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Magnetic separation has been proposed to greenly separate chalcopyrite and talc several decades ago, due to their extremely similar floatability of minerals. However, this approach was not achieved initially due to the inadequately magnetic induction of traditional magnetic separation, and fine particle size of chalcopyrite. Currently, the development of highly magnetic induction technology provides strong feasibility for this separation. In this work, we employed pulsating high-gradient magnetic separation (PHGMS) with highly magnetic induction (1.8T) to separate chalcopyrite and talc, and found that the PHGMS achieves a good separation of chalcopyrite from talc. But the chalcopyrite recovery decreased with the decrease of its particle size, and thus surface oxidation treatment was attempted to increase the magnetism and magnetic capture of ultrafine chalcopyrite. As a result, an increment of approximately 10 % was observed in the recovery of ultrafine chalcopyrite post-oxidation. As verified by the superconducting quantum interference device measurements, the oxidized ultrafine chalcopyrite exhibited a significant increase in the saturation magnetisation intensity, remanent magnetisation and coercivity values. Such magnetism enhancement is a result of the formation of paramagnetic Fe(III)–O–OH structures on the oxidized chalcopyrite surface, in terms of X-ray photoelectron spectroscopy and Mössbauer spectroscopy investigations. Furthermore, the density functional theory revealed that the formation of Fe(III)–O–OH structures caused a substantial increase in the magnetic moments of iron ions in antiferromagnetic chalcopyrite. These findings may extend the application of magnetic separation, and facilitate the flotation of ultrafine chalcopyrite from other minerals, at significantly reduced reagents use, and productive and environmental costs.

Abstract The capacitance model suitable for the non-circular cross-section plasma is studied based on the capacitance model of the circular cross-section plasma. The coaxial elliptic-torus capacitor property is further derived and used to determine the capacity of non-circular cross-section tokamak plasma, such as EAST (Experimental Advanced Superconducting Tokamak). By testing all the physical terms in this model, we find that the capacitance $$Cp$$ Cp ) is increasing exponentially with the increase of elongation ratio (k 2/k 1), while the minor radius ratio (a 2/a 1) is just reversed at the flat-top of plasma current, and the capacitance property is implicitly included in the H-mode study during the L–H transition. It is noted that C p-H mode is the least and C p-I mode is approximately equal to C p-L mode under the L-mode, I-mode and H-mode regimes based on this capacitance model in EAST. Consequently, it may be integrated into an equivalent circuit of the tokamak transformer or transport computer code of the edge plasma for use in precise simulations of fusion plasma behavior in the future, such as ITER (International Tokamak Experimental Reactor) or BEST (Burning-plasma Experimental Superconducting Tokamak) in China.

Spinal cord injury (SCI) is a major clinical problem in young patients. The major hurdle in SCI regeneration is the replacement of lost nerve communication signals due to injury. Here we have prepared a biocompatible electrical conductive composite such as Collagen-Polypyrrole combined with Quercetin (Col-PPy-Qur) composite. The prepared composites are characterized for their chemical functionality and morphology by the FTIR and SEM & TEM analysis, respectively. The Col-PPy-Qur composite observed electrical conductivity at 0.0653 s/cm due to the conductive Polypyrrole polymer present in the composite. The Col-PPy-Qur composite exhibits a mechanical strength of 0.1281 mPa, similar to the native human spinal cord's mechanical strength. In order to explore the regeneration potential, the viability of the composite has been tested with human astrocyte cells (HACs). The Tuj1 and GFAF marker expression was quantized by RT-PCR analysis. Increased Tuj1 and decreased GFAF expression by the Col-PPy-Qur composite indicated the potential differentiation ability of the HACs into neuron cells. The results indicated that the Col-PPy-Qur composite could have good regeneration and differentiation ability, better biocompatibility, and suitable mechanical and conductivity properties. It can act as an excellent strategy for spinal cord regeneration in the nearer future.

AbstractContext Intervertebral disc degeneration (IDD) is the pathological basis of spinal degenerative diseases. Puerarin (PU) is an isoflavonoid with functions and medicinal properties.Objective To explore the effect of PU on IDD and its potential mechanism of action.Materials and methods Sprague-Dawley (SD) rats were divided into sham, IDD, low PU, and high PU groups. Rat nucleus pulposus cells (NPCs) were isolated and divided into control, IL-1β, 100 and 200 μmol/mL PU, TAK-242 (TLR4 inhibitor), or 200 μmol/mL PU + LPS (TLR4 activator) groups. The water content, inflammatory factors, proliferation activity, TLR4/NF-κB pathway activity, apoptosis rate, protein expression of apoptosis, and histology of the extracellular matrix (ECM) were analysed.Results In vivo: Compared with the IDD group, disorganization of intervertebral disc tissue was significantly improved, water content (2.80 ± 0.24 mg, 3.91 ± 0.31 mg vs. 2.02 ± 0.21 mg) and expression levels of collagen II and aggrecan were significantly increased, and the levels of inflammatory factors and the expression levels of TLR4, MyD88, and p-p65 were significantly decreased in IDD rats treated with PU. In vitro: Compared with the IL-1β group, the proliferation activity of IL-1β-treated NPCs and the expression of collagen II and aggrecan were significantly increased, while the apoptosis rate, levels of inflammatory factors, and the expression levels of TLR4, MyD88, and p-p65 were significantly decreased in IL-1β-treated NPCs treated with PU. LPS reversed the biological function changes of IL-1β-treated NPCs induced by PU.Conclusions PU can delay the progression of IDD by inhibiting activation of the TLR4/NF-κB pathway.

In the construction of new power systems, the traditional network security protection mainly based on boundary protection belongs to static defense and still relies mainly on manual processing in vulnerability repair, threat response, etc. It is difficult to adapt to the security protection needs in large-scale distributed new energy, third-party aggregation platforms, and flexible interaction scenarios with power grid enterprise systems. It is necessary to conduct research on dynamic security protection models for IoT and other Blockchain-based IoT architectures. This article proposes a network security comprehensive protection model P2AEDR based on different interaction modes of cloud–edge interaction and cloud–cloud interaction. Through continuous trust evaluation, dynamic access control, and other technologies, it strengthens the internal defense capabilities of power grid business, shifting from static protection as the core mode to a real-time intelligent perception and automated response mode, and ultimately achieving the goal of dynamic defense, meeting the security protection needs of large-scale controlled terminal access and third-party aggregation platforms. Meanwhile, this article proposes a dynamic trust evaluation algorithm based on deep learning, which protects the secure access and use of various resources in a more refined learning approach based on the interaction information monitored in the system. Through experimental verification of the dynamic trust evaluation algorithm, it is shown that the proposed model has good trust evaluation performance. Therefore, this research is beneficial for trustworthy Power IoT and other Blockchain-based IoT architectures.

Exercise is increasingly recognized as an effective strategy to counteract skeletal muscle aging and conditions such as sarcopenia. However, the specific exercise-induced genes responsible for these protective effects remain unclear. To address this, we conducted an eight-week aerobic exercise regimen on late-middle-aged mice and developed an integrated approach that combines mouse exercise-induced genes with human GWAS datasets to identify causal genes for sarcopenia. This approach led to significant improvements in the skeletal muscle phenotype of the mice and the identification of exercise-induced genes and miRNAs. By constructing a miRNA regulatory network enriched with transcription factors and GWAS signals related to muscle function and traits, we focused on 896 exercise-induced genes. Using human skeletal muscle cis-eQTLs as instrumental variables, 250 of these exercise-induced genes underwent two-sample Mendelian randomization analysis, identifying 40, 68, and 62 causal genes associated with sarcopenia and its clinical indicators—appendicular lean mass (ALM) and hand grip strength (HGS), respectively. Sensitivity analyses and cross-phenotype validation confirmed the robustness of our findings. Consistently across the three outcomes, RXRA, MDM1, RBL2, KCNJ2, and ADHFE1 were identified as risk factors, while NMB, TECPR2, MGAT3, ECHDC2, and GINM1 were identified as protective factors, all with potential as biomarkers for sarcopenia progression. Biological activity and disease association analyses suggested that exercise exerts its anti-sarcopenia effects primarily through the regulation of fatty acid oxidation. Based on available drug–gene interaction data, 21 of the causal genes are druggable, offering potential therapeutic targets. Our findings highlight key genes and molecular pathways potentially responsible for the anti-sarcopenia benefits of exercise, offering insights into future therapeutic strategies that could mimic the safe and mild protective effects of exercise on age-related skeletal muscle degeneration.

Satellite multi-view stereo (MVS) is a fundamental task in large-scale Earth surface reconstruction. Recently, learning-based multi-view stereo methods have shown promising results in this field. However, these methods are mainly developed by transferring the general learning-based MVS framework to satellite imagery, which lacks consideration of the specific terrain features of the Earth’s surface and results in inadequate accuracy. In addition, mainstream learning-based methods mainly use equal height interval partition, which insufficiently utilizes the height hypothesis surface, resulting in inaccurate height estimation. To address these challenges, we propose an end-to-end terrain feature-aware height estimation network named SA-SatMVS for large-scale Earth surface multi-view stereo, which integrates information across different scales. Firstly, we transform the Sobel operator into slope feature-aware kernels to extract terrain features, and a dual encoder–decoder architecture with residual blocks is applied to incorporate slope information and geometric structural characteristics to guide the reconstruction process. Secondly, we introduce a pixel-wise unequal interval partition method using a Laplacian distribution based on the probability volume obtained from other scales, resulting in more accurate height hypotheses for height estimation. Thirdly, we apply an adaptive spatial feature extraction network to search for the optimal fusion method for feature maps at different scales. Extensive experiments on the WHU-TLC dataset also demonstrate that our proposed model achieves the best MAE metric of 1.875 and an RMSE metric of 3.785, which constitutes a state-of-the-art performance.

The adoption of brown fermented milk in the normal diet and daily beverages is accompanied by significant sugar intake and a high public health burden. To reduce the sugar content in dairy products while maintaining optimal nutritional properties, a novel low-calorie, lactose-free brown fermented milk was developed through enzymatic hydrolysis and the Maillard reaction. The optimal product was achieved using low-temperature lactase, where the lactose and glucose content were reduced 33-fold and 2.4-fold to 0.06 g/100 g and 13.32 g/L, respectively, meeting the criteria for being lactose-free (

Social progress and the improvement of living standards are often accompanied by the intensification of ecological crises. The long-term abuse of natural resources has led to the accumulation of ecological liabilities, which in turn seriously hinders economic development. This has prompted all sectors of society to recognize the importance of ecological carrying capacity (ECC) and ecological security (ES). Remarkable progress has been made in karst desertification control (KDC), which has helped reshape the ECC and ES pattern of forests. Currently, the research field of ECC and ES is experiencing rapid development. Further studies in these areas have immeasurable value in promoting regional sustainable development strategies and strengthening ecological civilization construction. The objective of this paper is to provide an overview of the current research status and potential challenges in the field of ECC and ES, with a view to optimizing the program of forest restoration and protection in KDC. This study systematically analyzed 350 relevant studies and found that (1) research on forest ECC and ES has shown a strong growth trend overall, especially after 2017, with a growth rate exceeding 75%; (2) the literature predominantly focuses on the assessment of forest ECC (40.58%) and the enhancement of forest ES (23.42%); and (3) geographically, research findings are heavily concentrated in Asia, representing 95.40% of the total. Notably, China emerges as the primary contributor to research in this field, accounting for a substantial 94.12%. Based on the above analysis, this review summarizes the significant advancements in forest ecosystems, ECC, and ES, while also delving into the key scientific issues that need to be addressed. Furthermore, it offers valuable insights from forest ecosystems in tackling KDC, with the goal of offering guidance and strategic recommendations for future research and practices in managing delicate ecological environments.

Traditional machine learning-based entity extraction methods rely heavily on feature engineering by experts, and the generalization ability of the model is poor. Prototype networks, on the other hand, can effectively use a small amount of labeled data to train models while using category prototypes to enhance the generalization ability of the models. Therefore, this paper proposes a prototype network-based named entity recognition (NER) method, namely the FSPN-NER model, to solve the problem of difficult recognition of sensitive data in data-sparse text. The model utilizes the positional coding model (PCM) to pre-train the data and perform feature extraction, then computes the prototype vectors to achieve entity matching, and finally introduces a boundary detection module to enhance the performance of the prototype network in the named entity recognition task. The model in this paper is compared with LSTM, BiLSTM, CRF, Transformer and their combination models, and the experimental results on the test dataset show that the model outperforms the comparative models with an accuracy of 84.8%, a recall of 85.8% and an F1 value of 0.853.

The inherent dual roles of “follower” and “leader” among ecosystem entrepreneurs inevitably introduce challenges in managing conflicting dependent and independent goals. Ecosystem entrepreneurs’ capabilities in conflict goals management directly influence new venture survival and development. This single-case qualitative study explores how ecosystem entrepreneurs develop conflict goals management capabilities through self-regulation, which is not only a unique practical challenge in ecosystem entrepreneurship, but also a cutting-edge topic in current theoretical research. Through research of entrepreneurs in Haier Entrepreneurship Ecosystem, the paper finds: (1) strategic corresponding and mechanism adapting emerge as the two trigger factors enabling ecosystem entrepreneurs to recognize the equilibrium or disequilibrium between conflicting goals; (2) by leveraging self-control, grit, and metacognition, ecosystem entrepreneurs construct decoupling mechanisms for antagonistic goal recognition and coupling mechanisms for synergistic goal recognition; (3) ecosystem entrepreneurs enhance their conflict goals management capabilities by developing both segregative and synergistic management capabilities. Furthermore, this research explores the self-regulation process underlying ecosystem entrepreneurs’ conflict goals management behaviors, including environmental interaction perception, conflict goals analysis, and delineation of goal relationships. Findings provide insights for ecosystem entrepreneurs on improving their conflict goals management capabilities through self-assessment and skill development.

Methylene blue (MB) was found to exert neuroprotective effect on different brain diseases, such as ischemic stroke. This study assessed the MB effects on ischemia induced brain edema and its role in the inhibition of aquaporin 4 (AQP4) and metabotropic glutamate receptor 5 (mGluR5) expression. Rats were exposed 1 h transient middle cerebral artery occlusion (tMCAO), and MB was injected intravenously following reperfusion (3 mg/kg). Magnetic resonance imaging (MRI) and 2,3,5-triphenyltetrazolium chloride (TTC) staining was performed 48 h after the onset of tMCAO to evaluate the brain infarction and edema. Brain tissues injuries as well as the glial fibrillary acidic protein (GFAP), AQP4 and mGluR5 expressions were detected. Oxygen and glucose deprivation/reoxygenation (OGD/R) was performed on primary astrocytes (ASTs) to induce cell swelling. MB was administered at the beginning of reoxygenation, and the perimeter of ASTs was measured by GFAP immunofluorescent staining. 3,5-dihydroxyphenylglycine (DHPG) and fenobam were given at 24 h before OGD to examine their effects on MB functions on AST swelling and AQP4 expression. MB remarkably decreased the volumes of T2WI and ADC lesions, as well as the cerebral swelling. Consistently, MB treatment significantly decreased GFAP, mGluR5 and AQP4 expression at 48 h after stroke. In the cultivated primary ASTs, OGD/R and DHPG significantly increased ASTs volume as well as AQP4 expression, which was reversed by MB and fenobam treatment. The obtained results highlight that MB decreases the post-ischemic brain swelling by regulating the activation of AQP4 and mGluR5, suggesting potential applications of MB on clinical ischemic stroke treatment.

BackgroundCurrently, the incidence of cerebral palsy is high in newborns. However, the current methods for diagnosing and treating patients with cerebral palsy are complex and poorly targeted. Moreover, these studies lack the support of bibliometric analysis results.ObjectiveOur study focused on a bibliometric analysis of published papers on the diagnosis and treatment of patients with cerebral palsy. This study identified the primary authors, institutions, and countries involved in analyzing the status and trends of research on the diagnosis and treatment of patients with cerebral palsy. Additionally, the study also involved screening pathways related to cerebral palsy.MethodsThe PubMed database was searched for publications on the diagnosis and treatment of patients with cerebral palsy between 1990 and 2023. R v4.2.2 and VOSviewer v1.6.18 software tools were utilized to perform bibliometric analysis and visualization.ResultsThere were 1,965 publications on cerebral palsy diagnosis and 5,418 articles on the qualified treatment strategies, and the annual number of publications also increased. The United States dominated in this field of research. Gregory Y.H. Lip and Patrizio Lancellotti published the most number of papers. The Cleveland Clinic published the most number of papers in the field. According to the analysis of the co-occurrence of keywords, we found that the main research directions were age, sex, disease diagnosis, and treatment. Newly emerging research has focused mainly on heart failure, which is related to valvular heart disease.ConclusionThe findings presented in this study offer valuable insights into ongoing research and potential future directions pertaining to cerebral palsy. These insights can assist researchers in identifying suitable collaborators and enhancing their investigations aimed at identifying the underlying molecular mechanisms associated with cerebral palsy, encompassing its etiology, preventive measures, and therapeutic interventions.

Background Postoperative sleep disturbance (PSD) is a common and serious postoperative complication and is associated with poor postoperative outcomes.Aims This study aimed to investigate the effect of transcranial direct current stimulation (tDCS) on PSD in older patients undergoing lower limb major arthroplasty.Methods In this prospective, double-blind, pilot, randomised, sham-controlled trial, patients 65 years and over undergoing lower limb major arthroplasty were randomly assigned to receive active tDCS (a-tDCS) or sham tDCS (s-tDCS). The primary outcomes were the objective sleep measures on postoperative nights (N) 1 and N2.Results 116 inpatients were assessed for eligibility, and a total of 92 patients were enrolled; 47 received a-tDCS and 45 received s-tDCS. tDCS improved PSD by altering the following sleep measures in the a-tDCS and s-tDCS groups; the respective comparisons were as follows: the promotion of rapid eye movement (REM) sleep time on N1 (64.5 (33.5–105.5) vs 19.0 (0.0, 45.0) min, F=20.10, p

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Nowadays, refrigerated food storage and transport vehicles are very common. However, with regard to the engine of vehicles, a significant amount of heat is discharged into the environment in the form of exhaust gas and jacket water. If the cooling system is used to convert this waste heat into cooling capacity, the thermal efficiency of the engine will be improved to a certain extent. Therefore, this paper uses two waste heat recovery jet refrigeration systems to recover heat from the exhaust gas and jacket water of the refrigerated vehicle. One is a conventional jet refrigeration system that uses only engine exhaust as the heat source, and the other is a system that adds a preheater upstream of the generator based on the conventional system, using engine jacket water to preheat the working fluid. This paper presents the results of comparing the impact of R141b/R123, R141b/R245fa, R142b/R134a, and R142b/R152a working fluids on system performance, and considers the effects of operating temperature and secondary flow pressure drop in the ejector receiving chamber on the system performance. The research results indicate that of the four selected working fluids, the R141b/R245fa (0.4/0.6) blend has the best overall performance. After the addition of a preheater, the system using R142b/R134a (0.6/0.4) hybrid working fluid achieves the maximum cooling capacity of 16.0994 kW and the maximum thermal efficiency of 5.45%, and the exergy loss in the generator is 1 kW lower than without the preheater.

The research on the recovery of low-grade thermal energy carried away by boiler flue gas is significant for sugar mills. This paper designs a waste heat recovery system based on sugar plant flue gas, integrating absorption refrigeration cycle and the organic Rankine cycle, and the effects of nine working fluids on the system are investigated. The aim is to realize the multi-form conversion of energy. The performance of the system is evaluated in terms of energy, exergy, and economic metrics. Multi-objective optimization is performed with the method of the NSGA-II genetic algorithm. The results show that Butane is the most suitable working fluid for ORC. The exergy efficiency of the system is 32.125% before optimisation, with an increased space cooling capacity of 15820.56 MW per year for the sugar mill. The exergy destruction analysis of the system reveals that the generator accounts for the highest proportion of exergy destruction (50.8%). The entire system shows the LCOE is as low as 0.0406$/kWh under the optimized condition. The optimized system can obtain an estimated annual electricity sales revenue of $136,300, and the sugar mill can save $308,600 in cooling costs. In addition, the payback period can be shortened to 5.79 years.