VBLC: Visibility Boosting and Logit-Constraint Learning for Domain Adaptive Semantic Segmentation under Adverse Conditions

Generalizing models trained on normal visual conditions to target domains under adverse conditions is demanding in the practical systems. One prevalent solution is to bridge the domain gap between clear- and adverse-condition images to make satisfactory prediction on the target. However, previous methods often reckon on additional reference images of the same scenes taken from normal conditions, which are quite tough to collect in reality. Furthermore, most of them mainly focus on individual adverse condition such as nighttime or foggy, weakening the model versatility when encountering other adverse weathers. To overcome the above limitations, we propose a novel framework, Visibility Boosting and Logit-Constraint learning (VBLC), tailored for superior normal-to-adverse adaptation. VBLC explores the potential of getting rid of reference images and resolving the mixture of adverse conditions simultaneously. In detail, we first propose the visibility boost module to dynamically improve target images via certain priors in the image level. Then, we figure out the overconfident drawback in the conventional cross-entropy loss for self-training method and devise the logit-constraint learning, which enforces a constraint on logit outputs during training to mitigate this pain point. To the best of our knowledge, this is a new perspective for tackling such a challenging task. Extensive experiments on two normal-to-adverse domain adaptation benchmarks, i.e., Cityscapes -> ACDC and Cityscapes -> FoggyCityscapes + RainCityscapes, verify the effectiveness of VBLC, where it establishes the new state of the art. Code is available at https://github.com/BIT-DA/VBLC.Comment: Camera ready for AAAI 2023. Code is available at https://github.com/BIT-DA/VBL

Annotator: A Generic Active Learning Baseline for LiDAR Semantic Segmentation

Active learning, a label-efficient paradigm, empowers models to interactively query an oracle for labeling new data. In the realm of LiDAR semantic segmentation, the challenges stem from the sheer volume of point clouds, rendering annotation labor-intensive and cost-prohibitive. This paper presents Annotator, a general and efficient active learning baseline, in which a voxel-centric online selection strategy is tailored to efficiently probe and annotate the salient and exemplar voxel girds within each LiDAR scan, even under distribution shift. Concretely, we first execute an in-depth analysis of several common selection strategies such as Random, Entropy, Margin, and then develop voxel confusion degree (VCD) to exploit the local topology relations and structures of point clouds. Annotator excels in diverse settings, with a particular focus on active learning (AL), active source-free domain adaptation (ASFDA), and active domain adaptation (ADA). It consistently delivers exceptional performance across LiDAR semantic segmentation benchmarks, spanning both simulation-to-real and real-to-real scenarios. Surprisingly, Annotator exhibits remarkable efficiency, requiring significantly fewer annotations, e.g., just labeling five voxels per scan in the SynLiDAR-to-SemanticKITTI task. This results in impressive performance, achieving 87.8% fully-supervised performance under AL, 88.5% under ASFDA, and 94.4% under ADA. We envision that Annotator will offer a simple, general, and efficient solution for label-efficient 3D applications. Project page: https://binhuixie.github.io/annotator-webComment: NeurIPS 2023. Project page at https://binhuixie.github.io/annotator-web

Photomodulating RNA cleavage using photolabile circular antisense oligodeoxynucleotides

Caged antisense oligodeoxynucleotides (asODNs) are synthesized by linking two ends of linear oligodeoxynucleotides using a photocleavable linker. Two of them (H30 and H40) have hairpin-like structures which show a large difference in thermal stability (ΔTm = 17.5°C and 11.6°C) comparing to uncaged ones. The other three (C20, C30 and C40) without stable secondary structures have the middle 20 deoxynucleotides complementary to 40-mer RNA. All caged asODNs have restricted opening which provides control over RNA/asODN interaction. RNase H assay results showed that 40-mer RNA digestion could be photo-modulated 2- to 3-fold upon light-activation with H30, H40, C30 and C40, while with C20, RNA digestion was almost not detectable; however, photo-activation triggered >20-fold increase of RNA digestion. And gel shift assays showed that it needed >0.04 μM H40 and 0.5 μM H30 to completely bind 0.02 μM 40-mer RNA, and for C40 and C30, it needed >0.2 μM and 0.5 μM for 0.02 μM 40-mer RNA binding. However, even 4 μM C20 was not able to fully bind the same concentration of 40-mer RNA. By simple adjustment of ring size of caged asODNs, we could successfully photoregulate their hybridization with mRNA and target RNA hydrolysis by RNase H with light activation

Research on Technical Points of Installation and Construction of Mechanical and Electrical Engineering

With the rapid development of China's overall economy, the construction engineering industry is gradually improving. Architectural engineering is an important environment for people to live, and its quality and safety are directly related to people's life and property. The most important part of the construction project is the mechanical and electrical installation, to realize the cost control of the project is the key point of the project. This article mainly explains the mechanical and electrical installation engineering in building engineering, and introduces the installation and construction technology in mechanical and electrical installation engineering in detail, and analyzes the control difficulties. It provides an important reference for the management of mechanical and electrical installation technology in the future

Optimization and validation of the protocol used to analyze the taste of traditional Chinese medicines using an electronic tongue

Tools to define the active ingredients and flavors of Traditional Chinese Medicines (TCMs) are limited by long analysis times, complex sample preparation and a lack of multiplexed analysis. The aim of the present study was to optimize and validate an electronic tongue (E‑tongue) methodology to analyze the bitterness of TCMs. To test the protocol, 35 different TCM concoctions were measured using an E‑tongue, and seven replicate measurements of each sample were taken to evaluate reproducibility and precision. E‑tongue sensor information was identified and classified using analysis approaches including least squares support vector machine (LS‑SVM), support vector machine (SVM), discriminant analysis (DA) and partial least squares (PLS). A benefit of this analytical protocol was that the analysis of a single sample took \u3c15 min for all seven sensors. The results identified that the LS‑SVM approach provided the best bitterness classification accuracy (binary classification accuracy, 100%; ternary classification accuracy, 89.66%). The E‑tongue protocol developed showed good reproducibility and high precision within a 6 h measurement cycle. To the best of our knowledge, this is the first study of an E‑tongue being applied to assay the bitterness of TCMs. This approach could be applied in the classification of the taste of TCMs, and serve important roles in other fields, including foods and beverages

Enhanced Light Utilization in Semitransparent Organic Photovoltaics Using an Optical Outcoupling Architecture

Buildingâ integrated photovoltaics employing transparent photovoltaic cells on window panes provide an opportunity to convert solar energy to electricity rather than generating waste heat. Semitransparent organic photovoltaic cells (STâ OPVs) that utilize a nonfullerene acceptorâ based nearâ infrared (NIR) absorbing ternary cell combined with a thin, semitransparent, high conductivity Cuâ Ag alloy electrode are demonstrated. A combination of optical outcoupling and antireflection coatings leads to enhanced visible transmission, while reflecting the NIR back into the cell where it is absorbed. This combination of coatings results in doubling of the light utilization efficiency (LUE), which is equal to the product of the power conversion efficiency (PCE) and the average photopic transparency, compared with a conventional semitransparent cell lacking these coatings. A maximum LUE = 3.56 ± 0.11% is achieved for an STâ OPV with a PCE = 8.0 ± 0.2% at 1 sun, reference AM1.5G spectrum. Moreover, neutral colored STâ OPVs are also demonstrated, with LUE = 2.56 ± 0.2%, along with Commission Internationale d’Eclairage chromaticity coordinates of CIE = (0.337, 0.349) and a color rendering index of CRI = 87.An efficient and neutral colored semitransparent organic photovoltaic cell (STâ OPV) is realized by utilizing a nearâ infrared (NIR) absorbing ternary cell combined with a thin, semitransparent, highâ conductivity Cuâ Ag alloy electrode. A combination of optical outcoupling and antireflection coatings leads to enhanced visible transmission, while reflecting the NIR back into the cell where it is absorbed.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151812/1/adma201903173.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151812/2/adma201903173_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151812/3/adma201903173-sup-0001-S1.pd

An insight into the mechanism and evolution of shale reservoir characteristics with over-high maturity

AbstractOver-high maturity is one of the most vital characteristics of marine organic-rich shale reservoirs from the Lower Paleozoic in the south part of China. The organic matter (OM) in shale gas reservoirs almost went through the entire thermal evolution. During this wide span, a great amount of hydrocarbon was available and numerous pores were observed within the OM including kerogen and solid bitumen/pyrobitumen. These nanopores in solid bitumen/pyrobitumen can be identified using SEM. The imaging can be dissected and understood better based on the sequence of diagenesis and hydrocarbon charge with the shape of OM and pores. In terms of the maturity process showed by the various typical cases, the main effects of the relationship between the reservoir porosity and organic carbon abundance are interpreted as follows: the change and mechanism of reservoirs properties due to thermal evolution are explored, such as gas carbon isotope from partial to complete rollover zone, wettability alteration from water-wet to oil-wet and then water-wet pore surface again, electrical resistivity reversal from the increasing to decreasing stage, and nonlinearity fluctuation of rock elasticity anisotropy. These indicate a possible evolution pathway for shale gas reservoirs from the Lower Paleozoic in the southern China, as well as the general transformation processes between different shale reservoirs in thermal stages

Clinical features of patients with MOG-IgG associated disorders and analysis of the relationship between fibrinogen-to-albumin ratio and the severity at disease onset

ObjectiveThe study aimed to investigate the differences in clinical features between pediatric and adult patients with first-episode MOG-IgG associated disorders (MOGAD) and evaluate the relationship between the fibrinogen-to-albumin ratio (FAR) and the severity of neurological deficits at disease onset.MethodsWe retrospectively collected and analyzed biochemical test results, imaging characteristics, clinical manifestations, expanded disability status scale (EDSS) score, and FAR. The Spearman correlation analysis and logistic regression models were used to examine the association between FAR and severity. Receiver operating characteristic (ROC) curve analysis was to analyze the predictive ability of FAR for the severity of neurological deficits.ResultsFever (50.0%), headache (36.1%), and blurred vision (27.8%) were the most common clinical manifestations in the pediatric group (<18 years old). However, in the adult group (≥18 years old), the most common symptoms were blurred vision (45.7%), paralysis (37.0%), and paresthesia (32.6%). Fever was more common in the pediatric group, while paresthesia was more common in the adult patients, with all differences statistically significant (P < 0.05). The most frequent clinical phenotype in the pediatric group was acute disseminated encephalomyelitis (ADEM; 41.7%), whereas optic neuritis (ON; 32.6%) and transverse myelitis (TM; 26.1%) were more common in the adult group. The differences in clinical phenotype between the two groups were statistically significant (P < 0.05). In both pediatric and adult patients, cortical/subcortical and brainstem lesions were the most common lesions on cranial magnetic resonance imaging (MRI), whereas, for spinal MRI, cervical and thoracic spinal cord lesions were the most commonly observed. According to binary logistic regression analysis, FAR was an independent risk factor for the severity of neurological deficits (odds ratio = 1.717; 95% confidence interval = 1.191–2.477; P = 0.004). FAR (r = 0.359, P = 0.001) was positively correlated with the initial EDSS score. The area under the ROC curve was 0.749.ConclusionThe current study found age-dependent phenotypes in MOGAD patients as ADEM was more commonly observed in patients < 18 years old, while ON and TM were more frequently found in patients ≥18 years old. A high FAR level was an independent indicator for more severe neurological deficits at disease onset in patients with a first episode of MOGAD