The connection relationships among 5 DEGs in the PPAR signaling pathway.

<p>A. The connection relationships in pmAF. B. The connection relationships in controls. The threshold of CC is 0.9.</p

The predicted pmAF – related signaling pathways.

<p>The predicted pmAF – related signaling pathways.</p

Revisiting One-stage Deep Uncalibrated Photometric Stereo via Fourier Embedding

This paper introduces a one-stage deep uncalibrated photometric stereo (UPS) network, namely Fourier Uncalibrated Photometric Stereo Network (FUPS-Net), for non-Lambertian objects under unknown light directions. It departs from traditional two-stage methods that first explicitly learn lighting information and then estimate surface normals. Two-stage methods were deployed because the interplay of lighting with shading cues presents challenges for directly estimating surface normals without explicit lighting information. However, these two-stage networks are disjointed and separately trained so that the error in explicit light calibration will propagate to the second stage and cannot be eliminated. In contrast, the proposed FUPS-Net utilizes an embedded Fourier transform network to implicitly learn lighting features by decomposing inputs, rather than employing a disjointed light estimation network. Our approach is motivated from observations in the Fourier domain of photometric stereo images: lighting information is mainly encoded in amplitudes, while geometry information is mainly associated with phases. Leveraging this property, our method “decomposes” geometry and lighting in the Fourier domain as guidance, via the proposed Fourier Embedding Extraction (FEE) block and Fourier Embedding Aggregation (FEA) block, which generate lighting and geometry features for the FUPS-Net to implicitly resolve the geometry-lighting ambiguity. Furthermore, we propose a Frequency-Spatial Weighted (FSW) block that assigns weights to combine features extracted from the frequency domain and those from the spatial domain for enhancing surface reconstructions. FUPS-Net overcomes the limitations of two-stage UPS methods, offering better training stability, a concise end-to-end structure, and avoiding accumulated errors in disjointed networks. Experimental results on synthetic and real datasets demonstrate the superior performance of our approach, and its simpler training setup, potentially paving the way for a new strategy in deep learning-based UPS methods.</p

Proportional and cumulative variances for the first 10 PCs.

<p>Proportional and cumulative variances for the first 10 PCs.</p

The classification results for the 29 samples by the first two PCs, where AF and N respectively indicate the pmAF and normal patients; The factor loading (FL) of a PC is defined as the correlation coefficients between original sample variables and this PC.

<p>FL1 and FL2 respectively denote the factor loadings of the first PC and the second PC on the 29 samples.</p

The first 10 PCs extracted by APCA and PCA [6].

<p>The first 10 PCs extracted by APCA and PCA <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0076166#pone.0076166-Censi1" target="_blank">[6]</a>.</p

Identified differential expression genes using the APCA algorithm.

<p>Identified differential expression genes using the APCA algorithm.</p

Length Effect of Alkyl Linkers on the Crystalline Transition in Naphthalene Diimide-Based Double-Cable Conjugated Polymers

The alkyl chains as linkers in double-cable conjugated polymers play an important role in the solubility, packing motif, morphology, and voltage loss in single-component organic solar cells (SCOSCs). In this work, we incorporate alkyl linkers with lengths from hexyl (C6H12) to hexadecyl (C16H32) into naphthalene diimide-based double-cable conjugated polymers. These polymers show a parabolic-type distribution in crystallinity, in which the crystalline degree of the polymers is enhanced in sequence from P06 (C6H12 linker) to P12 (C12H24 linker) and then decreased in longer alkyl linkers. These differences bring into deviations like optical bandgaps, packing motif, charge transport, and photovoltaic performance in SCOSCs. This work demonstrates the importance of linkers’ length on crystallinity and packing motif as well as provides a new viewpoint in guiding the design of new double-cable conjugated polymers

Miscibility-Controlled Mechanical and Photovoltaic Properties in Double-Cable Conjugated Polymer/Insulating Polymer Composites

Flexibility is one of the main characteristics of organic solar cells (OSCs), which enables them to possess potential applications in flexible electronics. The study of flexibility (such as mechanical and bending behaviors) of the photoactive layers and the strategy to enhance the flexibility are important research topics in this field. In this work, we have focused on studying the flexibility of a single photoactive layer via using a double-cable conjugated polymer instead of two-component bulk-heterojunction layers. This simplified system enabled us to add the insulating polymers into the double-cable polymer to generate a polymer/polymer mixtures. The results found that the miscibility between the double-cable conjugated polymer and insulating polymers was the key factor to influence the mechanical and photovoltaic properties. Good miscibility by using polystyrene as an additive can provide better crack-onset strains as well as high efficiency, while lower miscibility by using polydimethylsiloxane as an additive exhibited low efficiencies in single-component OSCs

<i>sScD4</i>, <i>fads2</i> and <i>fads1</i> transcripts in transfected cells were analyzed by RT-PCR.

<p>Lane 1 were cells transfected with pcDNA3.1-<i>EGFP</i>; Lane 2 were cells transfected with pcDNA3.1-F2F1; Lane 3 were cells co-transfected with pcDNA3.1- F2F1 and pcDNA3.1-sScD4.</p