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Article: [：Q].

Wei, Su-Jung / Chang, Hsiao-Yun / Chen, Shu-Ming / Yeh, Shu-Hui / Yang, Li-Hui

Hu li za zhi The journal of nursing

2019 Volume 66, Issue 6, Page(s) 33–42

Abstract: ... used Q-sort to collect data. A 56-item "Nurse Practitioner Role Capacity Questionnaire" was used ...

Abstract	Background: The gap between the expectation and the development of role competency is a dilemma that nurse practitioners (NPs) face in clinical settings. Purpose: This study was designed to explore the perceived importance and actual practice of the role competencies of NPs and to compare the differences between the ideal and practical domains as well as related factors. Methods: This cross-sectional design study used Q-sort to collect data. A 56-item "Nurse Practitioner Role Capacity Questionnaire" was used as the research tool. Two questionnaires: Perceptions of Important Role Competencies and Actual Execution of Role Competencies were distributed to NPs twice, at times that were 2 weeks apart. A total of 40 participants were recruited, including 21(52.5%) internal medicine NPs and 19 (47.5%) surgical medicine NPs. Results: The significant differences that were identified in this study between the perceived importance and actual practice of role competencies were, by domain: medical assistance (t = -5.62, p < .001), clinical research (t = 4.14, p < .001), professional consultation (t = 2.29, p = .027), and direct care (t = 2.21, p = .033). The correlative factors for these differences were: education level (t = -2.17, p = .036) and membership in the Nurse Practitioner Association (t = -2.36, p = .017). NPs with higher levels of education and with membership in the Nurse Practitioner Association earned higher scores for self-expectation in important clinical competency. Conclusions: NPs face discrepancies in their role expectations, in important part due to their role as providers of medical assistance in clinical practical settings. NPs need to learn and demonstrate the roles and functions of advanced nursing practice to enhance nursing professionalism profoundly.
MeSH term(s)	Clinical Competence ; Cross-Sectional Studies ; Humans ; Nurse Practitioners/psychology ; Nurse's Role/psychology ; Q-Sort ; Surveys and Questionnaires
Language	Chinese
Publishing date	2019-12-04
Publishing country	China (Republic : 1949- )
Document type	Journal Article
ISSN	0047-262X
ISSN	0047-262X
DOI	10.6224/JN.201912_66(6).06
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: q

Chen, Geng / Dong, Bin / Zhang, Yong / Shen, Dinggang / Yap, Pew-Thian

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

2017 Volume 10433, Page(s) 620–628

Abstract: Acquisition time in diffusion MRI increases with the number of diffusion-weighted images that need to be acquired. Particularly in clinical settings, scan time is limited and only a sparse coverage of the ... ...

Abstract	Acquisition time in diffusion MRI increases with the number of diffusion-weighted images that need to be acquired. Particularly in clinical settings, scan time is limited and only a sparse coverage of the vast
MeSH term(s)	Algorithms ; Brain/diagnostic imaging ; Datasets as Topic ; Diffusion Magnetic Resonance Imaging/methods ; Humans ; Image Enhancement/methods ; Time Factors
Language	English
Publishing date	2017-09-04
Publishing country	Germany
Document type	Journal Article
DOI	10.1007/978-3-319-66182-7_71
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Book ; Online: Q-Instruct

Wu, Haoning / Zhang, Zicheng / Zhang, Erli / Chen, Chaofeng / Liao, Liang / Wang, Annan / Xu, Kaixin / Li, Chunyi / Hou, Jingwen / Zhai, Guangtao / Xue, Geng / Sun, Wenxiu / Yan, Qiong / Lin, Weisi

Improving Low-level Visual Abilities for Multi-modality Foundation Models

2023

Abstract: ... with an average length of 45 words. The constructed **Q-Pathway** dataset includes 58K detailed human feedbacks ... into diverse-format 200K instruction-response pairs. Experimental results indicate that the **Q-Instruct ... is published at: https://q-future.github.io/Q-Instruct. ...

Abstract	Multi-modality foundation models, as represented by GPT-4V, have brought a new paradigm for low-level visual perception and understanding tasks, that can respond to a broad range of natural human instructions in a model. While existing foundation models have shown exciting potentials on low-level visual tasks, their related abilities are still preliminary and need to be improved. In order to enhance these models, we conduct a large-scale subjective experiment collecting a vast number of real human feedbacks on low-level vision. Each feedback follows a pathway that starts with a detailed description on the low-level visual appearance (e.g. clarity, color, brightness of an image, and ends with an overall conclusion, with an average length of 45 words. The constructed Q-Pathway dataset includes 58K detailed human feedbacks on 18,973 images with diverse low-level appearance. Moreover, to enable foundation models to robustly respond to diverse types of questions, we design a GPT-participated conversion to process these feedbacks into diverse-format 200K instruction-response pairs. Experimental results indicate that the Q-Instruct consistently elevates low-level perception and understanding abilities across several foundational models. We anticipate that our datasets can pave the way for a future that general intelligence can perceive, understand low-level visual appearance and evaluate visual quality like a human. Our dataset, model zoo, and demo is published at: https://q-future.github.io/Q-Instruct. Comment: 16 pages, 11 figures, page 12-16 as appendix
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Multimedia
Subject code	006
Publishing date	2023-11-12
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Q-Bench

Wu, Haoning / Zhang, Zicheng / Zhang, Erli / Chen, Chaofeng / Liao, Liang / Wang, Annan / Li, Chunyi / Sun, Wenxiu / Yan, Qiong / Zhai, Guangtao / Lin, Weisi

A Benchmark for General-Purpose Foundation Models on Low-level Vision

2023

Abstract: ... this gap, we present Q-Bench, a holistic benchmark crafted to systematically evaluate potential abilities ... potentials of MLLMs. Project Page: https://q-future.github.io/Q-Bench. ... Comment: 27 pages, 11 tables ...

Abstract	The rapid evolution of Multi-modality Large Language Models (MLLMs) has catalyzed a shift in computer vision from specialized models to general-purpose foundation models. Nevertheless, there is still an inadequacy in assessing the abilities of MLLMs on low-level visual perception and understanding. To address this gap, we present Q-Bench, a holistic benchmark crafted to systematically evaluate potential abilities of MLLMs on three realms: low-level visual perception, low-level visual description, and overall visual quality assessment. a) To evaluate the low-level perception ability, we construct the LLVisionQA dataset, consisting of 2,990 diverse-sourced images, each equipped with a human-asked question focusing on its low-level attributes. We then measure the correctness of MLLMs on answering these questions. b) To examine the description ability of MLLMs on low-level information, we propose the LLDescribe dataset consisting of long expert-labelled golden low-level text descriptions on 499 images, and a GPT-involved comparison pipeline between outputs of MLLMs and the golden descriptions. c) Besides these two tasks, we further measure their visual quality assessment ability to align with human opinion scores. Specifically, we design a softmax-based strategy that enables MLLMs to predict quantifiable quality scores, and evaluate them on various existing image quality assessment (IQA) datasets. Our evaluation across the three abilities confirms that MLLMs possess preliminary low-level visual skills. However, these skills are still unstable and relatively imprecise, indicating the need for specific enhancements on MLLMs towards these abilities. We hope that our benchmark can encourage the research community to delve deeper to discover and enhance these untapped potentials of MLLMs. Project Page: https://q-future.github.io/Q-Bench. Comment: 27 pages, 11 tables, with updated results
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Artificial Intelligence ; Computer Science - Multimedia
Subject code	006
Publishing date	2023-09-25
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Coenzyme Q

Hseu, You-Cheng / Tseng, Yu-Fang / Pandey, Sudhir / Shrestha, Sirjana / Lin, Kai-Yuan / Lin, Cheng-Wen / Lee, Chuan-Chen / Huang, Sheng-Teng / Yang, Hsin-Ling

Oxidative medicine and cellular longevity

2022 Volume 2022, Page(s) 4266214

Abstract: Coenzyme Q (CoQ) analogs with a variable number of isoprenoid units have exhibited ...

Abstract	Coenzyme Q (CoQ) analogs with a variable number of isoprenoid units have exhibited as anti-inflammatory as well as antioxidant molecules. Using novel quinone derivative CoQ
MeSH term(s)	Adenosine Triphosphate/metabolism ; Animals ; Humans ; Inflammasomes/drug effects ; Lipopolysaccharides/metabolism ; Macrophages/metabolism ; Mice ; Mitophagy/immunology ; Transfection ; Ubiquinone/pharmacology ; Ubiquinone/therapeutic use
Chemical Substances	Inflammasomes ; Lipopolysaccharides ; Ubiquinone (1339-63-5) ; Adenosine Triphosphate (8L70Q75FXE)
Language	English
Publishing date	2022-01-07
Publishing country	United States
Document type	Journal Article
ZDB-ID	2455981-7
ISSN	1942-0994 ; 1942-0994
ISSN (online)	1942-0994
ISSN	1942-0994
DOI	10.1155/2022/4266214
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Article ; Online: Super-resolved q-space learning of diffusion MRI.

Chen, Zan / Peng, Chenxu / Li, Yongqiang / Zeng, Qingrun / Feng, Yuanjing

Medical physics

2023 Volume 50, Issue 12, Page(s) 7700–7713

Abstract: ... on neural structures relies on the number of diffusion gradients in the q-space. High-angular (HA) dMRI ... compressive sensing-based q-space learning (DCS-qL) approach to estimate HA dMRI from low-angular dMRI ...

Abstract	Background: Diffusion magnetic resonance imaging (dMRI) provides a powerful tool to non-invasively investigate neural structures in the living human brain. Nevertheless, its reconstruction performance on neural structures relies on the number of diffusion gradients in the q-space. High-angular (HA) dMRI requires a long scan time, limiting its use in clinical practice, whereas directly reducing the number of diffusion gradients would lead to the underestimation of neural structures. Purpose: We propose a deep compressive sensing-based q-space learning (DCS-qL) approach to estimate HA dMRI from low-angular dMRI. Methods: In DCS-qL, we design the deep network architecture by unfolding the proximal gradient descent procedure that addresses the compressive sense problem. In addition, we exploit a lifting scheme to design a network structure with reversible transform properties. For implementation, we apply a self-supervised regression to enhance the signal-to-noise ratio of diffusion data. Then, we utilize a semantic information-guided patch-based mapping strategy for feature extraction, which introduces multiple network branches to handle patches with different tissue labels. Results: Experimental results show that the proposed approach can yield a promising performance on the tasks of reconstructed HA dMRI images, microstructural indices of neurite orientation dispersion and density imaging, fiber orientation distribution, and fiber bundle estimation. Conclusions: The proposed method achieves more accurate neural structures than competing approaches.
MeSH term(s)	Humans ; Algorithms ; Diffusion Magnetic Resonance Imaging/methods ; Data Compression/methods ; Brain/diagnostic imaging ; Signal-To-Noise Ratio ; Image Processing, Computer-Assisted/methods
Language	English
Publishing date	2023-05-23
Publishing country	United States
Document type	Journal Article
ZDB-ID	188780-4
ISSN	2473-4209 ; 0094-2405
ISSN (online)	2473-4209
ISSN	0094-2405
DOI	10.1002/mp.16478
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Article ; Online: Ultrahigh-Q Lead Halide Perovskite Microlasers.

Tang, Haijun / Wang, Yuhan / Chen, Yimu / Wang, Kaiyang / He, Xianxiong / Huang, Can / Xiao, Shumin / Yu, Shaohua / Song, Qinghai

Nano letters

2023 Volume 23, Issue 8, Page(s) 3418–3425

Abstract: ... high-quality (Q) modes, severely hindering their practical applications. Here, we combine an etchless ...

Abstract	Lead halide perovskites have been promising platforms for micro- and nanolasers. However, the fragile nature of perovskites poses an extreme challenge to engineering a cavity boundary and achieving high-quality (Q) modes, severely hindering their practical applications. Here, we combine an etchless bound state in the continuum (BIC) and a chemically synthesized single-crystalline CsPbBr
Language	English
Publishing date	2023-04-12
Publishing country	United States
Document type	Journal Article
ISSN	1530-6992
ISSN (online)	1530-6992
DOI	10.1021/acs.nanolett.3c00463
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Article: High Q Resonant Sb

Meng, Qi / Chen, Xingqiao / Xu, Wei / Zhu, Zhihong / Yuan, Xiaodong / Zhang, Jianfa

Nanomaterials (Basel, Switzerland)

2021 Volume 11, Issue 9

Abstract: ... Sb2S3 with LN and propose a new type of high Q resonant metasurface. Simulation results show ... that the Sb2S3-LN metasurface has extremely narrow linewidth of 0.096 nm and high quality (Q) factor of 15,964 ... of Sb2S3, and its combination with LN, makes it possible to realize a new family of high Q resonant ...

Abstract	Phase change materials (PCMs) are attracting more and more attentions as enabling materials for tunable nanophotonics. They can be processed into functional photonic devices through customized laser writing, providing great flexibility for fabrication and reconfiguration. Lithium Niobate (LN) has excellent nonlinear and electro-optical properties, but is difficult to process, which limits its application in nanophotonic devices. In this paper, we combine the emerging low-loss phase change material Sb2S3 with LN and propose a new type of high Q resonant metasurface. Simulation results show that the Sb2S3-LN metasurface has extremely narrow linewidth of 0.096 nm and high quality (Q) factor of 15,964. With LN as the waveguide layer, strong nonlinear properties are observed in the hybrid metasurface, which can be employed for optical switches and isolators. By adding a pair of Au electrodes on both sides of the LN, we can realize dynamic electro-optical control of the resonant metasurface. The ultra-low loss of Sb2S3, and its combination with LN, makes it possible to realize a new family of high Q resonant metasurfaces for actively tunable nanophotonic devices with widespread applications including optical switching, light modulation, dynamic beam steering, optical phased array and so on.
Language	English
Publishing date	2021-09-13
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662255-5
ISSN	2079-4991
ISSN	2079-4991
DOI	10.3390/nano11092373
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Article ; Online: Engineering high coenzyme Q

Fan, Hang / Liu, Yan / Li, Chen-Yi / Jiang, Yan / Song, Jiao-Jiao / Yang, Lei / Zhao, Qing / Hu, Yong-Hong / Chen, Xiao-Ya / Xu, Jing-Jing

Metabolic engineering

2021 Volume 68, Page(s) 86–93

Abstract: Coenzyme Q (CoQ) is vital for energy metabolism in living organisms. In humans, CoQ ...

Abstract	Coenzyme Q (CoQ) is vital for energy metabolism in living organisms. In humans, CoQ
MeSH term(s)	Carotenoids/metabolism ; Fruit/metabolism ; Humans ; Lycopersicon esculentum/genetics ; Mitochondria ; Ubiquinone/genetics
Chemical Substances	Ubiquinone (1339-63-5) ; Carotenoids (36-88-4)
Language	English
Publishing date	2021-09-21
Publishing country	Belgium
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1470383-x
ISSN	1096-7184 ; 1096-7176
ISSN (online)	1096-7184
ISSN	1096-7176
DOI	10.1016/j.ymben.2021.09.007
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Zs.A 6288: Show issues

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Book ; Online: Q-YOLOP

Chang, Chi-Chih / Lin, Wei-Cheng / Wang, Pei-Shuo / Yu, Sheng-Feng / Lu, Yu-Chen / Lin, Kuan-Cheng / Wu, Kai-Chiang

Quantization-aware You Only Look Once for Panoptic Driving Perception

2023

Abstract: In this work, we present an efficient and quantization-aware panoptic driving perception model (Q ...

Abstract	In this work, we present an efficient and quantization-aware panoptic driving perception model (Q- YOLOP) for object detection, drivable area segmentation, and lane line segmentation, in the context of autonomous driving. Our model employs the Efficient Layer Aggregation Network (ELAN) as its backbone and task-specific heads for each task. We employ a four-stage training process that includes pretraining on the BDD100K dataset, finetuning on both the BDD100K and iVS datasets, and quantization-aware training (QAT) on BDD100K. During the training process, we use powerful data augmentation techniques, such as random perspective and mosaic, and train the model on a combination of the BDD100K and iVS datasets. Both strategies enhance the model's generalization capabilities. The proposed model achieves state-of-the-art performance with an mAP@0.5 of 0.622 for object detection and an mIoU of 0.612 for segmentation, while maintaining low computational and memory requirements.
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Artificial Intelligence
Subject code	004
Publishing date	2023-07-10
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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