Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation of GOES-16 ABI VNIR channel radiometric performance with NPP and NOAA-20 VIIRS over the Sonoran Desert

Abstract. The advanced baseline imager (ABI) onboard Geostationary Operational Environmental Satellites-16 (GOES-16) provides high-quality visible and near-infrared (VNIR) imagery data. Radiometric performance of the GOES-16 ABI multiple VNIR bands (B1, B2, B3, B5, and B6) is evaluated over the Sonoran Desert by comparing measurements with Suomi National Polar-Orbiting Partnership (S-NPP) and NOAA-20 visible infrared imaging radiometer suite equivalent bands M3, M5, M7, M10, and M11, respectively. In order to minimize the uncertainties due to the difference in spectral response functions of similar bands from the different sensors, spectral band adjustment factor (SBAF) derived from Hyperion data over Sonoran Desert is used. The large viewing angle at the Sonoran Desert by ABI (56.34 deg) and a lack of comprehensive BRDF model at such viewing geometry are the main challenges for the comparison. Two schemes to address such challenges were developed. A data-derived (DD) method, based on confining the matched solar-zenith angle and view-zenith angle between ABI and VIIRS, interpolation in solar-zenithal and relative-azimuthal angles is developed to address this issue. It is shown that there is some residual bias for ABI B1 and its equivalent VIIRS M3 band, which is mainly due to unaccounted angular dependence of atmospheric scattering in this DD method. To address this issue, a radiative transfer modeling (RTM)-based method to account for atmospheric effects is developed to facilitate the comparison. The time series trending and mean bias of reflectance ratio between ABI and VIIRS measurements over the Sonoran Desert after SBAF and bidirectional reflectance distribution function corrections are derived to evaluate the radiometric performance of ABI with respect to net primary productivity and NOAA-20 VIIRS. The analysis shows that the radiometric biases of the five VNIR channels of GOES-16 ABI are all within 5% in comparison to the matched channels of NPP VIIRS after applying the RTM correction. The analysis also detects ∼6 % drop in the radiometric bias of GOES-16 ABI 0.64 μm channel after April 23, 2019, which can be traced to the implementation of a correction of the ABI B2 calibration coefficient around this date. Further, we evaluate the relative radiometric bias for the five VNIR channels between NPP and NOAA-20 VIIIRS using double difference method, and the comparison shows that NPP VIIRS has 2% to 3% higher bias than NOAA-20 VIIRS for these spectral bands.
Irradiation of successive pulsed and continuous-wave lasers on a transparent polyethylene film

Abstract. It is difficult to cut through a transparent material such as polyethylene (PE) film with a continuous-wave (CW) laser of the near-infrared wavelength, because of the low absorption of laser energy. The plasma induced by a pulsed laser, however, can damage the surface of a film, which can change the transparency of the material. In this study, a transparent PE film with a thickness of 0.6 mm was irradiated by various combinations of focused laser pulses and a CW laser. The test conditions and the processes were recorded visually by a Schlieren optics system on the side surface of the film and by a high-speed camera on the front surface. From the results, it can be concluded that, though it is difficult to cut through a transparent material such as PE film with only a pulsed or CW laser alone, once the transparency of the surface has been modified by multiple focused laser pulses, the PE film can be cut through easily by a CW laser with a near-infrared wavelength.
Nonuniform blind deblurring for single images based on adaptive edge-enhanced regularization

Abstract. Natural images inevitably suffer from spatially variant blur caused by the relative motion between a camera and objects. We present an effective and efficient patch-wise edge-enhanced image regularization and a robust kernel similarity constraint to perform an accurate kernel estimation from coarse-to-fine iterations. The proposed adaptive regularization introduces a gradient magnitude penalty function into total variation to preserve and enhance salient edges while smoothing out harmful subtle structures. In addition, the similarity constraint is engaged in each patch without camera rotation effects, ensuring that the erroneous kernels can be identified by measuring the similarity among the kernels of neighbor patches and be replaced with the well-estimated ones. After obtaining accurate kernels, numerous nonblind deblurring methods can be applied to restore an image. Numerical experiments demonstrate that the proposed algorithm performs favorably without ringing artifacts and possesses high processing efficiency for natural nonuniform blurred images.
Highly sensitive antimonene-coated black phosphorous-based surface plasmon-resonance biosensor for DNA hybridization: design and numerical analysis

Abstract. The design of an ultrasensitive surface plasmon resonance (SPR) sensor for the detection of deoxyribose nucleic acid (DNA) hybridization is highly desirable for biomedical applications. We have proposed an SPR sensor architecture (Prism-SF10/Al/Si/BP/Antimonene/phosphate buffer saline solution) and performed its numerical analysis for DNA hybridization using angular interrogation at 633 nm. Antimonene is used as a biorecognition element layer for better attachment of single stranded (ss), i.e., ss probe DNA on its surface, due to its higher binding energy for ssDNA (even greater than graphene). Silicon and black phosphorous are utilized to enhance the electromagnetic field at the sensing layer interface. Aluminum is used as an surface plasmon active metal and it also improves the quality factor. Remarkable sensitivity (202.37 deg / refractive index unit) is attained for this work, which is greater than any other SF10 prism-based SPR sensor proposed to date. The performance of the SPR biosensor is meticulously evaluated as limit-of-detection (0.0028 nM) and figure-of-merit (0.037 nM − 1) with respect to the concentration of complementary target ssDNA in the sensing medium. This versatile biosensor shows great application to detect deadly diseases via DNA hybridization in the biomedical field if developed as an SPR chip for experimental verification.
Efficient update of multilinear singular value decomposition in background subtraction applications

Abstract. Subtraction techniques are used to distinguish moving objects or foregrounds that are being tracked from a static background. To prevent possible local misclassifications, the subspace spanned by low-rank features computed from a multilinear singular value decomposition (MLSVD), can be used to filter out noises or gradual changes from the background. However, as it is prohibitively expensive to compute a new MLSVD from scratch at every iteration, we propose an adaptive and efficient method for updating an MLSVD by reusing previous decompositions while tracking more accurate decomposition errors. The experimental results reveal that the proposed MLSVD update algorithm exhibits a faster execution speed and better accuracy than other MLSVD update algorithms used in background subtraction applications.
Remote-sensing image super-resolution using classifier-based generative adversarial networks

Abstract. The rapid development of the aerospace industry has significantly increased the demand for remote-sensing images with high resolution and quality. Generating images with expected resolution from the samples obtained by common acquisition devices is a challenging task as the trade-off between cost and efficiency must be considered. We propose a super-resolution (SR) algorithm especially for remote-sensing images that is based on generative adversarial networks optimized by a classifier, which is called classifier-based super-resolution generative adversarial network (CSRGAN). We hypothesize that the confidence scores of classification can be a critical factor for representing the features in target remote-sensing images. To sufficiently take this factor into account during training, we add the class-score as an error into the loss function in addition to mean square error and high-dimensional features extracted from deep neural networks. Then, the classifier is utilized for both better SR performance and more precise classification. The classifier-testing branch of our system can also be flexibly combined with other network architectures to optimize SR performance on remote-sensing images. We validate the model on the NWPU-RESISC45 dataset considering both SR and classification performance. The final analysis is also provided and shows that the proposed CSRGAN outperforms existing algorithms.
Toward plant organs in nature: a new database for plant organ system

Abstract. The detection of plant organs is an important research field of plant recognition area. However, due to the lack of database of plant organs, the application of convolutional neural network-based object detection on plant species is very limited. A database of plant organs for deep learning-based object detection is constructed. A huge number of plant images are clawed using specific keywords through keyword search engines such as Baidu and Google. After that, an automatic junk image cleaning method is performed to remove junk images. Finally, artificial labeling is used to delineate plant organ regions. To evaluate the quality of the database, experiments in different object detection models are implemented. Results show that the established plant organ database has good performance in plant organs positioning and classification.
Occupancy-balancing downlink transmission for enhancing scalability of LoRa networks

LoRa/LoRaWAN is growing rapidly as an underlying technology for the Internet of Things because of its long-range connectivity and low power. However, its limited scalability, owing to spread spectrum–based modulation and contention-based medium access control, impedes its use in emerging massive applications. In this study, we propose a downlink transmission scheme for enhancing the scalability of LoRa networks. The proposed scheme consists of two mechanisms. First, a modulation parameter is adjusted using the different transmission power limitations between the gateways and end devices to reduce downlink duration. Second, the timing of downlink traffic is selected based on uplink traffic concentration analysis. The proposed scheme reduces the uplink failure, and consequently, allows more end devices to participate in the network. The simulation results show that the proposed scheme is superior to the standard protocol in terms of the packet delivery ratio.
Terahertz spectrum of Acesulfame-K

Terahertz time-domain spectroscopy (THz-TDS) is a new coherent spectral technique. The spectral characteristics of Acesulfame-K in the range of 0.2-2.6THz had been measured with THz-TDS. We obtained its transmission spectrum, refractive index spectrum and absorption spectrum at room temperature in the nitrogen atmosphere. The results show that Acesulfame-K had the abnormal dispersions at 0.40THz, 0.66THz, 0.94THz, 1.79THz and 2.30THz. The vibration absorption spectrum of single molecule of Acesulfame-K is simulated based on the Density Functional Theory (DFT). It is found that Acesulfame-K has the obvious absorbance in THz region. This result shows that THz-TDS has a potential application in the field of food security.
Improved methanol tolerance during Novozym435-mediated methanolysis of SODD for biodiesel production

SODD is proposed here as a sort of feedstock for biodiesel production. During lipase-catalyzed alcoholysis of soybean oil deodorizer distillate (SODD) for biodiesel production, lipase expressed higher tolerance to methanol compared to that with refined soybean oils as the feedstock, and much a faster reaction rate could be obtained. Further study showed that free fatty acid contained in SODD was the major factor contributing to the improvement of lipase tolerance to methanol. It was further demonstrated that the improved methanol tolerance was related to the hydrophobicity of the reactants (log Preactant), the lower the ∣log Preactant − log Pinterface∣, the higher the lipase tolerance to methanol that could be achieved. The highest biodiesel yield of 95% could be achieved by adding a 3 A molecular sieve as an adsorbent into the system to control the by-product water.
An NF-κB/IRF1 axis programs cDC1s to drive anti-tumor immunity

Conventional type 1 dendritic cells (cDC1s) are critical for anti-tumor immunity. They acquire antigens from dying tumor cells and cross-present them to CD8+ T cells, promoting the expansion of tumor-specific cytotoxic T cells. However, the signaling pathways that govern the anti-tumor functions of cDC1s are poorly understood. We mapped the molecular pathways regulating intra-tumoral cDC1 maturation using single cell RNA sequencing. We identified NF-κB and IFN pathways as being highly enriched in a subset of functionally mature cDC1s. The specific targeting of NF-κB or IFN pathways in cDC1s prevented the recruitment and activation of CD8+ T cells and the control of tumor growth. We identified an NF-κB-dependent IFNγ-regulated gene network in cDC1s, including cytokines and chemokines specialized in the recruitment and activation of cytotoxic T cells. We used single cell transcriptomes to map the trajectory of intra-tumoral cDC1 maturation which revealed the dynamic reprogramming of tumor-infiltrating cDC1s by NF-κB and IFN signaling pathways. This maturation process was perturbed by specific inactivation of either NF-κB or IRF1 in cDC1s, resulting in impaired expression of IFN-γ-responsive genes and consequently a failure to efficiently recruit and activate anti-tumoral CD8+ T cells. Finally, we demonstrate the relevance of these findings to cancer patients, showing that activation of the NF-κB/IRF1 axis in association with cDC1s is linked with improved clinical outcome. The NF-κB/IRF1 axis in cDC1s may therefore represent an important focal point for the development new diagnostic and therapeutic approaches to improve cancer immunotherapy. One Sentence Summary NF-κB and IRF1 coordinate intra-tumoral cDC1 maturation and control of immunogenic tumor growth.
Authentication of In Situ Measurements for Thoracic Aortic Aneurysms in Mice

Aortic diameter is a standard parameter for defining disease severity of thoracic aortic aneurysms. In mouse studies, aortic diameters can be measured in situ directly, but this approach has a potential confounder of underestimation due to the absence of physiological arterial blood pressure. In the present study, we developed an in situ approach for authentic aortic measurements. Thoracic aortic aneurysms were induced by beta-aminopropionitrile (BAPN, 0.5% wt/vol) administration in 4-week-old male C57BL/6J mice. Ultrasonography was performed to examine aortic dimensions, and mice with thoracic aortic dilatations were terminated subsequently. After saline perfusion through the left ventricle, periaortic tissues were removed to expose thoracic aortas. Optimal cutting temperature (OCT) compound was injected via the left ventricle to maintain aortic patency. In situ aortic images were captured pre- and post-OCT injection. In mice with severe thoracic aortic aneurysms, smaller aortic diameters were observed prior to OCT injection compared to ultrasound measurements, while aortic diameters in situ after OCT were comparable to diameters measured using ultrasound. A telemetry system demonstrated that maximal luminal pressures during 150 ul of OCT injection were 90 mmHg. Immunostaining for CD31 revealed that endothelial cells were preserved in the intima after OCT injection. These results indicate that OCT injection does not cause aortic damages due to excess pressures. In conclusion, in situ imaging with OCT injection provides authentic aortic measurements without overt aortic damage in mice with thoracic aortic aneurysms.
A Novel Mode of Photoprotection Mediated by a Cysteine Residue in the Chlorophyll Protein IsiA

Cyanobacteria, oxygenic photosynthetic microbes, constantly experience varying light regimes. Light intensities higher than those that saturate the photosynthetic capacity of the organism often lead to redox damage to the photosynthetic apparatus and often cell death. ABSTRACT Oxygenic photosynthetic organisms have evolved a multitude of mechanisms for protection against high-light stress. IsiA, a chlorophyll a-binding cyanobacterial protein, serves as an accessory antenna complex for photosystem I. Intriguingly, IsiA can also function as an independent pigment protein complex in the thylakoid membrane and facilitate the dissipation of excess energy, providing photoprotection. The molecular basis of the IsiA-mediated excitation quenching mechanism remains poorly understood. In this study, we demonstrate that IsiA uses a novel cysteine-mediated process to quench excitation energy. The single cysteine in IsiA in the cyanobacterium Synechocystis sp. strain PCC 6803 was converted to a valine. Ultrafast fluorescence spectroscopic analysis showed that this single change abolishes the excitation energy quenching ability of IsiA, thus providing direct evidence of the crucial role of this cysteine residue in energy dissipation from excited chlorophylls. Under stress conditions, the mutant cells exhibited enhanced light sensitivity, indicating that the cysteine-mediated quenching process is critically important for photoprotection. IMPORTANCE Cyanobacteria, oxygenic photosynthetic microbes, constantly experience varying light regimes. Light intensities higher than those that saturate the photosynthetic capacity of the organism often lead to redox damage to the photosynthetic apparatus and often cell death. To meet this challenge, cyanobacteria have developed a number of strategies to modulate light absorption and dissipation to ensure maximal photosynthetic productivity and minimal photodamage to cells under extreme light conditions. In this communication, we have determined the critical role of a novel cysteine-mediated mechanism for light energy dissipation in the chlorophyll protein IsiA.
Matrix stiffness and blood pressure together regulate vascular smooth muscle cell phenotype switching

Vascular smooth muscle cells (VSMCs) play a central role in the onset and progression of atherosclerosis. In pre-atherosclerotic lesions, VSMCs switch from a contractile to a synthetic phenotype and subsequently remodel the microenvironment, leading to further disease progression. Ageing and associated mechanical changes of the extracellular matrix as well as hypertension are major risk of atherosclerosis. Consequently, we sought here to systematically study the impact of mechanical stimulations on VSMC phenotypic switching, by modulating both stiffness and hydrodynamic pressure. Thereby we find that hemodynamic pressure and matrix stiffness individually affect the VSMC phenotype. However, only the combination of hypertensive pressure and matrix compliance, and as such mechanical stimuli that are prevalent during atherosclerosis, lead to a full phenotypic switch including the formation of matrix degrading podosomes. We further analyse the molecular mechanism in stiffness and pressure sensing and identify a regulation through different, but overlapping pathways, culminating in the regulation of the actin cytoskeleton through cofilin. Altogether, our data shows how different pathological mechanical signals combined, but through distinct pathways accelerate a phenotypic switch that will ultimately contribute to atherosclerotic disease progression.
A test of the hypothesis that variable mutation rates create signals that have previously been interpreted as evidence of archaic introgression into humans

It is widely accepted that non-African humans carry 1-2% Neanderthal DNA due to historical inter-breeding. However, inferences about introgression rely on a critical assumption that mutation rate is constant and that back-mutations are too rare to be important. Both these assumptions have been challenged, and recent evidence points towards an alternative model where signals interpreted as introgression are driven mainly by higher mutation rates in Africa. In this model, non-Africans appear closer to archaics not because they harbour introgressed fragments but because Africans have diverged more. Here I test this idea by using the density of rare, human-specific variants (RHSVs) as a proxy for recent mutation rate. I find that sites that contribute most to the signal interpreted as introgression tend to occur in tightly defined regions spanning only a few hundred bases in which mutation rate differs greatly between the two human populations being compared. Mutation rate is invariably higher in the population into which introgression is not inferred. I confirmed that RHSV density reflects mutation rate by conducting a parallel analysis looking at the density of RHSVs around sites with three alleles, an independent class of site that also requires recurrent mutations to form. Near-identical peaks in RHSV density are found, suggesting a common cause. Similarly, coalescent simulations confirm that, with constant mutation rate, introgressed fragments do not occur preferentially in regions with a high density of rare, human-specific variants. Together, these observations are difficult to reconcile with a model where excess base-sharing is driven by archaic legacies but instead provide support for a higher mutation rate inside Africa driving increased divergence from the ancestral human state.
Cortical layer‐specific modulation of neuronal activity after sensory deprivation due to spinal cord injury

Cortical areas have the capacity of large-scale reorganization following sensory deprivation. However, it remains unclear whether this phenomenon is a unique process that homogenously affects an entire deprived cortical region or it is suitable to changes depending on neuronal networks across distinct cortical layers. Here, we studied how local circuitries within each layer of the deprived cortex set the basis for neuroplastic changes after immediate sensory deprivation due to thoracic spinal cord injury (SCI) in anaesthetised rats. In vivo electrophysiological recordings from deprived hindlimb somatosensory cortex showed that SCI induces layer-specific changes mediating evoked and spontaneous activity. In supragranular layers 2/3, sensory deprivation increased gamma oscillations and the ability of these neurons to initiate up-states during spontaneous activity, suggesting altered corticocortical network and/or intrinsic properties that may serve to maintain the excitability of the cortical column after deprivation. On the other hand, sensory deprivation enhanced infragranular layers’ ability to integrate evoked-sensory inputs leading to increased and faster neuronal responses. Delayed evoked-responses onset were also observed in layers 5/6, suggesting alterations in thalamocortical connectivity. Altogether, our data indicate that SCI immediately modifies local circuitries within the deprived cortex allowing supragranular layers to better integrate spontaneous corticocortical information, and thus modifying column excitability, and infragranular layers to better integrate evoked-sensory inputs to preserve subcortical outputs. These layer-specific neuronal changes may guide the long-term alterations in neuronal excitability and plasticity associated to the rearrangements of somatosensory networks and the appearance of central sensory pathologies usually associated with spinal cord injury.