Toward Global Sensing Quality Maximization: A Configuration Optimization Scheme for Camera Networks

The performance of a camera network monitoring a set of targets depends crucially on the configuration of the cameras. In this paper, we investigate the reconfiguration strategy for the parameterized camera network model, with which the sensing qualities of the multiple targets can be optimized globally and simultaneously. We first propose to use the number of pixels occupied by a unit-length object in image as a metric of the sensing quality of the object, which is determined by the parameters of the camera, such as intrinsic, extrinsic, and distortional coefficients. Then, we form a single quantity that measures the sensing quality of the targets by the camera network. This quantity further serves as the objective function of our optimization problem to obtain the optimal camera configuration. We verify the effectiveness of our approach through extensive simulations and experiments, and the results reveal its improved performance on the AprilTag detection tasks. Codes and related utilities for this work are open-sourced and available at https://github.com/sszxc/MultiCam-Simulation.Comment: The 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022

High-Fidelity Lake Extraction via Two-Stage Prompt Enhancement: Establishing a Novel Baseline and Benchmark

The extraction of lakes from remote sensing images is a complex challenge due to the varied lake shapes and data noise. Current methods rely on multispectral image datasets, making it challenging to learn lake features accurately from pixel arrangements. This, in turn, affects model learning and the creation of accurate segmentation masks. This paper introduces a unified prompt-based dataset construction approach that provides approximate lake locations using point, box, and mask prompts. We also propose a two-stage prompt enhancement framework, LEPrompter, which involves prompt-based and prompt-free stages during training. The prompt-based stage employs a prompt encoder to extract prior information, integrating prompt tokens and image embeddings through self- and cross-attention in the prompt decoder. Prompts are deactivated once the model is trained to ensure independence during inference, enabling automated lake extraction. Evaluations on Surface Water and Qinghai-Tibet Plateau Lake datasets show consistent performance improvements compared to the previous state-of-the-art method. LEPrompter achieves mIoU scores of 91.48% and 97.43% on the respective datasets without introducing additional parameters or GFLOPs. Supplementary materials provide the source code, pre-trained models, and detailed user studies.Comment: 8 pages, 7 figure

PlantDet: A benchmark for Plant Detection in the Three-Rivers-Source Region

The Three-River-Source region is a highly significant natural reserve in China that harbors a plethora of untamed botanical resources. To meet the practical requirements of botanical research and intelligent plant management, we construct a large-scale dataset for Plant detection in the Three-River-Source region (PTRS). This dataset comprises 6965 high-resolution images of 2160*3840 pixels, captured by diverse sensors and platforms, and featuring objects of varying shapes and sizes. Subsequently, a team of botanical image interpretation experts annotated these images with 21 commonly occurring object categories. The fully annotated PTRS images contain 122, 300 instances of plant leaves, each labeled by a horizontal rectangle. The PTRS presents us with challenges such as dense occlusion, varying leaf resolutions, and high feature similarity among plants, prompting us to develop a novel object detection network named PlantDet. This network employs a window-based efficient self-attention module (ST block) to generate robust feature representation at multiple scales, improving the detection efficiency for small and densely-occluded objects. Our experimental results validate the efficacy of our proposed plant detection benchmark, with a precision of 88.1%, a mean average precision (mAP) of 77.6%, and a higher recall compared to the baseline. Additionally, our method effectively overcomes the issue of missing small objects. We intend to share our data and code with interested parties to advance further research in this field.Comment: 10 pages, 5 figure

Development of an ALK2-Biased BMP Type I Receptor Kinase Inhibitor

The bone morphogenetic protein (BMP) signaling pathway has essential functions in development, homeostasis, and the normal and pathophysiologic remodeling of tissues. Small molecule inhibitors of the BMP receptor kinase family have been useful for probing physiologic functions of BMP signaling in vitro and in vivo and may have roles in the treatment of BMP-mediated diseases. Here we describe the development of a selective and potent inhibitor of the BMP type I receptor kinases, LDN-212854, which in contrast to previously described BMP receptor kinase inhibitors exhibits nearly 4 orders of selectivity for BMP versus the closely related TGF-? and Activin type I receptors. In vitro, LDN-212854 exhibits some selectivity for ALK2 in preference to other BMP type I receptors, ALK1 and ALK3, which may permit the interrogation of ALK2-mediated signaling, transcriptional activity, and function. LDN-212854 potently inhibits heterotopic ossification in an inducible transgenic mutant ALK2 mouse model of fibrodysplasia ossificans progressiva. These findings represent a significant step toward developing selective inhibitors targeting individual members of the highly homologous BMP type I receptor family. Such inhibitors would provide greater resolution as probes of physiologic function and improved selectivity against therapeutic targets

Interferon-γ-Induced Intestinal Epithelial Barrier Dysfunction by NF-κB/HIF-1α Pathway

Interferon-? (IFN-?) plays an important role in intestinal barrier dysfunction. However, the mechanisms are not fully understood. As hypoxia-inducible factor-1 (HIF-1) is a critical determinant response to hypoxia and inflammation, which has been shown to be deleterious to intestinal barrier function, we hypothesized that IFN-? induces loss of barrier function through the regulation of HIF-1α activation and function. In this study, we detected the expressions of HIF-1α and tight junction proteins in IFN-?-treated T84 intestinal epithelial cell line. IFN-? led to an increase of HIF-1α expression in time- and dose-dependent manners but did not change the expression of HIF-1?. The IFN-?-induced increase in HIF-1α was associated with an activation of NF-?B. Treatment with the NF-?B inhibitor, pyrolidinedithiocarbamate (PDTC), significantly suppressed the activation of NF-?B and the expression of HIF-1α. In addition, IFN-? also increased intestinal epithelial permeability and depletion of tight junction proteins; inhibition of NF-?B or HIF-1α prevented the increase in intestinal permeability and alteration in tight junction protein expressions. Interestingly, we demonstrated that a significant portion of IFN-? activation NF-kB and modulation tight junction expression is mediated through HIF-1α. Taken together, this study suggested that IFN-? induced the loss of epithelial barrier function and disruption of tight junction proteins, by upregulation of HIF-1α expression through NF-?B pathway.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140108/1/jir.2013.0044.pd

In situ atomic scale mechanisms of strain-induced twin boundary shear to high angle grain boundary in nanocrystalline Pt

Twin boundary can both strengthen and soften nanocrystalline metals and has been an important path for improving the strength and ductility of nano materials. Here, using in-lab developed double-tilt tensile stage in the transmission electron microscope, the atomic scale twin boundary shearing process was in situ observed in a twin-structured nanocrystalline Pt. It was revealed that the twin boundary shear was resulted from partial dislocation emissions on the intersected {111} planes, which accommodate as large as 47% shear strain. It is uncovered that the partial dislocations nucleated and glided on the two intersecting {111} slip planes lead to a transition of the original symmetric tilt ∑3/(111) coherent twin boundary into a symmetric tilt ∑9/(114) high angle grain boundary. These results provide insight of twin boundary strengthening mechanisms for accommodating plasticity strains in nanocrystalline metals

Structure–activity relationship study of bone morphogenetic protein (BMP) signaling inhibitors

A structure–activity relationship study of dorsomorphin, a previously identified inhibitor of SMAD 1/5/8 phosphorylation by bone morphogenetic protein (BMP) type 1 receptors ALK2, 3, and 6, revealed that increased inhibitory activity could be accomplished by replacing the pendent 4-pyridine ring with 4-quinoline. The activity contributions of various nitrogen atoms in the core pyrazolo[1,5-a]pyrimidine ring were also examined by preparing and evaluating pyrrolo[1,2-a]pyrimidine and pyrazolo[1,5-a]pyridine derivatives. In addition, increased mouse liver microsome stability was achieved by replacing the ether substituent on the pendent phenyl ring with piperazine. Finally, an optimized compound 13 (LDN-193189 or DM-3189) demonstrated moderate pharmacokinetic characteristics (e.g., plasma t1/2 = 1.6 h) following intraperitoneal administration in mice. These studies provide useful molecular probes for examining the in vivo pharmacology of BMP signaling inhibition

Historical Developments of BHR Humanoid Robots

Humanoid robots can achieve increasingly complex functions and adapt to more complex environments. To boost the development of humanoid robot technology, a team at Beijing Institute of Technology initiated the research on humanoid robots from 2000. Their research primarily focuses on stable walking, whole-body complex motion, human-robot interaction, and multimodal motion of humanoid robots. Thus far, the team has developed 6 generations of humanoid robots. The latest humanoid robot, BHR-6P, can achieve multi-mode motions (for example, walk, jump, fall protection, crawl and roll), which will significantly improve the ability of robot to adapt to the environment. This paper presented the historical evolution of BHR humanoid robots and outlined their functions and features

Direct transformation of-alkane into all-conjugated polyene via cascade dehydrogenation

Selective C(sp$^{3}$) −H activation is of fundamental importance in processing alkane feedstocks to produce high-value-added chemical products. By virtue of an on-surface synthesis strategy, we report selective cascade dehydrogenation of n-alkane molecules under surface constraints, which yields monodispersed all-trans conjugated polyenes with unprecedented length controllability. We are also able to demonstrate the generality of this concept for alkyl-substituted molecules with programmable lengths and diverse functionalities, and more importantly its promising potential in molecular wiring