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All animals must maintain genome and proteome integrity, especially when experiencing endogenous or exogenous stress. To cope, organisms have evolved sophisticated and conserved response systems: unfolded protein responses (UPRs) ensure proteostasis, while DNA damage responses (DDRs) maintain genome integrity. Emerging evidence suggests that UPRs and DDRs crosstalk, but this remains poorly understood. Here, we demonstrate that depletion of the DNA primases pri-1 or pri-2 , which synthesize RNA primers at replication forks and whose inactivation causes DNA damage, activates the UPR of the endoplasmic reticulum (UPR-ER) in Caenorhabditis elegans , with especially strong activation in the germline. We observed activation of both the inositol-requiring-enzyme 1 (ire-1) and the protein kinase RNA-like endoplasmic reticulum kinase (pek-1) branches of the (UPR-ER). Interestingly, activation of the (UPR-ER) output gene heat shock protein 4 (hsp-4) was partially independent of its canonical activators, ire-1 and X-box binding protein (xbp-1), and instead required the third branch of the (UPR-ER), activating transcription factor 6 (atf-6), suggesting functional redundancy. We further found that primase depletion specifically induces the (UPR-ER), but not the distinct cytosolic or mitochondrial UPRs, suggesting that primase inactivation causes compartment-specific rather than global stress. Functionally, loss of ire-1 or pek-1 sensitizes animals to replication stress caused by hydroxyurea. Finally, transcriptome analysis of pri-1 embryos revealed several deregulated processes that could cause (UPR-ER) activation, including protein glycosylation, calcium signaling, and fatty acid desaturation. Together, our data show that the (UPR-ER), but not other UPRs, responds to replication fork stress and that the (UPR-ER) is required to alleviate this stress. [ABSTRACT FROM AUTHOR]

Small interfering RNA (siRNA)drugs have great potential in the field of anti-tumor, but they have poor biological stability and are easily degraded by nucleases in vivo, resulting in poor bioavailability. In this study, a novel albumin Poly(lactide-co-glycolide) (PLGA) nanocarrier was prepared to efficiently deliver siRNA to glioma cells to achieve tumor-targeted therapy. Recombinant VAR2CSA protein (RVP) targeting albumin PLGA nanocarriers (RVP–APN–siRNA) loaded with EGFR-siRNA were prepared by a double emulsion method. Determine its characterization performance, loading rate, in vitro release and cell uptake, and investigate the effects of nanoparticles on the cytotoxicity, proliferation and apoptosis of brain glioma cells. The prepared nanoparticles are spherical with uniform particle size, the average particle size distribution is 120–180 nm, the average potential distribution is 20–30 mv, and the loading rate is 82.36 ± 1.84%. The release rate of siRNA within 24 h is 93%, with low cytotoxicity and targeting performance, effectively inhibiting the activity of glioma cells. The prepared albumin nanoparticles have good physical and chemical properties, and have dual functions of targeted recognition of glioma cells and tumor treatment. They are efficient and safe nano-carriers for tumor-targeted treatment, and have good potential in the application of siRNA-targeted drug delivery. [ABSTRACT FROM AUTHOR]

AbstractClustering is a widely used unsupervised learning technique that groups data into homogeneous clusters. However, when dealing with real-world data that contain categorical values, existing algorithms can be computationally costly in high dimensions and can struggle with noisy data that has missing values. Furthermore, except for one algorithm, no others provide theoretical guarantees of clustering accuracy. In this article, we propose a general categorical data encoding method and a computationally efficient spectral-based algorithm to cluster high-dimensional noisy categorical data (nominal or ordinal). Under a statistical model for data on m attributes from n subjects in r clusters with missing probability ϵ, we show that our algorithm exactly recovers the true clusters with high probability when mn(1−ϵ)≥CMr2 log 3M, with M=max(n,m) and a fixed constant C. In addition, we show that mn(1−ϵ)2≥rδ/2 with 0<δ<1 is necessary for any algorithm to succeed with probability at least (1+δ)/2. In cases where m = n and r are fixed, the sufficient condition matches with the necessary condition up to a polylog(n) factor. In numerical studies our algorithm outperforms several existing algorithms in both clustering accuracy and computational efficiency. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

Background: Time-restricted eating (TRE), a feasible form of intermittent fasting, has been proven to benefit metabolic health in animal models and humans. To our knowledge, specific guidance on the appropriate period for eating during TRE has not yet been promoted. Therefore, to compare and assess the relative effectiveness estimates and rankings of TRE with different eating windows on human metabolic health, we conducted a systematic review and network meta-analysis (NMA). Method: PubMed, EMBASE and the Cochrane Library were searched for randomized controlled trials that compared different eating windows on human metabolic health for adults. A Bayesian NMA was used to compare direct and indirect effects to determine the best different eating windows, and scientific evidence using GRADE. Results: Twenty-seven RCTs comparing TRE with different eating windows on human metabolic health were reviewed, and all were included in the NMA. Compared with the normal diet group (non-TRE), the TRE group has certain benefits in reducing weight and fasting insulin. In terms of reducing fasting insulin, the 18:6 group (eating time = 6 h) was better than the 14:10 group (eating time = 10 h) and 16:8 group (eating time = 8 h) (P < 0.05); The < 6 group (eating time < 6 h) was better than the 14:10 group (P < 0.05). In terms of reducing fasting glucose, the < 6 group was better than the 14:10 group (P < 0.05). There were no statistical variations in weight, HDL, TG, and LDL across the different modes of TRE (P > 0.05). Conclusions: Our research showed that no particular metabolic advantages of various eating windows were found. Therefore, our results suggested that different eating windows could promote similar benefits for metabolic parameters. [ABSTRACT FROM AUTHOR]

To reduce the energy consumption of the hydrogen liquefaction process, a hydrogen liquefaction process based on cascaded mixed refrigerant cycles is proposed in this paper. The two mixed refrigerant cycles are connected in series so that the cooling capacity of refrigerants can be fully utilized. Cascaded processes with different numbers of pre-cooling stages are compared. The processes are optimized using the particle swarm algorithm. And cascaded and non-cascaded processes are compared under the same conditions. The results show that the more the number of pre-cooling stages, the lower the SEC and the higher the exergy efficiency. And the cascaded process has higher energy efficiency than the non-cascaded process. The specific power consumption of the process is 5.664 kWh/kg LH2 , the coefficient of performance is 0.2322, and the exergy efficiency is 52.77%. This research can provide valuable ideas and methods for the improvement of hydrogen liquefaction process design. • A cascaded dual mixed refrigerant hydrogen liquefaction process is put up. • The cascaded process has higher energy efficiency than the non-cascaded process. • The SEC of the process is 5.664 kWh/kg LH2 and the exergy efficiency is 52.77%. • The efficiency of this liquefaction process reaches the highest level currently. [ABSTRACT FROM AUTHOR]

Objective: Leukodystrophies are a diverse group of rare inherited disorders that affect the white matter of the central nervous system with a wide phenotypic spectrum. We aimed to characterize the clinical and genetic features of leukodystrophies in a central‐southern Chinese cohort. Methods: A cohort of 16 Chinese probands with leukodystrophy was recruited and performed genetic analysis by targeted panels or whole‐exome sequencing. Further functional analysis of identified mutations in the colony stimulating factor 1 receptor (CSF1R) gene was explored. Results: A total of eight pathogenic variants (3 novel, 5 documented) were identified in genes including AARS2, ABCD1, CSF1R, and GALC. Common symptoms of leukodystrophy such as cognitive decline, behavioral symptoms, bradykinesia, and spasticity were observed in mutation carriers as well as other rare features (e.g., seizure, dysarthric, and vision impairment). Overexpressing CSF1R mutants p.M875I and p.F971Sfs*7 in vitro showed pronounced cleavage CSF1R and suppressed protein expression, respectively, and reduced transcripts of both mutants were observed. CSF1 treatment revealed deficient and suppressed CSF1R phospho‐activation with the mutants. In contrast to the plasma membrane and endoplasmic reticulum (ER) localized wild‐type CSF1R, M875I mutant showed much less membrane association and greater detainment in the ER, whereas F971Sfs*7 mutation led to aberrant non‐ER localization. Both mutations caused suppressed cell viability, which was partially resulted from deficient/suppressed CSF1R‐ERK signaling. Interpretation: In summary, our findings expand the mutation spectrum of these genes in leukodystrophies. Supported by in vitro validation of the pathogenicity of heterozygous CSF1R mutations, our data also provide insights into the pathogenic mechanisms of CSF1R‐related leukodystrophy. [ABSTRACT FROM AUTHOR]

This study evaluated the effect of Lentinus edodes fermentation (LEF) on digestive enzyme activity, antioxidant capacity and morphology of the liver and intestine in largemouth bass (Micropterus salmoides) fed high plant protein diets (HPPD). LEF was supplemented in HPPD with 0 g kg−1 (LEF0), 10 g kg−1 (LEF1), 20 g kg−1 (LEF2), 30 g kg−1 (LEF3), 40 g kg−1 (LEF4), 50 g kg−1 (LEF5), respectively, and then the six diets were fed to largemouth bass with a body weight of 28.8 ± 0.05 g for eight weeks. Juvenile fish were randomized into 6 groups and each group had 4 replicates with 40 fish. Dietary LEF supplementation alleviated the liver inflammatory reaction of largemouth bass caused by HPPD and improved liver morphology. Goblet cells multiplied and the gut muscle layer thickened after LEF supplementation. The LEF significantly increased amylase activity in the liver and intestine of largemouth bass in individual experimental groups. The LEF could increase the activity of catalase in the liver and intestine of largemouth bass (p < 0.05). The content of malondialdehyde was significantly lower than that in the control group (p < 0.05). Dietary LEF supplementation had no significant effect on the intestinal flora of largemouth bass. These findings imply that LEF supplementation can reduce liver inflammation, enhance intestinal tissue morphology, and eventually benefit largemouth bass health. [ABSTRACT FROM AUTHOR]

Although the advantage of spike timing-based over rate-based network computation has been recognized, the underlying mechanism remains unclear. Using Tempotron and Perceptron as elementary neural models, we examined the intrinsic difference between spike timing-based and rate-based computations. For more direct comparison, we modified Tempotron computation into rate-based computation with the retention of some temporal information. Previous studies have shown that spike timing-based computation are computationally more powerful than rate-based computation in terms of the number of computational units required and the capability in classifying random patterns. Our study showed that spike timing-based and rate-based Tempotron computations provided similar capability in classifying random spike patterns, as well as in text sentiment classification and spam text detection. However, spike timing-based computation is superior in performing a task involving discriminating forward vs. reverse sequence of events, i.e., information mainly temporal in nature. Further studies revealed that this superiority required the asymmetry in the profile of the postsynaptic potential (PSP), and that temporal sequence information was converted to biased spatial distribution of synaptic weight modifications during learning. Thus, the intrinsic PSP asymmetry is a mechanistic basis for the high efficiency of spike timing-based computation for processing temporal information. [ABSTRACT FROM AUTHOR]

It is of great significance to control the energy, location, topological charge, and other parameters of each beam in three-dimensional space. Thus, optical array is proposed and widely used in processing, communication, microscopy, storage, and other fields. However, the current methods to generate optical array are only effective in specific scenarios. In this work, we present an efficient and general method, which separates iterative calculation and parameter selection by introducing a special mapping space, allowing the generation of optical arrays with arbitrary dimensions, optional parameters, and any energy ratios. This method is compared with traditional methods from both simulation and experiment and is superior in diffraction efficiency, focus amount, and calculation speed. Additionally, a five-dimensional optical array with specially designed parameters is produced to show the versatility for different parameters. It shows advantages in beam shaping and parallelization and will be instrumental for applications in information storage, industrial processing, and three-dimensional imaging. [ABSTRACT FROM AUTHOR]

The internal defect detection of solar cells indifferent production processes currently adopts manual visual verification on the images captured by electroluminescence or photoluminescence system. To improve the efficiency and reliability of the inspection, this article proposes a generic and automatic component-of-interest superposition graph(CISG) method. First, the solar cell inspection region is located by shape-based matching. Second, based on the properties of Fourier transform and singular value decomposition, the frequency components of the testing image are modified adaptively, and then component graphs with different local saliency are generated. According to the normalized marginal gains of energy, these component graphs are combined into a saliency map. Finally, defective regions are extracted from the saliency map using the global threshold technique. By employing various compared approaches to conduct experiments on five datasets from different production processes, the great performance of our presented method is revealed, which also implies this method outperforms the current methods. [ABSTRACT FROM AUTHOR]

This paper studies the problem of recovering the hidden vertex correspondence between two edge-correlated random graphs. We focus on the Gaussian model where the two graphs are complete graphs with correlated Gaussian weights and the Erdős-Rényi model where the two graphs are subsampled from a common parent Erdős-Rényi graph ${\mathcal {G}}(n,p)$. For dense Erdős-Rényi graphs with $p=n^{-o(1)}$ , we prove that there exists a sharp threshold, above which one can correctly match all but a vanishing fraction of vertices and below which correctly matching any positive fraction is impossible, a phenomenon known as the “all-or-nothing” phase transition. Even more strikingly, in the Gaussian setting, above the threshold all vertices can be exactly matched with high probability. In contrast, for sparse Erdős-Rényi graphs with $p=n^{-\Theta (1)}$ , we show that the all-or-nothing phenomenon no longer holds and we determine the thresholds up to a constant factor. Along the way, we also derive the sharp threshold for exact recovery, sharpening the existing results in Erdős-Rényi graphs. The proof of the negative results builds upon a tight characterization of the mutual information based on the truncated second-moment computation and an “area theorem” that relates the mutual information to the integral of the reconstruction error. The positive results follows from a tight analysis of the maximum likelihood estimator that takes into account the cycle structure of the induced permutation on the edges. [ABSTRACT FROM AUTHOR]

The monocrystalline solar cell (MSC) interior is prone to miscellaneous defects that affect energy conversion efficiency and even cause fatal damage to the photovoltaic module. In this study, an automatic defect inspection method for MSC interior is presented. Electroluminescence (EL) imaging technology is utilized to visualize defects inside MSC. Also, accurate cell positioning is the precondition of full inspection, so a sigmoid-Hough-transform-based geometric segmentation (SHTGS) algorithm is designed to extract the complete cell region in the EL image, even though the fuzzy boundaries of the cell contain defects. Furthermore, a self-comparison method (SCM) is proposed to detect defects in the background with nonuniform luminance and complicated texture. The experimental results verify the effectiveness of this method in terms of inspection speed and recognition rate. [ABSTRACT FROM AUTHOR]

Understanding the correlation between cognitive ability and risk preferences is crucial for promoting technological progress and innovation in China. This study aims to investigate this relationship using survey data from the China Family Panel Studies. The results reveal a significant positive correlation between cognitive ability and risk tolerance. These findings have important implications for understanding the relationship between cognitive ability and risk preferences, as well as for informing policy decisions in areas such as financial investments and entrepreneurship incentives. [ABSTRACT FROM AUTHOR]

We study the problem of reconstructing a perfect matching M ∗ hidden in a randomly weighted n × n bipartite graph. The edge set includes every node pair in M ∗ and each of the n (n - 1) node pairs not in M ∗ independently with probability d/n. The weight of each edge e is independently drawn from the distribution P if e ∈ M ∗ and from Q if e ∉ M ∗ . We show that if d B (P , Q) ≤ 1 , where B (P , Q) stands for the Bhattacharyya coefficient, the reconstruction error (average fraction of misclassified edges) of the maximum likelihood estimator of M ∗ converges to 0 as n → ∞ . Conversely, if d B (P , Q) ≥ 1 + ϵ for an arbitrarily small constant ϵ > 0 , the reconstruction error for any estimator is shown to be bounded away from 0 for both the sparse (fixed d) and dense (growing d) regimes, resolving the conjecture in Moharrami et al. (Ann Appl Probab 31(6):2663–2720, 2021. https://doi.org/10.1214/20-AAP1660) and Semerjian et al. (Phys Rev E 102:022304, 2020. https://doi.org/10.1103/PhysRevE.102.022304). Furthermore, in the special case of complete exponentially weighted graph with d = n , P = exp (λ) , and Q = exp (1 / n) , for which the sharp threshold simplifies to λ = 4 , we prove that when λ = 4 - ϵ , the optimal reconstruction error is exp - Θ (1 / ϵ) , confirming the conjectured infinite-order phase transition in Semerjian et al. (2020). [ABSTRACT FROM AUTHOR]

Recently, our proposed speaker extraction model, WASE (learning When to Attend for Speaker Extraction) yielded superior performance over the prior state-of-the-art methods by explicitly modeling onset clue and regarding it as important guidance in speaker extraction tasks. However, it still remains challenging when it comes to the deployments on the resource-constrained devices, where the model must be tiny and fast to perform inference with minimal budget in CPU and memory while keeping the speaker extraction performance. In this work, we utilize model compression techniques to alleviate the problem and propose a lightweight speaker extraction model, TinyWASE, which aims to run on resource-constrained devices. Specifically, we mainly investigate the grouping effects of quantization-aware training and knowledge distillation techniques in the speaker extraction task and propose Distillation-aware Quantization. Experiments on WSJ0-2mix dataset show that our proposed model can achieve comparable performance as the full-precision model while reducing the model size using ultra-low bits (e.g. 3 bits), obtaining 8.97x compression ratio and 2.15 MB model size. We further show that TinyWASE can combine with other model compression techniques, such as parameter sharing, to achieve compression ratio as high as 23.81 with limited performance degradation. Our code is available at https://github.com/aispeech-lab/TinyWASE. [ABSTRACT FROM AUTHOR]

Eggshell color plays important biological roles and attracts the attention of both egg retailers and researchers. However, whether non-coding RNAs are involved in pigment deposition among different eggshell colors remains unknown. In this study, RNA sequencing was used to analyse the uterine gland transcriptome (CircRNA and miRNA) of Changshun chicken blue-shell hens producing four different eggshell color eggs including dark blue PK(DB) and light blue (LB), dark brown and greenish (between blue and pink, DP) and pink (p). We found that miR-192-x, targeting SLC16a7, was expressed in DB, DP, and LB groups compared with the PK group, which indicates that miR-192-x may play a role in the blue eggshell color. KEGG and GO analyses showed that the "metabolic pathways" with targeted genes such BLVRA and HMOX1 were detected in dark and light blue color eggshell chickens, which confirms the different ratios of biliverdin and HO-1 involved in the deposition of blue color. As annotated by connectivity analysis, RASGRF1 and RASGRF2, belonging to the RASGRF family, are involved in the Ras signaling pathway, which plays an important role in cell growth, differentiation, metastasis and apoptosis. Our findings enrich the database of circRNA, miRNAs and genes for chicken uterine tissue, which will be useful in accelerating molecular selection for blue eggshell color layers. [ABSTRACT FROM AUTHOR]

The state-of-the-art (SOTA) crack segmentation methods still face the challenges in low-contrast shallow crack recognition and multi-scene compatibility. Therefore, this paper proposes a solution based on a multi-dimensional structure information fusion-based network (MDSIFNet). This network consists of two branches, one for extracting two-dimensional (2D) spatial feature information and another for acquiring three-dimensional (3D) geometric one. In the former, the designed 2D curve structure constraint module based on prior knowledge combined with a pretrained 2D feature extraction module can reduce learning samples and realize crack segmentation in unseen scenes. In the latter, a one-hot transformation and a 3D geometric structure information extraction module are designed to make the network pay attention to the geometric features of shallow cracks and improve their segmentation accuracy. Finally, a fusion module couples the multi-dimensional structure feature information of these two branches and outputs pixel-wise segmentation results that can be used for crack measurement and quantitative analysis. The experimental results show that the designed model network MDSIFNet performs better than the SOTA methods in terms of performance and visualized results. • A pixel-wise crack segmentation network model for the safety assessment of concrete structures is proposed. • 2D curve structure constraint and 3D geometric structure information extraction modules are designed. • 2D curve structure information can improve the multi-scene compatibility of the network model. • 3D geometric structure features of small receptive fields are beneficial for low-contrast shallow crack recognition. • Experimental results of the network model on three different datasets are analyzed. [ABSTRACT FROM AUTHOR]

Deep learning has great potential on decoding EEG in brain-computer interface. While common deep learning algorithms cannot directly train models with data from multiple individuals because of the inter-individual differences in EEG. Collecting enough data for each subject to satisfy the training of deep learning would result in an increase in training cost. This study proposes a novel transfer learning, EEGNet-based multi-source domain filter for transfer learning (EEGNet-MDFTL), to reduce the amount of training data and improve the performance of BCI. The EEGNet-MDFTL uses bagging ensemble learning to learn domain-invariant features from the multi-source domain and utilizes model loss value to filter the multi-source domain. Compared with baseline methods, the accuracy of the EEGNet-MDFTL reaches 91.96%, higher than two state-of-the-art methods, which demonstrates source domain filter can select similar source domains to improve the accuracy of the model, and remains a high level even when the data amount is reduced to 1/8, proving that ensemble learning learns enough domain invariant features from the multi-source domain to make the model insensitive to data amount. The proposed EEGNet-MDFTL is effective in improving the decoding performance with a small amount of data, which is helpful to save the BCI training cost. [ABSTRACT FROM AUTHOR]

Motivated by applications such as discovering strong ties in social networks and assembling genome subsequences in biology, we study the problem of recovering a hidden 2k-nearest neighbor (NN) graph in an n-vertex complete graph, whose edge weights are independent and distributed according to Pn for edges in the hidden 2k-NN graph and Qn otherwise. The special case of Bernoulli distributions corresponds to a variant of the Watts-Strogatz small-world graph. We focus on two types of asymptotic recovery guarantees as n → ∞ : (1) exact recovery: all edges are classified correctly with probability tending to one; (2) almost exact recovery: the expected number of misclassified edges is o(nk). We show that the maximum likelihood estimator achieves (1) exact recovery for 2 ≤ k ≤ no(1) if lim inf 2αn/log n > 1; (2) almost exact recovery for 1 ≤ k ≤ o (log n/log log n) if lim inf kD(Pn||Qn)/log n > 1, where αn ≜ −2 log ∫ √d Pn d Qn is the Rényi divergence of order 1/2 and D(Pn||Qn) is the Kullback-Leibler divergence. Under mild distributional assumptions, these conditions are shown to be information-theoretically necessary for any algorithm to succeed. A key challenge in the analysis is the enumeration of 2k-NN graphs that differ from the hidden one by a given number of edges. We also analyze several computationally efficient algorithms and provide sufficient conditions under which they achieve exact/almost exact recovery. In particular, we develop a polynomial-time algorithm that attains the threshold for exact recovery under the small-world model. [ABSTRACT FROM AUTHOR]

Holographic beam modulation is widely applied in optical tweezers, hard-brittle material marking, high-density storage, etc. To generate high-fidelity arbitrary 3-dimensional (3D) parallel multifoci inside the material, the spherical aberration compensated automatic differentiation (SACAD) algorithm is presented. All polarization components are included and the spherical aberration compensation is embedded in the physical model. The technique of automatic differentiation is used in the error backpropagation procedure, ensuring efficient parallel computing of pixel-by-pixel gradients. In several simulation tests, the root mean square errors of the generated 3D multifoci distributions are all less than 0.01 and the diffraction efficiencies are all beyond 90%, outperforming the results of the established algorithms. In the experiments, we have verified the advantage of SACAD algorithm in complicated 3D internal marking with spherical aberration compensation. Since the SACAD algorithm can achieve high fidelity and efficiency phase retrieval with a straightforward procedure, it has the potential to become a well-received solution for internal parallel beam modulation. • Comprehensive algorithm for beam modulation with built-in aberration compensation. • Surpassing the GSW algorithm in diffraction efficiency and fidelity. • Compatible with high efficiency parallel computing using automatic differentiation. • High fidelity and low interlayer crosstalk in internal laser direct writing. [ABSTRACT FROM AUTHOR]

We analyze a new spectral graph matching algorithm, GRAph Matching by Pairwise eigen-Alignments (GRAMPA), for recovering the latent vertex correspondence between two unlabeled, edge-correlated weighted graphs. Extending the exact recovery guarantees established in a companion paper for Gaussian weights, in this work, we prove the universality of these guarantees for a general correlated Wigner model. In particular, for two Erdős-Rényi graphs with edge correlation coefficient 1 - σ 2 and average degree at least polylog (n) , we show that GRAMPA exactly recovers the latent vertex correspondence with high probability when σ ≲ 1 / polylog (n) . Moreover, we establish a similar guarantee for a variant of GRAMPA, corresponding to a tighter quadratic programming relaxation of the quadratic assignment problem. Our analysis exploits a resolvent representation of the GRAMPA similarity matrix and local laws for the resolvents of sparse Wigner matrices. [ABSTRACT FROM AUTHOR]

Graph matching aims at finding the vertex correspondence between two unlabeled graphs that maximizes the total edge weight correlation. This amounts to solving a computationally intractable quadratic assignment problem. In this paper, we propose a new spectral method, graph matching by pairwise eigen-alignments (GRAMPA). Departing from prior spectral approaches that only compare top eigenvectors, or eigenvectors of the same order, GRAMPA first constructs a similarity matrix as a weighted sum of outer products between all pairs of eigenvectors of the two graphs, with weights given by a Cauchy kernel applied to the separation of the corresponding eigenvalues, then outputs a matching by a simple rounding procedure. The similarity matrix can also be interpreted as the solution to a regularized quadratic programming relaxation of the quadratic assignment problem. For the Gaussian Wigner model in which two complete graphs on n vertices have Gaussian edge weights with correlation coefficient 1 - σ 2 , we show that GRAMPA exactly recovers the correct vertex correspondence with high probability when σ = O (1 log n) . This matches the state of the art of polynomial-time algorithms and significantly improves over existing spectral methods which require σ to be polynomially small in n. The superiority of GRAMPA is also demonstrated on a variety of synthetic and real datasets, in terms of both statistical accuracy and computational efficiency. Universality results, including similar guarantees for dense and sparse Erdős–Rényi graphs, are deferred to a companion paper. [ABSTRACT FROM AUTHOR]

[Display omitted] • A Si-based microchannel heatsink was used to improve the transient response characteristics of IR emitter. • A 3-D FEM was used to analyze the electrical-thermal and heat transfer behaviors of devices. • The devices performance can be improved when the flow velocity of coolant is larger than 0.5 m/s. Structure design and thermal simulation of MEMS-based thermal infrared (TIR) emitter integrated with Si-based microchannel heatsink (MCHS) were presented for gas sensing application. The MCHS attached on the bottom of TIR emitter was used to transfer heat to coolant for improving the transient response characteristics of TIR emitters. A three-dimensional finite element method was used to analyze the electrical heating and heat transfer behaviors of the TIR emitter with MCHS through COMSOL Multiphysics® platform. The surface temperature distribution and transient response were simulated when different flow velocities of coolant passed through the MCHS, and the influence of the flow velocity on the response characteristics was analyzed. The result shows that the temperature in the Si frame of TIR emitters will be significant reduced when the flow velocity of coolant is larger than 0.5 m/s, which will enable an effective improvement in the response characteristics of MEMS TIR emitters. [ABSTRACT FROM AUTHOR]

Bamboo forest is a unique forest landscape that is mainly composed of herbal plants. It has a stronger capability to increase terrestrial carbon sinks than woody forests in the same environment, thus playing a special role in absorbing atmospheric CO2. Accurate and timely bamboo forest maps are necessary to better understand and quantify their contribution to the carbon and hydrological cycles. Previous studies have reported that the unique phenology pattern of bamboo forests, i.e., the on- and off-year cycle, can be detected with time-series high spatial resolution remote sensing (RS) images. Nevertheless, this information has not yet been applied in large-scale bamboo mapping. In this study, we innovatively incorporate newly designed phenology features reflecting the aforementioned on- and off-year cycles into a typical end-to-end classification workflow, including two features describing growing efficiency during the green-up season and two features describing the difference between annual peak greenness. Additionally, two horizonal morphology features and one tree height feature were employed, simultaneously. An experiment in southeast China was carried out to test the method's performance, in which seven categories were focused. A total of 987 field samples were used for training and validation (70% and 30%, respectively). The results show that combining the time-series features based on spectral bands and vegetation indices and newly designed phenology and morphology patterns can differentiate bamboo forests from other vegetation categories. Based on these features, the classification results exhibit a reasonable spatial distribution and a satisfactory overall accuracy (0.89). The detected bamboo area proportion in 82 counties agrees with the statistics from China's Third National Land Survey, which was produced based on high resolution images from commercial satellites and human interpretation (correlation coefficient = 0.69, and root mean squared error = 5.1%). This study demonstrates that the new scheme incorporating phenology features helps to map bamboo forests accurately while reducing the sample size requirement. [ABSTRACT FROM AUTHOR]

Surgical resection of lesions and closed‐loop suppression are the two main treatment options for patients with refractory epilepsy whose symptoms cannot be managed with medicines. Unfortunately, failures in foci localization and seizure prediction are constraining these treatments. Electrical impedance tomography (EIT), sensitive to impedance changes caused by blood flow or cell swelling, is a potential new way to locate epileptic foci and predict seizures. Animal validation is a necessary research process before EIT can be used in clinical practice, but it is unclear which among the many animal epilepsy models is most suited to this task. The selection of an animal model of epilepsy that is similar to human seizures and can be adapted to EIT is important for the accuracy and reliability of EIT research results. This study provides an overview of the animal models of epilepsy that have been used in research on the use of EIT to locate the foci or predict seizures; discusses the advantages and disadvantages of these models regarding inducement by chemical convulsant and electrical stimulation; and finally proposes optimal animal models of epilepsy to obtain more convincing research results for foci localization and seizure prediction by EIT. The ultimate goal of this study is to facilitate the development of new treatments for patients with refractory epilepsy. This article is categorized under:Neuroscience > Clinical NeurosciencePsychology > Brain Function and Dysfunction [ABSTRACT FROM AUTHOR]

Autologous blood transfusion is an important blood protection measure. Red blood cells have a certain degree of immunogenicity and their surface membrane proteins CD28 and MHC can participate in the immune response and interact with CD8+ T cells. We build a cell model with a transwell system. The binding characteristics of RBCs and CD8+ T cells were observed with a fluorescent confocal microscope. The content of the inflammatory factor TNF-α and IFN-γ produced was analyzed by ELISA. The proliferation characteristics of CD8+ T cells were analyzed by CFSE staining, and the content of CD3+CD8+ T cells was analyzed by flow cytometry. Cell migration and invasion experiments were used to analyze the malignant metastasis ability of liver cancer cells. The expression of vimentin, E-cadherin, and β-catenin was analyzed by Western blot. We establish a liver cancer model in rats and group them for autologous blood transfusion. The content of CD3+CD8+T cells in the blood of each group of rats was analyzed by flow cytometry. Western blot was used to analyze the expression of vimentin, E-cadherin, and β-catenin in the liver tissues of rats in each group. The red blood cells in the autologous reinfusion blood and CD8+ T cells have an obvious combination. The degree of combination of the two is related to the expression of CD28 and MHC. If CD28 and MHC are expressed at the same time, the combination of the two cells will be high, the proliferation of CD8+ T cells will increase, and the expression of inflammatory factors will also increase, while the expression of the three proteins that are positively correlated with the activity of cancer cells will decrease. If only one of CD28 and MHC is normally expressed, the result is contrary to the situation where both membrane proteins are normally expressed. Our project has proved that autologous infusion of red blood cell surface membrane proteins CD28 and MHC combined with CD8+ T cells can promote the proliferation of CD8+ T cells to inhibit the malignant transformation of liver cancer. [ABSTRACT FROM AUTHOR]

The ortho-to-para hydrogen conversion (OPC) is an integral part of the hydrogen liquefaction process. The optimal stages and conversion temperatures of OPC are important to reduce the specific energy consumption (SEC) of the process. However, a limited number of studies directly discuss this aspect of the effect of the OPC stages on the SEC. Therefore, based on an efficient refrigeration liquefaction cycle, this paper analyzes the effect of different OPC stages on the SEC of the efficient refrigeration cycle. Additionally, the impact of different combinations of conversion temperatures for the same OPC stages on the SEC is investigated. Results are obtained using a process model developed in HYSYS V10 and the particle swarm optimization algorithm in MATLAB. The results show the impact of OPC stages on the SEC, and that the increase in the stages of OPC can reduce the SEC, but the reduction tends to be slow. The SEC of the five-stage OPC process decreases by 16.39% compared to the SEC of the one-stage. Furthermore, the reduction of SEC for the process with the same stages of OPC can be achieved by setting the optimal combinations of conversion temperatures, which can reduce the SEC by up to 10.63%. The results of this study demonstrate that optimizing the OPC stages is important to reduce the SEC and will provide valuable information for the design of OPC for hydrogen liquefaction processes. • The SEC decreases with increasing OPC stages, and the SEC for five-stage OPC is 16.39% lower than that for one-stage. • The SEC under the same OPC stage can be reduced up to 10.63% by setting the conversion temperatures appropriately. • The SEC under the same OPC stage is extremely influenced by the temperature of a particular conversion node. [ABSTRACT FROM AUTHOR]

Di (2-ethylhexyl) phthalate (DEHP) and dibutyl phthalate (DBP) are the most widely used plasticizers for agricultural mulching films and one of the most common organic pollutants in black soil. However, little is known about the effect of these two contaminants on nitrification in black soil. This study investigated the changes of 20 mg/kg DEHP and DBP on the diversity of nitrification microbial communities, the abundance of ammonia oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB) related genes, and the activities of key enzymes involved in nitrification. During ammonia oxidation, DEHP and DBP had uncompetitive inhibition of urease, reducing the copy number of amoA gene, and microorganisms (Azoarcus , Streptomyces and Caulobacter) would use inorganic nitrogen as a nitrogen source for physiological growth. During nitrite oxidation, the copy number of nxrA gene also reduced, and the relative abundance of chemoautotrophic nitrifying bacteria (Nitrosomonas and Nitrobacter) decreased. Moreover, the path analysis results showed that DEHP and DBP mainly directly or indirectly affect AOB and NOB through three ways. These results help better understand the ecotoxicological effects of DEHP and DBP on AOB and NOB in black soil. [Display omitted] • DEHP and DBP have a negative competitive impact on the ammonia oxidation. • DEHP and DBP have a greater impact on inorganic nitrogen than enzymes. • Actinobacteria may be affected first and play a major role in microbial functions. [ABSTRACT FROM AUTHOR]

This study presents a self-powered humidity sensor that utilizes the moisture-electric generation effect, with nanostructured silicon serving as the sensing element. The surface area of the silicon nanowires (SiNWs) is significantly increased due to their oriented nanochannel structure, while their superior electrical conductivity enables a strong dependence of the output voltage on humidity. The sensor shows quick response/recovery times (∼0.10 s/∼0.17 s), ultra-high sensitivity, and a broad detection range (3.94 mV/1% for 50–95% RH/1.13 mV/1% for 0–50% RH). Furthermore, a wearable sensor structure is proposed that can distinguish between different respiration styles, recognize different language instructions, and facilitate non-contact human–machine interaction. The elaborate self-powered humidity sensor proposed in our work could as well potentially be exploited for establishing wearable and integrated health monitoring platforms in the future. [Display omitted] • Successfully developed a moisture generation device utilizing silicon nanowires (SiNWs) material which exhibits a significant voltage-current response to changes in humidity. • The SiNWs humidity sensor boasting a broad detection range of approximately 10–95%, high sensitivity of 2.70 mV/1%, and rapid response and recovery times of 0.10 s and 0.17 s, respectively. • The versatile nature of the SiNWs device allows it to be utilized as a self-powered wearable respiratory monitoring system and non-contact human–machine interface. • The silent speech recognition system utilizing the SiNWs device opens up new communication channels for individuals with aphasia. Humidity sensors have been widely applied in health management, including respiration monitoring and non-contact sensing for human–machine interaction. Nevertheless, most existing monitoring systems hinging on moisture-sensitive materials require an additional external power source. In addition, the inferior sensitivity and long response/recovery time of the sensors still hinder their desirable healthcare applications. Here, we developed a self-powered humidity sensor built on the moisture-directly triggered electricity generation (MEG) effect, where silicon nanowire arrays (SiNWs) function as the sensing element, exhibiting an ultrafast response to humidity changes with high-level sensitivity. Humidity gradients induce charge directional transport in SiNWs nanochannels, directly actuating electricity signals generation without any additional power units for sensing. The enlarged surface area, oriented nanochannel structure, and superior electrical conductivity of SiNWs facilitate a robust dependence of the output voltage on humidity, enabling the sensor with quick response/recovery (∼0.10 s/∼0.17 s), ultra-high sensitivity, and broad detection range (3.94 mV/1% for 50–95% RH /1.13 mV/1% for 0–50% RH). Furthermore, we designed a smart respiratory monitoring system that can extract various respiration patterns and distinguish different language commands. We also constructed a non-contact human–machine interface leveraging the SiNWs sensor that can effectively disrupt virus propagation and bacterial infection. The elaborate self-powered humidity sensor proposed in our work could as well potentially be exploited for establishing wearable and integrated health monitoring platforms in the future. [ABSTRACT FROM AUTHOR]

[Display omitted] • La/PDA/DNS32 had superior performance in the removal of P and atrazine. • The La/PDA nanoparticles provided a distinct protective effect for strain DNS32. • La/PDA-induced sorption facilitated atrazine transmembrane transport. • Doping with La increased electrophilic sites and reduced adsorption energy. A novel biobased composite was developed for the removal of phosphate (P) and atrazine from agricultural wastewater. A composite with strong P affinity and good biocompatibility, synthesized from La3+ and polydopamine (PDA), was immobilized onto an atrazine-degrading bacterium Acinetobacter lwoffii DNS32 (La/PDA/DNS32). Following Box-Behnken design optimization, the maximum removal rate of P (500 mg L-1) and atrazine (100 mg L-1) by La/PDA/DNS32 reached 28 % and 100 %, respectively. Density functional theory calculations revealed that La/PDA had more negative adsorption energy (−5.90 eV) than PDA alone and exhibited prominent electrophilic sites. Additionally, La/PDA-induced sorption of atrazine improved transmembrane transport and enhanced expression of degradation-associated genes in strain DNS32. La/PDA nanoparticles surrounding strain DNS32 provided a shielding effect and exhibited desirable biostability, thermal stability, and acid-alkaline resistance under contamination stress. This study demonstrates the promising potential of La/PDA/DNS32 in reducing the P and atrazine pollution caused by agricultural production. [ABSTRACT FROM AUTHOR]

[Display omitted] • The synergism on co-pyrolysis of polyethylene and lignin is promoted by pressure. • Radical mass transfer efficiency is regulated by pressure and raw material ratio. • Pressure helps to inhibit coke by promoting radical transfer and water release. • Aromatics with smaller steric hindrance are easier to alkylate and polycondensate. Ex-situ catalytic co-pyrolysis of plastic and biomass to aromatics has been extensively investigated, simultaneously, aromatization have been reported to be promoted under pressure, but available research did not discuss the combined effect of catalytic co-pyrolysis and pressure on aromatics production. In this work, ex-situ catalytic co-pyrolysis of polyethylene and lignin over HZSM-5 under a series of pressure (0.1–0.8 MPa) in a Py-GC/MS system was investigated. We show that pressurized operation during co-pyrolysis of polyethylene and lignin leads to a large increase in BTEX relative yield while maintaining catalyst stability. A very high BTEX relative yield of 70.94% can be achieved at temperature of 650 °C, pressure of 0.5 MPa, polyethylene to lignin ratio of 1:1, and catalyst to raw material ratio of 4:1. Ratio of two raw materials significantly affects efficiency of hydrogen radicals-mass transfer by regulation of hydrogen radical emission and reception. A peak value of BTEX relative yield of 70.27% was obtained at a polyethylene to lignin ratio of 4:3. Among BTEX, benzene and toluene are more prone to alkylate and polycondensate into highly branched and polycyclic aromatics, due to a lower steric hindrance. Hydrogen radicals-mass transfer has a significant effect on BTEX production, and mass transfer efficiency can be regulated by appropriate pressure and raw materials ratios. Meanwhile, pressurized operation has a dual positive effect on coke inhibition via promoting hydrogen radicals-mass transfer and water release, such that catalyst stability and BTEX production are promoted. This study offers new insight into efficient production of BTEX. [ABSTRACT FROM AUTHOR]

Osteosarcoma is a disease with high mortality of malignant tumors in children and adolescents. CDC42 effector protein 3 (CDC42EP3) has been reported to be associated with human cancer cell progression. This study aimed to investigate the biological function and preliminary molecular mechanism of CDC42EP3 in osteosarcoma. CDC42EP3 expression in osteosarcoma was analyzed by immunohistochemical (IHC) staining. Secondly, the biological effects of CDC42EP3 in osteosarcoma cells was determined by loss/gain-of-function assays in vitro and in vivo. CDC42EP3 expression was higher in osteosarcoma tissue than in noncancerous tissue. The expression of CDC42EP3 was positively correlated with age, pathological stage and grade of patients with osteosarcoma. Furthermore, downregulation of CDC42EP3 suppressed tumor progression by inhibiting proliferation, migration and inducing apoptosis in vivo. Importantly, knockdown of CDC42EP3 reduced the expression of interstitial markers (N-cadherin, Vimentin and Snail) and increased the expression of epithelial markers (E-cadherin). In addition, CDC42EP3 knockdown downregulated PI3K and reduced the phosphorylation levels of AKT and mTOR. The mice xenograft model further confirmed that CDC42EP3 knockdown inhibited osteosarcoma growth in vitro. In summary, these findings highlighted the significance of CDC42EP3 in tumor progression, which implicated CDC42EP3 as a promising candidate molecular target for osteosarcoma therapy. [ABSTRACT FROM AUTHOR]

Increased model complexity and data quantities have raised the computing power requirement for efficient evapotranspiration (ET) estimation. A cloud-based service is presented to encapsulate and publish the ETWatch modeling algorithms as web application programming interfaces (APIs) in a consistent style to provide extensible model calculation service and data storage service in a cloud platform for water managers and stakeholders. The prototype system, named ETWatch Cloud allows users to rapidly and easily set up an ET generation project for any region of interest by invoking APIs directly to produce ET data using a web browser or local integrated development environment. The case study demonstrates that ETWatch Cloud can provide a highly scalable and interoperable ET generation tool for stakeholders from ET community, helping to facilitate the application of remote sensing-based ET algorithms for water management in hydrology sector. • A new high scalability, easy interoperability, cloud-based for ET generation at reginal scale. • Encapsule and publish ETWatch modeling algorithm to web API in a consistent style. • A general solution for the publishing, running and management of modules in the cloud. • Provides stakeholders in the ET community and hydrology sector with an innovative tool. • Generate ET data without additional computing, storage, or algorithm development. [ABSTRACT FROM AUTHOR]

• A field-scale 10 m daily ET estimation model was developed with Sentinel-2 data. • The plant optimization theory was applied to the remote sensing-based ET model. • ET sensitivity towards warming and elevated CO2 concentration was analyzed based on the proposed model. • The remote sensing spatial scale effect on ET models was quantified. Crop evapotranspiration (ET) is an essential part of agricultural water consumption, and robust monitoring of remote sensing (RS)-based ET at the field scale improves agricultural water management against water shortages. In this study, we propose a high-resolution optical RS-driven daily ET estimation framework coupling water vaporization and carbon assimilation based on Sentinel-2 satellite data. To determine if the proposed framework is accurate compared with flux observations, three tower sites are chosen (Guantao and Huailai from the Haihe Basin; Daman from the Heihe Basin), with a total of four years of observations adopted for model validation. The correlation coefficient R ranges from 0.870 to 0.912, and the RMSE ranges from 0.89 to 1.21 mm/day. Sensitivity analyses indicate that ET is most sensitive to air temperature, followed by ambient CO 2 concentration and absorbed shortwave radiation, which provides indications into potential future farming strategies to confront global climate change. Finally, we discuss the scale effects on the proposed model at the field scale. Results from three sites show that for a larger area of interest (AOI) the impact of scales increases. This research provides insights into ET calculations across several spatial scales and application potential in precision agricultural water management. [ABSTRACT FROM AUTHOR]

Global climate change and human activities have resulted in immense changes in the Earth's ecosystem, and the interaction between the land surface and the atmosphere is one of the most important processes. Wind is a reference for studying atmospheric dynamics and climate change, analyzing the wind speed change characteristics in historical periods, and studying the influence of wind on the Earth-atmosphere interaction; additionally, studying the wind, contributes to analyzing and alleviating a series of problems, such as the energy crisis, environmental pollution, and ecological deterioration facing human beings. In this study, data from 697 meteorological stations in China from 2000 to 2019 were used to study the distribution and trend of wind speed over the past two decades. The relationships between wind speed and climate factors were explored using statistical methods; furthermore, combined with terrain, climate change, and human activities, we quantified the contribution of environmental factors to wind speed. The results show that a downward trend was recorded before 2011, but overall, there was an increasing trend that was not significant; moreover, the wind speed changes showed obvious seasonality and were more complicated on the monthly scale. The wind speed trend mainly increased in the western region, decreased in the eastern region, was higher in the northeastern, northwestern, and coastal areas, and was lower in the central area. Temperature, bright sunshine duration, evaporation, and precipitation had a strong influence, in which wind speed showed a significant negative correlation with temperature and precipitation and vice versa for sunshine and evapotranspiration. The influence of environmental factors is diverse, and these results could help to develop environmental management strategies across ecologically fragile areas and improve the design of wind power plants to make better use of wind energy. [ABSTRACT FROM AUTHOR]

In this work, Caenorhabditis elegans was employed as an in vivo model to determine the toxic effects of atrazine at different concentrations. After the exposure period from the larval stage L1 to adulthood day 1, atrazine (10 mg/L) significantly decreased the body length and lifespan of nematodes. In addition, exposure to ≥0.01 mg/L atrazine remarkably increased the intestinal reactive oxygen species (ROS) levels and reduced locomotion behavior of nematodes, while exposure to ≥ 1 mg/L atrazine decreased the brood size of nematodes. Moreover, atrazine (0.001–0.1 mg/L) upregulated the expression levels of hsp-6::GFP and hsp-6 / 60 in nematodes, indicating the activation of mitochondrial unfolded protein response (mtUPR). On the contrary, atrazine (1–10 mg/L) downregulated the expression levels of hsp-6::GFP and hsp-6 / 60 in nematodes. Furthermore, mtUPR induction governed by the RNAi knockdown of atfs-1 could increase the vulnerability of nematodes against atrazine toxicity. Overall, our findings highlighted the dynamic responses of nematodes toward different concentrations of atrazine, which could be monitored using different sublethal endpoints as bioindicators. [Display omitted] • Dynamic response to atrazine could be monitored by different sublethal endpoints. • mt UPR was very sensitive to atrazine exposure. • mt UPR could provide a protective response to atrazine. [ABSTRACT FROM AUTHOR]