the configuration represents a quantum-gravitational condensate in a semiclassical manner. Published by the American Physical Society 2025

Remote Radio Frequency Sensing Based on 5G New Radio Positioning Reference Signals.

In this paper, the idea of a radar based on orthogonal frequency division multiplexing (OFDM) is applied to 5G NR Positioning Reference Signals (PRS). This study demonstrates how the estimation of the communication channel using the PRS can be applied for the identification of objects moving near the 5G NR receiver. In this context, this refers to a 5G NR base station capable of detecting a high-speed train (HST). The anatomy of a 5G NR frame as a sequence of OFDM symbols is presented, and different PRS configurations are described. It is shown that spectral analysis of time-varying channel impulse response weights, estimated with the help of PRS pilots, can be used for the detection of transmitted signal reflections from moving vehicles and the calculation of their time and frequency/Doppler shifts. Different PRS configurations with varying time and frequency reference signal densities are tested in simulations. The peak-to-noise-floor ratio (PNFR) of the calculated radar range-velocity maps (RVM) is used for quantitative comparison of PRS-based radar scenarios. Additionally, different echo signal strengths are simulated while also checking various observation window lengths (FFT lengths). This study proves the practicality of using PRS pilots in remote sensing; however, it shows that the most dense configurations do not provide notable improvements, while also demanding considerably more resources.

Development, fabrication, and validation of custom-built accelerometers to monitor wave propagation during vibratory soil compaction

Abstract Historically, accelerometers have been heavily utilized in the geotechnical community for applications such as earthquake ground motion monitoring, centrifuge testing, pile driving analysis, and continuous compaction control of soils. Industrial-grade accelerometers that are commonly used for these types of studies can be expensive for monitoring programs requiring a dense configuration of accelerometers. In the current study, a dense array of relatively inexpensive custom-built accelerometers, previously developed by the authors, were deployed along an earthen embankment and subjected to real-world vibratory soil compaction conditions. Several industrial-grade accelerometers were also installed along the embankment for comparison purposes. This study describes the fabrication, calibration, and installation process of these custom-built accelerometers and compares their performance against the industrial-grade accelerometers. Accelerations recorded by both sensors during compaction were generally consistent with one another ultimately indicating that these custom-built accelerometers could offer a cost-effective option for dense sensor arrays for future geotechnical monitoring programs.

Multi-Objective Optimization of the Layout of Tall Building Sites in Dense Urban Configurations for Improved Sustainability Outcomes

Multi-objective evolutionary algorithms have long been used by architects to find objective solutions to complex building problems involving trade-offs implicit in sustainable building design. At a larger scale, urban designers have created a variety of tools to improve sustainability in urban-and-larger scale design. However, to date, fewer studies have focused on improving sustainability outcomes at the “in between” scale of the neighborhood and urban site. Existing scholarship on optimization at this scale has tended to take a narrow view of sustainability. We seek to expand the implementation of multi-objective evolutionary algorithms to this sometimes overlooked scale while taking a broad view of sustainability which includes social, environmental, and economic design factors. In doing so, we argue this optimization method is uniquely well suited to help designers balance the sometimes competing demands of multiple axes of sustainability which are applicable to design at this larger-than-building scale. In demonstrating the application of such an algorithm to a hypothetical problem in Chicago, we find the method offers a promising way of narrowing potential design solutions. Finally, we discuss the suitability of the solutions generated, the virtues and shortcomings of the method, and offer areas for future study.

Enhancing Large Language Model Reliability: Minimizing Hallucinations with Dual Retrieval-Augmented Generation Based on the Latest Diabetes Guidelines.

Background/Objectives: Large language models (LLMs) show promise in healthcare but face challenges with hallucinations, particularly in rapidly evolving fields like diabetes management. Traditional LLM updating methods are resource-intensive, necessitating new approaches for delivering reliable, current medical information. This study aimed to develop and evaluate a novel retrieval system to enhance LLM reliability in diabetes management across different languages and guidelines. Methods: We developed a dual retrieval-augmented generation (RAG) system integrating both Korean Diabetes Association and American Diabetes Association 2023 guidelines. The system employed dense retrieval with 11 embedding models (including OpenAI, Upstage, and multilingual models) and sparse retrieval using BM25 algorithm with language-specific tokenizers. Performance was evaluated across different top-k values, leading to optimized ensemble retrievers for each guideline. Results: For dense retrievers, Upstage's Solar Embedding-1-large and OpenAI's text-embedding-3-large showed superior performance for Korean and English guidelines, respectively. Multilingual models outperformed language-specific models in both cases. For sparse retrievers, the ko_kiwi tokenizer demonstrated superior performance for Korean text, while both ko_kiwi and porter_stemmer showed comparable effectiveness for English text. The ensemble retrievers, combining optimal dense and sparse configurations, demonstrated enhanced coverage while maintaining precision. Conclusions: This study presents an effective dual RAG system that enhances LLM reliability in diabetes management across different languages. The successful implementation with both Korean and American guidelines demonstrates the system's cross-regional capability, laying a foundation for more trustworthy AI-assisted healthcare applications.

Aerosol Jet Printing, Electrodeposition, and Passivation Process for Fabrication of Flexible Rhenium Interconnects

Additive manufacturing (AM) is an adaptable and cost-effective method in both rapid prototyping and the fabrication of flexible electronic components. Aerosol jet printing (AJP), a direct write printing technique, can print features down to 10 microns in size. When combined with electroplating, AJP can pattern materials not directly printable. Here, we use this approach for developing flexible interconnects for quantum computing applications. Current quantum computers are limited by rigid coaxial cables configured in low densities where the interconnects can suffer from significant joule heating due to their resistance. A novel solution to this problem is to fabricate the interconnects from a superconducting material operating below its critical temperature, which will not exhibit joule heating and can be arranged in more dense configurations. Rhenium (Re), a superconductive material with a critical temperature of 6K, can be electrochemically deposited (ECD) onto a conductive trace. In this instantiation, we investigate the ECD of Re onto aerosol jet-printed test structures. Herein, we demonstrate the printing and sintering of gold (Au) onto polished flexible polyimide substrates followed by the electrochemical deposition of Re. The corrosion of Re was found to occur in the presence of oxygen and water. To prevent Re corrosion, it is necessary to passivate the Re surface. Here, two candidate materials were investigated: SU-8 and Norland Optical Adhesive (NOA). The Kapton-Au-Re-NOA/SU8 samples were subjected to environmental testing to evaluate the performance of the passivation layers by observing signs of visual corrosion and measuring electrical performance. Cyclic bend tests were conducted to evaluate the mechanical flexibility of the material stack. The passivation of Re deposited onto AJP gold and the flexibility of the materials without failure were successfully demonstrated. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525

Chain-based lattice printing for efficient robotically-assembled structures

Due to the nature of their implementation, nearly all low-level fabrication processes produce solidly filled structures. However, lattice structures are significantly stronger for the same amount of material, resulting in structures that are much lighter and more materially efficient. Here we propose an approach for fabricating lattice structures that echoes 3D printing techniques. In it, a modular chain of specially designed links is “extruded” onto a substrate to produce various lattices configurations depending on the chosen assembly algorithm, ranging from rigid regular lattices with nodal connectivity of 12, octet-truss, to significantly less dense configurations. Compared to conventional additive manufacturing methods, our approach allows for efficient use of nearly any material or combination of materials to construct lattices with programmed arrangements. We experimentally demonstrate that a 3x3x2 lattice structure (287 total links) is fabricated in 27 minutes via a modified robotic arm and can support approximately 1000 N in compression testing.

Achieving Controllable Thermochromic Fluorescence via Synergistic Intramolecular Charge Transfer and Molecular Packing.

Thermochromic fluorescent materials (TFMs) have attracted significant attention due to their unique fluorescent colorimetric response to temperature. However, existing TFMs still suffer from weak stimulus responsiveness, broad temperature response ranges, uncontrollable emission color changes, and low quantum yields. In this study, we address these issues by designing and synthesizing three diketone-boron complexes with distinct emission wavelengths (NWPU-(2-4)). Utilizing a molecular engineering strategy to manipulate intramolecular charge transfer transitions and molecular packing modes, our synthesized complexes exhibit efficient fluorescence emission in both solution and solid states. Moreover, their emission wavelengths are highly sensitive to environmental polarity. By incorporating these compounds into thermosensitive matrices of long-chain alkanes, we produced TFMs with varied fluorescence emission peak variation ranges. Notably, the TFM based on NWPU-4, owing to its strong charge transfer transitions and dense J-aggregate packing configuration, not only exhibits intense fluorescence emission spanning the deep red to near-infrared spectrum but also displays a remarkable 90 nm broad range of thermochromic properties. Ultimately, it was successfully applied to programmable, thermally controlled, multi-level information encryption.

Ordered and disordered stealthy hyperuniform point patterns across spatial dimensions

In previous work [] it was shown that stealthy hyperuniform systems can be regarded as hard spheres in Fourier space in the sense that the structure factor is exactly zero in a spherical region around the origin in analogy with the pair-correlation function of real-space hard spheres. While this earlier work focused on spatial dimensions d=1–4, here we extend the analysis to higher dimensions in order to make connections to high-dimensional sphere packings and the mean-field theory of glasses. We exploit this correspondence to confirm that the densest Fourier-space hard-sphere system is that of a Bravais lattice in contrast to real-space hard spheres, whose densest configuration is conjectured to be disordered. In passing, we give a concise form for the position of the first Bragg peak. We also extend the virial series previously suggested for disordered stealthy hyperuniform systems to higher dimensions in order to predict spatial decorrelation as a function of dimension. This prediction is then borne out by numerical simulations of disordered stealthy hyperuniform ground states in dimensions d=2–8, which have only recently been made possible due to a highly parallelized algorithm. Published by the American Physical Society 2024

Multi‐Scale Seismic Imaging of the Ridgecrest, CA, Region With Waveform Inversion of Regional and Dense Array Data

AbstractWe develop an inversion procedure for deriving multi‐scale velocity models with waveform inversions of earthquake and ambient noise data at multi‐frequency bands recorded by regional and dense sensor configurations. The method is applied for the area around the 2019 Ridgecrest earthquake rupture zones, utilizing data recorded by regional stations and dense 2D and 1D arrays with station spacings of ∼5 km and ∼100 m, respectively. Starting with regional Vp, Vs models and locations of Ridgecrest aftershocks, the velocity models and event locations are improved iteratively by inversions of waveforms recorded by regional stations and the 2D array, using a minimum spectral element size of ∼600 m. Waveforms from local events recorded by dense 1D arrays across the M7.1 rupture zone with frequencies of up to 10 Hz are used to resolve small‐scale features of the rupture zone and shallow crust with a local spectral element size of 80 m. The refined models provide self‐consistent descriptions of the rupture zone and the shallow crust embedded in the regional structures. The results reveal pronounced low Vs and high Vp/Vs in the M6.4 and M7.1 rupture zones coinciding with concentrations of seismicity, and also around the Garlock fault and in several local basins. We also observe clear velocity contrasts across the Garlock fault with polarity reversals along strike and with depth. The obtained multi‐scale velocity models can be used to improve derivations of earthquake source properties, simulations of dynamic ruptures and ground motions, and the understanding of fault and tectonic processes in the region.

Effect of partition walls on the vibration serviceability of cross-laminated timber floors

The current standards need more specific serviceability criteria for Cross-Laminated Timber (CLT) floors. This paper presents a comprehensive analysis of a relevant case study in Norway, which presented unexpectedly high accelerations in the CLT floors after construction. The lack of a sufficiently detailed design process resulted in the poor vibration performance of the floors, which partially compromised their functionality. The paper thoroughly investigates and discusses the experimental dynamic characterization of seven CLT floors within the considered building. The authors estimated the modal parameters and serviceability metrics based on both Eurocode 5 (EC5) and the new draft version of it. Specifically, the authors compared the analytical predictions of the fundamental frequency and the root mean square acceleration against the corresponding experimental estimations. Using a sensor-roving approach, a dense sensor configuration was adopted to describe seven floors’ mode shapes and serviceability metrics. These metrics include mean square acceleration and Vibration Dose Value. The scenarios examined in this study shed light on the significance of partition walls, a factor not considered in the practical design for serviceability verifications. The presence of partition walls can enhance the vibration comfort of timber floors by providing a stiffening effect, leading to a significant increase in the first fundamental frequency. A parametric finite element model was developed using OpenSeesPy to investigate this phenomenon further. The model, firstly validated against selected experimental results, is employed to assess the influence of partition walls on floor dynamics. The model predicts the increase in the first frequency caused by randomly generated partition walls. The paper proposes an empirical expression calibrated on the simulated data to estimate the relative increment of the floor’s fundamental frequency based on the partition walls’ layout. This formulation can be included in the analytical expression enclosed in the EC5 draft to predict the fundamental frequency of timber floors.

Human motion data expansion from arbitrary sparse sensors with shallow recurrent decoders.

Advances in deep learning and sparse sensing have emerged as powerful tools for monitoring human motion in natural environments. We develop a deep learning architecture, constructed from a shallow recurrent decoder network, that expands human motion data by mapping a limited (sparse) number of sensors to a comprehensive (dense) configuration, thereby inferring the motion of unmonitored body segments. Even with a single sensor, we reconstruct the comprehensive set of time series measurements, which are important for tracking and informing movement-related health and performance outcomes. Notably, this mapping leverages sensor time histories to inform the transformation from sparse to dense sensor configurations. We apply this mapping architecture to a variety of datasets, including controlled movement tasks, gait pattern exploration, and free-moving environments. Additionally, this mapping can be subject-specific (based on an individual's unique data for deployment at home and in the community) or group-based (where data from a large group are used to learn a general movement model and predict outcomes for unknown subjects). By expanding our datasets to unmeasured or unavailable quantities, this work can impact clinical trials, robotic/device control, and human performance by improving the accuracy and availability of digital biomarker estimates.

Direct numerical simulation of shock wave/boundary layer interaction controlled by steady microjet in a compression ramp

Shock wave/boundary layer interaction in a 24° turning angle of the compression ramp at Mach number 2.9 controlled by steady microjet is investigated using direct numerical simulation. Three different jet spacings which are termed as sparse, moderate and dense are considered, and the induced vortex system and shock structures are compared. A moderate jet spacing configuration is found to generate counter-rotating vortex pairs that transport high-momentum fluid towards the vicinity of wall and strengthen the boundary layer to resist separation, reducing the separation region. The dense jet spacing configuration creates a larger momentum deficit region, reducing the friction downstream of the corner. Analysis of pressure and pressure gradient reveals that dense jet spacing configuration reduces the intensity of separation shock. The impact of varying jet spacings on the turbulent kinetic energy transport mechanism is also investigated by decomposing the budget terms in the transport equation. Furthermore, the spectral characteristics of the separation region are studied using power spectral density and dynamic mode decomposition methods, revealing that moderate jet spacing configuration suppresses low-frequency fluctuations in the separation region.

Urban morphology as a key parameter for mitigating urban heat? – A literature review

Abstract More frequent and intense heat waves, especially in urban centers, represent a growing challenge for urban designers and building planners. In the last five years, extensive research has been undertaken on the relation between urban form, including density, and urban heat phenomena. Dense urban configurations are often considered central drivers of hot microclimates. However, less dense cities easily cause other ecological (e.g. land consumption), functional (public mobility), and socioeconomic (social diversity) problems. Consequently, the current panoply of recommended heat mitigation and sustainability measures constitutes an unclear basis for strategic planning decisions. Thus, this study examines the literature on urban morphology in relation to urban heat events. Around 800 scientific articles and studies are categorized regarding the applied methodology, the studied geographic location, the observed urban form parameters, and the examined thermal parameter. Most identified literature uses traditional field measurement, remote sensing, numerical simulation, or a combination. Air temperature and land surface temperature are the most observed thermal parameters, while the growing number of studies that focus on human outdoor thermal comfort is highly relevant for effective heat mitigation and adaptation. This study suggests that from a scientific point of view, urban morphology measures do not principally carry a paramount role in heat mitigation compared to other aspects, such as vegetation or materialization. Current planning approaches for climate-resilient cities are highly case-specific, where no generally applicable rules or effective recipes regarding urban built form are available.

Multipoint temperature measurement system composed of fiber-optic Fabry–Perot interference sensors and a wavelength-division multiplexing filter

A multipoint optical-fiber remote temperature measurement system was developed using reflection-type sensors consisting of a Fabry–Perot interference (FPI) structure with good temperature characteristics combined with a wavelength-division multiplexing (WDM) filter. The FPI sensor was fabricated using a short temperature-sensing region sandwiched between single-mode fibers. FPI optical fibers and a WDM filter functioned as the temperature sensors and wavelength-selective optical source using an amplified spontaneous emission light source, respectively. This system was operated in a dense WDM configuration using an arrayed waveguide wavelength filter.

Structural characteristics and in vitro starch digestibility of oil-modified cooked rice with varied addition manipulations

Lipid has crucial applications in improving the quality of starchy products during heat processing. Herein, the influence of lipid modification and thermal treatment on the physicochemical properties and starch digestibility of cooked rice prepared with varied addition manipulations was investigated. Rice bran oil (RO) and medium chain triglyceride oil (MO) manipulations were performed either before (BC) or after cooking (AC). GC–MS was applied to determine the fatty acid profiles. Nutritional quality was analyzed by quantifying total phenolics, atherogenic, and thrombogenic indices. All complexes exhibited higher surface firmness, a soft core, and less adhesive. FTIR spectrum demonstrated that the guest component affected some of the dense structural attributes of V-amylose. The kinetic constant was in the range between 0.47 and 0.86 min−1 wherein before mode presented a higher value. The lowest glucose release was observed in the RO_BC sample, whereas the highest complexing index was observed in the RO_AC sample, indicating that the dense molecular configuration of complexes that could resist enzymatic digestion was more critical than the quantity of complex formation. Despite the damage caused by mass and heat transfer, physical barrier, intact granule forms, and strengthened dense structure were the central contributors affecting the digestion characteristics of lipid-starch complexes.

Self-gravity and Bekenstein-Hawking entropy

We study the effect of self-gravity on entropy by directly solving the 4D semi-classical Einstein equation. In particular, we focus on whether the Bekenstein-Hawking formula holds when self-gravity is extremely strong. As an example, we consider a simple spherically symmetric static configuration consisting of many quanta and construct a self-consistent non-perturbative solution for ħ in which the entropy exactly follows the area law for many local degrees of freedom of any kind. This can be a candidate for black holes in quantum theory. It represents a compact dense configuration with near-Planckian curvatures, and the interior typically behaves like a local thermal state due to particle creation inside. Here, the information content is stored in the interior bulk, and the self-gravity plays an essential role in changing the entropy from the volume law to the area law. We finally discuss implications to black holes in quantum gravity and a speculative view of entropy as a gravitational charge.

Smart urban windcatcher: Conception of an AI-empowered wind-channeling system for real-time enhancement of urban wind environment

The dense configuration and rapid proliferation of high-rise buildings in central Hong Kong have led to increasing stagnation of pedestrian-level airflows, lowering the wind speed and exacerbating issues in wind and thermal comfort. Addressing these problems can be difficult without significant building renovations and urban re-planning. This paper introduces a novel framework for the real-time enhancement of the local urban wind environment using motion-controlled billboards, or smart urban windcatchers, managed by a deep reinforcement learning (DRL) agent. The DRL agent determines the windcatchers' optimal positions based on street-level sensor data, independent of meteorological data. The framework's effectiveness was assessed using a simplified city grid model, where two windcatchers aimed to optimize the pedestrian-level wind environment on a specific street. Simulation results indicated that the windcatchers could effectively alter the flow direction in the streets, promoting or diverting air passages per demand. The DRL agent also gave accurate instructions to the windcatchers under various weather conditions, achieving near-optimal wind environment scores. This paper introduces the conception and confirms the feasibility of the windcatcher system, laying the groundwork for future research—as it is much needed and welcomed—to enhance the system and overcome the acknowledged challenges in large-scale, real-world implementation.

Distributed Acoustic Sensing for Crowd Motion and Firecracker Explosions in the Fireworks Show

Abstract Urban seismology has recently emerged as a vibrant scientific field, driven by the growing interest in seismic signals generated by major public events, sports gatherings, and transportation services. However, deploying dense traditional seismometers in economically active, densely populated urban areas with heavy traffic poses significant challenges. In this study, we conducted a field experiment utilizing distributed acoustic sensing (DAS) technology during a fireworks display in Guangzhou on 5 February 2023. About 572 m of optical fiber was turned into 286 seismic sensors and deployed on LingShan Island to monitor various vibration signals generated during the fireworks show. Our analysis revealed substantial correlations between crowd motions during different phases of the event and ambient noise features recorded by DAS. Moreover, the cross-correlation functions of the ambient noise with its dispersion characteristics pointed to near-field pedestrian activity as the primary noise source. Real-time heat maps of human crowd motions were reconstructed from DAS recording, offering significant insights into the variations of activity intensity across different locations. Discerning fireworks events on the DAS array is more effective than on a scattered seismometer array, because it is easier to ensure that the same event is picked for all the sites in the DAS dense linear configuration. The DAS data inspection allowed us to pick up a total of 549 firecracker explosions in comparison to the seismometer data that only allowed us to detect 116 firecracker events. The heights of fireworks were located by the grid-search method and predominantly distributed at 75–300 m, closely aligning with actual fireworks explosion locations. Our findings underscore that the DAS technology can monitor crowd motion and detect vibration signals in the air, bridging the gap between fundamental earth science research and human social activities.

Reexpansion of charged nanoparticle assemblies in concentrated electrolytes

Electrostatic forces in solutions are highly relevant to a variety of fields, ranging from electrochemical energy storage to biology. However, their manifestation in concentrated electrolytes is not fully understood, as exemplified by counterintuitive observations of colloidal stability and long-ranged repulsions in molten salts. Highly charged biomolecules, such as DNA, respond sensitively to ions in dilute solutions. Here, we use non-base-pairing DNA-coated nanoparticles (DNA-NP) to analyze electrostatic interactions in concentrated salt solutions. Despite their negative charge, these conjugates form colloidal crystals in solutions of sufficient divalent cation concentration. We utilize small-angle X-ray scattering (SAXS) to study such DNA-NP assemblies across the full accessible concentration ranges of aqueous CaCl2, MgCl2, and SrCl2 solutions. SAXS shows that the crystallinity and phases of the assembled structures vary with cation type. For all tested salts, the aggregates contract with added ions at low salinities and then begin expanding above a cation-dependent threshold salt concentration. Wide-angle X-ray scattering (WAXS) reveals enhanced positional correlations between ions in the solution at high salt concentrations. Complementary molecular dynamics simulations show that these ion-ion interactions reduce the favorability of dense ion configurations within the DNA brushes below that of the bulk solution. Measurements in solutions with lowered permittivity demonstrate a simultaneous increase in ion coupling and decrease in the concentration at which aggregate expansion begins, thus confirming the connection between these phenomena. Our work demonstrates that interactions between charged objects continue to evolve considerably into the high-concentration regime, where classical theories project electrostatics to be of negligible consequence.