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Written information on the surface of cultural relics can record important historical events. Due to the influence of natural and human factors, the surface of cultural relics fades and the words are difficult to identify. Take advantage of the hyperspectral data image and spectral unity and wide spectral range, a cultural relics surface handwriting enhancement method based on manifold learning and mixed pixel decomposition was proposed. First, the minimum noise fraction (MNF) transformation was carried out on the hyperspectral image, and then the top 10 bands were selected for inverse MNF transformation to reduce noise of the hyperspectral image. Then, the reconstructed image was dimensionally reduced by locally linear embedding (LLE) to obtain a gray image with the maximum amount of information. At the same time, the spectral features of the handwriting and background area in the reconstructed image were analysed. The automatic target generation process (ATGP) was adopted for endmember extraction on the reconstructed image to identify the endmember of handwriting. The abundance map of handwriting area was obtained by the fully constrained least squares (FCLS). Finally, the gray image and the abundance map of the handwriting region were weighted together to obtain the handwriting enhanced image. The true color image was synthesized from the reconstructed image, Then the true color image and the handwriting enhancement image were fused to obtain the handwritting fusion image. The hyperspectral image of a faded text in Shuozhou City, Shanxi Province, China, was used as an example for verification, and the results showed that the method can effectively enhance the text on the surface of the artifacts.

Cellular diversification is critical for specialized functions of the brain including learning and memory(1). Single cell RNA-sequencing facilitates transcriptomic profiling of distinct major types of neurons(2-4), but divergence of transcriptomic profiles within a neuronal population and their link to function remain poorly understood. Here, we isolate nuclei tagged(5) in specific cell types followed by single nuclear RNA sequencing to profile Purkinje neurons and map their responses to motor activity and learning. We find that two major subpopulations of Purkinje neurons, identified by the genes Aldoc and Plcb4, bear distinct transcriptomic features. Plcb4+, but not Aldoc+, Purkinje neurons display robust plasticity of gene expression in mice subjected to sensorimotor and learning experience. In vivo calcium imaging and optogenetic perturbation reveal that Plcb4+ Purkinje neurons play a crucial role in associative learning. Integrating single nuclear RNA-seq datasets with weighted gene network analysis uncovers a learning gene module that includes components of FGFR2 signaling in Plcb4+ Purkinje neurons. Knockout of Fgfr2 in Plcb4+ Purkinje neurons in mice by a CRISPR approach disrupts motor learning. Our findings define how diversification of Purkinje neurons links to their responses in motor learning and provide a foundation for understanding their differential vulnerability to neurological disorders.

The desire to understand how the brain generates and patterns behavior has driven rapid methodological innovation in tools to quantify natural animal behavior. While advances in deep learning and computer vision have enabled markerless pose estimation in individual animals, extending these to multiple animals presents unique challenges for studies of social behaviors or animals in their natural environments. Here we present Social LEAP Estimates Animal Poses (SLEAP), a machine learning system for multi-animal pose tracking. This system enables versatile workflows for data labeling, model training and inference on previously unseen data. SLEAP features an accessible graphical user interface, a standardized data model, a reproducible configuration system, over 30 model architectures, two approaches to part grouping and two approaches to identity tracking. We applied SLEAP to seven datasets across flies, bees, mice and gerbils to systematically evaluate each approach and architecture, and we compare it with other existing approaches. SLEAP achieves greater accuracy and speeds of more than 800 frames per second, with latencies of less than 3.5 ms at full 1,024 × 1,024 image resolution. This makes SLEAP usable for real-time applications, which we demonstrate by controlling the behavior of one animal on the basis of the tracking and detection of social interactions with another animal.

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Individuals with Neurofibromatosis type 1 (NF1) experience a high degree of motor problems. The cerebellum plays a pivotal role in motor functioning and the NF1 gene is highly expressed in cerebellar Purkinje cells. However, it is not well understood to what extent NF1 affects cerebellar functioning and how this relates to NF1 motor functioning. Therefore, we subjected global Nf1+/− mice to a cerebellum-dependent associative learning task, called Pavlovian eyeblink conditioning. Additionally, we assessed general motor function and muscle strength in Nf1+/− mice. To our surprise, we found that Nf1+/− mice showed a moderately increased learning rate of conditioned eyeblink responses, as well as improved accuracy in the adaptive timing of the eyeblink responses. Locomotion, balance, general motor function, and muscle strength were not affected in Nf1+/− mice. Together, our results support the view that cerebellar function in Nf1+/− mice is unimpaired.

Individuals with Neurofibromatosis type 1 (NF1) experience a high degree of motor problems. The cerebellum plays a pivotal role in motor functioning and the NF1 gene is highly expressed in cerebellar Purkinje cells. However, it is not well understood to what extent NF1 affects cerebellar functioning and how this relates to NF1 motor functioning. Therefore, we subjected global Nf1+/− mice to a cerebellar-specific associative learning task, called Pavlovian eyeblink conditioning. Additionally, we assessed general motor function and muscle strength in Nf1+/− mice. To our surprise, we found that Nf1+/− mice showed a moderately increased learning rate of conditioned eyeblink responses, as well as improved accuracy in the adaptive timing of the eyeblink responses. Locomotion, balance, general motor function, and muscle strength were not affected in Nf1+/− mice. Together, our results support the view that cerebellar function in Nf1+/− mice is unimpaired.

Information regarding the correct pedigree of and relationship between animals is useful for managing dairy breeding, reducing inbreeding, estimating breeding value, and establishing correct breeding programs. Additionally, the successful implementation of progeny testing is crucial for improving the genetics of dairy cattle, which depends on the availability of correct pedigree information. Incorrect pedigree information leads to bias in bull evaluation. In this study, Neogen GeneSeek Genomic Profiler (GGP) 50K SNP chips were used to identify and verify the sire of Taiwanese Holstein dairy cattle and analyze the reasons that lead to incorrect sire records. Samples were collected from 2,059 cows of 36 dairy farms, and the pedigree information was provided by breeders. The results of sire verification can be divided into three categories: submitted unconfirmed sire, submitted confirmed sire, and incorrectly submitted verified sire. Data on the sires of 1,323 (64.25%) and 572 (27.78%) dairy cows were verified and discovered, respectively. Sires of 1,895 (92.03%) dairy cattle were identified, which showed that the paternal pedigree of dairy cattle could be discovered and verified through genetic testing. An error-like analysis revealed that the data of 37 sires were incorrectly recorded because the bull's NAAB code number was incorrectly entered into the insemination records: for 19 sires, the wrong bull was recorded because the frozen semen of a bull placed in the wrong storage tank was used, 6 had no sire records, and for 12 sires, the NAAB code of the correct bull was recorded but with a wrong stud code, marketing code, or unique number for the stud or breed. To reduce recorded sire error rates by at least 27.78%, automated identification of the mated bull must be adopted to reduce human error and improve dairy breeding management on dairy farms.

Arsenic is a non-metallic element, and the International Agency for Research on Cancer has identified arsenic and its compounds as carcinogens. Arsenic and its compounds can be absorbed through the respiratory tract, skin and digestive tract, distributed in the liver, kidney, lung and skin, and cause damage. Non-coding RNAs are closely related to arsenic-induced nervous system disorders, cell necrosis, reproductive toxicity, and carcinogenesis. In recent years, the network regulation of microRNAs (miRNAs) , long non-coding RNAs (lncRNAs) , and circular RNAs (circRNAs) among non-coding RNAs in various diseases induced by arsenic has become a new research field. This paper summarizes the existing scientific research results, and expounds the mechanism of miRNAs, lncRNAs and circRNAs in arsenic toxicity, and provides basic data and theoretical basis for the prevention and treatment of arsenic poisoning.砷是一种非金属元素，国际癌症研究机构已经明确砷及其化合物是致癌物质。砷及其化合物可经呼吸道、皮肤和消化道吸收，分布于肝、肾、肺以及皮肤中，并对其造成损伤。而非编码RNA与砷所致神经系统紊乱、细胞坏死、生殖毒性和癌变等密切相关。近年来，非编码RNA中的微小RNA（miRNAs）、长链非编码RNA（lncRNAs）和环状RNA（circRNAs）在砷诱导的各种疾病中的网络调控已成为新的研究领域。本文通过总结已有的科研成果，对miRNAs、lncRNAs和circRNAs在砷毒性中的作用机制进行阐述，为砷中毒的防治提供基础资料和理论依据。.

A thermoelectric energy generator (TEG) is to convert the temperature difference between the hot and cold junctions into electrical energy by Seebeck effect. This work proposes a TEG design implemented by standard CMOS process to improve energy harvesting performance and to expedite the fabrication process. The TEG has double cavity with the upper cavity of $5.2~\mu \text{m}$ and the lower cavity of $10~\mu \text{m}$ in depth, which are created by dry etching post process for thermal isolation to improve energy conversion. The size and geometry of the thermocouples are determined to match their thermal/electrical resistance for optimal performance. A $5\times5$ mm2 TEG chip with four $2\times2$ mm2 cells, two in electrical series and another two in parallel, is implemented by CMOS process in semiconductor foundry service (TSMC D35 2P4M). Experiments validate that the voltage/power factor of the cells in the TEG chip agree very well. In simulation, the double cavity design achieves the performance 30% higher than that in previous work with only lower cavity. In experimental measurement, the TEG has voltage factor 2.889 V/cm2K and power factor $0.0450~\mu \text{W}$ /cm2K2. This is by far best TEG performance by matured, standard CMOS process in semiconductor foundry.

Background Repetitive action, resistance to environmental change and fine motor disruptions are hallmarks of autism spectrum disorder (ASD) and other neurodevelopmental disorders, and vary considerably from individual to individual. In animal models, conventional behavioral phenotyping captures such fine-scale variations incompletely. Here we observed male and female C57BL/6J mice to methodically catalog adaptive movement over multiple days and examined two rodent models of developmental disorders against this dynamic baseline. We then investigated the behavioral consequences of a cerebellum-specific deletion in Tsc1 protein and a whole-brain knockout in Cntnap2 protein in mice. Both of these mutations are found in clinical conditions and have been associated with ASD. Methods We used advances in computer vision and deep learning, namely a generalized form of high-dimensional statistical analysis, to develop a framework for characterizing mouse movement on multiple timescales using a single popular behavioral assay, the open-field test. The pipeline takes virtual markers from pose estimation to find behavior clusters and generate wavelet signatures of behavior classes. We measured spatial and temporal habituation to a new environment across minutes and days, different types of self-grooming, locomotion and gait. Results Both Cntnap2 knockouts and L7-Tsc1 mutants showed forelimb lag during gait. L7-Tsc1 mutants and Cntnap2 knockouts showed complex defects in multi-day adaptation, lacking the tendency of wild-type mice to spend progressively more time in corners of the arena. In L7-Tsc1 mutant mice, failure to adapt took the form of maintained ambling, turning and locomotion, and an overall decrease in grooming. However, adaptation in these traits was similar between wild-type mice and Cntnap2 knockouts. L7-Tsc1 mutant and Cntnap2 knockout mouse models showed different patterns of behavioral state occupancy. Limitations Genetic risk factors for autism are numerous, and we tested only two. Our pipeline was only done under conditions of free behavior. Testing under task or social conditions would reveal more information about behavioral dynamics and variability. Conclusions Our automated pipeline for deep phenotyping successfully captures model-specific deviations in adaptation and movement as well as differences in the detailed structure of behavioral dynamics. The reported deficits indicate that deep phenotyping constitutes a robust set of ASD symptoms that may be considered for implementation in clinical settings as quantitative diagnosis criteria.

既往左心耳内血栓是左心耳封堵的禁忌证。该文报道1例心房颤动患者，有反复脑梗死病史，合并糖尿病、肾功能不全及冠心病，心脏CT血管成像诊断左心耳血栓，因抗凝治疗不耐受，故行左心耳封堵术。术后予抗凝和/或抗血小板治疗仍反复发生器械相关血栓。提示心房颤动合并左心耳血栓患者应慎行左心耳封堵术，术后需个体化调整抗栓方案、密切随诊。.

Climbing fiber inputs to Purkinje cells provide instructive signals critical for cerebellum-dependent associative learning. Studying these signals in head-fixed mice facilitates the use of imaging, electrophysiological, and optogenetic methods. Here, a low-cost behavioral platform (~$1000) was developed that allows tracking of associative learning in head-fixed mice that locomote freely on a running wheel. The platform incorporates two common associative learning paradigms: eyeblink conditioning and delayed tactile startle conditioning. Behavior is tracked using a camera and the wheel movement by a detector. We describe the components and setup and provide a detailed protocol for training and data analysis. This platform allows the incorporation of optogenetic stimulation and fluorescence imaging. The design allows a single host computer to control multiple platforms for training multiple animals simultaneously.

The high P content in steel slag limits its recycling during the smelting process, and the P can be effectively removed from the steel slag by gasification dephosphorization. In this experiments, the effects of temperature, basicity, and FeO for gasification dephosphorization rate are studied through thermodynamic calculations. The Scanning Electron Microscope (SEM) and Energy Dispersive Spectrometer (EDS) analysis that microscopic morphology of slag before and after reduction. In addition, a model is established to describe the phosphorus migration behavior of gasification dephosphorization process.

Perturbation to the cerebellum can lead to motor dysfunction, cognitive deficits, and behavioral inflexibility. Here we report that a cerebellum-specific transgenic mouse model with disrupted Purkinje cell function shows unexpectedly accelerated learning on a sensory evidence-accumulation task, as well as enhanced sensory reactivity to touch and auditory cues. Computational latent-state analysis of behavior revealed that accelerated learning was associated with enhanced focus on current over past trials. Learning was also accelerated by providing cue-locked optogenetic stimulation of Purkinje cells, but unaffected by continuous optogenetic interference with Purkinje cell activity. Both transgenic and optogenetically-boosted mice showed prolonged electrophysiological activity in Purkinje-cell complex spikes and anterior cingulate cortex. We suggest that cerebellar activity may shape evidence-accumulation learning by enhancing task focus and neocortical processing of current experience.

The cerebellum regulates nonmotor behavior, but the routes by which it exerts its influence are not well characterized. Here we report a necessary role for the posterior cerebellum in guiding a reversal learning task, acting through a network of diencephalic and neocortical structures. After chemogenetic inhibition of Purkinje cells in lobule VI or crus I, mice could learn a water Y-maze task but were impaired in their ability to reverse their initial choice. To map targets of perturbation, we imaged c-Fos activation in cleared whole brains using light-sheet microscopy. Reversal learning activated diencephalic regions and associative neocortical regions. Distinctive subsets of structures were altered by perturbation of lobule VI (including thalamus and habenula) and crus I (including hypothalamus and prelimbic/orbital cortex), and both perturbations influenced anterior cingulate and infralimbic cortex. To identify functional networks, we used correlated variation in c-Fos activation within each test group. Lobule VI inactivation weakened within-thalamus correlations, while crus I inactivation divided neocortical activity into well-separated sensorimotor and associative subnetworks. In both groups, high-throughput automated analysis of complex whole-body movement revealed deficiencies in across-day adaptation to an open field environment. Neither perturbation affected gait, within-day open-field adaptation, or location preference. Taken together, these experiments reveal brainwide systems for cerebellar influence that can affect multiple flexible responses.Significance statementThe cerebellum, a part of all vertebrate brains, provides feedback to the rest of the brain on a split-second basis in response to unexpected events. The consequent changes can range from minute adjustments in movement to broad changes in behavior. In mice, we investigated cerebellar regions that help guide flexible behavior. Inactivation of these regions prevented mice from responding flexibly to a changing Y-shaped maze. We used light-sheet microscopy of c-fos protein expression to map brainwide effects of different stages of learning and cerebellar inactivation. Inactivation caused changes in thalamocortical activity that were similar in pattern, but opposite in sign, from normal learning. Lobule VI inactivation weakened thalamic functional networks, while crus I inactivation divided sensorimotor from associative neocortical networks. The same inactivation also impaired multiday adaptation to an open arena, as tracked using machine vision. Our work shows how the cerebellum’s influence over flexible response can be mediated by a widespread brain network.

《三消论》为刘完素的遗稿，主要探讨了消渴病的病因病机、治疗原则，选录了专治消渴的方剂。书中引用文献多来自其本人著作，有部分来自于《内经》等前人著作，当是刘完素在其他著作完成之后又对消渴病进行的思考总结之作。《三消论》最早被附于金代刊行的《儒门事亲》中，朝鲜的《医方类聚》（1445）有引录，明万历二十九年（1601）刊行的《儒门事亲》全文录入，此为国内通行本之基础，后被《四库全书》录入。清代末期，周学海将通行本加上按语单独成书，纳入《周氏医学丛书》中，又有单行本刊行。.

Calcium imaging with protein-based indicators is widely used to follow neural activity in intact nervous systems. The popular GCaMP indicators are based on the calcium-binding protein calmodulin and the RS20 peptide. These sensors report neural activity at timescales much slower than electrical signaling, limited by their biophysical properties and trade-offs between sensitivity and speed. We used large-scale screening and structure-guided mutagenesis to develop and optimize several fast and sensitive GCaMP-type indicators. The resulting ‘jGCaMP8’ sensors, based on calmodulin and a fragment of endothelial nitric oxide synthase, have ultra-fast kinetics (rise times, 2 ms) and still feature the highest sensitivity for neural activity reported for any protein-based sensor. jGCaMP8 sensors will allow tracking of larger populations of neurons on timescales relevant to neural computation.

Background: Repetitive action, resistance to environmental change, and fine motor disruptions are hallmarks of autism spectrum disorder (ASD) and other neurodevelopmental disorders, and vary considerably from individual to individual. In animal models, conventional behavioral phenotyping captures such fine-scale variations incompletely. Here, we aimed at investigating behavioral consequences of a cerebellum-specific deletion in Tsc1 protein and a whole-brain knockout in Cntnap2 protein in mice, both mutations are found in the clinical conditions and have been associated with ASD. We observed male and female C57BL/6J mice to methodically catalog adaptive movement over multiple days and examined two rodent models of developmental disorders against this dynamic baseline. Methods: Here, we use advances in computer vision and deep learning, a generalized form of high-dimensional statistical analysis, to develop a framework for characterizing mouse movement on multiple time scales using a single popular behavioral assay, the open field test. The pipeline takes virtual markers from pose estimation to find behavior clusters and generate wavelet signatures of behavior classes. We measured spatial and temporal habituation to a new environment across minutes and days, different types of self-grooming, locomotion and gait. Results: Both Cntnap2 knockout and L7-Tsc1 mutants showed forelimb lag during gait. L7-Tsc1 mutants showed complex defects in multi-day adaptation, lacking the tendency of wild-type mice to spend progressively more time in corners of the arena. In L7-Tsc1 mutant mice, failure-to-adapt took the form of maintained ambling, turning, and locomotion, and an overall decrease in grooming. Adaptation in Cntnap2 knockout mice more broadly resembled that of wild-type. L7-Tsc1 mutant and Cntnap2 knockout mouse models showed different patterns of behavioral state occupancy. Limitations: Genetic risk factors for autism are numerous, and here we tested only two. Our pipeline was only applied to conditions of free behavior. Testing under task or social conditions would reveal more information about behavioral dynamics and variability. Conclusions: Our automated pipeline for deep phenotyping successfully captures model-specific deviations in adaptation and movement as well as differences in the detailed structure of behavioral dynamics. The reported deficits indicate that deep phenotyping constitutes a robust set of ASD symptoms that may be considered for implementation in clinical settings as a quantitative diagnosis criteria.

Development of brain circuitry requires precise regulation and timing of proliferation and differentiation of neural progenitor cells. The p75 neurotrophin receptor (p75NTR) is highly expressed in the proliferating granule cell precursors (GCPs) during development of the cerebellum. In a previous paper, we showed that proNT3 promoted GCP cell cycle exit via p75NTR. Here we used genetically modified rats and mice of both sexes to show that p75NTR regulates the duration of the GCP cell cycle, requiring activation of RhoA. Rats and mice lacking p75NTR have dysregulated GCP proliferation, with deleterious effects on cerebellar circuit development and behavioral consequences persisting into adulthood. In the absence of p75NTR, the GCP cell cycle is accelerated, leading to delayed cell cycle exit, prolonged GCP proliferation, increased glutamatergic input to Purkinje cells, and a deficit in delay eyeblink conditioning, a cerebellum-dependent form of learning. These results demonstrate the necessity of appropriate developmental timing of the cell cycle for establishment of proper connectivity and associated behavior.SIGNIFICANCE STATEMENTThe cerebellum has been shown to be involved in numerous behaviors in addition to its classic association with motor function. Cerebellar function is disrupted in a variety of psychiatric disorders, including those on the autism spectrum. Here we show that the p75 neurotrophin receptor, which is abundantly expressed in the proliferating cerebellar granule cell progenitors, regulates the cell cycle of these progenitors. In the absence of this receptor, the cell cycle is dysregulated, leading to excessive progenitor proliferation, which alters the balance of inputs to Purkinje cells, disrupting the circuitry and leading to functional deficits that persist into adulthood.

Key points Spike doublets comprise ∼10% of in vivo complex spike events under spontaneous conditions and ∼20% (up to 50%) under evoked conditions. Under near-physiological slice conditions, single complex spikes do not induce parallel fibre long-term depression. Doublet stimulation is required to induce long-term depression with an optimal parallel-fibre to first-complex-spike timing interval of 150 ms. Abstract The classic example of biological supervised learning occurs at cerebellar parallel fibre (PF) to Purkinje cell synapses, comprising the most abundant synapse in the mammalian brain. Long-term depression (LTD) at these synapses is driven by climbing fibres (CFs), which fire continuously about once per second and therefore generate potential false-positive events. We show that pairs of complex spikes are required to induce LTD. In vivo, sensory stimuli evoked complex-spike doublets with intervals ≤150 ms in up to 50% of events. Using realistic [Ca2+ ]o and [Mg2+ ]o concentrations in slices, we determined that complex-spike doublets delivered 100-150 ms after PF stimulus onset were required to trigger PF-LTD, which is consistent with the requirements for eyeblink conditioning. Inter-complex spike intervals of 50-150 ms provided optimal decoding. This stimulus pattern prolonged evoked spine calcium signals and promoted CaMKII activation. Doublet activity may provide a means for CF instructive signals to stand out from background firing.

Owing to their small interaction cross-section, neutrinos are unparalleled astronomical tracers. Ultra-high energy (UHE; E > 10 PeV) neutrinos probe the most distant, most explosive sources in the Universe, often obscured to optical telescopes. Radio-frequency (RF) detection of Askaryan radiation in cold polar ice is currently regarded as the best experimental measurement technique for UHE neutrinos, provided the RF properties of the ice target can be well-understood. To that end, the Askaryan Radio Array (ARA) experiment at the South Pole has used long-baseline RF propagation to extract information on the index-of-refraction ( n = ϵ r ) in South Polar ice. Owing to the increasing ice density over the upper 150–200 m, rays are measured along two, nearly parallel paths, one of which refracts through an inflection point, with differences in both arrival time and arrival angle that can be used to constrain the neutrino properties. We also observe (first) indications for RF ice birefringence for signals propagating along predominantly horizontal trajectories, corresponding to an asymmetry of order 0.1% between the ordinary and extra-ordinary birefringent axes, numerically compatible with previous measurements of birefringent asymmetries for vertically-propagating radio-frequency signals at South Pole. Qualitatively, these effects offer the possibility of redundantly measuring the range from receiver to a neutrino interaction in Antarctic ice, if receiver antennas are deployed at shallow (z ∼ −25 m) depths. Such range information is essential in determining both the neutrino energy, as well as the incident neutrino direction.

The Askaryan Radio Array (ARA) is a ground-based radio detector at the South Pole designed to capture Askaryan emission from ultra-high energy neutrinos interacting within the Antarctic ice. The newest ARA station has been equipped with a phased array trigger, in which radio signals in multiple antennas are summed in predetermined directions prior to the trigger. In this way, impulsive signals add coherently, while noise likely does not, allowing the trigger threshold to be lower than a traditional ARA station. Early results on just a fraction of available data from this new system prove the feasibility of a low-threshold analysis.