Dynamic Range Research Articles

Ultrasensitive detection of miRNA 21 achieved through DNA structure-mediated self-assembly of Au NCs array functionalized surface-enhanced Raman scattering biosensor

The involvement of microRNA (miRNA) in the transcriptional and regulatory processes of gene expression in organisms, along with its aberrant expression patterns in various malignant diseases such as tumors, underscores its significance. Surface-enhanced Raman scattering (SERS) biosensing technology offers distinct advantages for miRNA detection, including simplified procedures, non-destructive analysis, fingerprint spectroscopy capabilities, and rapid detection times. This study presents the development of a novel SERS-based biosensor utilizing miRNA-21 stimulated-responsive DNA-functionalized nanomaterials. The DNA structure within the the catalyzed hairpin amplification (CHA) was utilized to modify Fe3O4 and Au nanocubes (Au NCs), and subsequently, miRNA21 served as a key to trigger the CHA reaction between these two materials. Notably, during this process, the signal probe Cy3 underwent directed migration and accumulation from Fe3O4 to Au NCs, resulting in the unidirectional enrichment of beacon probe from Fe3O4 to Au NCs, which was facilitated by the progression of the CHA cycle. This facilitated robust generation of SERS signals for precise quantification of miRNA-21. The sensor utilized Au NCs enriched with Cy3 to form highly stable and well-ordered two-dimensional arrays at the water-cyclohexane interface, demonstrating exceptional stability and reproducibility. It achieved an impressive detection limit of 0.81 fM across a dynamic range from 1 to 1 × 10⁶ fM. This work advances practical methods for amplification analysis in the sensing field, demonstrating significant potential for clinical medicine and early cancer diagnosis.

SiPM and readout electronics for the JUNO-TAO Central Detector

The Taishan Antineutrino Observatory (TAO) is a satellite experiment of the Jiangmen Underground Neutrino Observatory (JUNO). TAO consists of a spherical ton-level Gadolinium-doped Liquid Scintillator detector and its main purpose is the precise measurement of the reactor antineutrino spectrum by detection of light produced in v̅e + p⟶ e + + n reaction, as a reference for JUNO. About 4,500 photoelectrons per MeV could be detected by instrumenting the sphere surface (∼10 m2) with state-of-the-art Silicon PhotoMultipliers (SiPMs), resulting in a sub-percent energy resolution. In this work we present the implemented architecture of the readout electronics based on low-noise, high-speed Front-End Boards (FEBs) connected to a 50×50 mm2 SiPM Hamamatsu tile, composed by 32 SiPM elements of 12×6 mm2 each, divided into two independent output channels. The overall 4,024 FEBs will be supplied through eight custom flanges that have to bring in about 1.5 kW. On the same flanges the 8,048 output signal cables are distributed and routed to the Front-End Controllers (FECs), based on Virtex Ultrascale FPGAs, able to manage up to eight 16-channel ADCs, for a total of 128 channels on a single FEC, with a maximum sampling rate of 250 MHz with 12-bit resolution. A dedicated trigger and data-acquisition system will filter and record occurring events, rejecting dark count events. We report the results of the characterization for the pre-production FEBs batch, following the main figures of merit defined for the experiment, showing single photoelectron resolution better than 13% and dynamic range up to 250 photoelectrons.

Multi-exposure fused light field image quality assessment for dynamic scenes: Benchmark dataset and objective metric

The luminance dynamic range in natural scenes is exceedingly wide. However, capturing the wide dynamic range information of natural scenes through a single exposure is challenging for commercial light field cameras. One solution to expand the luminance dynamic range of captured light field images is to employ multi-exposure imaging techniques. Nevertheless, this approach may introduce various distortions during the image fusion procedure, especially for dynamic scenes. To evaluate the visual quality of multi-exposure fused light field images (MEFLFIs) and compare the performance of different multi-exposure light field fusion methods, we initially conduct a subjective quality assessment on MEFLFIs for dynamic scenes and establish the first MEFLFI benchmark dataset, which comprises 480 fused light field images generated by eleven state-of-the-art multi-exposure fusion algorithms and two tone-mapping algorithms, along with their corresponding subjective scores. Subsequently, a novel specially designed objective quality assessment metric for MEFLFIs is developed, which incorporates both local–global joint features and angular quality-aware features. The key contribution of this work lies in establishing a pioneering benchmark dataset for MEFLFIs along with a novel tailored objective quality metric. Experimental results conducted over our established MEFLFI database demonstrate that the proposed metric achieves superior performance, with Pearson linear correlation coefficient (PLCC) and Spearman rank correlation coefficient (SROCC) values of 0.8895 and 0.8658 respectively, representing a significant improvement of approximately 5.7 % and 4.9 % compared to the second-best specifically-designed LFI quality metric available. Furthermore, ablation experiments have confirmed that the integration of local–global joint features and angular features significantly enhances the performance of our objective metric, resulting in a better alignment with human visual perception

Implementation and Linearization of a Coupled Panel and Vortex Particle Method in State-Space Form

This paper describes the implementation and linearization of a coupled panel and vortex particle method in a state-variable form. More specifically, the coupled panel and vortex particle dynamics are formulated as a nonlinear system of ordinary differential equations in first-order form to be self-contained and inherently linearizable. Linearization of this coupled panel and vortex particle method is demonstrated via finite differencing and a novel analytical linearization technique to yield a linear time-invariant representation. The code is implemented in MATLAB® and validated against an open-source aerodynamic solver for a fixed wing in both stationary and unsteady conditions. The linearized models are verified against the nonlinear dynamics both in the time and frequency domains. Linearized models accurately represent the wake dynamics about the equilibrium condition for moderate amplitude inputs and for input frequencies covering the typical frequency range of flight dynamics and flight controls, i.e., 0.3–30 rad/s. Analytical linearization is shown to abate the cost of linearization over perturbation methods by O(n2), where n is the total number of states of the system. Linearized models of the coupled panel and vortex particle dynamics have applications in the flight dynamics of both fixed- and rotary-wing vehicles, where these dynamics can be used to augment the rigid-body dynamics. The coupled rigid-body and wake dynamics can be leveraged to assess the stability, response characteristics, and handling qualities of vehicles experiencing aerodynamic interactions between rotors, wings, and/or obstacles.

Determination of insoluble (INSOL) calcium content in Cheddar, Feta, Juustoleipa, and Mozzarella cheeses using acid-base buffering curves

The amount of colloidal calcium phosphate (CCP) complex associated with caseins (INSOL Ca) determines the body, texture, flavor and breakdown of cheese constituents during aging. The continuous pH decline during cheese making because of lactic acid fermentation results in solubilization of insoluble (INSOL) calcium. Measuring INSOL Ca in such a dynamic and wide range pH system (6.6 to 5.3) is challenging. The purpose of this study was to test utility of acid-base auto-titration method in differentiating INSOL Ca content in cheeses with a wide range of pH (i.e., Juustoleipa 6.6, Mozzarella 5.6, Cheddar 5.3, Feta 4.8) and also to understand the relationship between pH, protein content, and INSOL Ca. A positive relationship was obtained for pH (R2 = 0.62) and protein content (R2 = 0.85) with INSOL Ca, suggesting concomitant release of CCP content at lower pH values and association of higher amount of CCP with higher protein content. Despite having a pH slightly closer to Mozzarella (pH 5.56), Cheddar cheese (pH 5.25) had more INSOL Ca (0.67%) owing to the highest amount of protein (26%) and low moisture content (33%). Feta had the lowest amount of INSOL Ca (0.15%) owing to a low pH (4.79), higher moisture content (55%), and low protein content (14%). Juustoleipa had the highest percentage of INSOL Ca out of total calcium (88%) due to higher pH (6.62) and more intact casein. It was evident that the acid-base titration method was able to differentiate INSOL Ca between different types of cheeses with varying pH and protein content. Findings of this work will help tracking the proportion of INSOL Ca at various stages of cheese making and understanding kinetics of INSOL Ca solubilization and its role in causing pH variation in the early stage of cheese ripening.

Ultra-sensitive detection of femtomolar lead ions using DNAzyme-mediated biosensing on tilted fiber Bragg grating plasmonic sensor

Ultra-trace lead ion detection has significant implications in various domains, notably in point-of-care testing, environmental monitoring, and cancer-targeted therapies and diagnostics. The demand for rapid and precise lead-ion detection in clinical settings necessitates innovative approaches. In this study, a lead-ion biosensor was designed using DNAzyme-based tilted fiber Bragg grating surface plasmon resonance (TFBG-SPR). The lead ions specifically cleave toward DNAzyme’s ribonucleotide adenosine (rA)-containing substrate strand, and a high sensitivity “on–off” sensing structure on the TFBG-SPR surface was established by using the DNA-conjugated AuNPs as a signal amplification element. This “on–off”-type lead ion biosensor has a competitive limit of detection of 3 fM and a wide dynamic measurement range up to ten orders, meeting stringent requirements for ultra-trace, label-free and online clinical detection. Owing to the unique catalytic effect of DNAzyme binding to lead ions, high selectivity was demonstrated. Moreover, to validate its practicality in clinical diagnosis, we successfully achieved spiked-recovery results with 100.39 % average recovery rate and a swift 17-minute analysis time within the colorectal cancer patient samples. By combining DNA biomolecular, TFBG-SPR probe and “on–off” AuNPs-DNA structure, the fM level detection of lead ion in fiber highlighted its potential in vivo and in vitro complex application scenarios.

Model integration of circadian- and sleep-wake-driven contributions to rhythmic gene expression reveals distinct regulatory principles

Analyses of gene-expression dynamics in research on circadian rhythms and sleep homeostasis often describe these two processes using separate models. Rhythmically expressed genes are, however, likely to be influenced by both processes. We implemented a driven, damped harmonic oscillator model to estimate the contribution of circadian- and sleep-wake-driven influences on gene expression. The model reliably captured a wide range of dynamics in cortex, liver, and blood transcriptomes taken from mice and humans under various experimental conditions. Sleep-wake-driven factors outweighed circadian factors in driving gene expression in the cortex, whereas the opposite was observed in the liver and blood. Because of tissue- and gene-specific responses, sleep deprivation led to a long-lasting intra- and inter-tissue desynchronization. The model showed that recovery sleep contributed to these long-lasting changes. The results demonstrate that the analyses of the daily rhythms in gene expression must take the complex interactions between circadian and sleep-wake influences into account. A record of this paper's transparent peer review process is included in the supplemental information.

Double diffraction imaging of x-ray induced structural dynamics in single free nanoparticles

Because of their high photon flux, x-ray free-electron lasers (FEL) allow to resolve the structure of individual nanoparticles via coherent diffractive imaging (CDI) within a single x-ray pulse. Since the inevitable rapid destruction of the sample limits the achievable resolution, a thorough understanding of the spatiotemporal evolution of matter on the nanoscale following the irradiation is crucial. We present a technique to track x-ray induced structural changes in time and space by recording two consecutive diffraction patterns of the same single, free-flying nanoparticle, acquired separately on two large-area detectors opposite to each other, thus examining both the initial and evolved particle structure. We demonstrate the method at the extreme ultraviolet (XUV) and soft x-ray Free-electron LASer in Hamburg (FLASH), investigating xenon clusters as model systems. By splitting a single XUV pulse, two diffraction patterns from the same particle can be obtained. For focus intensities of about 2×1012 W cm−2 we observe still largely intact clusters even at the longest delays of up to 650 picoseconds of the second pulse, indicating that in the highly absorbing systems the damage remains confined to one side of the cluster. Instead, in case of five times higher flux, the diffraction patterns show clear signatures of disintegration, namely increased diameters and density fluctuations in the fragmenting clusters. Future improvements to the accessible range of dynamics and time resolution of the approach are discussed.

A foreground calibration technique with multi-level dither for a 14-bit 1-MS/s SAR ADC

A foreground calibration is proposed to obtain the real weights in the split capacitor digital-to-analog- converter (CDAC) of a 14-bit 1-MS/s successive-approximation-register (SAR) ADC. Since the non-linearity of high-resolution SAR ADC is mainly caused by the mismatch of capacitors, calibration of weights of more significant bits is necessary when the resolution of SAR ADC comes to more than 12 bits. By injecting a multi-level dither signal in both the calibration and conversion phases of the calibration scheme, the precision and non-linearity of SAR ADC can be significantly improved. Simulation results indicate that the peak signal-to-noise-and-distortion ratio (SNDR) and the spurious-free dynamic range (SFDR) achieve 79.93 dB and 91.21 dB by employing the proposed calibration technique in a 14-bit split-CDAC SAR ADC. Besides, integral non-linearity (INL) achieves 0.22 least-significant bit (LSB).

An 11-bit SAR ADC for high frame rate and high-dynamic X-ray imaging at future XFELs

The paper presents the design and test results of an 11-bit successive approximation register (SAR) ADC, suitable for massive on-chip integration in a pixel readout chip. The objective is to establish new digital readout architectures for X-ray pixel detectors at future X-ray free electron laser (XFEL) facilities, enabling high frame rates and a high dynamic range simultaneously. The prototype chip has been designed and fabricated in a 130 nm CMOS process, with the core circuit occupying an area of ~ 0.034 mm2. The measured differential nonlinearity (DNL) and integral nonlinearity (INL) are +0.78/-0.78 LSB and +0.58/-0.52 LSB, respectively. The signal-to-noise-and-distortion ratio (SINAD) is 61.6 dB at 2 MS/s, achieving an effective number of bit (ENOB) of ~ 9.94-bit. The core circuit power consumption is 47 μW at 2 MS/s with a 1.2 V supply.

Multi-stage coarse-to-fine progressive enhancement network for single-image HDR reconstruction

Compared with traditional imaging, high dynamic range (HDR) imaging technology can record scene information more accurately, thereby providing users higher quality of visual experience. Inverse tone mapping is a direct and effective way to realize single-image HDR reconstruction, but it usually suffers from some problems such as detail loss, color deviation and artifacts. To solve the problems, this paper proposes a multi-stage coarse-to-fine progressive enhancement network (named MSPENet) for single-image HDR reconstruction. The entire multi-stage network architecture is designed in a progressive manner to obtain higher-quality HDR images from coarse-to-fine, where a mask mechanism is used to eliminate the effects of over-exposure regions. Specifically, in the first two stages, two asymmetric U-Nets are constructed to learn the multi-scale information of input image and perform coarse reconstruction. In the third stage, a residual network with channel attention mechanism is constructed to learn the fusion of progressively transferred multi-level features and perform fine reconstruction. In addition, a multi-stage progressive detail enhancement mechanism is designed, including progressive gated recurrent unit fusion mechanism and multi-stage feature transfer mechanism. The former fuses the progressively transferred features with coarse HDR features to reduce the error stacking effect caused by multi-stage networks. Meanwhile, the latter fuses early features to supplement the lost information during each stage of feature delivery and combines features from different stages. Extensive experimental results show that the proposed method can reconstruct higher quality HDR images and effectively recover texture and color information in over-exposure regions compared to the state-of-the-art methods.

E-Gaze: Gaze Estimation With Event Camera.

Near-eye gaze estimation is a task that maps the recording of an eye captured by an adjacent camera to the direction of a person's gaze in space. In contrast to frame-based cameras, event cameras are characterized by high sensing rates, low latency, sparse asynchronous data outputs, and high dynamic range, which are well suited for recording the fast eye movements. However, algorithms and system designs that operate on frame-based cameras are not applicable to event-based data, due to the natural differences in the data characteristics. In this work, we study the pattern of near-eye event-based data streams and extract eye features to estimate gaze. First, by analyzing eye parts and movements, and harnessing the polar, spatial, and temporal distribution of the events, we introduce a real-time pipeline to extract pupil features. Second, we present a recurrent neural network with a proposed coordinate-to-angle loss function to accurately estimate gaze from pupil feature sequence. We demonstrated that our system achieves accurate real-time estimation with angular accuracy of 0.46 ° and update rates of 950 Hz, thus opening up avenues for novel applications. To our knowledge, this is the first system that operates only on event-based data to perform gaze estimation.

Self-assembled flower-like carbon nanosheets for magnetic solid-phase extraction of microcystins from aquatic organism

Adsorbents with good dispersibility and high efficiency are crucial for magnetic solid-phase extraction (MSPE). In this study, flower-like magnetic nanomaterials (F-Ni@NiO@ZnO2-C) were successfully prepared by calcination of metal-organic framework (MOF) precursors that was stacked by two-dimensional (2D) nanosheet. The synthesized F-Ni@NiO@ZnO2-C has a flower-like layered structure with a large amount of pore space, promoting the rapid diffusion of targets. In addition, Zn2+ doped in MOF precursors was still retained that further produced strong metal chelation with targets. The unique structure of F-Ni@NiO@ZnO2-C was used as MSPE adsorbent, and combined with high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) for extraction of three microcystins (MCs) detection, including microcystin-LR (MC-LR), microcystin-RR (MC-RR), microcystin-YR (MC-YR). The resulting method has a detection limit of 0.2–1.0 pg mL−1, a linear dynamic range of 0.6–500.0 pg mL−1 and has good linearity (R ≥ 0.9996). Finally, the established method was applied to the highly selective enrichment of MCs in biological samples, successfully detecting trace amounts of MCs (8.4–15.0 pg mL−1) with satisfactory recovery rates (83.7–103.1 %). The results indicated that flower-like magnetic F-Ni@NiO@ZnO2-C was a promising adsorbent, providing great potential for the determination of trace amounts of MCs in biological samples.

Design and thermal simulation of the front-end module for STARLIGHT

This paper presents a front-end module emulator for SemiconducTor Array detectoR with Large dynamIc ranGe and cHarge inTegrating readout (STARLIGHT), a versatile hybrid silicon pixel detector with a high frame rate (≥10kHz) and serving as the first charge-integrating pixel detector for XFEL in China. The detector is intended for operation in a vacuum environment, with the front-end module generating a thermal power of up to 5.443 mW/mm2, presenting a significant challenge for thermal management. To assess the thermal management capabilities of the mechanical and PCB designs for the project, a thermal emulator was developed to replicate the heat generated by the ASIC. This was particularly crucial during the early stages of the project when the ASIC was not yet available, achieved by placing copper wires on the PCB. Subsequent thermal simulations were conducted and compared with the results obtained from the thermal emulator. The comparison shows that the experimental results are very close to the thermal simulation results, validating the thermal performance of the STARLIGHT front-end modules. These endeavors not only provide validation but also offer valuable insights to ensure the thermal efficiency of the STARLIGHT front-end modules.

High Dynamic Range Scanning Tunneling Microscopy

High Dynamic Range Scanning Tunneling Microscopy

Application of a Green Deep Eutectic Solvent for Preconcentration and Determination of Copper and Cadmium in Food, Cosmetic, and Water Samples

Background:: Determination of environmental pollutants is important due to their harmful effects on the health of living organisms. However, direct measurement of many of these pollutants is not possible due to their low concentrations, which necessitates the need for sample preparation methods. One of the rapid and simple sample preparation methods is the Air-Agitated Liquid-Liquid Microextraction (AALLME) method, which requires toxic organic solvents that can lead to environmental pollution. Therefore, finding green solvents like Deep Eutectic Solvents (DESs) to replace them can be investigated. Methods:: A novel Deep Eutectic Solvent (DES) was synthesized from a combination of choline chloride and 2-phenylethanol with a molar ratio of 1:4, and it was examined using FT-IR analysis. This solvent was used in an AALLME method for measuring copper and cadmium heavy metal ions in complex real samples with Flame Atomic Absorption Spectroscopy (FAAS). Results:: The influential parameters of this method, such as solution pH (5.4), extraction cycles (12), and extraction solvent volume (440 μL), were optimized utilizing central composite design (CCD). Underneath the optimized circumstances, the detection limits for Cu2+ and Cd2+ were 0.14 and 0.09 ng mL-1, and the linear dynamic range was 0.47-50.0 and 0.32-22.5 ng mL-1, respectively. The preconcentration factors for these cations were 139.7 and 133.4, respectively. Conclusion:: Combining this novel green solvent and rapid sample preparation method for the preconcentration and determination of the studied heavy metal ions has shown promising results in terms of enrichment factors and detection limit values.

Fabrication of a highly sensitive glucose-6-phosphate biosensor based on direct electron transfer using phage display and autodisplay technologies

Glucose in biological cells is metabolized and exists as glucose-6-phosphate (G6P). A G6P biosensor was fabricated using a combination of phage display and autodisplay technologies for the detection of G6P. Active G6P dehydrogenase (G6PDH) was expressed and anchored to the outer membrane of Escherichia coli (E. coli) cells using autodisplay technology. Autodisplayed G6PDH exhibited high activity as confirmed by OM protein analysis. A conductive nanomesh layer was formed using a phage display to enhance the direct electron transfer of the enzyme. G6PDH autodisplaying E. coli cells were then immobilized on the layer using a polyelectrolyte interlayer. The nicotinamide adenine dinucleotide phosphate redox pairs in the fabricated electrode of the autodisplayed G6PDH exhibited a redox reaction, resulting in a significant increase in the peak currents in the presence of G6P. The G6P biosensor exhibited a wide dynamic range with high sensitivity, exhibiting linear responses in the ranges of 0.1 fM – 10nM and 10nM – 100μM. The biosensor detected G6P without interference from other sugar molecules. The combination of phage display and autodisplay technologies is a promising approach for the fabrication of highly sensitive and specific biosensors.

Flexible circuit-based spatially aware modular optical brain imaging system for high-density measurements in natural settings.

Functional near-infrared spectroscopy (fNIRS) presents an opportunity to study human brains in everyday activities and environments. However, achieving robust measurements under such dynamic conditions remains a significant challenge. The modular optical brain imaging (MOBI) system is designed to enhance optode-to-scalp coupling and provide a real-time probe three-dimensional (3D) shape estimation to improve the use of fNIRS in everyday conditions. The MOBI system utilizes a bendable and lightweight modular circuit-board design to enhance probe conformity to head surfaces and comfort for long-term wearability. Combined with automatic module connection recognition, the built-in orientation sensors on each module can be used to estimate optode 3D positions in real time to enable advanced tomographic data analysis and motion tracking. Optical characterization of the MOBI detector reports a noise equivalence power of 8.9 and at 735 and 850nm, respectively, with a dynamic range of 88dB. The 3D optode shape acquisition yields an average error of 4.2mm across 25 optodes in a phantom test compared with positions acquired from a digitizer. Results for initial in vivo validations, including a cuff occlusion and a finger-tapping test, are also provided. To the best of our knowledge, the MOBI system is the first modular fNIRS system featuring fully flexible circuit boards. The self-organizing module sensor network and automatic 3D optode position acquisition, combined with lightweight modules ( ) and ergonomic designs, would greatly aid emerging explorations of brain function in naturalistic settings.

An enrichment strategy based on hydrophobic tagging and reversed-phase chromatographic separation for the analysis of lysine-containing peptides

Lysine (K) is widely used in the design of lysine-targeted crosslinkers, structural elucidation of protein complexes, and analysis of protein-protein interactions. In "shotgun" proteomics, which is based on liquid chromatography-tandem mass spectrometry (LC-MS/MS), proteins from complex samples are enzymatically digested, generating thousands of peptides and presenting significant challenges for the direct analysis of K-containing peptides. In view of the lack of effective methods for the enrichment of K-containing peptides, this work developed a method which based on a hydrophobic-tag-labeling reagent C10-S-S-NHS and reversed-phase chromatography (termed as HYTARP) to achieve the efficient enrichment and identification of K-containing peptides from complex samples. The C10-S-S-NHS synthesized in this work successfully labeled standard peptides containing various numbers of K and the labeling efficiency achieved up to 96% for HeLa cell protein tryptic digests. By investigating the retention behavior of these labeled peptides in C18 RP column, we found that most K-labeled peptides were eluted once when acetonitrile percentage reached 57.6% (v/v). Further optimization of the elution gradient enabled the efficient separation and enrichment of the K-labeled peptides in HeLa digests via a stepwise elution gradient. The K-labeled peptides accounted for 90% in the enriched peptides, representing an improvement of 35% compared with the number of peptides without the enrichment. The dynamic range of proteins quantified from the enriched K-containing peptides spans 5-6 orders of magnitude, and realized the detection of low-abundance proteins in the complex sample. In summary, the HYTARP strategy offers a straightforward and effective approach for reducing sample complexity and improving the identification coverage of K-containing peptides and low-abundance proteins.

Virtual home staging and relighting from a single panorama under natural illumination

Virtual staging technique can digitally showcase a variety of real-world scenes. However, relighting indoor scenes from a single image is challenging due to unknown scene geometry, material properties, and outdoor spatially-varying lighting. In this study, we use the High Dynamic Range (HDR) technique to capture an indoor panorama and its paired outdoor hemispherical photograph, and we develop a novel inverse rendering approach for scene relighting and editing. Our method consists of four key components: (1) panoramic furniture detection and removal, (2) automatic floor layout design, (3) global rendering with scene geometry, new furniture objects, and the real-time outdoor photograph, and (4) virtual staging with new camera position, outdoor illumination, scene texture, and electrical light. The results demonstrate that a single indoor panorama can be used to generate high-quality virtual scenes under new environmental conditions. Additionally, we contribute a new calibrated HDR (Cali-HDR) dataset that consists of 137 paired indoor and outdoor photographs. The animation for virtual rendered scenes is available here.