Search

Observational evidence suggests the existence of dark matter (DM), which comprises approximately $84.4\%$ of matter in the universe. Recent advances in tabletop quantum sensor technology have enabled searches for nongravitational interactions of DM. Our experiment named ChangE utilizes Coupled Hot Atom eNsembles to search for liGht dark mattEr and new physics. We identify a strongly-coupled hybrid spin-resonance (HSR) regime that enhances the bandwidth of $^{21}$Ne nuclear spin by three orders of magnitude while maintaining high sensitivity. In combination with a self-compensating mode (SC) for low frequencies, we present a comprehensive broadband search for axion-like dark matter with Compton frequencies in the range of $[0.01, 1000]$ Hz. We set new constraints on the DM interactions with neutrons and protons, accounting for the stochastic effect. For the axion-neutron coupling, our results reach a low value of $|g_{ann}|\le 3\times 10^{-10}$ in the frequency range $[0.02 , 4]$ Hz surpassing astrophysical limits and provide the strongest laboratory constraints in the $[10, 100]$ Hz range. For the axion-proton coupling, we offer the best terrestrial constraints for the frequency below 100 Hz., Comment: 14 pages, 5 figures

Revealing the essence of dark matter (DM) and dark energy is essential for understanding our universe. Ultralight (rest energy $<$10 eV) bosonic particles, including pseudoscalar axions and axion-like particles (ALPs) have emerged among leading candidates to explain the composition of DM and searching for them has become an important part of precision-measurement science. Ultrahigh-sensitivity alkali-noble-gas based comagnetometers and magnetometers are being used as powerful haloscopes, i.e., devices designed to search for DM present in the galactic halo. A broad variety of such devices include clock-comparison comagnetometers, self-compensating comagnetometers, hybrid-spin-resonance magnetometer, spin-exchange-relaxation-free magnetometers, nuclear magnetic-resonance magnetometers, Floquet magnetometers, masers, as well as devices like the cosmic axion spin-precession experiment (CASPEr) using liquid $^{129}$Xe, prepolarized via spin-exchange optical pumping with rubidium atoms. The combination of alkali metal and noble gas allows one to take the best advantage of the complementary properties of the two spin systems. This review summarizes the operational principles, experimental setups and the successful explorations of new physics using these haloscopes. Additionally, some limiting factors are pointed out for further improvement.

Experiments aimed at detecting ultralight dark matter typically rely on resonant effects, which are sensitive to the dark matter mass that matches the resonance frequency. In this study, we investigate the nucleon couplings of ultralight axion dark matter using a magnetometer operating in a nuclear magnetic resonance (NMR) mode. Our approach involves the use of a $^{21}$Ne spin-based sensor, which features the lowest nuclear magnetic moment among noble-gas spins. This configuration allows us to achieve an ultrahigh sensitivity of 0.73 fT/Hz$^{1/2}$ at around 5 Hz, corresponding to energy resolution of approximately 1.5$\times 10^{-23}\,\rm{eV/Hz^{1/2}}$. Our analysis reveals that under certain conditions it is beneficial to scan the frequency with steps significantly larger than the resonance width. The analytical results are in agreement with experimental data and the scan strategy is potentially applicable to other resonant searches. Further, our study establishes stringent constraints on axion-like particles (ALP) in the 4.5--15.5 Hz Compton-frequency range coupling to neutrons and protons, improving on prior work by several-fold. Within a band around 4.6--6.6 Hz and around 7.5 Hz, our laboratory findings surpass astrophysical limits derived from neutron-star cooling. Hence, we demonstrate an accelerated resonance search for ultralight dark matter, achieving an approximately 30-fold increase in scanning step while maintaining competitive sensitivity., Comment: 13 pages, 9 figures

Observational evidence suggests the existence of dark matter (DM), which comprises approximately $84.4\%$ of matter in the universe. Recent advances in tabletop quantum sensor technology have enabled searches for nongravitational interactions of DM. Our experiment named ChangE utilizes Coupled Hot Atom eNsembles to search for liGht dark mattEr and new physics. We identify a strongly-coupled hybrid spin-resonance (HSR) regime that enhances the bandwidth of $^{21}$Ne nuclear spin by three orders of magnitude while maintaining high sensitivity. In combination with a self-compensating mode (SC) for low frequencies, we present a comprehensive broadband search for axion-like dark matter with Compton frequencies in the range of $[0.01, 1000]$ Hz. We set new constraints on the DM interactions with neutrons and protons, accounting for the stochastic effect. For the axion-neutron coupling, our results reach a low value of $|g_{ann}|\le 3\times 10^{-10}$ in the frequency range $[0.02 , 4]$ Hz surpassing astrophysical limits and provide the strongest laboratory constraints in the $[10, 100]$ Hz range. For the axion-proton coupling, we offer the best terrestrial constraints for the frequency below 100 Hz., Comment: 14 pages, 5 figures

Experiments aimed at detecting ultralight dark matter typically rely on resonant effects, which are sensitive to the dark matter mass that matches the resonance frequency. In this study, we investigate the nucleon couplings of ultralight axion dark matter using a magnetometer operating in a nuclear magnetic resonance (NMR) mode. Our approach involves the use of a $^{21}$Ne spin-based sensor, which features the lowest nuclear magnetic moment among noble-gas spins. This configuration allows us to achieve an ultrahigh sensitivity of 0.73 fT/Hz$^{1/2}$ at around 5 Hz, corresponding to energy resolution of approximately 1.5$\times 10^{-23}\,\rm{eV/Hz^{1/2}}$. Our analysis reveals that under certain conditions it is beneficial to scan the frequency with steps significantly larger than the resonance width. The analytical results are in agreement with experimental data and the scan strategy is potentially applicable to other resonant searches. Further, our study establishes stringent constraints on axion-like particles (ALP) in the 4.5--15.5 Hz Compton-frequency range coupling to neutrons and protons, improving on prior work by several-fold. Within a band around 4.6--6.6 Hz and around 7.5 Hz, our laboratory findings surpass astrophysical limits derived from neutron-star cooling. Hence, we demonstrate an accelerated resonance search for ultralight dark matter, achieving an approximately 30-fold increase in scanning step while maintaining competitive sensitivity., Comment: 13 pages, 9 figures

Observational evidence suggests the existence of dark matter (DM), which comprises approximately $84.4\%$ of matter in the universe. Recent advances in tabletop quantum sensor technology have enabled searches for nongravitational interactions of DM. Our experiment named ChangE utilizes Coupled Hot Atom eNsembles to search for liGht dark mattEr and new physics. We identify a strongly-coupled hybrid spin-resonance (HSR) regime that enhances the bandwidth of $^{21}$Ne nuclear spin by three orders of magnitude while maintaining high sensitivity. In combination with a self-compensating mode (SC) for low frequencies, we present a comprehensive broadband search for axion-like dark matter with Compton frequencies in the range of $[0.01, 1000]$ Hz. We set new constraints on the DM interactions with neutrons and protons, accounting for the stochastic effect. For the axion-neutron coupling, our results reach a low value of $|g_{ann}|\le 3\times 10^{-10}$ in the frequency range $[0.02 , 4]$ Hz surpassing astrophysical limits and provide the strongest laboratory constraints in the $[10, 100]$ Hz range. For the axion-proton coupling, we offer the best terrestrial constraints for the frequency below 100 Hz., Comment: 14 pages, 5 figures

To ensure that large precision instruments and equipment are in the best working condition, it is necessary to provide a suitable working environment for them. At this time, there is a high requirement for the vibration of the foundation at the location. Measuring the foundation vibration parameters, analyzing the foundation vibration state, and taking necessary damping measures during the construction process to provide basis are the premise of equipment installation and normal work. Combined with an application example, this paper briefly introduces the general situation of a project blasting, and obtains the basic characteristic parameters such as the peak velocity of ground motion and the time of arrival during the blasting operation; Based on the basic principle of regression analysis, the relationship between the peak velocity and the distance between the detonation centers and the charge weight is obtained by fitting the Sadovsky formula.

Xiaofei Huang,1 Lihua Shi,1 Yin Lin,1 Cong Zhang,1 Penghui Liu,1 Ran Zhang,2 Qiqi Chen,1 Xudong Ouyang,3 Yuanyuan Gao,2 Yingshuai Wang,3,&ast; Tongyi Sun1,&ast; 1Shandong Key Laboratory of Proteins and Peptides Pharmaceutical Engineering, Shandong Universities Key Laboratory of Biological Medicine, School of Life Science and Technology, Weifang Medical University, Weifang, Shandong, 261053, People’s Republic of China; 2School of Pharmacy, Weifang Medical University, Weifang, Shandong, 261053, People’s Republic of China; 3School of Life Science and Technology, Weifang Medical University, Weifang, Shandong, 261053, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Tongyi Sun, Shandong Key Laboratory of Proteins and Peptides Pharmaceutical Engineering, Shandong Universities Key Laboratory of Biological Medicine, School of Life Science and Technology, Weifang Medical University, Baotong Road, Weifang, Shandong, 261053, People’s Republic of China, Tel/Fax +86-536-8462067, Email sd_sty@126.com Yingshuai Wang, School of Life Science and Technology, Weifang Medical University, Baotong Road, Weifang, Shandong, 261053, People’s Republic of China, Tel/Fax +86-536-8462052, Email yingshuaiwang1987@163.comPurpose: Diabetic foot ulcers (DFU) are severe complications of diabetes, posing significant health and societal challenges. Elevated levels of reactive oxygen species (ROS) at the ulcer site hinder wound healing in most patients, while individuals with diabetes are also more susceptible to bacterial infections. This study aims to synthesize a comprehensive therapeutic material using polysaccharides from Pycnoporus sanguineus to promote DFU wound healing, reduce ROS levels, and minimize bacterial infections.Methods: Polysaccharides from P.sanguineus were employed as reducing and stabilizing agents to fabricate polysaccharide-based composite particles (PCPs) utilizing silver ions as templates. PCPs were characterize

The Transformer has been successfully used in medical image segmentation due to its excellent long-range modeling capabilities. However, patch segmentation is necessary when building a Transformer class model. This process may disrupt the tissue structure in medical images, resulting in the loss of relevant information. In this study, we proposed a Heterogeneous Swin Transformer with Multi-Receptive Field (HST-MRF) model based on U-shaped networks for medical image segmentation. The main purpose is to solve the problem of loss of structural information caused by patch segmentation using transformer by fusing patch information under different receptive fields. The heterogeneous Swin Transformer (HST) is the core module, which achieves the interaction of multi-receptive field patch information through heterogeneous attention and passes it to the next stage for progressive learning. We also designed a two-stage fusion module, multimodal bilinear pooling (MBP), to assist HST in further fusing multi-receptive field information and combining low-level and high-level semantic information for accurate localization of lesion regions. In addition, we developed adaptive patch embedding (APE) and soft channel attention (SCA) modules to retain more valuable information when acquiring patch embedding and filtering channel features, respectively, thereby improving model segmentation quality. We evaluated HST-MRF on multiple datasets for polyp and skin lesion segmentation tasks. Experimental results show that our proposed method outperforms state-of-the-art models and can achieve superior performance. Furthermore, we verified the effectiveness of each module and the benefits of multi-receptive field segmentation in reducing the loss of structural information through ablation experiments.

Automated human action recognition, a burgeoning field within computer vision, boasts diverse applications spanning surveillance, security, human-computer interaction, tele-health, and sports analysis. Precise action recognition in infants serves a multitude of pivotal purposes, encompassing safety monitoring, developmental milestone tracking, early intervention for developmental delays, fostering parent-infant bonds, advancing computer-aided diagnostics, and contributing to the scientific comprehension of child development. This paper delves into the intricacies of infant action recognition, a domain that has remained relatively uncharted despite the accomplishments in adult action recognition. In this study, we introduce a groundbreaking dataset called ``InfActPrimitive'', encompassing five significant infant milestone action categories, and we incorporate specialized preprocessing for infant data. We conducted an extensive comparative analysis employing cutting-edge skeleton-based action recognition models using this dataset. Our findings reveal that, although the PoseC3D model achieves the highest accuracy at approximately 71%, the remaining models struggle to accurately capture the dynamics of infant actions. This highlights a substantial knowledge gap between infant and adult action recognition domains and the urgent need for data-efficient pipeline models.

We apply computer vision pose estimation techniques developed expressly for the data-scarce infant domain to the study of torticollis, a common condition in infants for which early identification and treatment is critical. Specifically, we use a combination of facial landmark and body joint estimation techniques designed for infants to estimate a range of geometric measures pertaining to face and upper body symmetry, drawn from an array of sources in the physical therapy and ophthalmology research literature in torticollis. We gauge performance with a range of metrics and show that the estimates of most these geometric measures are successful, yielding strong to very strong Spearman's $\rho$ correlation with ground truth values. Furthermore, we show that these estimates, derived from pose estimation neural networks designed for the infant domain, cleanly outperform estimates derived from more widely known networks designed for the adult domain

Research in medical visual question answering (MVQA) can contribute to the development of computeraided diagnosis. MVQA is a task that aims to predict accurate and convincing answers based on given medical images and associated natural language questions. This task requires extracting medical knowledge-rich feature content and making fine-grained understandings of them. Therefore, constructing an effective feature extraction and understanding scheme are keys to modeling. Existing MVQA question extraction schemes mainly focus on word information, ignoring medical information in the text. Meanwhile, some visual and textual feature understanding schemes cannot effectively capture the correlation between regions and keywords for reasonable visual reasoning. In this study, a dual-attention learning network with word and sentence embedding (WSDAN) is proposed. We design a module, transformer with sentence embedding (TSE), to extract a double embedding representation of questions containing keywords and medical information. A dualattention learning (DAL) module consisting of self-attention and guided attention is proposed to model intensive intramodal and intermodal interactions. With multiple DAL modules (DALs), learning visual and textual co-attention can increase the granularity of understanding and improve visual reasoning. Experimental results on the ImageCLEF 2019 VQA-MED (VQA-MED 2019) and VQA-RAD datasets demonstrate that our proposed method outperforms previous state-of-the-art methods. According to the ablation studies and Grad-CAM maps, WSDAN can extract rich textual information and has strong visual reasoning ability.

Bilateral postural symmetry plays a key role as a potential risk marker for autism spectrum disorder (ASD) and as a symptom of congenital muscular torticollis (CMT) in infants, but current methods of assessing symmetry require laborious clinical expert assessments. In this paper, we develop a computer vision based infant symmetry assessment system, leveraging 3D human pose estimation for infants. Evaluation and calibration of our system against ground truth assessments is complicated by our findings from a survey of human ratings of angle and symmetry, that such ratings exhibit low inter-rater reliability. To rectify this, we develop a Bayesian estimator of the ground truth derived from a probabilistic graphical model of fallible human raters. We show that the 3D infant pose estimation model can achieve 68% area under the receiver operating characteristic curve performance in predicting the Bayesian aggregate labels, compared to only 61% from a 2D infant pose estimation model and 60% from a 3D adult pose estimation model, highlighting the importance of 3D poses and infant domain knowledge in assessing infant body symmetry. Our survey analysis also suggests that human ratings are susceptible to higher levels of bias and inconsistency, and hence our final 3D pose-based symmetry assessment system is calibrated but not directly supervised by Bayesian aggregate human ratings, yielding higher levels of consistency and lower levels of inter-limb assessment bias.

Di Mei,1,&ast; Xiaolong Guo,2,&ast; Yirong Wang,1 Xiaofei Huang,1 Li Guo,1 Pengfei Zou,3 Delong Ge,1 Xinxin Wang,1 Wenhui Lee,4 Tongyi Sun,1 Zhiqin Gao,1 Yuanyuan Gao3 1School of Life Science and Technology, Shandong Key Laboratory of Proteins and Peptides Pharmaceutical Engineering, Shandong Universities Key Laboratory of Biopharmaceuticals, Weifang Medical University, Weifang, Shandong, 261053, People’s Republic of China; 2School of Basic Medicine, Weifang Medical University, Weifang, Shandong, 261053, People’s Republic of China; 3School of Pharmacy, Weifang Medical University, Weifang, Shandong, 261053, People’s Republic of China; 4Key Laboratory of Animal Models and Human Disease Mechanism, Institute of Zoology, Kunming, Yunnan, 650233, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Zhiqin GaoSchool of Life Science and Technology, Shandong Key Laboratory of Proteins and Peptides Pharmaceutical Engineering, Shandong Universities Key Laboratory of Biopharmaceuticals, Weifang Medical University, Weifang, Shandong, 261053, People’s Republic of ChinaTel +86 5368462066Email zhiqingao2013@163.comYuanyuan GaoSchool of Pharmacy, Weifang Medical University, Baotong Road, Weifang, Shandong Province, 261053, People’s Republic of ChinaTel +86 536 846 2067Email yyg20062006@126.comBackground: The treatment of Staphylococcus aureus (S. aureus)-infected wounds is difficult. It causes extreme pain to tens of thousands of patients and increases the cost of medical care. The antimicrobial peptide OH-CATH30 (OH30) has a good killing activity against S. aureus and can play a role in accelerating wound healing and immune regulation. Therefore, it shows great potential for wound healing.Purpose: The aim of this study was to overcome the short half-life and easy enzymolysis of OH30 by using graphene oxide conjugated with polyethylene glycol to load OH30 (denoted as PGO-OH30), as well as to evaluate its effect on wound

Di Mei,1,&ast; Xiaolong Guo,2,&ast; Yirong Wang,1 Xiaofei Huang,1 Li Guo,1 Pengfei Zou,3 Delong Ge,1 Xinxin Wang,1 Wenhui Lee,4 Tongyi Sun,1 Zhiqin Gao,1 Yuanyuan Gao3 1School of Life Science and Technology, Shandong Key Laboratory of Proteins and Peptides Pharmaceutical Engineering, Shandong Universities Key Laboratory of Biopharmaceuticals, Weifang Medical University, Weifang, Shandong, 261053, People’s Republic of China; 2School of Basic Medicine, Weifang Medical University, Weifang, Shandong, 261053, People’s Republic of China; 3School of Pharmacy, Weifang Medical University, Weifang, Shandong, 261053, People’s Republic of China; 4Key Laboratory of Animal Models and Human Disease Mechanism, Institute of Zoology, Kunming, Yunnan, 650233, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Zhiqin GaoSchool of Life Science and Technology, Shandong Key Laboratory of Proteins and Peptides Pharmaceutical Engineering, Shandong Universities Key Laboratory of Biopharmaceuticals, Weifang Medical University, Weifang, Shandong, 261053, People’s Republic of ChinaTel +86 5368462066Email zhiqingao2013@163.comYuanyuan GaoSchool of Pharmacy, Weifang Medical University, Baotong Road, Weifang, Shandong Province, 261053, People’s Republic of ChinaTel +86 536 846 2067Email yyg20062006@126.comBackground: The treatment of Staphylococcus aureus (S. aureus)-infected wounds is difficult. It causes extreme pain to tens of thousands of patients and increases the cost of medical care. The antimicrobial peptide OH-CATH30 (OH30) has a good killing activity against S. aureus and can play a role in accelerating wound healing and immune regulation. Therefore, it shows great potential for wound healing.Purpose: The aim of this study was to overcome the short half-life and easy enzymolysis of OH30 by using graphene oxide conjugated with polyethylene glycol to load OH30 (denoted as PGO-OH30), as well as to evaluate its effect on wound

We lay the groundwork for research in the algorithmic comprehension of infant faces, in anticipation of applications from healthcare to psychology, especially in the early prediction of developmental disorders. Specifically, we introduce the first-ever dataset of infant faces annotated with facial landmark coordinates and pose attributes, demonstrate the inadequacies of existing facial landmark estimation algorithms in the infant domain, and train new state-of-the-art models that significantly improve upon those algorithms using domain adaptation techniques. We touch on the closely related task of facial detection for infants, and also on a challenging case study of infrared baby monitor images gathered by our lab as part of in-field research into the aforementioned developmental issues.

Infant motion analysis is a topic with critical importance in early childhood development studies. However, while the applications of human pose estimation have become more and more broad, models trained on large-scale adult pose datasets are barely successful in estimating infant poses due to the significant differences in their body ratio and the versatility of their poses. Moreover, the privacy and security considerations hinder the availability of adequate infant pose data required for training of a robust model from scratch. To address this problem, this paper presents (1) building and publicly releasing a hybrid synthetic and real infant pose (SyRIP) dataset with small yet diverse real infant images as well as generated synthetic infant poses and (2) a multi-stage invariant representation learning strategy that could transfer the knowledge from the adjacent domains of adult poses and synthetic infant images into our fine-tuned domain-adapted infant pose (FiDIP) estimation model. In our ablation study, with identical network structure, models trained on SyRIP dataset show noticeable improvement over the ones trained on the only other public infant pose datasets. Integrated with pose estimation backbone networks with varying complexity, FiDIP performs consistently better than the fine-tuned versions of those models. One of our best infant pose estimation performers on the state-of-the-art DarkPose model shows mean average precision (mAP) of 93.6.

Computer vision (CV) has achieved great success in interpreting semantic meanings from images, yet CV algorithms can be brittle for tasks with adverse vision conditions and the ones suffering from data/label pair limitation. One of this tasks is in-bed human pose estimation, which has significant values in many healthcare applications. In-bed pose monitoring in natural settings could involve complete darkness or full occlusion. Furthermore, the lack of publicly available in-bed pose datasets hinders the use of many successful pose estimation algorithms for this task. In this paper, we introduce our Simultaneously-collected multimodal Lying Pose (SLP) dataset, which includes in-bed pose images from 109 participants captured using multiple imaging modalities including RGB, long wave infrared, depth, and pressure map. We also present a physical hyper parameter tuning strategy for ground truth pose label generation under extreme conditions such as lights off and being fully covered by a sheet/blanket. SLP design is compatible with the mainstream human pose datasets, therefore, the state-of-the-art 2D pose estimation models can be trained effectively with SLP data with promising performance as high as 95% at PCKh@0.5 on a single modality. The pose estimation performance can be further improved by including additional modalities through collaboration.

Non-nutritive sucking (NNS) is defined as the sucking action that occurs when a finger, pacifier, or other object is placed in the baby's mouth, but there is no nutrient delivered. In addition to providing a sense of safety, NNS even can be regarded as an indicator of infant's central nervous system development. The rich data, such as sucking frequency, the number of cycles, and their amplitude during baby's non-nutritive sucking is important clue for judging the brain development of infants or preterm infants. Nowadays most researchers are collecting NNS data by using some contact devices such as pressure transducers. However, such invasive contact will have a direct impact on the baby's natural sucking behavior, resulting in significant distortion in the collected data. Therefore, we propose a novel contact-less NNS data acquisition and quantification scheme, which leverages the facial landmarks tracking technology to extract the movement signals of baby's jaw from recorded baby's sucking video. Since completion of the sucking action requires a large amount of synchronous coordination and neural integration of the facial muscles and the cranial nerves, the facial muscle movement signals accompanying baby's sucking pacifier can indirectly replace the NNS signal. We have evaluated our method on videos collected from several infants during their NNS behaviors and we have achieved the quantified NNS patterns closely comparable to results from visual inspection as well as contact-based sensor readings.

Strongly fluorescent and water soluble bioprobes are in great demand for studying important biological events and processes. The quenching effect of conventional organic dyes caused by aggregation, and the high toxicity of inorganic quantum dots are thorny issues that have constantly obsessed scientists in this area of research. In this work, a large number of tetraphenylethene (TPE) units were successfully attached to N-succinyl-chitosan (NSCS) macromolecular chains to fabricate a novel TPE-NSCS fluorescent bioconjugate, which was strongly emissive in the solid state due to its aggregation-induced emission effect. TPE-NSCS could be solubilized in water over a wide range of pH values. We were pleasantly surprised to see that stained cells still showed a bright fluorescence emission for as many as 30 passages. The water solubility over a wide pH range, ultra long-term retention in cells, and strong fluorescence signals indicate that TPE-NSCS is a promising candidate for various biomedical applications.

Strongly fluorescent and water soluble bioprobes are in great demand for studying important biological events and processes. The quenching effect of conventional organic dyes caused by aggregation, and the high toxicity of inorganic quantum dots are thorny issues that have constantly obsessed scientists in this area of research. In this work, a large number of tetraphenylethene (TPE) units were successfully attached to N-succinyl-chitosan (NSCS) macromolecular chains to fabricate a novel TPE-NSCS fluorescent bioconjugate, which was strongly emissive in the solid state due to its aggregation-induced emission effect. TPE-NSCS could be solubilized in water over a wide range of pH values. We were pleasantly surprised to see that stained cells still showed a bright fluorescence emission for as many as 30 passages. The water solubility over a wide pH range, ultra long-term retention in cells, and strong fluorescence signals indicate that TPE-NSCS is a promising candidate for various biomedical applications.

Strongly fluorescent and water soluble bioprobes are in great demand for studying important biological events and processes. The quenching effect of conventional organic dyes caused by aggregation, and the high toxicity of inorganic quantum dots are thorny issues that have constantly obsessed scientists in this area of research. In this work, a large number of tetraphenylethene (TPE) units were successfully attached to N-succinyl-chitosan (NSCS) macromolecular chains to fabricate a novel TPE-NSCS fluorescent bioconjugate, which was strongly emissive in the solid state due to its aggregation-induced emission effect. TPE-NSCS could be solubilized in water over a wide range of pH values. We were pleasantly surprised to see that stained cells still showed a bright fluorescence emission for as many as 30 passages. The water solubility over a wide pH range, ultra long-term retention in cells, and strong fluorescence signals indicate that TPE-NSCS is a promising candidate for various biomedical applications.

Most of atoms and molecule found in nature are capable of evolving towards and staying at their ground states, the lowest energy states. This paper offers a global optimization approach to understand the ground state as the equilibrium point of an $n$-player game under cooperation. With the same approach, Nash equilibrium can be viewed as the equilibrium point under competition. The former can offer higher payoffs and stability of game playing than the later. It is truly an inspiration from nature for us to build societies for quality and stability under cooperation rather than competition.

The fundamental laws of quantum world upsets the logical foundation of classic physics. They are completely counter-intuitive with many bizarre behaviors. However, this paper shows that they may make sense from the perspective of a general decision-optimization principle for cooperation. This principle also offers a generalization of Nash equilibrium, a key concept in game theory, for better payoffs and stability of game playing.

In a society of completely selfish individuals where everybody is only interested in maximizing his own payoff, does any equilibrium exist for the society? John Nash proved more than 50 years ago that an equilibrium always exists such that nobody would benefit from unilaterally changing his strategy. Nash Equilibrium is a central concept in game theory, which offers a mathematical foundation for social science and economy. However, it is important from both a theoretical and a practical point of view to understand game playing where individuals are less selfish. This paper offers a constructive generalization of Nash equilibrium to study n-person games where the selfishness of individuals can be defined at any level, including the extreme of complete selfishness. The generalization is constructive since it offers a protocol for individuals in a society to reach an equilibrium. Most importantly, this paper presents experimental results and theoretical investigation to show that the individuals in a society can reduce their selfishness level together to reach a new equilibrium where they can have better payoffs and the society is more stable at the same time. This study suggests that, for the benefit of everyone in a society (including the financial market), the pursuit of maximal payoff by each individual should be controlled at some level either by voluntary good citizenship or by imposed regulations.

In a society of multiple individuals, if everybody is only interested in maximizing his own payoff, will there exist any equilibrium for the society? John Nash proved more than 50 years ago that an equilibrium always exists such that nobody would benefit from unilaterally changing his strategy. Nash Equilibrium is a central concept in game theory, which offers the mathematical foundation for social science and economy. However, the original definition is declarative without including a solution to find them. It has been found later that it is computationally difficult to find a Nash equilibrium. Furthermore, a Nash equilibrium may be unstable, sensitive to the smallest variation of payoff functions. Making the situation worse, a society with selfish individuals can have an enormous number of equilibria, making it extremely hard to find out the global optimal one. This paper offers a constructive generalization of Nash equilibrium to cover the case when the selfishness of individuals are reduced to lower levels in a controllable way. It shows that the society has one and only one equilibrium when the selfishness is reduced to a certain level. When every individual follows the iterative, soft-decision optimization process presented in this paper, the society converges to the unique equilibrium with an exponential rate under any initial conditions. When it is a consensus equilibrium at the same time, it must be the global optimum. The study of this paper suggests that, to build a good, stable society (including the financial market) for the benefit everyone in it, the pursuing of maximal payoff by each individual should be controlled at some level either by voluntary good citizenship or some proper regulations.

Often times, individuals working together as a team can solve hard problems beyond the capability of any individual in the team. Cooperative optimization is a newly proposed general method for attacking hard optimization problems inspired by cooperation principles in team playing. It has an established theoretical foundation and has demonstrated outstanding performances in solving real-world optimization problems. With some general settings, a cooperative optimization algorithm has a unique equilibrium and converges to it with an exponential rate regardless initial conditions and insensitive to perturbations. It also possesses a number of global optimality conditions for identifying global optima so that it can terminate its search process efficiently. This paper offers a general description of cooperative optimization, addresses a number of design issues, and presents a case study to demonstrate its power.

The belief propagation algorithm has been recognized in the information theory community as a soft-decision iterative decoding algorithm. It is the most powerful algorithm found so far for attacking hard optimization problems in channel decoding. Quantum mechanics is the foundation of modern physics with the time-independent Schrodinger equation being one of the most important equations. This paper shows that the equation can be derived from a generalized belief propagation algorithm. Such a connection on a mathematical basis might shed new insights into the foundations of quantum mechanics and quantum computing., Comment: An extended abstract version of this paper has been presented at International Conference on Quantum Foundation and Technology, August, 2006, HangZhou, China (ICQFT'06)

Many implementations for decoding LDPC codes are based on the (normalized/offset) min-sum algorithm due to its satisfactory performance and simplicity in operations. Usually, each iteration of the min-sum algorithm contains two scans, the horizontal scan and the vertical scan. This paper presents a single-scan version of the min-sum algorithm to speed up the decoding process. It can also reduce memory usage or wiring because it only needs the addressing from check nodes to variable nodes while the original min-sum algorithm requires that addressing plus the addressing from variable nodes to check nodes. To cut down memory usage or wiring further, another version of the single-scan min-sum algorithm is presented where the messages of the algorithm are represented by single bit values instead of using fixed point ones. The software implementation has shown that the single-scan min-sum algorithm is more than twice as fast as the original min-sum algorithm., Comment: Accepted by IEEE Information Theory Workshop, Chengdu, China, 2006

In this paper, we present a fast min-sum algorithm for decoding LDPC codes over GF(q). Our algorithm is different from the one presented by David Declercq and Marc Fossorier in ISIT 05 only at the way of speeding up the horizontal scan in the min-sum algorithm. The Declercq and Fossorier's algorithm speeds up the computation by reducing the number of configurations, while our algorithm uses the dynamic programming instead. Compared with the configuration reduction algorithm, the dynamic programming one is simpler at the design stage because it has less parameters to tune. Furthermore, it does not have the performance degradation problem caused by the configuration reduction because it searches the whole configuration space efficiently through dynamic programming. Both algorithms have the same level of complexity and use simple operations which are suitable for hardware implementations., Comment: Accepted by IEEE Information Theory Workshop, Chengdu, China, 2006

The normalized min-sum algorithm can achieve near-optimal performance at decoding LDPC codes. However, it is a critical question to understand the mathematical principle underlying the algorithm. Traditionally, people thought that the normalized min-sum algorithm is a good approximation to the sum-product algorithm, the best known algorithm for decoding LDPC codes and Turbo codes. This paper offers an alternative approach to understand the normalized min-sum algorithm. The algorithm is derived directly from cooperative optimization, a newly discovered general method for global/combinatorial optimization. This approach provides us another theoretical basis for the algorithm and offers new insights on its power and limitation. It also gives us a general framework for designing new decoding algorithms., Comment: Accepted by IEEE Information Theory Workshop, Chengdu, China, 2006

Cooperative optimization is a new way for finding global optima of complicated functions of many variables. It has some important properties not possessed by any conventional optimization methods. It has been successfully applied in solving many large scale optimization problems in image processing, computer vision, and computational chemistry. This paper shows the application of this optimization principle in decoding LDPC codes, which is another hard combinatorial optimization problem. In our experiments, it significantly out-performed the sum-product algorithm, the best known method for decoding LDPC codes. Compared to the sum-product algorithm, our algorithm reduced the error rate further by three fold, improved the speed by six times, and lowered error floors dramatically in the decoding., Comment: 5 pages, submitted to the 2005 IEEE International Symposium on Information Theory

The Hopfield network has been applied to solve optimization problems over decades. However, it still has many limitations in accomplishing this task. Most of them are inherited from the optimization algorithms it implements. The computation of a Hopfield network, defined by a set of difference equations, can easily be trapped into one local optimum or another, sensitive to initial conditions, perturbations, and neuron update orders. It doesn't know how long it will take to converge, as well as if the final solution is a global optimum, or not. In this paper, we present a Hopfield network with a new set of difference equations to fix those problems. The difference equations directly implement a new powerful optimization algorithm., Comment: 6 pages, accepted by International Joint Conference on Neural Networks 2005