Research on Isomorphic Task Transfer Algorithm Based on Knowledge Distillation in Multi-Agent Collaborative Systems.

In response to the increasing number of agents and changing task scenarios in multi-agent collaborative systems, existing collaborative strategies struggle to effectively adapt to new task scenarios. To address this challenge, this paper proposes a knowledge distillation method combined with a domain separation network (DSN-KD). This method leverages the well-performing policy network from a source task as the teacher model, utilizes a domain-separated neural network structure to correct the teacher model's outputs as supervision, and guides the learning of agents in new tasks. The proposed method does not require the pre-design or training of complex state-action mappings, thereby reducing the cost of transfer. Experimental results in scenarios such as UAV surveillance and UAV cooperative target occupation, robot cooperative box pushing, UAV cooperative target strike, and multi-agent cooperative resource recovery in a particle simulation environment demonstrate that the DSN-KD transfer method effectively enhances the learning speed of new task policies and improves the proximity of the policy model to the theoretically optimal policy in practical tasks.

Lightweight Knowledge Distillation-Based Transfer Learning Framework for Rolling Bearing Fault Diagnosis.

Compared to fault diagnosis across operating conditions, the differences in data distribution between devices are more pronounced and better aligned with practical application needs. However, current research on transfer learning inadequately addresses fault diagnosis issues across devices. To better balance the relationship between computational resources and diagnostic accuracy, a knowledge distillation-based lightweight transfer learning framework for rolling bearing diagnosis is proposed in this study. Specifically, a deep teacher-student model based on variable-scale residual networks is constructed to learn domain-invariant features relevant to fault classification within both the source and target domain data. Subsequently, a knowledge distillation framework incorporating a temperature factor is established to transfer fault features learned by the large teacher model in the source domain to the smaller student model, thereby reducing computational and parameter overhead. Finally, a multi-kernel domain adaptation method is employed to capture the feature probability distribution distance of fault characteristics between the source and target domains in Reproducing Kernel Hilbert Space (RKHS), and domain-invariant features are learned by minimizing the distribution distance between them. The effectiveness and applicability of the proposed method in situations of incomplete data across device types were validated through two engineering cases, spanning device models and transitioning from laboratory equipment to real-world operational devices.

Establishment and evaluation of glucose-modified nanocomposite liposomes for the treatment of cerebral malaria.

Cerebral malaria (CM) is a life-threatening neurological complication caused by Plasmodium falciparum. About 627,000 patients died of malaria in 2020. Currently, artemisinin and its derivatives are the front-line drugs used for the treatment of cerebral malaria. However, they cannot target the brain, which decreases their effectiveness. Therefore, increasing their ability to target the brain by the nano-delivery system with brain-targeted materials is of great significance for enhancing the effects of antimalarials and reducing CM mortality. This study used glucose transporter 1 (GLUT1) on the blood-brain barrier as a target for a synthesized cholesterol-undecanoic acid-glucose conjugate. The molecular dynamics simulation found that the structural fragment of glucose in the conjugate faced the outside the phospholipid bilayers, which was conducive to the recognition of brain-targeted liposomes by GLUT1. The fluorescence intensity of the brain-targeted liposomes (na-ATS/TMP@lipoBX) in the mouse brain was significantly higher than that of the non-targeted liposomes (na-ATS/TMP@lipo) in vivo (P < 0.001) after intranasal administration. The infection and recurrence rate of the mice receiving na-ATS/TMP@lipoBX treatment were significantly decreased, which had more advantages than those of other administration groups. The analysis of pharmacokinetic data showed that na-ATS/TMP@lipoBX could enter the brain in both systemic circulation and nasal-brain pathway to treat malaria. Taken together, these results in this study provide a new approach to the treatment of cerebral malaria.

Development of artesunate intelligent prodrug liposomes based on mitochondrial targeting strategy.

Breast cancer is the leading cause of cancer-related deaths in women and remains a formidable therapeutic challenge. Mitochondria participate in a myriad of essential cellular processes, such as metabolism, and are becoming an ideal target for cancer therapy. Artemisinin and its derivatives have demonstrated multiple activities in the context of various cancers. Mitochondrial autophagy(mitophagy) is one of the important anti-tumor mechanisms of artemisinin drugs. However, the lack of specific tumor targeting ability limits the anti-tumor efficacy of artemisinin drugs. In this study, a GSH-sensitive artesunate smart conjugate (TPP-SS-ATS) was synthesized and liposomes (TPP-SS-ATS-LS) that target tumor cells and mitochondria were further prepared. The advantages of TPP-SS-ATS-LS targeting to the breast tumor were verified by in vivo and in vitro evaluations. In our study, the cytotoxicity was obviously enhanced in vitro and tumor growth inhibition rate was increased from 37.7% to 56.4% at equivalent artesunate dosage in breast cancer orthotopic implanted mice. Meanwhile, mitochondrial dysfunction, suppression of ATP production and respiratory capacity were detected in breast cancer cells. We further discovered that TPP-SS-ATS-LS inhibited tumor cells proliferation through mitophagy by regulating PHB2 and PINK1 expression. These results provide new research strategies for the development of new artemisinin-based anti-tumor drugs.

[Research of preparation quality markers of Yulian Tang with anti-inflammatory activity].

The lipopolysaccharide(LPS)-indused RAW264.7 cells inflammation model was used as a carrier to investigated the effects of the preparation quality markers of Yulian Tang with anti-inflammatory activity in vitro. RAW264.7 cells were treated with LPS(50 ng·mL~(-1)) or/and different concentrations(low dose 0.1 µmol·L~(-1); medium dose 1 µmol·L~(-1); high dose 10 µmol·L~(-1)) of 18 chemical components in Yulian Tang for 24 h. Then the activity of RAW264.7 cell was detected using Cell Counting Kit-8(CCK-8) and the concentrations of inflammatory factors TNF-α and IL-6 in the supernatant of RAW264.7 cell were detected by ELISA assay. As the concentrations of chemical components in Yulian Tang increased, berberine, coptisine, magnoflorine, epiberberine, columbamine and costunolide had stronger inhibitory effects on TNF-α, whereas limonin, dehydroevodiamine, chlorogenic acid, neochlorogenic acid, groenlandicine, evodiamine, rutaecarpine and phellodendrine showed weakened inhibitory effects on TNF-α. The concentrations of palmatine, jatrorrhizine, dehydrocostus lactone and cryptochlorogenic acid had no significant effect on their inhibitory effect on TNF-α. Furthermore, dehydrorutaecarpine, chlorogenic acid, neochlorogenic acid, evodiamine, rutaecarpine, costunolide, phellodendrine and cryptochlorogenic acid showed stronger inhibitory effect on IL-6 as their concentrations increased; berberine, coptisine, magnoflorine, epiberberine, limonin, columbamine, groenlandicine and dehydrocostus lactone had no changes in their inhibitory effects on IL-6 as the concentrations increased. Palmatine and jatrorrhizine had the best inhibitory effect on IL-6. Combining the previous analysis of qualitative and quantitative preparation quality markers of Yulian Tang with the above result of dose-response relationship, we finally identified 15 preparation quality markers of Yulian Tang with anti-inflammatory activity, namely berberine, coptisine, palmatine, magnoflorine, epiberberine, limonin, columbamine, jatrorrhizine, neochlorogenic acid, chlorogenic acid, groenlandicine, evodiamine, rutaecarpine, dehydrocostus lactone and costunolide. In conclusion, our study provides a quick strategy for screening the qualitative preparation quality markers of Yulian Tang with anti-inflammatory activity. Moreover, it also provides an explicit route for the determination of preparation quality markers of Yulian Tang with other activities.

Clustering-Based Noise Elimination Scheme for Data Pre-Processing for Deep Learning Classifier in Fingerprint Indoor Positioning System.

Wi-Fi-based indoor positioning systems have a simple layout and a low cost, and they have gradually become popular in both academia and industry. However, due to the poor stability of Wi-Fi signals, it is difficult to accurately decide the position based on a received signal strength indicator (RSSI) by using a traditional dataset and a deep learning classifier. To overcome this difficulty, we present a clustering-based noise elimination scheme (CNES) for RSSI-based datasets. The scheme facilitates the region-based clustering of RSSIs through density-based spatial clustering of applications with noise. In this scheme, the RSSI-based dataset is preprocessed and noise samples are removed by CNES. This experiment was carried out in a dynamic environment, and we evaluated the lab simulation results of CNES using deep learning classifiers. The results showed that applying CNES to the test database to eliminate noise will increase the success probability of fingerprint location. The lab simulation results show that after using CNES, the average positioning accuracy of margin-zero (zero-meter error), margin-one (two-meter error), and margin-two (four-meter error) in the database increased by 17.78%, 7.24%, and 4.75%, respectively. We evaluated the simulation results with a real time testing experiment, where the result showed that CNES improved the average positioning accuracy to 22.43%, 9.15%, and 5.21% for margin-zero, margin-one, and margin-two error, respectively.

[Screening of quantitative preparation quality markers of Yulian Decoction].

On the basis of the qualitative preparation quality markers of Yulian Decoction, we screened out the quantitative markers and explored a general strategy for analyzing the component migration in Chinese herbal pieces, preparations, and plasma. A method capable of simultaneously determining 28 chemical components in Yulian Decoction was established based on HPLC-MS/MS. This method was used to determine the migrated components in herbal pieces-lyophilized powder preparations-rat plasma after administration of Yulian Decoction. Liquid chromatography was performed under the following conditions: C_(18)-reversed phase chromatographic column(2.1 mm × 100 mm, 1.8 µm); acetonitrile-water(containing 0.1% formic acid) as the mobile phase for gradient elution; the flow rate of 0.2 mL·min~(-1). Electrospray ionization source was adopted for mass spectrometry detection, in which positive and negative ion modes and multiple reaction monitoring were applied. Confirmed by the methodological investigation in linear range, recovery(95.48%-103.4%), precision(RSD, 0.45%-3.8%), stability, and repeatability(RSD, 5.6%-14%), the established method was suitable for the detection and quantification of the components in Yulian Decoction. The results showed that in the lyophilized powder of Yulian Decoction, berberine was greater than 5% in mass fraction, magnoflorine, epiberberine, coptisine, palmatine, and limonin in the range of 1%-5%, and dehydroevodiamine, evodiamine, rutaecarpine, costunolide, and dehydrocostus lactone in the range of 0.002%-1%. Of the 28 components detected in pieces, 27 were found to migrate to the lyophilized powder, and 11 were detected in rat plasma. Fifteen components were preliminarily determined as quantitative preparation quality markers for Yulian Decoction, including berberine, epiberberine, coptisine, palmatine, evodiamine, rutaecarpine, limonin, costunolide, dehydrocostus lactone, magnoflorine, jatrorrhizine, columbamine, groenlandicine, chlorogenic acid, and neochlorogenic acid. In conclusion, the HPLC-MS/MS general strategy was established for analyzing the migration of multiple components in Chinese herbal pieces, preparations, and plasma, which can provide the basis for the screening of quantitative preparation quality markers and multi-index quality control of Yulian Decoction.

[Study on classic preparations].

In this paper, classic preparations in Treatise on Febrile Diseases were systematically investigated to obtain their process parameters, and provide literature evidence and technical support for drug research and development. This paper includes the following sections: drug dose, solvents, excipients, and process parameters of classic preparations. The drug dose in Treatise on Febrile Diseases was not consistent with that in Pharmacopoeia of the People's Republic of China 2015, for example, "Yi-Liang" was about 15.625 g, and "Yi-Sheng" was about 200 mL. The solvents of classic preparations can be divided into two types: wine and water. There were eight kinds of water: water, "Dongliu water" "Ganlan water" "acid pulp" "Jinghua water" "Lao water" "Mafei Tang" "spring water". There four kinds of wines: "wine" "Bai wine" "Qing wine" "Ku wine". There were two kinds of excipients: rice and honey. Classic prescription powder had two kinds of processes: "whole prescription powder" and "Yidaoshai Hezhizhi powder". Classic prescription pills had three kinds of processes: direct whole prescription pilling, pilling after extraction, and pilling with excipients after smashing. Classic prescription decoction had six kinds of processes: "wine Tang", "Mafei Tang", "Jingmi Tang", "Mijian Tang", "water Tang" "Zhugao Tang". Drug dose, solvents, excipients, processes and other key parameters of classic preparations were systemically reviewed in this study, and the process parameters were clarified to provide literature evidence and technical support for drug development.

[Summarize drug dosage forms in treatment of age-related macular degeneration disease].

In this review, the authors summarized the drugs in treatment of the age-related macular degeneration (AMD or ARMD), including the pathogenesis of the age-related macular degeneration at home and abroad, dosage forms used in the treatment, and the drugs research and development directions in the future. AMD disease is the third largest blinding diseases all over the world, with an incidence of 6.62%. The dosage form of the traditional medicine is mostly oral formulations, playing a role in body, while the newly dosage form is topical drug delivery formulation. Traditional Chinese medicine (TCM) has certain advantages in the treatment of AMD disease and the development of topical drug delivery preparations with newly preparation technologies would have a very bright prospect in the future.

[Study on in vitro release and percutaneous absorption of Huoxue Zhitong gel].

To evaluate in vitro release and transdermal behaviors of Huoxue Zhitong gel, modified Franz diffusion cell methods was applied to investigate in vitro transdermal absorption of Huoxue Zhitong gel and the content of paeonolan in receptor fluid composed of PEG400%-95% ethanol-water (l:3:6)were determined by HPLC. The results were processed and different equations were fitted. The release law were in accordance with Weibull equation and the fitting equation was In[-1/(1 - Q)] = -0.790 51nt - 1.7012 (r = 0.9809). In 8 hours, cumulative release of paeonol was 85. 18% and the release rate was 2.827 µg . cm-2 h-1. Transdermal actions were consistent with zero-level model fit and the fitting equation was Q(t) = 1.7579t + 0. 7213 (r = 0.9991). In 8 hours, cumulative transdermal rate and transmission rate of paeonol was 54. 85%, 1. 820 µg . cm-2 h-1. So the Huoxue Zhitong gel had a good release and transdermal properties.

Emerindanols A and B: Two Bipolyhydroindenol Sesterterpenes with 5/6-6/5 Coupled Ring System Discovered by Genome Mining.

Genome mining of Emericella sp. XL-029 achieved a new type E sesterterpene synthase, EmES, which affored a novel bipolyhydroindenol sesterterpene, emerindanol A. Heterologous coexpression with the upstream P450 oxidase revealed C-4 hydroxylated product, emerindanol B. Notably, emerindanols A and B represented the first sesterterpenes featuring a unique 5/6-6/5 coupled ring system. EmES was postulated to initiate through C1-IV-V pathway and convert the fused ring intermediate into the final coupled ring product through a spiro skeleton.

Magnetized bentonite modified rice straw biochar: Qualitative and quantitative analysis of Cd(II) adsorption mechanism.

Industrialization has caused a significant global issue with cadmium (Cd) pollution. In this study, Biochar (Bc), generated through initial pyrolysis of rice straw, underwent thorough mixing with magnetized bentonite clay, followed by activation with KOH and subsequent pyrolysis. Consequently, a magnetized bentonite modified rice straw biochar (Fe3O4@B-Bc) was successfully synthesized for effective treatment and remediation of this problem. Fe3O4@B-Bc not only overcomes the challenges associated with the difficult separation of individual bentonite or biochar from water, but also exhibited a maximum adsorption capacity of Cd(II) up to 241.52 mg g-1. The characterization of Fe3O4@B-Bc revealed that its surface was rich in C, O and Fe functional groups, which enable efficient adsorption. The quantitative calculation of the contribution to the adsorption mechanism indicates that cation exchange and physical adsorption accounted for 65.87% of the total adsorption capacity. In conclusion, Fe3O4@B-Bc can be considered a low-cost and recyclable green adsorbent, with broad potential for treating cadmium-polluted water.

Recent Advances in Whiskers: Properties and Clinical Applications in Dentistry.

Whiskers are nanoscale, high-strength fibrous crystals with a wide range of potential applications in dentistry owing to their unique mechanical, thermal, electrical, and biological properties. They possess high strength, a high modulus of elasticity and good biocompatibility. Hence, adding these crystals to dental composites as reinforcement can considerably improve the mechanical properties and durability of restorations. Additionally, whiskers are involved in inducing the value-added differentiation of osteoblasts, odontogenic osteocytes, and pulp stem cells, and promoting the regeneration of alveolar bone, periodontal tissue, and pulp tissue. They can also enhance the mucosal barrier function, inhibit the proliferation of tumor cells, control inflammation, and aid in cancer prevention. This review comprehensively summarizes the classification, properties, growth mechanisms and preparation methods of whiskers and focuses on their application in dentistry. Due to their unique physicochemical properties, excellent biological properties, and nanoscale characteristics, whiskers show great potential for application in bone, periodontal, and pulp tissue regeneration. Additionally, they can be used to prevent and treat oral cancer and improve medical devices, thus making them a promising new material in dentistry.

Automatic three-dimensional facial symmetry reference plane construction based on facial planar reflective symmetry net.

OBJECTIVES: Three-dimensional (3D) facial symmetry analysis is based on the 3D symmetry reference plane (SRP). Artificial intelligence (AI) is widely used in the dental and oral sciences. This study developed a novel deep learning model called the facial planar reflective symmetry net (FPRS-Net) to automatically construct an SRP and established a method for defining a 3D point-cloud region of interest (ROI) and high-dimensional feature computations suitable for this network model. METHODS: Overall, 240 patients were enroled. The deep learning model was trained and predicted using 200 samples, and its clinical suitability was evaluated with 40 samples. Four FPRS-Net models were prepared, each using supervised and unsupervised learning approaches based on full facial and ROI data (FPRS-NetS, FPRS-NetSR, FPRS-NetU, and FPRS-NetUR). These models were trained on 160 3D facial datasets, validated on 20 cases, and tested on another 20 cases. The model predictions were evaluated using an additional 40 clinical 3D facial datasets by comparing the mean square error of the SRP between the parameters predicted by the four FPRS-Net models and the truth plane. The clinical suitability of FPRS-Net models was evaluated by measuring the angle error between the predicted and ground-truth planes; experts evaluated the predicted SRP of the four FPRS-Net models using the visual analogue scales (VAS) method. RESULTS: The FPRS-NetSR and FPRS-NetU models achieved an average angle error of 0.84° and 0.99° in predicting 3D facial SRP, respectively, with a VAS value of >8. Using the four FPRS-Net models to create an SRP in 40 cases of 3D facial data required <4 s. CONCLUSIONS: Our study demonstrated a new solution for automatically constructing oral clinical 3D facial SRPs. CLINICAL SIGNIFICANCE: This study proposes a novel deep learning algorithm (FPRS-Net) to construct a symmetry reference plane that can reduce workload, shorten the time required for digital design, reduce dependence on expert experience, and improve therapeutic efficiency and effectiveness in dental clinics.

Low-Power Perovskite Neuromorphic Synapse with Enhanced Photon Efficiency for Directional Motion Perception.

The advancement of artificial intelligent vision systems heavily relies on the development of fast and accurate optical imaging detection, identification, and tracking. Framed by restricted response speeds and low computational efficiency, traditional optoelectronic information devices are facing challenges in real-time optical imaging tasks and their ability to efficiently process complex visual data. To address the limitations of current optoelectronic information devices, this study introduces a novel photomemristor utilizing halide perovskite thin films. The fabrication process involves adjusting the iodide proportion to enhance the quality of the halide perovskite films and minimize the dark current. The photomemristor exhibits a high external quantum efficiency of over 85%, which leads to a low energy consumption of 0.6 nJ. The spike timing-dependent plasticity characteristics of the device are leveraged to construct a spiking neural network and achieve a 99.1% accuracy rate of directional perception for moving objects. The notable results offer a promising hardware solution for efficient optoneuromorphic and edge computing applications.

A Self-Oscillated Organic Synapse for In-Memory Two-Factor Authentication.

Entering the era of AI 2.0, bio-inspired target recognition facilitates life. However, target recognition may suffer from some risks when the target is hijacked. Therefore, it is significantly important to provide an encryption process prior to neuromorphic computing. In this work, enlightened from time-varied synaptic rule, an in-memory asymmetric encryption as pre-authentication is utilized with subsequent convolutional neural network (ConvNet) for target recognition, achieving in-memory two-factor authentication (IM-2FA). The unipolar self-oscillated synaptic behavior is adopted to function as in-memory asymmetric encryption, which can greatly decrease the complexity of the peripheral circuit compared to bipolar stimulation. Results show that without passing the encryption process with suitable weights at the correct time, the ConvNet for target recognition will not work properly with an extremely low accuracy lower than 0.86%, thus effectively blocking out the potential risks of involuntary access. When a set of correct weights is evolved at a suitable time, a recognition rate as high as 99.82% can be implemented for target recognition, which verifies the effectiveness of the IM-2FA strategy.

Correction: Affective computing for human-machine interaction via a bionic organic memristor exhibiting selective in situ activation.

Correction for 'Affective computing for human-machine interaction via a bionic organic memristor exhibiting selective in situ activation' by Bingjie Guo et al., Mater. Horiz., 2024, https://doi.org/10.1039/D3MH01950K.

Affective computing for human-machine interaction via a bionic organic memristor exhibiting selective in situ activation.

Affective computing, representing the forefront of human-machine interaction, is confronted with the pressing challenges of the execution speed and power consumption brought by the transmission of massive data. Herein, we introduce a bionic organic memristor inspired by the ligand-gated ion channels (LGICs) to facilitate near-sensor affective computing based on electroencephalography (EEG). It is constructed from a coordination polymer comprising Co ions and benzothiadiazole (Co-BTA), featuring multiple switching sites for redox reactions. Through advanced characterizations and theoretical calculations, we demonstrate that when subjected to a bias voltage, only the site where Co ions bind with N atoms from four BTA molecules becomes activated, while others remain inert. This remarkable phenomenon resembles the selective in situ activation of LGICs on the postsynaptic membrane for neural signal regulation. Consequently, the bionic organic memristor network exhibits outstanding reliability (200 000 cycles), exceptional integration level (210 pixels), ultra-low energy consumption (4.05 pJ), and fast switching speed (94 ns). Moreover, the built near-sensor system based on it achieves emotion recognition with an accuracy exceeding 95%. This research substantively adds to the ambition of realizing empathetic interaction and presents an appealing bionic approach for the development of novel electronic devices.

[Study on percutaneous absorption of xiaozheng zhitong cataplasm].

OBJECTIVE: To study the transdermal behavior of Xiaozheng Zhitong cataplasm in rats. METHOD: With tetrahydropalmatine as the index, the Franz diffusion cell method was adopted for the experiment. Sample content was determined with HPLC. RESULT: The transdermal permeability and the transmission rate of tetrahydropalmatine accumulated for 24 h were 20.20% and 0.744 1 microg x cm(-2) x h(-1), respectively. CONCLUSION: The transdermal behaviors of Xiaozheng Zhitong cataplasm were ideal in conformity with the zero order kinetic model.

[Study on in vitro release and percutaneous absorption for Zhitong cataplasm].

To evaluate in vitro release and transdermal behaviors of Zhitong cataplasm, modified Franz diffusion cell method was applied to investigate in vitro transdermal absorption of Zhitong cataplasm and the content of tetrahydropalmatine was determined by HPLC. In 24 hours, accumulative release rate of tetrahydropalmatine was 81. 9%, transmission rate was 2.26 microg x cm(-2) x h(-1). In 48 hours, accumulative transdermal rate and transmission rate of tetrahydropalmatine were 20.31%, 0.22 pg x cm(-2) x h(-1). So Zhitong cataplasm had a good release and transdermal properties and transdermal actions were consistent with zero-order kinetics process.