Solid-state laser refrigeration of a semiconductor optomechanical resonator

Photothermal heating represents a major constraint that limits the performance of many nanoscale optoelectronic and optomechanical devices including nanolasers, quantum optomechanical resonators, and integrated photonic circuits. Although radiation-pressure damping has been reported to cool an individual vibrational mode of an optomechanical resonator to its quantum ground state, to date the internal material temperature within an optomechanical resonator has not been reported to cool via laser excitation. Here we demonstrate the direct laser refrigeration of a semiconductor optomechanical resonator >20K below room temperature based on the emission of upconverted, anti-Stokes photoluminescence of trivalent ytterbium ions doped within a yttrium-lithium-fluoride (YLF) host crystal. Optically-refrigerating the lattice of a dielectric resonator has the potential to impact several fields including scanning probe microscopy, the sensing of weak forces, the measurement of atomic masses, and the development of radiation-balanced solid-state lasers. In addition, optically refrigerated resonators may be used in the future as a promising starting point to perform motional cooling for exploration of quantum effects at mesoscopic length scales,temperature control within integrated photonic devices, and solid-state laser refrigeration of quantum material

Robust Inference for the Stepped Wedge Design

Based on a permutation argument, we derive a closed form expression for an estimate of the treatment effect, along with its standard error, in a stepped wedge design. We show that these estimates are robust to misspecification of both the mean and covariance structure of the underlying data-generating mechanism, thereby providing a robust approach to inference for the treatment effect in stepped wedge designs. We use simulations to evaluate the type I error and power of the proposed estimate and to compare the performance of the proposed estimate to the optimal estimate when the correct model specification is known. The limitations, possible extensions, and open problems regarding the method are discussed

MBEToolbox: a Matlab toolbox for sequence data analysis in molecular biology and evolution

BACKGROUND: MATLAB is a high-performance language for technical computing, integrating computation, visualization, and programming in an easy-to-use environment. It has been widely used in many areas, such as mathematics and computation, algorithm development, data acquisition, modeling, simulation, and scientific and engineering graphics. However, few functions are freely available in MATLAB to perform the sequence data analyses specifically required for molecular biology and evolution. RESULTS: We have developed a MATLAB toolbox, called MBEToolbox, aimed at filling this gap by offering efficient implementations of the most needed functions in molecular biology and evolution. It can be used to manipulate aligned sequences, calculate evolutionary distances, estimate synonymous and nonsynonymous substitution rates, and infer phylogenetic trees. Moreover, it provides an extensible, functional framework for users with more specialized requirements to explore and analyze aligned nucleotide or protein sequences from an evolutionary perspective. The full functions in the toolbox are accessible through the command-line for seasoned MATLAB users. A graphical user interface, that may be especially useful for non-specialist end users, is also provided. CONCLUSION: MBEToolbox is a useful tool that can aid in the exploration, interpretation and visualization of data in molecular biology and evolution. The software is publicly available at and

MBEToolbox 2.0: An enhanced version of a MATLAB toolbox for Molecular Biology and Evolution

MBEToolbox is an extensible MATLAB-based software package for analysis of DNA and protein sequences. MBEToolbox version 2.0 includes enhanced functions for phylogenetic analyses by the maximum likelihood method. For example, it is capable of estimating the synonymous and nonsynonymous substitution rates using a novel or several known codon substitution models. MBEToolbox 2.0 introduces new functions for estimating site-specific evolutionary rates by using a maximum likelihood method or an empirical Bayesian method. It also incorporates several different methods for recombination detection. Multi-platform versions of the software are freely available at http://www.bioinformatics.org/mbetoolbox/

Automatic Craniomaxillofacial Landmark Digitization via Segmentation-Guided Partially-Joint Regression Forest Model and Multiscale Statistical Features

The goal of this paper is to automatically digitize craniomaxillofacial (CMF) landmarks efficiently and accurately from cone-beam computed tomography (CBCT) images, by addressing the challenge caused by large morphological variations across patients and image artifacts of CBCT images

Fabrication of Nanometer and Micrometer Scale Protein Structures by Site-Specific Immobilization of Histidine-Tagged Proteins to Aminosiloxane Films with Photoremovable Protein-Resistant Protecting Groups

The site-specific immobilization of histidine-tagged proteins to patterns formed by far-field and near-field exposure of films of aminosilanes with protein-resistant photolabile protecting groups is demonstrated. After deprotection of the aminosilane, either through a mask or using a scanning near-field optical microscope, the amine terminal groups are derivatized first with glutaraldehyde and then with N-(5-amino-1-carboxypentyl)iminodiacetic acid to yield a nitrilo triacetic acid (NTA) terminated surface. After complexation with Ni2+, this surface binds histidine-tagged GFP and CpcA-PEB in a site-specific fashion. The chemistry is simple and reliable, and leads to extensive surface functionalization. Bright fluorescence is observed in fluorescence microscopy images of micrometer- and nanometer-scale patterns. X-ray photoelectron spectroscopy is used to study quantitatively the efficiency of photodeprotection and the reactivity of the modified surfaces. The efficiency of the protein binding process is investigated quantitatively by ellipsometry and by fluorescence microscopy. We find that regions of the surface not exposed to UV light bind negligible amounts of His-tagged proteins, indicating that the oligo(ethylene glycol) adduct on the nitrophenyl protecting group confers excellent protein resistance; in contrast, exposed regions bind His-GFP very effectively, yielding strong fluorescence that is almost completely removed on treatment of the surface with imidazole, confirming a degree of site-specific binding in excess of 90%. This simple strategy offers a versatile generic route to the spatially selective site-specific immobilization of proteins at surfaces

Quadratic Volume Preserving Maps

We study quadratic, volume preserving diffeomorphisms whose inverse is also quadratic. Such maps generalize the Henon area preserving map and the family of symplectic quadratic maps studied by Moser. In particular, we investigate a family of quadratic volume preserving maps in three space for which we find a normal form and study invariant sets. We also give an alternative proof of a theorem by Moser classifying quadratic symplectic maps.Comment: Ams LaTeX file with 4 figures (figure 2 is gif, the others are ps

Federated Cross Learning for Medical Image Segmentation

Federated learning (FL) can collaboratively train deep learning models using isolated patient data owned by different hospitals for various clinical applications, including medical image segmentation. However, a major problem of FL is its performance degradation when dealing with the data that are not independently and identically distributed (non-iid), which is often the case in medical images. In this paper, we first conduct a theoretical analysis on the FL algorithm to reveal the problem of model aggregation during training on non-iid data. With the insights gained through the analysis, we propose a simple and yet effective method, federated cross learning (FedCross), to tackle this challenging problem. Unlike the conventional FL methods that combine multiple individually trained local models on a server node, our FedCross sequentially trains the global model across different clients in a round-robin manner, and thus the entire training procedure does not involve any model aggregation steps. To further improve its performance to be comparable with the centralized learning method, we combine the FedCross with an ensemble learning mechanism to compose a federated cross ensemble learning (FedCrossEns) method. Finally, we conduct extensive experiments using a set of public datasets. The experimental results show that the proposed FedCross training strategy outperforms the mainstream FL methods on non-iid data. In addition to improving the segmentation performance, our FedCrossEns can further provide a quantitative estimation of the model uncertainty, demonstrating the effectiveness and clinical significance of our designs. Source code will be made publicly available after paper publication.Comment: 10 pages, 4 figure

Adamantyl Retinoid-Related Molecules Induce Apoptosis in Pancreatic Cancer Cells by Inhibiting IGF-1R and Wnt/β-Catenin Pathways

Pancreatic carcinoma has a dismal prognosis as it often presents as locally advanced or metastatic. We have found that exposure to adamantyl-substituted retinoid-related (ARR) compounds 3-Cl-AHPC and AHP3 resulted in growth inhibition and apoptosis induction in PANC-1, Capan-2, and MiaPaCa-2 pancreatic cancer cell lines. In addition, AHP3 and 3-Cl-AHPC inhibited growth and induced apoptosis in spheres derived from the CD44+/CD24+ (CD133+/EpCAM+) stem-like cell population isolated from the pancreatic cancer cell lines. 3-Cl-AHPC-induced apoptosis was preceded by decreasing expression of IGF-1R, cyclin D1, β-catenin, and activated Notch-1 in the pancreatic cancer cell lines. Decreased IGF-1R expression inhibited PANC-1 proliferation, enhanced 3-Cl-AHPC-mediated apoptosis, and significantly decreased sphere formation. 3-Cl-AHPC inhibited the Wnt/β-catenin pathway as indicated by decreased β-catenin nuclear localization and inhibited Wnt/β-catenin activation of transcription factor TCF/LEF. Knockdown of β-catenin using sh-RNA also induced apoptosis and inhibited growth in pancreatic cancer cells. Thus, 3-Cl-AHPC and AHP3 induce apoptosis in pancreatic cancer cells and cancer stem-like cells and may serve as an important potential therapeutic agent in the treatment of pancreatic cancer