Miracle-dz/UniFAR-FTUs huggingface dataset:
sSLAM: Speeded-Up Visual SLAM Mixing Artificial Markers and Temporary Keypoints

Environment landmarks are generally employed by visual SLAM (vSLAM) methods in the form of keypoints. However, these landmarks are unstable over time because they belong to areas that tend to change, e.g., shadows or moving objects. To solve this, some other authors have proposed the combination of keypoints and artificial markers distributed in the environment so as to facilitate the tracking process in the long run. Artificial markers are special elements (similar to beacons) that can be permanently placed in the environment to facilitate tracking. In any case, these systems keep a set of keypoints that is not likely to be reused, thus unnecessarily increasing the computing time required for tracking. This paper proposes a novel visual SLAM approach that efficiently combines keypoints and artificial markers, allowing for a substantial reduction in the computing time and memory required without noticeably degrading the tracking accuracy. In the first stage, our system creates a map of the environment using both keypoints and artificial markers, but once the map is created, the keypoints are removed and only the markers are kept. Thus, our map stores only long-lasting features of the environment (i.e., the markers). Then, for localization purposes, our algorithm uses the marker information along with temporary keypoints created just in the time of tracking, which are removed after a while. Since our algorithm keeps only a small subset of recent keypoints, it is faster than the state-of-the-art vSLAM approaches. The experimental results show that our proposed sSLAM compares favorably with ORB-SLAM2, ORB-SLAM3, OpenVSLAM and UcoSLAM in terms of speed, without statistically significant differences in accuracy.
Fault-Tolerant Dual Active Isolated DC-DC Converter

In this paper a fault-tolerant isolated dc-dc converter is proposed for shipboard power applications. In this topology, an active 5-level T-type converter is used on the primary and secondary sides of a high-frequency transformer. The operation of the proposed converter is optimized based on minimizing the losses. A fault-tolerant analysis is carried out for this converter and post-fault switching methods are proposed for each faulty condition. The proposed converter features better fault tolerance options and higher efficiency compared to the common dual active bridge dc-dc converters. Finally, the operation of the proposed structure in the normal and faulty conditions are verified through experiments.
Infrared surface photometry of dwarf galaxies in Fornax

Despite its utility in exploring possible spatial variations in the stellar populations in galaxies, infrared surface photometry of low-luminosity dwarf elliptical (dE) galaxies is generally lacking, due to the technical difficulties in observing low surface brightness objects against the bright infrared sky. Here we attempt to remedy this shortfall to some extent by presenting K-band photometry at arcsecond resolution, including radial profiles, 1D and 2D model fits and the quantification of nuclear components, for a small sample of dE galaxies, with absolute magnitudes MB? -15 to -13, in the Fornax Cluster. In the second part of the paper, we explore the comparison of these data with corresponding optical observations and attempt to interpret this in terms of stellar population models and their radial trends. A significant range of global opticalinfrared colours is present in our sample, but radial colour gradients in the galaxies are usually small. However, while the nuclear regions tend to be bluer in optical colours, they are systematically redder than the surrounding galaxy in (R-K). The stellar population modelling suggests that these colour differences are probably an effect of both higher metallicity and younger age in the nuclei. Excluding the nuclear regions, the global colour profiles typically change in the same direction, again indicating older, more metal-poor stellar populations in the outskirts of the galaxies.
An experimental investigation of cloud cavitation about a sphere

Cloud cavitation occurrence about a sphere is investigated in a variable-pressure water tunnel using low- and high-speed photography. The model sphere, 0.15 m in diameter, was sting-mounted within a 0.6 m square test section and tested at a constant Reynolds number of 1.5 × 106 with cavitation numbers varying between 0.36 and 1.0. High-speed photographic recordings were made at 6 kHz for several cavitation numbers providing insight into cavity shedding and nucleation physics. Shedding phenomena and frequency content were investigated by means of pixel intensity time series data using wavelet analysis. Instantaneous cavity leading edge location was investigated using image processing and edge detection. The boundary layer at cavity separation is shown to be laminar for all cavitation numbers, with Kelvin–Helmholtz instability and transition to turbulence in the separated shear layer the main mechanism for cavity breakup and cloud formation at high cavitation numbers. At intermediate cavitation numbers, cavity lengths allow the development of re-entrant jet phenomena, providing a mechanism for shedding of large-scale Kármán-type vortices similar to those for low-mode shedding in single-phase subcritical flow. This shedding mode, which exists at supercritical Reynolds numbers for single-phase flow, is eliminated at low cavitation numbers with the onset of supercavitation. Complex interactions between the separating laminar boundary layer and the cavity were observed. In all cases the cavity leading edge was structured in laminar cells separated by well-known ‘divots’. The initial laminar length and divot density were modulated by the unsteady cavity shedding process. At cavitation numbers where shedding was most energetic, with large portions of leading edge extinction, re-nucleation was seen to be circumferentially periodic and to consist of stretched streak-like bubbles that subsequently became fleck-like. This process appeared to be associated with laminar–turbulent transition of the attached boundary layer. Nucleation occurred periodically in time at these preferred sites and formed the characteristic cavity leading edge structure after sufficient accumulation of vapour had occurred. These observations suggest that three-dimensional instability of the decelerating boundary layer flow may have significantly influenced the developing structure of the cavity leading edge.
The Timing of Surgery Following Stereotactic Body Radiation Therapy Impacts Local Control for Borderline Resectable or Locally Advanced Pancreatic Cancer

Simple Summary The role of radiation therapy in localized pancreatic cancer is controversial. The interval of time from the end of radiotherapy to surgery has been shown in some cancer disease sites to affect subsequent outcomes but has not been studied in pancreatic cancer. We aimed to characterize the optimal timing of surgery following stereotactic body radiation therapy (SBRT) in patients with borderline resectable or locally advanced pancreatic cancer. We found that patients who underwent surgery more than 6 weeks after completing SBRT had improved local control outcomes compared to those who had received surgery within 6 weeks of completing SBRT, even when controlling for other clinical factors such as the pathological response to neoadjuvant chemotherapy. These findings could be used to inform future studies, including prospective trials to better select patients with localized pancreatic cancer who may benefit from radiotherapy. Abstract We aimed to evaluate the impact of time from stereotactic body radiation therapy (SBRT) to surgery on treatment outcomes and post-operative complications in patients with borderline resectable or locally advanced pancreatic cancer (BRPC/LAPC). We conducted a single-institutional retrospective analysis of patients with BRPC/LAPC treated from 2016 to 2021 with neoadjuvant chemotherapy followed by SBRT and surgical resection. Covariates were stratified by time from SBRT to surgery. A Cox regression model was used to identify variables associated with survival outcomes. In 171 patients with BRPC/LAPC, the median time from SBRT to surgery was 6.4 (range: 2.7–25.3) weeks. Hence, patients were stratified by the timing of surgery: ≥6 and <6 weeks after SBRT. In univariable Cox regression, surgery ≥6 weeks was associated with improved local control (LC, HR 0.55, 95% CI 0.30–0.98; p = 0.042), pathologic node positivity, elevated baseline CA19-9, and inferior LC if of the male sex. In multivariable analysis, surgery ≥6 weeks (p = 0.013; HR 0.46, 95%CI 0.25–0.85), node positivity (p = 0.019; HR 2.09, 95% CI 1.13–3.88), and baseline elevated CA19-9 (p = 0.002; HR 2.73, 95% CI 1.44–5.18) remained independently associated with LC. Clavien–Dindo Grade ≥3B complications occurred in 4/63 (6.3%) vs. 5/99 (5.5%) patients undergoing surgery <6 weeks and ≥6 weeks after SBRT (p = 0.7). In summary, the timing of surgery ≥6 weeks after SBRT was associated with improved local control and low post-operative complication rates, irrespective of the surgical timing. Further investigation of the influence of surgical timing following radiotherapy is warranted.
Laser-Induced Optical Property Changes Inside Bi-Doped Glass

We report an unusual phenomenon of optical properties changes in Bi-doped glass under irradiation with a femtosecond laser. Not only broadband absorption in the visible but also infrared luminescence variations have been observed after irradiation. This behavior is related to the process of laser initiating local chemical reactions involving multiple active centers of Bi. This phenomenon provides a convenient method for 3-D selective fabrication by ultrashort laser pulses, and applications in ultrahigh density optical memory and micro photonics.
ADMM Based Interference Exploitation Multi-User One-Bit Massive MIMO Precoding

In this article, we focus on the 1-bit precoding design for a multi-user massive multiple-input multiple-output (MIMO) system, where the concept of constructive interference (CI) is employed to formulate the optimization problem. By adopting the symbol-scaling CI metric, the formulated optimization problem is transformed such that the alternating direction method of multipliers (ADMM) framework can be used to solve this problem. Furthermore, we obtain the closed-form solution to the subproblem in each step within the ADMM iteration, thus achieving lower complexity. We further provide the computational complexity analysis of the proposed algorithm. Numerical experiments verify the superior bit error rate (BER) performance of the proposed ADMM-based CI precoding (CI-ADMM) scheme over the state-of-the-art, with proper initialization.
Low-Acceleration-Voltage Electron Irradiation Damage in Single-Walled Carbon Nanotubes

Low-acceleration-voltage electron irradiation effects on single-walled carbon nanotubes were studied by resonant Raman spectroscopy. The irradiation at acceleration voltages of 0.5 to 25 kV was found to extinguish the characteristic optical property of the nanotubes and reduce their tolerance against annealing in air, indicating that the nanotubes are inevitably damaged by ordinary scanning electron microscope observation. The acceleration voltage of around 1 kV caused the most extensive damage. Less defective SWNTs were found to have a higher tolerance against the irradiation damage.
Ginsenoside ompound K reduces neuronal damage and improves neuronal synaptic dysfunction by targeting Aβ

Background: Alzheimer’s disease (AD) is the most common neurodegenerative condition worldwide, with amyloid ß (Aβ) fibrils presenting as its main pathological feature. This study investigated whether Ginsenoside Compound K (CK) has activity against Aβ and its mechanism in reducing synaptic damage and cognitive impairment. Methods: The binding capacity of CK to Aβ42 and Nrf2/Keap1 was determined using molecular docking. Transmission electron microscopy was used to monitor CK-mediated degradation of Aβ fibrils. The effect of CK on the survival of Aβ42-damaged HT22 cells was determined using a CCK-8 assay. The therapeutic efficacy of CK in a scopoletin hydrobromide (SCOP) induced cognitive dysfunction mouse model was measured using a step-down passive avoidance test. GO enrichment analysis of mouse brain tissue was peformed using Genechip. Hydroxyl radical scavenging and reactive oxygen species assays were performed to verify the antioxidant activity of CK. The effects of CK on the expression of Aβ42, the Nrf2/Keap1 signaling pathway, and other proteins were determined by western blotting, immunofluorescence, and immunohistochemistry. Results: Molecular docking results showed that CK interacts with Lys16 and Glu3 of Aβ42. CK reduced the aggregation of Aβ42 as observed using transmission electron microscopy. CK increased the level of insulin-degrading enzyme and decreased the levels ß-secretase and γ-secretase; therefore, it can potentially inhibit the accumulation of Aβ in neuronal extracellular space in vivo. CK improved cognitive impairment and increased postsynaptic density protein 95 and synaptophysin expression levels in mice with SCOP-induced cognitive dysfunction. Further, CK inhibited the expression of cytochrome C, Caspase-3, and cleaved Caspase-3. Based on Genechip data, CK was found to regulate molecular functions such as oxygen binding, peroxidase activity, hemoglobin binding, and oxidoreductase activity, thus affecting the production of oxidative free radicals in neurons. Further, CK regulated the expression of the Nrf2/Keap1 signaling pathway through its interaction with the Nrf2/Keap1 complex. Conclusion: Our findings show that CK regulates the balance between Aβ monomers production and clearance, CK binds to Aβ monomer to inhibits the accumulation of Aβ, increases the level of Nrf2 in neuronal nuclei, reduces oxidative damage of neurons, improves synaptic function, thus ultimately protecting neurons.
Protective effect of compatible herbs in Jin-Gu-Lian formula against Alangium chinense-induced neurotoxicity via oxidative stress, neurotransmitter metabolisms, and pharmacokinetics

Background: A. chinense frequently used in Miao medicine to treat rheumatic diseases. However, as a famous toxic herb, Alangium chinense and its representative components exhibit ineluctable neurotoxicity, thus creating significant challenges for clinical application. The combined application with compatible herbs in Jin-Gu-Lian formula attenuates such neurotoxicity according to the compatible principle of traditional Chinese medicines. Purpose: We aimed to investigate the detoxification of the compatible herbs in Jin-Gu-Lian formula on A. chinense-induced neurotoxicity and investigate its mechanism. Methods: Neurobehavioral and pathohistological analysis were used to determine the neurotoxicity in rats administered with A. chinense extract (AC), extract of compatible herbs in Jin-Gu-Lian formula (CH) and combination of AC with CH for 14 days. The mechanism underlying the reduction of toxicity by combination with CH was assessed by enzyme-linked immunosorbent assays, spectrophotometric assays, liquid chromatography tandem-mass spectrometry and real-time reverse transcription-quantitative polymerase chain reaction. Results: Compatible herbs attenuated the AC-induced neurotoxicity as evidenced by increased locomotor activity, enhanced grip strength, the decreased frequency of AC-induced morphological damage in neurons, as well as a reduction of neuron-specific enolase (NSE) and neurofilament light chain (NEFL) levels. The combination of AC and CH ameliorated AC-induced oxidative damage by modulating the activities of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px), and total antioxidant capacity (T-AOC). AC treatment significantly reduced the levels of monoamine and acetylcholine neurotransmitters in the brains of rats, including acetylcholine (Ach), dopamine (DA), 3,4-dihydroxyphenylacetic acid (DOPAC), homovanillic acid (HVA), norepinephrine (NE), and serotonin (5-HT). Combined AC and CH treatment regulated the abnormal concentrations and metabolisms of neurotransmitters. Pharmacokinetic studies showed that the co-administration of AC and CH significantly decreased plasma exposure levels of two main components of AC, as evidenced by the reduction of maximum plasma concentration (Cmax), area under the plasma concentration-time curve (AUC) compared to AC. In addition, the AC-induced downregulation in mRNA expression of cytochrome P450 enzymes was significantly reduced in response to combined AC and CH treatment. Conclusion: Compatible herbs in Jin-Gu-Lian formula alleviated the neurotoxicity induced by A. chinense by ameliorating oxidative damage, preventing abnormality of neurotransmitters and modulating pharmacokinetics.
Scene classification based on spatial pyramid representation by superpixel lattices and contextual visual features

Abstract. Natural scene classification is a challenging open problem in computer vision. We present a novel spatial pyramid representation scheme for recognizing scene category. Initially, each image is partitioned into sub-blocks, applying the technology of superpixel lattices segmentation according to a boosted edge learning boundary map, which makes the objects in each sub-block have the integrity—that is, the features in each sub-block are relatively consistent. Then, we extract the dense scale-invariant feature transform features of the images and form the contextual visual feature description. Finally, the image representations are performed by following the methodology of spatial pyramid. The feature descriptions we present include both local structural information and global spatial structural information; therefore, they are more discriminative for scene classification. Experiments demonstrate that the classification rate can achieve about 87.13% on a set of 15 categories of complex scenes.
A Computational Model as Neurodecoder Based on Synchronous Oscillation in the Visual Cortex

Based on synchronized responses of neuronal populations in the visual cortex to external stimuli, we proposed a computational model consisting primarily of a neuronal phase-locked loop (NPLL) and multiscaled operator. The former reveals the function of synchronous oscillations in the visual cortex. Regardless of which of these patterns of the spike trains may be an average firing-rate code, a spike-timing code, or a rate-time code, the NPLL can decode original visual information from neuronal spike trains modulated with patterns of external stimuli, because a voltage-controlled oscillator (VCO), which is included in the NPLL, can precisely track neuronal spike trains and instantaneous variations, that is, VCO can make a copy of an external stimulus pattern. The latter, however, describes multi-scaled properties of visual information processing, but not merely edge and contour detection. In this study, in which we combined NPLL with a multiscaled operator and maximum likelihood estimation, we proved that the model, as a neurodecoder, implements optimum algorithm decoding visual information from neuronal spike trains at the system level. At the same time, the model also obtains increasingly important supports, which come from a series of experimental results of neurobiology on stimulus-specific neuronal oscillations or synchronized responses of the neuronal population in the visual cortex. In addition, the problem of how to describe visual acuity and multiresolution of vision by wavelet transform is also discussed. The results indicate that the model provides a deeper understanding of the role of synchronized responses in decoding visual information.
Key Issues and Novel Strategies of Stem Cell Intervention and Decellularized Scaffold Liver Tissue Engineer for End-Stage Liver Disease

: End-stage liver disease (ESLD) is ultimation of all kinds of chronic liver diseases. It is highly morbidity and mortality disease and currently no effective treatment is available. Liver transplantation (LTx) is the only way for the treatment. However, the organ source limitation interferes with clinical application of LTx. For the goal of crossing liver source shortage barrier, researches attempt to explore techniques or methods like stem cells and tissue engineering, and recent years sounds developed rapidly and bright prospects, for example, artificial liver, tissue-engineered liver and xenotransplantation etc., in particular adult stem cells like bone marrow-derived mesenchymal stem cells ( BM MSCs) and decellularized liver scaffold for large scale liver tissue engineer seems more eye-catching, and such decellularization / recellularization technology used has become the first strategy to build complex organs. We have previously discussed some points in the <Chinese Journal of Digestive Surgery > about optimizing bioscaffold materials that probably will be benificial for tissue engineer. In the present review, we would like to discuss some new developments based on research status and provide a little new thoughts, hopefully those can help people in this field in order to treat ESLD in the near future.
A Parallel Algorithm for Variational Assimilation in Oceanography and Meteorology

Abstract A parallel algorithm is described for variational assimilation of observations into oceanic and atmospheric models. The algorithm may be coded first for execution on a serial computer and then trivially modified for execution on a parallel computer such as the Intel iPSC/860. The speedup factor for parallel execution is roughly P(2M+3) (2M+3P)−1, where P is the number of processors and M is the number of observations (M≥P). The speedup factor approaches P from below as M→∞. The algorithm has been applied in serial form to ocean tides (Bennett and McIntosh 1982; McIntosh and Bennett 1984; Bennett 1985) and oceanic equatorial interannual variability (Bennett 1990). It has been applied in parallel form to oceanic synoptic-scale circulation (Bennett and Thorburn 1992); a parallel application to operational forecasting of tropical cyclones is in progress (Bennett et al. 1992). For the sake of simplicity, the parallel algorithm is described here for a model consisting of a linear, first-order wave equa.
Prediction of a Large-Scale Database of Collision Cross-Section and Retention Time Using Machine Learning to Reduce False Positive Annotations in Untargeted Metabolomics

Metabolite identification in untargeted metabolomics is complex, with the risk of false positive annotations. This work aims to use machine learning to successively predict the retention time (Rt) and the collision cross-section (CCS) of an open-access database to accelerate the interpretation of metabolomic results. Standards of metabolites were tested using liquid chromatography coupled with high-resolution mass spectrometry. In CCSBase and QSRR predictor machine learning models, experimental results were used to generate predicted CCS and Rt of the Human Metabolome Database. From 542 standards, 266 and 301 compounds were detected in positive and negative electrospray ionization mode, respectively, corresponding to 380 different metabolites. CCS and Rt were then predicted using machine learning tools for almost 114,000 metabolites. R2 score of the linear regression between predicted and measured data achieved 0.938 and 0.898 for CCS and Rt, respectively, demonstrating the models’ reliability. A CCS and Rt index filter of mean error ± 2 standard deviations could remove most misidentifications. Its application to data generated from a toxicology study on tobacco cigarettes reduced hits by 76%. Regarding the volume of data produced by metabolomics, the practical workflow provided allows for the implementation of valuable large-scale databases to improve the biological interpretation of metabolomics data.