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This paper proposes a representational model for image pairs such as consecutive video frames that are related by local pixel displacements, in the hope that the model may shed light on motion perception in primary visual cortex (V1). The model couples the following two components: (1) the vector representations of local contents of images and (2) the matrix representations of local pixel displacements caused by the relative motions between the agent and the objects in the 3D scene. When the image frame undergoes changes due to local pixel displacements, the vectors are multiplied by the matrices that represent the local displacements. Thus the vector representation is equivariant as it varies according to the local displacements. Our experiments show that our model can learn Gabor-like filter pairs of quadrature phases. The profiles of the learned filters match those of simple cells in Macaque V1. Moreover, we demonstrate that the model can learn to infer local motions in either a supervised or unsupervised manner. With such a simple model, we achieve competitive results on optical flow estimation.

Neodymium naphthenate-loaded organic phase stripping using sodium oxalate solution was studied to explore the feasibility of synchronous rare earth-loaded organic phase stripping, rare earth precipitation, and blank organic phase saponification. Experimental results show that loaded organic phase stripping, rare earth precipitation, and blank organic phase saponification can be realized simultaneously. When using 20% excess of sodium oxalate over the stoichiometry with the volume ratio of organic phase to aqueous phase of 1:1 at 25 °C for 40 min, the single stage stripping rate and saponification value are about 40% and 0.29 mol/L, respectively. After 16 stages of countercurrent continuous stripping, the stripping rate of neodymium can reach 99%, the saponification value is 0.42 mol/L, the Nd3+ concentration in saponified organic phase is less than 0.0020 mol/L, and the main phase in precipitation is Nd2(C2O4)3∙10H2O. Afterwards, this saponified organic phase can be used in the extraction of NdCl3 solution, and then the loaded organic phases (neodymium naphthenate) with 0.16 mol/L Nd3+ can be retrieved. The morphology, particle size distribution, and composition of the Nd2(C2O4)3∙10H2O products are similar to those of the current direct precipitation products. The neodymium oxide prepared by continuous calcination of neodymium oxalate meets the national standard of China (GB/T 5240−2015). These results prove the feasibility of stripping neodymium naphthenate-loaded organic phase by using sodium oxalate solution. Sodium oxalate can serve as a stripping agent, a saponifier, and a precipitator, thereby simplifying rare earth extraction and separation. This study provides theoretical and technical support for the development of a novel method for rare earth extraction and separation.

Background: As a vital amino acid in the human body, tyrosine is indispensable in various biological processes, and therefore its accurate and simple determination is of crucial importance. In this work, a facile approach was developed to construct a molecularly imprinted sensor for tyrosine via co-electrodeposition of chitosan, β-cyclodextrin and tyrosine on the surface of indium tin oxide that was pre-coated with multi-walled carbon nanotubes (MWNTs). Methods: Benefitting from the excellent film-forming ability and the rich functional groups to form a hydrogen bond with target molecules, chitosan was utilized to form a recognition matrix. MWNTs and β-cyclodextrin were then introduced to enhance the selectivity and sensitivity to tyrosine, due to the subtle electronic, catalytic properties and possible π-π interaction of MWNTs with tyrosine, as well as recognition ability of β-cyclodextrin. The morphology of the imprinted films was characterized by a scanning electron microscope. The electrochemistry and tyrosine sensing performance were investigated in detail by cyclic voltammetry and chronoamperometry. Results: Amperometry results showed that the imprinted sensor exhibited a linear range of 1.0×10−6 to 1.0×10−4 M and 1.0×10−4 to 1.0×10−3 M for tyrosine determination, with a detection limit of 6.0 × 10−7 M (S/N=3). Moreover, a satisfactory recovery in the range of 99.0% to 105.1% was obtained with the application of the imprinted sensor in artificial urine samples analysis. Conclusion: The imprinted electrode is reusable with satisfactory reproducibility and stability in tyrosine determination.

Background: Anti-PD-(L)1 antibody monotherapy or in combination with VEGF(R) blockade has been applied widely for cancer treatment. Whether combination therapy increases irAEs still remains controversial.Methods: A systematic review and meta-analysis comparing PD-(L)1 and VEGF(R) blockade combination therapy with PD-(L)1 inhibitors alone was performed. Phase II or III randomized clinical trials reporting irAEs or trAEs were included. The protocol was registered with PROSPERO, CRD42021287603.Results: Overall, 77 articles were included in the meta-analysis. A total of 31 studies involving 8,638 participants were pooled and an incidence for PD-(L)1 inhibitor monotherapy with any grade and grade ≥3 irAEs of 0.25 (0.20, 0.32) and 0.06 (0.05, 0.07), respectively, were reported. Two studies with 863 participants pooled for PD-(L)1 and VEGF(R) blockade showed that an incidence of any grade and grade ≥3 irAEs were 0.47 (0.30, 0.65) and 0.11 (0.08, 0.16), respectively. Regarding pairwise comparisons for irAEs, only one study was included, indicating no significant difference between the two regimens in terms of colitis, hyperthyroidism, and hypothyroidism for any grade and grade ≥3, while there was a trend of higher incidence for any grade hyperthyroidism under the combination therapy. The incidence of reactive cutaneous capillary endothelial proliferation (RCCEP) was as high as 0.80 under camrelizumab monotherapy.Conclusion: Total incidences of any grade and grade ≥3 irAEs were higher in the combination treatment group. Direct comparisons indicated no significant difference between the two regimens for any grade and grade ≥3 specific irAEs. RCCEP and thyroid disorders need to be paid attention to clinically. Moreover, trials with direct comparisons are needed and the safety profiles of the two regimens should be further explored. Exploration of the mechanism of action and regulatory management of adverse events should be enhanced.Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=287603, identifier CRD42021287603

Background: The optimal body mass index (BMI) for cardiovascular disease (CVD) prevention in older adults remains uncertain. We aimed to evaluate the relationship between BMI and CVD mortality and identify the nadirs for CVD mortality in older (≥65 years) and younger ( Methods: We used data from the 1997 to 2018 National Health Interview Survey, linked to the National Death Index (NDI). We included adults aged 18 years and older with BMI and NDI follow-up data available. We used Cox regression to estimate hazard ratios (HRs) and 95% confidence intervals (CI) for the association between BMI and CVD mortality. Fully adjusted models were stratified by age and controlled for baseline age, sex, race, income, education, marital status, diabetes, cancer, general health, physical activity, smoking, and alcohol status. Results: Among 490,037 adults, the mean(±SD) age was 47(18) years; 55% were female. During a median follow-up period of 11 years, 19,194 CVD deaths occurred. The associations between BMI and CVD mortality were J-shaped in adults aged ≥ 65 years and < 65 years. The CVD mortality was minimized at a BMI of 26 kg/m 2 in adults aged ≥ 65 years and 22 kg/m 2 in those aged < 65 years. In adults aged ≥ 65 years, being overweight was associated with a lower risk of CVD mortality (HR 0.93, [95% CI, 0.89-0.96]); having level I obesity (0.90 [0.94-1.05]) and level II obesity (1.06 [0.97-1.16]) did not increase the risk of CVD mortality; and level III obesity was associated with increased risk of CVD mortality in comparison with individuals who had a normal BMI ( Figure ). In individuals aged < 65 years, being overweight, level I, II, and III obesity were associated with a progressively higher risk of CVD mortality. Conclusion: Overweight and level I obesity seem to be protective against CVD mortality in older adults. This obesity paradox suggests that the optimal BMI might be sensitive to age. Thus, weight management should be individualized.

BackgroundVocational education is an important part of high school education in China. However, there is little research on high school students' mental health. This study aimed to investigate the prevalence of suicidal behavior (SB) among this population and the mediating role of insomnia, depression, anxiety, and stress in the relationship between Internet addiction (IA) and SB using a structural equation model.MethodsA cross-sectional questionnaire survey was conducted among several vocational high school students in Hunan Province, and 7,968 valid questionnaires were obtained. General demographic data and data from the Dual-Mode Self-Control Scale, Athens Insomnia Scale, Depression Anxiety Stress scale-21, and Revised Chen Internet Addiction Scale were collected. A structural equation model was used to explore the different pathways from IA to SB.ResultsAmong the participants, 37.7, 15.7, and 21.8% reported suicidal ideation, plans, and attempts, respectively. The structural equation model confirmed that IA was indirectly related to SB and was mediated by insomnia and/or depression, anxiety, and stress.LimitationsFirst, we only recruited students from vocational schools in Hunan Province, therefore, the sample may not represent the entire population of vocational students in China. Second, self-report scales were used in this study, and clinical diagnosis required professional interviews. Third, since this study had a cross-sectional design, the causal relationship between the variables could not be determined.ConclusionsThe prevalence of SB among vocational high school students in China was significantly high. The prevention of SB related to IA can be attributed to the improvement of insomnia and emotional problems.

Supplementary Material 1

Despite the extensive studies of topological systems, the experimental characterizations of strongly nonlinear topological phases have been lagging. To address this shortcoming, we design and build elliptically geared isostatic metamaterials. Their nonlinear topological transitions can be realized by collective soliton motions, which stem from the transition of nonlinear Berry phase. Endowed by the intrinsic nonlinear topological mechanics, surface polar elasticity and dislocation-bound zero modes can be created or annihilated as the topological polarization reverses orientation. Our approach integrates topological physics with strongly nonlinear mechanics and promises multi-phase structures at the micro and macro scales., Comment: Accepted by Physical Review Letters, 5+19 pages, 4+20 figures

Supplementary Material 1

This paper studies the fundamental problem of learning multi-layer generator models. The multi-layer generator model builds multiple layers of latent variables as a prior model on top of the generator, which benefits learning complex data distribution and hierarchical representations. However, such a prior model usually focuses on modeling inter-layer relations between latent variables by assuming non-informative (conditional) Gaussian distributions, which can be limited in model expressivity. To tackle this issue and learn more expressive prior models, we propose an energy-based model (EBM) on the joint latent space over all layers of latent variables with the multi-layer generator as its backbone. Such joint latent space EBM prior model captures the intra-layer contextual relations at each layer through layer-wise energy terms, and latent variables across different layers are jointly corrected. We develop a joint training scheme via maximum likelihood estimation (MLE), which involves Markov Chain Monte Carlo (MCMC) sampling for both prior and posterior distributions of the latent variables from different layers. To ensure efficient inference and learning, we further propose a variational training scheme where an inference model is used to amortize the costly posterior MCMC sampling. Our experiments demonstrate that the learned model can be expressive in generating high-quality images and capturing hierarchical features for better outlier detection.

It is broadly known that deep neural networks are susceptible to being fooled by adversarial examples with perturbations imperceptible by humans. Various defenses have been proposed to improve adversarial robustness, among which adversarial training methods are most effective. However, most of these methods treat the training samples independently and demand a tremendous amount of samples to train a robust network, while ignoring the latent structural information among these samples. In this work, we propose a novel Local Structure Preserving (LSP) regularization, which aims to preserve the local structure of the input space in the learned embedding space. In this manner, the attacking effect of adversarial samples lying in the vicinity of clean samples can be alleviated. We show strong empirical evidence that with or without adversarial training, our method consistently improves the performance of adversarial robustness on several image classification datasets compared to the baselines and some state-of-the-art approaches, thus providing promising direction for future research., Comment: 13 pages, 4 figures

Additional file 1: Supplementary Table S1. Mutation types of 506 patients by Sanger sequencing.

We study quantum phase transitions in Bose-Fermi mixtures driven by inter-species interaction in the quantum Hall regime. In the absence of such interaction, the bosons and fermions form their respective fractional quantum Hall (FQH) states at certain filling factors. A symmetry-protected topological (SPT) state is identified as the ground state for strong inter-species interaction. The phase transitions between them are proposed to be described by Chern-Simons-Higgs field theories. For a simple microscopic Hamiltonian, we present numerical evidence for the existence of the SPT state and a continuous transition to the FQH state. It is also found that the entanglement entropy between the bosons and fermions exhibits scaling behavior in the vicinity of this transition., Comment: 9 pages, 5 figures

Additional file 3: Supplementary Figure S1. Examination images of case 2. (A) CT revealed an irregular mass sized 18.5×7.3×28.2 cm located in the left abdominal cavity. The margins of the lesion could not be clearly discriminated from the stomach and intestinal walls (red arrow). (B) The tumor showed an epithelioid growth pattern by H&E staining (200×). (C) The tumor cells showed a positive cytoplasmic signal for CD117 (200×). (D) The tumor cells showed a positive cytoplasmic signal for DOG1 (200×). (E) The tumor cells showed a negative cytoplasmic signal for SMA (200×). (F) ALK IHC showed positive strong and diffuse staining by the 1A4 clone (200×). (G) ALK IHC showed positive strong and diffuse staining by the D5F3 clone (200×). (H) A break-apart fluorescent in situ hybridization (FISH) assay did not reveal ALK rearrangement (1000×). Supplementary Figure 2. Examination images of case 3. (A) Preoperative CT showed a mixed slightly low-density mass of approximately 15.7×7.6 cm in the right-middle abdomen. Contrast-enhanced scanning showed uneven enhancement, with multiple areas of unenhanced necrosis (red arrow). (B) The tumor demonstrated epithelioid and spindle growth by H&E staining (200×). (C) The tumor cells showed a positive cytoplasmic signal for CD117 (200×). (D) The tumor cells showed a positive cytoplasmic signal for DOG1 (200×). (E) The tumor cells showed a negative cytoplasmic signal for SMA (200×). (F) ALK IHC showed strong positive staining by the 1A4 clone (200×). (G) ALK IHC showed strong positive staining by the D5F3 clone (200×). (H) A break-apart fluorescent in situ hybridization (FISH) assay did not identify ALK rearrangement, but some tumor cells were identified as having a copy number >2 (1000×). Supplementary Figure 3. The examination images of case 4. (A) Examination CT showed uneven enhanced density shadows in the pelvic cavity, right rectus abdominus region and deep right abdominal wall, the maximum size of which was 11.0 cm×6.7 cm (red arrow). (B) The tumor demonstrated a spindle growth pattern stained by H&E staining (200×). (C) The tumor cells showed a positive cytoplasmic signal for CD117 (200×). (D) The tumor cells showed a positive cytoplasmic signal for DOG1 (200×). (E) The tumor cells showed a positive cytoplasmic signal for SMA (200×). (F) ALK IHC showed positive staining by the 1A4 clone (200×). (G) ALK IHC showed strong positive staining by the D5F3 clone (200×). (H) A break-apart fluorescent in situ hybridization (FISH) assay did not reveal ALK rearrangement (1000×). Supplementary Figure 4. PAGE electrophoresis results of RT-PCR products of two available pairwise tissues. Lane 1-4 and 5-8 show the electrophoresis results of case 1 and case 3. Lane M, DNA marker; Lane 1/5, PCR amplification product obtained with ALK gene primers from normal tissues; Lane 2/6, PCR amplification product obtained with ALK gene primers from tumor tissues; Lane 3/7, PCR amplification product obtained with GAPDH gene primers from normal tissues; Lane 4/8, PCR amplification product obtained with GAPDH gene primers from tumor tissues.

Additional file 2: Supplementary Table S2. Demographic and clinicopathological features of ALK-positive group and ALK-negative group.

Supplemental Material for The Effect of Surgery on the Prognosis of Gastric Lymphoma: A Meta-analysis by Min Shi, Yao Yao, Haifeng Ding, Jian Yang, Cong Zhang, Ying Wu, and Tao Guo in The American Surgeon™.

Supplemental material, sj-pdf-1-jcb-10.1177_0271678X231165842 for The relationship between cytochrome c oxidase, CBF and CMRO2 in mouse cortex: A NIRS-MRI study by Mada Hashem, Ying Wu and Jeff F Dunn in Journal of Cerebral Blood Flow & Metabolism

Additional file 1: Table S1. Demographic data for the enrolled cohorts. Table S2. In-silico pathogenicity predictions for rare variants in SPTLC1 and SPTLC2. Table S3. Enrichment analysis of rare variants in SPTLC1 and SPTLC2 in amyotrophic lateral sclerosis.

Supplemental material, sj-pdf-1-jcb-10.1177_0271678X231165842 for The relationship between cytochrome c oxidase, CBF and CMRO2 in mouse cortex: A NIRS-MRI study by Mada Hashem, Ying Wu and Jeff F Dunn in Journal of Cerebral Blood Flow & Metabolism

Generation of molecules with desired chemical and biological properties such as high drug-likeness, high binding affinity to target proteins, is critical for drug discovery. In this paper, we propose a probabilistic generative model to capture the joint distribution of molecules and their properties. Our model assumes an energy-based model (EBM) in the latent space. Conditional on the latent vector, the molecule and its properties are modeled by a molecule generation model and a property regression model respectively. To search for molecules with desired properties, we propose a sampling with gradual distribution shifting (SGDS) algorithm, so that after learning the model initially on the training data of existing molecules and their properties, the proposed algorithm gradually shifts the model distribution towards the region supported by molecules with desired values of properties. Our experiments show that our method achieves very strong performances on various molecule design tasks.

Simulation-to-real is the task of training and developing machine learning models and deploying them in real settings with minimal additional training. This approach is becoming increasingly popular in fields such as robotics. However, there is often a gap between the simulated environment and the real world, and machine learning models trained in simulation may not perform as well in the real world. We propose a framework that utilizes a message-passing pipeline to minimize the information gap between simulation and reality. The message-passing pipeline is comprised of three modules: scene understanding, robot planning, and performance validation. First, the scene understanding module aims to match the scene layout between the real environment set-up and its digital twin. Then, the robot planning module solves a robotic task through trial and error in the simulation. Finally, the performance validation module varies the planning results by constantly checking the status difference of the robot and object status between the real set-up and the simulation. In the experiment, we perform a case study that requires a robot to make a cup of coffee. Results show that the robot is able to complete the task under our framework successfully. The robot follows the steps programmed into its system and utilizes its actuators to interact with the coffee machine and other tools required for the task. The results of this case study demonstrate the potential benefits of our method that drive robots for tasks that require precision and efficiency. Further research in this area could lead to the development of even more versatile and adaptable robots, opening up new possibilities for automation in various industries., Comment: Published as a conference paper at FTC 2023

The capability to generate responses with diversity and faithfulness using factual knowledge is paramount for creating a human-like, trustworthy dialogue system. Common strategies either adopt a two-step paradigm, which optimizes knowledge selection and response generation separately, and may overlook the inherent correlation between these two tasks, or leverage conditional variational method to jointly optimize knowledge selection and response generation by employing an inference network. In this paper, we present an end-to-end learning framework, termed Sequential Posterior Inference (SPI), capable of selecting knowledge and generating dialogues by approximately sampling from the posterior distribution. Unlike other methods, SPI does not require the inference network or assume a simple geometry of the posterior distribution. This straightforward and intuitive inference procedure of SPI directly queries the response generation model, allowing for accurate knowledge selection and generation of faithful responses. In addition to modeling contributions, our experimental results on two common dialogue datasets (Wizard of Wikipedia and Holl-E) demonstrate that SPI outperforms previous strong baselines according to both automatic and human evaluation metrics.

Large language models (LLMs) have achieved remarkable progress in solving various natural language processing tasks due to emergent reasoning abilities. However, LLMs have inherent limitations as they are incapable of accessing up-to-date information (stored on the Web or in task-specific knowledge bases), using external tools, and performing precise mathematical and logical reasoning. In this paper, we present Chameleon, an AI system that mitigates these limitations by augmenting LLMs with plug-and-play modules for compositional reasoning. Chameleon synthesizes programs by composing various tools (e.g., LLMs, off-the-shelf vision models, web search engines, Python functions, and heuristic-based modules) for accomplishing complex reasoning tasks. At the heart of Chameleon is an LLM-based planner that assembles a sequence of tools to execute to generate the final response. We showcase the effectiveness of Chameleon on two multi-modal knowledge-intensive reasoning tasks: ScienceQA and TabMWP. Chameleon, powered by GPT-4, achieves an 86.54% overall accuracy on ScienceQA, improving the best published few-shot result by 11.37%. On TabMWP, GPT-4-powered Chameleon improves the accuracy by 17.0%, lifting the state of the art to 98.78%. Our analysis also shows that the GPT-4-powered planner exhibits more consistent and rational tool selection via inferring potential constraints from instructions, compared to a ChatGPT-powered planner., Comment: 31 pages, 9 figures. Project page: https://chameleon-llm.github.io

Displacement damage effects on the Charge-Coupled Device (CCD) induced by neutrons at back-streaming white neutron (Back-n) in the China spallation neutron source (CSNS) are analyzed according to the online irradiation experiment. The hot pixels, random telegraph signal (RTS), mean dark signal, dark current, and dark signal non-uniformity (DSNU) induced by Back-n are presented. The dark current is calculated according to the mean dark signal at various integration times. The single-particle displacement damage and transient response are also observed based on the online measuring data. The trends of hot pixels, mean dark signal, DSNU, and RTS degradation were related to integration times and irradiation fluence. The mean dark signal, dark current, and DSNU2 are nearly linear with neutron irradiation fluence when nearly most of the pixels are not reach saturation. In addition, the mechanisms of the displacement damage effects on the CCD are demonstrated by combining the experimental results and TCAD simulation. Radiation-induced traps in the space charge region of CCD will act as generation/recombination (G/R) centers of electro-hole pairs which lead to the dark signal increase.

Motivated by the experiments on double monolayer graphene that observe a variety of fractional quantum Hall states [Liu et al., Nat. Phys. 15, 893 (2019); Li et al., Nat. Phys. 15, 898 (2019)], we study the special setting in which two monolayers have different areas. It has not been considered before and allows us to construct a class of exotic topological states. The elementary excitations of these states do not carry fractional charges but obey fractional statistics. This is in sharp contrast to all previously studied cases, where the two properties are intimately connected and serve as hallmarks of fractional quantum Hall states. Numerical calculations are performed to demonstrate that some states can be realized with realistic parameters.

9 pages, 1 tables, 1 figure.-- This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY), The anthropogenic introduction of significant amounts of reactive nitrogen in the coastal zone particularly since the discovery and application of the Haber-Bosch process has profound consequences over organic carbon storage and transformations at both regional and global scales. Here, we review our current knowledge on cause-effect chains for nitrogen, especially dissolved inorganic nitrogen, on organic carbon cycling in coastal tropical systems. We focus on the feedback mechanisms for turnover of different organic carbon species to nitrogen excess and links to current environmental and climate changes. We pay special attention to organic carbon dynamics in tropical coasts due to their high primary productivity, rapid sedimentation, and significant needs of nitrogen for agriculture and industry usages. Together with land-use changes and economy development, we highlight the vulnerability of carbon storage in tropical coasts triggered by nitrogen overloading and outline possible industrial strategies with low carbon cycling disturbance to benefit the development of tropical countries, This work is supported by the National Natural Science Foundation of China (Nos. 42090043 and 41876074)

Stimulus set of normed animal pictures

BACKGROUND The management of severe extravasation injuries is still controversial. Extravasation injuries can be treated in many ways. AIM To present a series of patients with severe extravasation injuries due to infusion who were managed with ethacridine lactate dressing combined with localized closure and phototherapy. METHODS In this study, we evaluated the data of eight patients, including six from the Department of Burn, one (with colorectal carcinoma) from the Veteran Cadre Department, and one (with leukemia) from the Hematology Department. Of these, three patients were male and five were female. Age of the patients ranged from 10 mo to 72 years, including two children (10 and 19 mo of age). In this study, the infusion was stopped immediately when the extravasation was identified. The extravasation event was managed routinely using a blocking solution. A ring-shaped localized closure was performed using the blocking agents. Moreover, ethacridine lactate dressing and phototherapy were applied for 3-5 d. RESULTS In this study, the drugs contained in the infusates were iodixanol, norepinephrine, alprostadil, amino acids, fat emulsion, cefoselis, cefoxitin, and potassium chloride + concentrated sodium chloride. All of the patients achieved complete healing after treatment and no obvious adverse reactions were observed. CONCLUSION The treatment of severe extravasation injuries using a combination of localized closure, ethacridine lactate dressing, and phototherapy resulted in satisfactory outcomes in patients.

In China, a shift in early math teaching from a teacher-directed approach to a child-centered approach has been recommended. This study explored Chinese teachers’ beliefs about early math teaching ...

This paper studies the unsupervised cross-domain translation problem by proposing a generative framework, in which the probability distribution of each domain is represented by a generative cooperative network that consists of an energy-based model and a latent variable model. The use of generative cooperative network enables maximum likelihood learning of the domain model by MCMC teaching, where the energy-based model seeks to fit the data distribution of domain and distills its knowledge to the latent variable model via MCMC. Specifically, in the MCMC teaching process, the latent variable model parameterized by an encoder-decoder maps examples from the source domain to the target domain, while the energy-based model further refines the mapped results by Langevin revision such that the revised results match to the examples in the target domain in terms of the statistical properties, which are defined by the learned energy function. For the purpose of building up a correspondence between two unpaired domains, the proposed framework simultaneously learns a pair of cooperative networks with cycle consistency, accounting for a two-way translation between two domains, by alternating MCMC teaching. Experiments show that the proposed framework is useful for unsupervised image-to-image translation and unpaired image sequence translation., Comment: The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI) 2021

The culinary-medicinal mushroom Grifola frondosa is widely cultivated in East Asia. In this study, the complete mitochondrial genome of G. frondosa was determined using Illumina sequencing. The circular molecule was 197,486 bp in length with a content of 25.01% GC, which was one of the largest mitochondrial genomes in the order Polyporales. A total of 39 known genes encoding 13 common mitochondrial genes, 24 tRNA genes, 1 ribosomal protein s3 gene (rps3), and 1 DNA polymerase gene (dpo) were predicted in this genome. The phylogenetic analysis showed that G. frondosa clustered together with Sparassis crispa, Laetiporus sulphureus, Wolfiporia cocos, and Taiwanofungus camphoratus. The complete mitochondrial genome reported here may provide new insight into genetic information and evolution for further studies.

ObjectiveThis study aimed to investigate white matter (WM) microstructural alterations and their relationship correlation with disease severity in anti-NMDA receptor (NMDAR) encephalitis. Multivariate pattern analysis (MVPA) was applied to discriminate between patients and healthy controls and explore potential imaging biomarkers.MethodsThirty-two patients with anti-NMDAR encephalitis and 26 matched healthy controls underwent diffusion tensor imaging. Tract-based spatial statistics and atlas-based analysis were used to determine WM microstructural alterations between the two groups. MVPA, based on a machine-learning algorithm, was applied to classify patients and healthy controls.ResultsPatients exhibited significantly reduced fractional anisotropy in the corpus callosum, fornix, cingulum, anterior limb of the internal capsule, and corona radiata. Moreover, mean diffusivity was increased in the anterior corona radiata and body of the corpus callosum. On the other hand, radial diffusivity was increased in the anterior limb of the internal capsule, cingulum, corpus callosum, corona radiata, and fornix. WM changes in the cingulum, fornix, and retrolenticular part of the internal capsule were correlated with disease severity. The accuracy, sensitivity, and specificity of fractional anisotropy-based classification were each 78.33%, while they were 67.71, 65.83, and 70% for radial diffusivity.ConclusionWidespread WM lesions were detected in anti-NMDAR encephalitis. The correlation between WM abnormalities and disease severity suggests that these alterations may serve a key role in the pathophysiological mechanisms of anti-NMDAR encephalitis. The combination of tract-based spatial statistics and MVPA may provide more specific and complementary information at the group and individual levels.

Cold seeps globally host dense unique oasis-type ecosystems, mainly fuelled by chemosynthetic microorganisms via reduced gases such as methane and hydrogen sulfide. However, the origin and pathway of nitrogen chemosynthesis in this widely distributed symbiont ecosystem remain poorly understood. Here, we explore biomarker methods (bulk stable isotope, amino acid (AA), fatty acid (FA) and compound-specific isotope analyses in gill tissues of mussels) to demonstrate the relative contributions of inorganic and organic nitrogen to symbiotic mussels at cold seeps in the South China Sea and their impact on the synthesis and metabolism of amino acids. Gigantidas platifrons (G. platifrons) symbioses with type II methanotrophs via the Serine pathway, and Bathymodiolus aduloides (B. aduloides) thrives with sulfur-oxidizing bacteria via the Calvin pathway, as revealed by bulk δ13C and δ13C of FAs. Based on the δ15N values in gill tissues of mussels, organic nitrogen from sediment is estimated as the dominant nitrogen source for B. aduloides (97-98%), in contrast, NH4+ was the main nitrogen source for G. platifrons. Different dominant nitrogen sources result in the δ15N of AAs in the gills of two mussel species having opposite trends, which might be related to synthesis and metabolism of AAs in symbiotic bacteria and host, respectively. Our findings reveal that the mechanism of nitrogen acquisition in cold seep systems is plastic and related to DIN sources/uptake and changing environmental conditions. These findings uncover novel biosynthesis of nitrogen in the deep sea, typically at cold seeps, and may have important implications for nitrogen biogeochemistry and deep-sea conservation.

Perovskite CsPbBr3 semiconductors exhibit unusually high defect tolerance leading to outstanding and unique optoelectronic properties, demonstrating strong potential for γ-radiation and X-ray detection at room temperature. However, the total dose effects of the perovskite CsPbBr3 must be considered when working in a long-term radiation environment. In this work, the Schottky type of perovskite CsPbBr3 detector was fabricated. Their electrical characteristics and γ-ray response were investigated before and after 60Co γ ray irradiation with 100 and 200 krad (Si) doses. The γ-ray response of the Schottky-type planar CsPbBr3 detector degrades significantly with the increase in total dose. At the total dose of 200 krad(Si), the spectral resolving ability to γ-ray response of the CsPbBr3 detector has disappeared. However, with annealing at room temperature for one week, the device’s performance was partially recovered. Therefore, these results indicate that the total dose effects strongly influence the detector performance of the perovskite CsPbBr3 semiconductor. Notably, it is concluded that the radiation-induced defects are not permanent, which could be mitigated even at room temperature. We believe this work could guide the development of perovskite detectors, especially under harsh radiation conditions.

Phytoplankton blooms, including the diatom-to-dinoflagellate succession in coastal regions, are frequently observed by researchers through incubation experiments, albeit mainly in nutrient-enrichment conditions. This study, complementary to such previous experiments, aims at the dynamics of nutrients and organic matter during the natural community shift in a nutrient-constraint condition. A nutrient-constraint incubation experiment is conducted herein to investigate nutrient dynamics during a diatom-to-dinoflagellate succession and evaluate its effects on carbon cycling. The incubation successfully induced a transition from a diatom bloom dominated by Skeletonema costatum to a dinoflagellate bloom dominated by Prorocentrum donghaiense. Results showed that the DIP limitation triggers the succession. This experiment provides an excellent opportunity to examine how senescent bloom under nutrient stress affects the amount and bioavailability of dissolved organic matter (DOM) that is produced. Under the nutrient limitation, organic carbon production was significantly influenced by nutrient availability. Particulate organic carbon (POC) production is closely related to phytoplankton growth phases, while dissolved organic carbon (DOC) is related to nutrient structure. The relative partitioning of net production to POC is higher in the dinoflagellate-dominant stage than that in the diatom-dominant stage, which is driven by quick turnover of DOM related to nutrient structure in different stages. In terms of C:Chl a ratio, it was strongly dependent on growth phases and nutrient conditions. From the signatures of chromophoric dissolved organic matter (CDOM), the bioavailability of DOM decreased during the succession. In different phases, DOM composition varied, containing more protein-like components in the degradation phase than in the growth phases. Differences of DOM composition among varying community dominance were far smaller than different growth phases during this succession. Such an observation of a diatom-to-dinoflagellate succession and the related dynamics of nutrients and organic matter benefits the prediction of organic carbon export during community shifts in ecological models.

Sterile fluid transfer between vessels is a key step in cell therapy manufacturing and requires specialised devices to maintain sterility of both vessels before, during and after the transfer. This review introduces two main types of devices for sterile fluid transfer in cell therapy manufacturing, namely single-use sterile connectors and tube welders. While these are excellent devices for infrequent moderate to large volume transfers, a new multiple-use aseptic connector may fill the gap for frequent small volume fluid transfers that are particularly important for autologous cell therapy manufacturing.

Parent-mediated intervention is a prominent approach to supplementing service insufficiency for the population with autism spectrum disorder, yet individuals from low-resource areas are largely under-represented among participants in the global parent-mediated intervention research. This systematic review and meta-analysis is the first to inspect the overall effects and research quality of parent-mediated interventions in mainland China, Hong Kong, and Taiwan. A total of 21 parent-mediated interventions were included in systematic review, and among them, 12 randomized controlled trials representing 964 children were analyzed in meta-synthesis. Overall, results of meta-analysis showed favorable effects of parent-mediated interventions with standardized mean difference ranging from 0.63 (social competence) to 1.00 (symptom severity) and averaged 0.76 across domains. However, the results should be interpreted with caution due to poor evidence quality as assessed in GRADE ratings. In terms of methodological quality, QualSyst evaluation showed that more than half (14/21) of the included studies were below satisfactory. Identified programs lack the capacity to be further disseminated in the Chinese societies due to the absence of solid theoretical foundations, the negligence of implementation outcomes, and the inadequacy of sophisticated cultural adaptations. This review reinforces the need for promotion and improvement of parent-mediated interventions in low-resource context (PROSPERO: CRD42019138723). Lay abstract The ideal dosage for early intensive interventions for autism spectrum disorder has been suggested to be at least 25-hour per week to reach optimal effects. However, insufficient service use and unmet needs among families with children with autism spectrum disorder are frequently reported worldwide. Helping parents to develop strategies for interaction and management of behavior through parent training has been demonstrated to be a prominent way to supplementing service insufficiency for autism spectrum disorder, which is particularly crucial in less-resourced areas. This review included 21 parent-mediated intervention programs conducted in China, the most populated developing country. Among them, we were able to combine outcome information from 12 randomized controlled trials to increase confidence in the results. We also rated the quality of methodology and evidence for all included studies, which was taken into account in making conclusions. The included programs varied in the content, length, and delivery method of trainings. Although targeting different training outcomes, the majority of the studies aimed to help parents be more competent and responsive during interactions with their child in order to decrease symptom severity. Overall, results showed sufficient evidence that parent training did improve child outcomes as intended. However, the quality of more than half (14/21) of the included studies were below satisfactory. Identified programs lack the capacity to be further transported in the Chinese societies due to the lack of solid theoretical foundations, implementation manuals, and appropriate cultural adaptations. This review reinforces the need for promotion and improvement of parent-mediated interventions in low-resource context.

There is an increasing demand for effective noninvasive diagnosis against common pulmonary diseases, which are rising sharply due to the serious air pollution. Human neutrophil elastase (HNE), a typical protease highly involved in pulmonary inflammatory diseases and lung cancer, is a potential predictor for disease progression. Currently, few of the HNE-targeting probes are applicable in vivo due to the limitation in sensitivity and biocompatibility. Herein, we reported the achievement of in vitro detection and in vivo imaging of HNE by incorporating the HNE-specific peptide substrate, quantum dots (QDs), and organic dyes into the fluorescence resonance energy transfer (FRET) system. The refined nanoprobe, termed QDP, could specifically measure the HNE with excellent sensitivity of 7.15 pM in aqueous solution and successfully image the endogenous and exogenous HNE in living cells. In addition, this nanoprobe enabled HNE imaging in mouse models of lung cancer and acute lung injury, and the HNE activity at high temporal and spatial resolution was continuously monitored. Most importantly, QDP successfully discriminated the serums of patients with lung diseases from those of the healthy controls based on the HNE activity determination. Overall, this study demonstrates the advantages of a FRET-system-based nanoprobe in imaging performance and provides an applicable tool for in vivo HNE detection and pulmonary disease diagnosis.

Structural defects in metal–organic frameworks (MOFs) have the potential to yield desirable properties that could not be achieved by “defect-free” crystals, but previous works in this area have focused on limited versions of defects due to the difficulty of detecting defects in MOFs. In this work, a modeling library containing 425 defective UiO-66 (UiO-66-Ds) with a comprehensive population (in terms of concentration and distribution) of missing-linker defects was created. Taking ethane–ethylene separation as a case study, we demonstrated that machine learning could provide data-driven insight into how the defects control the performance of UiO-66-Ds in adsorption, separation, and mechanical stability. We found that the missing-linker ratio in real materials could be predicted from the gravimetric surface area and pore volume, making it a useful complement for the challenges of directly measuring the defect concentration. We further identified the “privileged” UiO-66-Ds that were optimal in overall properties and provided decision trees as guidance to access and design these top performers. This work offers a general strategy for fully exploring the defects in MOFs, providing long-term opportunities for the development of defect engineering in the adsorption community.