IFKMHC: Implicit Fuzzy K-Means Model for High-Dimensional Data Clustering.

The graph-information-based fuzzy clustering has shown promising results in various datasets. However, its performance is hindered when dealing with high-dimensional data due to challenges related to redundant information and sensitivity to the similarity matrix design. To address these limitations, this article proposes an implicit fuzzy k-means (FKMs) model that enhances graph-based fuzzy clustering for high-dimensional data. Instead of explicitly designing a similarity matrix, our approach leverages the fuzzy partition result obtained from the implicit FKMs model to generate an effective similarity matrix. We employ a projection-based technique to handle redundant information, eliminating the need for specific feature extraction methods. By formulating the fuzzy clustering model solely based on the similarity matrix derived from the membership matrix, we mitigate issues, such as dependence on initial values and random fluctuations in clustering results. This innovative approach significantly improves the competitiveness of graph-enhanced fuzzy clustering for high-dimensional data. We present an efficient iterative optimization algorithm for our model and demonstrate its effectiveness through theoretical analysis and experimental comparisons with other state-of-the-art methods, showcasing its superior performance.

Three-component acyloxylation of diazo compounds with carboxylic acids and azadienes.

Despite many studies on benzofuran-derived azadiene being reported, multi-component studies have scarcely been reported on this heterocyclic skeleton. The first cascade three-component acyloxylation of diazos with acids and azadienes has been reported under mild conditions. The reaction is applicable to various (A/A) diazo compounds, generating diverse complex benzofuran derivatives.

Hui Medicine Moxibustion Promotes the Absorption of Lumbar Disc Herniation and the Recovery of Motor Function in Rats through Fas/FasL Signaling Pathway.

Objectives: To study the resorption of the herniated lumbar disc (RHLD) and its mechanism in the SD rats of lumbar intervertebral disc herniation treated with Hui medicine moxibustion (HMM). Methods: Forty SD rats were randomly divided into four groups, normal group, lumbar disc herniation (LDH) group, HMM group, and antagonist (HMM+Met12) group, with 10 rats in each group. The rat model of LDH was prepared with the method of lumbar epidural emplacement of the caudal intervertebral disc. In the HMM group and HMM+Met12 groups, 4 weeks after modeling, HMM therapy was performed in the lumbar spine for 3 months with 1 time per day and 20 min each time, the samples were collected 8 weeks after the treatment. The histological degeneration was observed through HE staining, and the neovascularization of intervertebral disc tissues was detected by the expression of CD34 and vascular endothelial growth factor (VEGF). The apoptosis of nucleus pulpous cells was detected by TUNEL assay, and the activity of caspase-3, -8, and -9 and extracellular matrix enzymes was detected by western blotting. Results: HMM treatment significantly improved the behavioral ability of rats with LDH surgery. The morphological structure was obviously destroyed in the LDH group, but disc structure was significantly repaired in the HMM group, and mild structure alterations were observed in the HMM+Met12 group. Higher levels of CD34 and VEGF were detected in the HMM group indicating that neovascularization is formed. The expression level of FasL was significantly increased in the HMM group. The protein expression levels of cleaved-caspase-3, cleaved-caspase-8, and cleaved-caspase-9 in nucleus pulposus (NP) tissues were also elevated when treated with HMM, and the TUNEL staining showed the same results. The protein expression levels of matrix metalloproteinases- (MMP-) 1, MMP-2, MMP-3, MMP-13, and ADAMTS-4 were markedly promoted in the HMM group. Met12, a small peptide antagonist of FasL, significantly reduced the effects of HMM. Conclusion: HMM can promote the formation of neovascularization of lumbar intervertebral disc, support the apoptosis of NP cells through Fas/FasL signaling, and regulate the degradation of extracellular matrix enzyme, which then accelerates the absorption of lumbar intervertebral disc herniation and the recovery of motor function in rats.

On the philosophical, cognitive and mathematical foundations of symbiotic autonomous systems.

Symbiotic autonomous systems (SAS) are advanced intelligent and cognitive systems that exhibit autonomous collective intelligence enabled by coherent symbiosis of human-machine interactions in hybrid societies. Basic research in the emerging field of SAS has triggered advanced general-AI technologies that either function without human intervention or synergize humans and intelligent machines in coherent cognitive systems. This work presents a theoretical framework of SAS underpinned by the latest advances in intelligence, cognition, computer, and system sciences. SAS are characterized by the composition of autonomous and symbiotic systems that adopt bio-brain-social-inspired and heterogeneously synergized structures and autonomous behaviours. This paper explores the cognitive and mathematical foundations of SAS. The challenges to seamless human-machine interactions in a hybrid environment are addressed. SAS-based collective intelligence is explored in order to augment human capability by autonomous machine intelligence towards the next generation of general AI, cognitive computers, and trustworthy mission-critical intelligent systems. Emerging paradigms and engineering applications of SAS are elaborated via autonomous knowledge learning systems that symbiotically work between humans and cognitive robots. This article is part of the theme issue 'Towards symbiotic autonomous systems'.

Hyperspectral Leaf Image-Based Cucumber Disease Recognition Using the Extended Collaborative Representation Model.

Collaborative representation (CR)-based classification has been successfully applied to plant disease recognition in cases with sufficient training samples of each disease. However, collecting enough training samples is usually time consuming and labor-intensive. Moreover, influenced by the non-ideal measurement environment, samples may be corrupted by variables introduced by bad illumination and occlusions of adjacent leaves. Consequently, an extended collaborative representation (ECR)-based classification model is presented in this paper. Then, it is applied to cucumber leaf disease recognition, which constructs a pure spectral library consisting of several representative samples for each disease and designs a universal variation spectral library that deals with linear variables superimposed on samples. Thus, each query sample is encoded as a linear combination of atoms from these two spectral libraries and disease identity is determined by the disease of minimal reconstruction residuals. Experiments are conducted on spectral curves extracted from normal leaves and the disease lesions of leaves infected with cucumber anthracnose and brown spot. The diagnostic accuracy is higher than 94.7% and the average online diagnosis time is short, about 1 to 1.3 ms. The results indicate that the ECR-based classification model is feasible in the fast and accurate diagnosis of cucumber leaf diseases.

Effects of extreme pH conditions on the stability of As(V)-bearing schwertmannite.

Schwertmannite (Sch) is known to be an effective scavenger of arsenic (As) due to its strong binding affinity for toxic As species. However, the evolution of As-bearing schwertmannite under extreme pH conditions is poorly understood. In this study, we investigated the effects of extremely acidic and alkaline conditions on the stability of schwertmannite with structurally incorporated As(V) (CO-Sch) and schwertmannite with adsorbed As(V) (AD-Sch). The results show that both extremely acidic and alkaline conditions have significant effects on the evolution of minerals and liberation of iron and sulfate. At extremely acidic pH, the maximal release of ferric iron (Fe(III)) and sulfate from CO-Sch were greater than that from AD-Sch, whereas 6.2% and 0.3% of total As released from AD-Sch and CO-Sch, respectively. At extremely alkaline pH, aqueous Fe(III) was not observed, and Fe(III) was retained in As-bearing schwertmannite due to the chemical equilibrium between the dissolution of schwertmannite and re-precipitation of goethite; structurally incorporated As(V) promoted the liberation of sulfate. In addition, the adsorbed As on schwertmannite is more stable, which led to a minor release of As (0.8%) over a 30-d period, however, the liberated As(V) from CO-Sch accounts for up to 3.2%. Under extremely acidic and alkaline conditions, portions of AD-Sch and CO-Sch transformed from schwertmannite to goethite after 30 d, while schwertmannite was still the dominant mineral. Adsorbed As(V) inhibited the transformation of As-bearing schwertmannite to goethite more significantly than structurally incorporated As(V).

Graph Constraint and Collaborative Representation Classifier Steered Discriminative Projection with Applications for the Early Identification of Cucumber Diseases.

Accurate, rapid and non-destructive disease identification in the early stage of infection is essential to ensure the safe and efficient production of greenhouse cucumbers. Nevertheless, the effectiveness of most existing methods relies on the disease already exhibiting obvious symptoms in the middle to late stages of infection. Therefore, this paper presents an early identification method for cucumber diseases based on the techniques of hyperspectral imaging and machine learning, which consists of two procedures. First, reconstruction fidelity terms and graph constraints are constructed based on the decision criterion of the collaborative representation classifier and the desired spatial distribution of spectral curves (391 to 1044 nm) respectively. The former constrains the same-class and different-class reconstruction residuals while the latter constrains the weighted distances between spectral curves. They are further fused to steer the design of an offline algorithm. The algorithm aims to train a linear discriminative projection to transform the original spectral curves into a low dimensional space, where the projected spectral curves of different diseases own better separation trends. Then, the collaborative representation classifier is utilized to achieve online early diagnosis. Five experiments were performed on the hyperspectral data collected in the early infection stage of cucumber anthracnose and Corynespora cassiicola diseases. Experimental results demonstrated that the proposed method was feasible and effective, providing a maximal identification accuracy of 98.2% and an average online identification time of 0.65 ms. The proposed method has a promising future in practical production due to its high diagnostic accuracy and short diagnosis time.

Human Body Mixed Motion Pattern Recognition Method Based on Multi-Source Feature Parameter Fusion.

Aiming at the requirement of rapid recognition of the wearer's gait stage in the process of intelligent hybrid control of an exoskeleton, this paper studies the human body mixed motion pattern recognition technology based on multi-source feature parameters. We obtain information on human lower extremity acceleration and plantar analyze the relationship between these parameters and gait cycle studying the motion state recognition method based on feature evaluation and neural network. Based on the actual requirements of exoskeleton per use, 15 common gait patterns were determined. Using this, the studies were carried out on the time domain, frequency domain, and energy feature extraction of multi-source lower extremity motion information. The distance-based feature screening method was used to extract the optimal features. Finally, based on the multi-layer BP (back propagation) neural network, a nonlinear mapping model between feature quantity and motion state was established. The experimental results showed that the recognition accuracy in single motion mode can reach up to 98.28%, while the recognition accuracy of the two groups of experiments in mixed motion mode was found to be 92.7% and 97.4%, respectively. The feasibility and effectiveness of the model were verified.

Jinzhi protects lipopolysaccharide-treated mice against mortality by repairing intestinal mucosal barrier damage and intestinal microecology.

OBJECTIVE: Intestinal mucosal barrier damage is an important mechanism for the development of sepsis and multiple organ dysfunction syndrome. At present, there are no satisfactory and effective methods for the protection of the intestinal mucosal barrier. Jinzhi, the first fecal microbiota transplantation worldwide, is often used to treat critically ill patients; however, the specific mechanism involved in this process remains unclear. The aim of this study was to investigate the therapeutic effect and mechanism of Jinzhi intervention on mice with sepsis induced through treatment with lipopolysaccharide (LPS). METHODS: Mice were intraperitoneally injected with LPS to simulate intestinal mucosal barrier function damage in sepsis; intervention was performed through the oral administration of Jinzhi. The effect of Jinzhi on LPS-induced sepsis was analyzed by comparing the vital signs and survival rate of mice under different treatments. Pathological staining and enzyme-linked immunosorbent assay were used to identify the effects of LPS or treatment with Jinzhi on the intestinal mucosal barrier in mice. The effect of LPS or treatment with Jinzhi on the intestinal flora was analyzed via 16S rRNA gene sequencing of ileal contents. RESULTS: Immunohistochemistry and enzyme-linked immunosorbent assay showed that treatment with LPS increased levels of inflammatory factors (interleukin-1α, interleukin-6, tumor necrosis factor-α), caspase-3, and caspase-8 in the serum and ileum, and destroyed the tight junction between epithelial cells. Intervention with Jinzhi reduced levels of serum LPS and tumor necrosis factor-α, and repaired the tight junction between epithelial cells. Furthermore, 16S rRNA gene sequencing analysis showed that treatment with Jinzhi improved the diversity and physiological function of the intestinal flora. CONCLUSIONS: These results suggest that Jinzhi may be a promising option for the treatment of sepsis caused by LPS, and emphasize that Jinzhi exerts a recovery effect on the imbalance of intestinal flora.

In-situ remediation of hexavalent chromium contaminated groundwater and saturated soil using stabilized iron sulfide nanoparticles.

Hexavalent chromium (Cr(VI)) is one of prevalent toxic and mobile heavy metal contaminants in the environment. In this study, synthetic iron sulfide nanoparticles (FeS NPs) stabilized with carboxymethyl cellulose (CMC) were applied to remediate Cr(VI) contaminated groundwater and saturated soil. The batch test results showed that aqueous Cr(VI) was removed with a capacity as high as 1046.1 mg Cr(VI) per gram of FeS NPs. The removal of aqueous Cr(VI) mainly involves adsorption, reduction and co-precipitation. Aqueous Cr(VI) removal by using FeS NPs was a strong pH-dependent process. Dissolved oxygen (DO) would compete with Cr(VI) for Fe(II) and S(-II) and inhibit the process of Cr(VI) reduction at pH 5.6. For ionic strength and natural organic matter (NOM), there were no significant influences on the aqueous Cr(VI) removal. Column tests demonstrated that the concentrations of Cr(VI) in the effluent were lower than 0.005 mg L-1 after an elution of 45 pore volumes (PVs) of stabilized FeS NPs suspension. The leached Cr(VI) decreased from 4.58 mg L-1 of raw Cr(VI)-contaminated soil to 46.8-80.7 µg L-1 from the surface to bottom treated soil in column through Toxicity Characteristic Leaching Procedure (TCLP). Therefore, the synthesized FeS NPs hold high potential for the in-situ remediation of Cr(VI)-contaminated groundwater and saturated soil.

Uncertain Data Clustering in Distributed Peer-to-Peer Networks.

Uncertain data clustering has been recognized as an essential task in the research of data mining. Many centralized clustering algorithms are extended by defining new distance or similarity measurements to tackle this issue. With the fast development of network applications, these centralized methods show their limitations in conducting data clustering in a large dynamic distributed peer-to-peer network due to the privacy and security concerns or the technical constraints brought by distributive environments. In this paper, we propose a novel distributed uncertain data clustering algorithm, in which the centralized global clustering solution is approximated by performing distributed clustering. To shorten the execution time, the reduction technique is then applied to transform the proposed method into its deterministic form by replacing each uncertain data object with its expected centroid. Finally, the attribute-weight-entropy regularization technique enhances the proposed distributed clustering method to achieve better results in data clustering and extract the essential features for cluster identification. The experiments on both synthetic and real-world data have shown the efficiency and superiority of the presented algorithm.

Effect of stimulating acupoint Guanyuan (CV 4) on lower back pain by burning moxa heat for different time lengths: a randomized controlled clinical trial.

OBJECTIVE: To investigate the effect of different heat-stimulating time lengths on lower back pain. METHODS: Forty participants were randomly assigned to four groups of various heating time lengths. The short heating time length group (SL), moderate heating time length group (ML), and long heating time length group (LL) respectively received 15, 30, and 60 min of moxibustion therapy stimulating the acupoint Guanyuan (CV 4). The conventional acupuncture group (CA) received needle acupuncture treatment as a control group. The participants were treated continuously over a 2-week treatment period for a total of 10 sessions, with five sessions given per week. Participants were assessed weekly by blinded assessors,using the visual analogue scale (VAS) and Roland Morris Questionnaire (RMQ). RESULTS: The VAS and RMQ scores reduced in all four groups during treatment. There were significant differences in VAS scores (P < 0.01) and RMQ scores (P < 0.01) between before treatment and after 2 weeks of treatment in the LL group. After treatment, the LL group reported significantly lower VAS scores compared with the CA group, ML group, and SL group (P < 0.05). CONCLUSION: The long and moderate lengths of heat-stimulating time of 30 and 60 min may be more effective for relieving lower back pain than that of short stimulating time lengths.

Effect of acupuncture anesthesia on acne vulgaris of pricking-bloodletting cupping: a single-blind randomized clinical trail.

OBJECTIVE: To evaluate the effect on acne vulgaris of pricking-bloodletting cupping at Dazhui (GV 14) under acupuncture anesthesia, and establish whether providing anesthesia to the treatment area by manipulating Hegu (LI 4) and Quchi (LI 11) might have an additional therapeutic benefit. METHODS: Thirty-eight patients were recruited and randomized into a control group and an intervention group with a single-blind (observer-blind) method. The control group was treated by pricking-bloodletting cupping at Dazhui (GV 14)-and the studied group by pricking-bloodletting cupping at Dazhui (GV 14) under acupuncture anesthesia at Hegu (LI 4) and Quchi (LI 11). Both groups were treated twice weekly for 6 weeks. The analgesic and therapeutic effects of acupuncture were evaluated on a visual analog scale (VAS) and global acne grading system (GAGS), respectively. RESULTS: There were differences in the VAS scores of pain on pricking and in the pricked area, and the duration of pain between the groups. After 12 treatments, there was a significant reduction in GAGS scores from baseline in both groups, but there was no significant difference between the groups. CONCLUSION: Acupuncture anesthesia at Hegu (LI 4) and Quchi (LI 11) is an effective means of alleviating the pain of pricking-bloodletting cupping and reducing the duration of pain in the treatment area. Pricking-bloodletting cupping at Dazhui (GV 14) improves the skin lesions of patients with moderate acne vulgaris, but acupuncture anesthesia does not appear to have an additional therapeutic effect.

Optimum predrilled hole size for bone screws used in osteochondral fixation: in vitro biomechanical study and clinical case.

BACKGROUND: Bone screws have a mechanical advantage over bone pegs for fixation of osteochondral fractures. The purpose of this study was to investigate predrilling methods to facilitate bone screw insertion. METHODS: The 162 bone screws (major diameter 3.0 mm; minor diameter 2.5 mm; length 10 mm) used were made from porcine tibial cortical bone. Metal screws of the same design were used as a control. The screws were inserted, without tapping, into predrilled holes of six different sizes (2.4-2.9 mm diameter; 80%-97% of the screw) made in cancellous bone harvested from porcine femoral condyle, and pullout strength was determined. The volumetric bone mineral densities of porcine bones were compared to those of human bones. In a clinical case, an osteochondral fracture of the patella was repaired using three autologous bone screws. RESULTS: Bone screws occasionally broke due to high insertion torque (108-158 N.mm); the incidences were 30% and 19% with the 80% and 83% sized holes, respectively. None of the screws inserted into holes of size >/= 87% broke, and their insertion torques never exceeded 100 N.mm. Metal screws were inserted without breakage regardless of hole size. Bone screws inserted into 80%-93% holes had the greatest pullout strengths (range 154-165 N), whereas 97% holes had a mean strength of 84 N. Metal screws had large pullout strengths when inserted into 80% and 83% holes (164 and 169 N, respectively). The mineral density of porcine bone was lower than that of human bone (1167 and 1357 mg/cm(3) for cortical bone and 193 and 269 mg/cm(3) for cancellous bone, respectively). In the clinical case, bone screws were inserted smoothly into 90% holes. CONCLUSIONS: The optimal size of predrilled holes for bone screws (87%-93%) differs from that for metal screws.

Proximal half angle of the screw thread is a critical design variable affecting the pull-out strength of cancellous bone screws.

BACKGROUND: Screws with strong pull-out strength have been sought for the treatment of cancellous bone. We hypothesized that an obliquely angled screw thread has advantages over conventional vertical thread with a minimal proximal half angle. METHODS: Metal and bone screws were made of stainless steel and porcine cortical bone. Their proximal half angle was set at 0 degrees , 30 degrees , or 60 degrees . The screws were inserted into porcine cancellous bone. At 0 degrees , the thread faced the recipient bone vertically. Pullout tests at a rate of 30 mm/min (n=40, each screw type) and microcomputed tomography (n=6) were conducted. FINDINGS: The pull-out strength of the screws was maximal at 30 degrees ; 348.8 (SD, 44.1)N with metal and 326.6 (39.4)N with bone. It was intermediate at 0 degrees ; 301.9 (35.9)N with metal and 278.2 (30.6)N with bone. It was minimal at 60 degrees; 126.5 (39.0)N with metal and 174.8 (29.7)N with bone. Cancellous bone was damaged between the threads at 30 degrees , while intact cancellous bone was preserved between the threads at 0 degrees. INTERPRETATION: A proximal half angle of around 30 degrees is appropriate because the pullout force is applied to the recipient bone evenly. Commercial cancellous screws can be improved by changing the thread shape to minimize the damage to recipient bone.

Contemporary cybernetics and its facets of cognitive informatics and computational intelligence.

This paper explores the architecture, theoretical foundations, and paradigms of contemporary cybernetics from perspectives of cognitive informatics (CI) and computational intelligence. The modern domain and the hierarchical behavioral model of cybernetics are elaborated at the imperative, autonomic, and cognitive layers. The CI facet of cybernetics is presented, which explains how the brain may be mimicked in cybernetics via CI and neural informatics. The computational intelligence facet is described with a generic intelligence model of cybernetics. The compatibility between natural and cybernetic intelligence is analyzed. A coherent framework of contemporary cybernetics is presented toward the development of transdisciplinary theories and applications in cybernetics, CI, and computational intelligence.