Survey on Controlable Image Synthesis with Deep Learning

Image synthesis has attracted emerging research interests in academic and industry communities. Deep learning technologies especially the generative models greatly inspired controllable image synthesis approaches and applications, which aim to generate particular visual contents with latent prompts. In order to further investigate low-level controllable image synthesis problem which is crucial for fine image rendering and editing tasks, we present a survey of some recent works on 3D controllable image synthesis using deep learning. We first introduce the datasets and evaluation indicators for 3D controllable image synthesis. Then, we review the state-of-the-art research for geometrically controllable image synthesis in two aspects: 1) Viewpoint/pose-controllable image synthesis; 2) Structure/shape-controllable image synthesis. Furthermore, the photometrically controllable image synthesis approaches are also reviewed for 3D re-lighting researches. While the emphasis is on 3D controllable image synthesis algorithms, the related applications, products and resources are also briefly summarized for practitioners.Comment: 19 pages, 17 figure

Identification and expression of the TIP subfamily in apple in response to drought stress

Abstract [Objective] This study aims to identify and analyze the members of the tonoplast intrinsic protein (TIP) subfamily in apple, and to investigate the expression patterns under drought stress. It provides information for further research on utilization of drought resistance gene resources in apple. [Methods] The MdTIPs in apple genome was identified by bioinformatics methods. The physicochemical properties, gene structures, conserved motifs, cis-regulatory elements, and phylogenetic trees, etc. of the subfamily members were analyzed. The expression patterns of MdTIPs in different organs under drought stress were analyzed by qRT-PCR. [Results] A total of 13 MdTIP genes were identified in the apple genome, and most members were localized at the plasma membrane. Chromosome localization analysis suggested that all members were distributed on 10 chromosomes, with 1-3 members on each chromosome. Besides, the promoter regions of the genes contained response elements for hormonal and adversity stresses. qRTPCR showed that MdTIP members were up-regulated in roots except MdTIP1;1, of which MdTIP1;3 and MdTIP1;4 were up-regulated 5.27 times and 5.69 times, respectively, compared with the control, suggesting that these two genes might be critical in response to drought stress. [Conclusion] Identification of MdTIP subfamily members is provided in this study. 10 MdTIP members are differentially expressed in roots, stems, and leaves, and 12 members are highly expressed in roots

Machine learning models reveal the critical role of nighttime systolic blood pressure in predicting functional outcome for acute ischemic stroke after endovascular thrombectomy

BackgroundBlood pressure (BP) is a key factor for the clinical outcomes of acute ischemic stroke (AIS) receiving endovascular thrombectomy (EVT). However, the effect of the circadian pattern of BP on functional outcome is unclear.MethodsThis multicenter, retrospective, observational study was conducted from 2016 to 2023 at three hospitals in China (ChiCTR2300077202). A total of 407 patients who underwent endovascular thrombectomy (EVT) and continuous 24-h BP monitoring were included. Two hundred forty-one cases from Beijing Hospital were allocated to the development group, while 166 cases from Peking University Shenzhen Hospital and Hainan General Hospital were used for external validation. Postoperative systolic BP (SBP) included daytime SBP, nighttime SBP, and 24-h average SBP. Least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), Boruta were used to screen for potential features associated with functional dependence defined as 3-month modified Rankin scale (mRS) score ≥ 3. Nine algorithms were applied for model construction and evaluated using area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy.ResultsThree hundred twenty-eight of 407 (80.6%) patients achieved successful recanalization and 182 patients (44.7%) were functional independent. NIHSS at onset, modified cerebral infarction thrombolysis grade, atrial fibrillation, coronary atherosclerotic heart disease, hypertension were identified as prognostic factors by the intersection of three algorithms to construct the baseline model. Compared to daytime SBP and 24-h SBP models, the AUC of baseline + nighttime SBP showed the highest AUC in all algorithms. The XGboost model performed the best among all the algorithms. ROC results showed an AUC of 0.841 in the development set and an AUC of 0.752 in the validation set for the baseline plus nighttime SBP model, with a brier score of 0.198.ConclusionThis study firstly explored the association between circadian BP patterns with functional outcome for AIS. Nighttime SBP may provide more clinical information regarding the prognosis of patients with AIS after EVT

International R&D Spillovers and Innovation Efficiency

The objective of this study is to examine the impact of international research and development (R&D) spillovers on innovation efficiency of specific R&D outcomes, employing the country-level panel data for 44 countries in the 1996⁻2013 period. Fully considering the heterogeneity of different R&D outputs, scientific papers, PCT (Patent Cooperation Treaty) patents, US patents, and domestic patents are observed separately, which enriches the angles of measuring international R&D spillovers. By applying a stochastic frontier analysis to knowledge production function, we find that foreign R&D capital stock positively contributes to the innovation efficiency of scientific papers, but suppresses the productivity of domestic patents, whereas it does not really matter for PCT or US patents. These results are robust to control for a set of institutional factors and also in sensitivity analyses. Hence, dependence on international R&D spillovers seems neither to be the right way for emerging economies to catch up, nor to be a sustainable model for developing countries to fill the technical gap. Local R&D capital stock, instead, keeps an essential contributor to all four R&D outputs, so raising internal R&D expenditure is actually the key to improving innovation level and sustainable development ability

Economic Growth Effect and Optimal Carbon Emissions under China’s Carbon Emissions Reduction Policy: A Time Substitution DEA Approach

In this paper, provincial panel data for China during 1995–2015 and the time substitution data envelopment analysis (DEA) model were used to measure the influences of China’s carbon emissions reduction policy on economic growth under various reduction targets and to determine optimal economic growth and optimal carbon emissions of each province. In addition, this paper empirically examines the factors that influence the optimal economic growth and carbon emissions. The results indicate that not all provinces will suffer from a loss in gross domestic product (GDP) when confronted by the constraints of carbon emissions reductions. Certain provinces can achieve a win-win situation between economic growth and carbon emissions reductions if they are allowed to reallocate production decisions over time. Provinces with higher environmental efficiency, higher per capita GDP, smaller populations, and lower energy intensity might suffer from a larger loss in GDP. Therefore, they should set lower carbon emissions reduction targets

Enhanced Electron Transfer from the Excited Eosin Y to mpg‑C₃N₄ for Highly Efficient Hydrogen Evolution under 550 nm Irradiation

Graphitic carbon nitride (g-C₃N₄) is a novel and stable metal-free photocatalyst that can generate H₂ from water under visible light irradiation, but its activity is significantly limited due to the insufficient light absorption in the solar spectrum (weak absorption in the wavelength longer than 460 nm). In this paper, we demonstrate that the photoresponse of the mesoporous g-C₃N₄ (mpg-C₃N₄) can be greatly extended up to nearly 600 nm by sensitization with Eosin Y (EY). This sensitization photocatalyst demonstrates high and rather stable photocatalytic activity for H₂ evolution under visible light irradiation, especially in the longer wavelength regions (450–600 nm). The apparent quantum efficiency (AQE) of 19.4% under 550 nm irradiation has been obtained. These results indicate that efficient electron transfer between excited EY molecules and mpg-C₃N₄ is achieved. The mpg-C₃N₄ with high surface area and nanoporous structure can greatly facilitate EY molecules assembly on the surface, thus promoting the activity via improved light harvesting