Modeling of MZM-Based Photonic Link Power Budget

An accurate methodology for analyzing the Mach-Zehnder modulator (MZM) based optical link power budget is presented. It optimizes the transceiver’s system-level performance to meet the specifications of the optical links with N-level (N=2,4,8) pulse amplitude modulation format for high-speed signaling

CLCI-Net: Cross-Level fusion and Context Inference Networks for Lesion Segmentation of Chronic Stroke

Segmenting stroke lesions from T1-weighted MR images is of great value for large-scale stroke rehabilitation neuroimaging analyses. Nevertheless, there are great challenges with this task, such as large range of stroke lesion scales and the tissue intensity similarity. The famous encoder-decoder convolutional neural network, which although has made great achievements in medical image segmentation areas, may fail to address these challenges due to the insufficient uses of multi-scale features and context information. To address these challenges, this paper proposes a Cross-Level fusion and Context Inference Network (CLCI-Net) for the chronic stroke lesion segmentation from T1-weighted MR images. Specifically, a Cross-Level feature Fusion (CLF) strategy was developed to make full use of different scale features across different levels; Extending Atrous Spatial Pyramid Pooling (ASPP) with CLF, we have enriched multi-scale features to handle the different lesion sizes; In addition, convolutional long short-term memory (ConvLSTM) is employed to infer context information and thus capture fine structures to address the intensity similarity issue. The proposed approach was evaluated on an open-source dataset, the Anatomical Tracings of Lesions After Stroke (ATLAS) with the results showing that our network outperforms five state-of-the-art methods. We make our code and models available at https://github.com/YH0517/CLCI_Net

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Positioning absorptive root respiration in the root economics space across woody and herbaceous species

<p>Root respiration is essential for nutrient acquisition. The respiration rate of absorptive roots theoretically relates to the economics of carbon-nutrient exchange, but its empirical role remains largely unexplored in the trait space defining nutrient uptake strategies. Here, we measured the respiration rates of the distal, non-woody, absorptive roots of 252 woody and herbaceous species from subtropical and temperate climate zones, including both arbuscular mycorrhizal and ectomycorrhizal fungal hosts. We found a consistent and positive correlation between root respiration rate and specific root length (root length per dry weight), irrespective of growth form, mycorrhizal type, and climate zone. Root respiration rate was also positively, but less strongly and less frequently correlated with root nitrogen concentration. Root morphology strongly explained the fast-slow gradient of root respiration in the root economics space. By quantifying the ratio of arbuscular mycorrhizal fungal DNA copy number and root tissue DNA copy number using qPCR, we found that the morphology-driven gradient did not explain the full variation in fungal collaboration; thick roots were consistently well colonized, but medium and thin roots displayed a wide range of colonization intensity. Synthesis: These results advance our understanding of the fundamental trait relationships that underpin the root economics space. Our study also provides a physiological linkage to the frequently-measured root morphological traits and relates the root economics space to root-derived carbon-nutrient cycling processes.</p><p>Funding provided by: Natural Science Foundation of Zhejiang Province<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100004731<br>Award Number: LR21C030002</p><p>Funding provided by: National Natural Science Foundation of China<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100001809<br>Award Number: 32001163</p><p>Funding provided by: National Natural Science Foundation of China<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100001809<br>Award Number: 32101293</p><p>Funding provided by: National Natural Science Foundation of China<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100001809<br>Award Number: 32271623</p><p>Funding provided by: National Key Research and Development Program of China<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100012166<br>Award Number: 2022YFF1301700</p><p>Funding provided by: Natural Science Foundation of Zhejiang Province<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100004731<br>Award Number: LY23C030004</p><p>Funding provided by: Cao Guangbiao High Science and Technology Foundation, Zhejiang University<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100002928<br>Award Number: 2020QN018</p&gt