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An integrated thermodynamic model was developed to determine the equilibrium between the slag and the steel at high temperatures, employing the Unified Interaction Parameter Formalism (UIPF) and the Associate Model (AM) for a twelve-element molten steel system (Fe–Al–C–Ca–Cr–Mg–Mn–N–O–S–Si–Ti). A model for slag activity was based on the Ion and Molecular Coexistence Theory (IMCT) and applied to a refining slag system (CaO–MgO–FeO–MnO–CaF2–SiO2–Al2O3–Fe2O3). Comparative analyses were conducted using FactSage software and experimental data, validating the accuracy of the established model. The impact of slag modifiers, specifically aluminum granules, on slag oxidability, and the role of CaO/Al2O3 ratio in slag desulfurization were investigated. The effect of slag modifier on the oxidability and the influence of CaO/Al2O3 on the desulfurization of the slag were determined using the current model. Aluminum in the slag modifier reacted with MnO and FeO in the slag, thereby reducing the oxidability of the slag. With a 30 wt% slag modifier, the MnO content in the slag (initially 15 wt%) stabilized and showed minimal change, dropping below 1 wt%. An increase in CaO content above 80 wt% in the slag led to a reduction of equilibrium sulfur in the steel to below 10 ppm. Little amount of calcium transferred from the slag into the steel with the increase in CaO content, but the [Ca] content remained below 0.5 ppm even though the content of CaO in the slag was greater than 80 wt%. The developed model offered a versatile tool for designing slag compositions tailored to various purposes.

Abstract Residents' participation is crucial for sustainable old neighborhood regeneration. Residents' intentions to participate in the regeneration are low in China, resulting in unsustainable neighborhood development problems. Therefore, it is essential to investigate the drivers of residents' participation. Residents' behavioral mechanisms are deeply embedded in their social networks, especially in acquaintance social networks typical of old neighborhoods in China. By constructing a mediated moderation model based on the Theory of Planned Behavior (TPB) and danwei system and taking the old neighborhood regeneration in Xi'an as a case study, this paper investigates the paths and mechanisms of the social network embeddedness, TPB, and danwei system on residents' participation intention. The results show that social network embeddedness can improve residents' intention to participate in regeneration through both direct and indirect pathways, and its indirect effect is much larger than the direct effect. Attitude, subjective norm, and perceived behavioral control significantly and positively mediated the contribution of social network embeddedness on participation intention. However, the specific mediating effect of attitude is significantly smaller than the other two. The danwei system has a significant moderating effect in the first stage of the relationship between social network embeddedness and participation intention. These imply that the extrinsic social factor of social network embeddedness is internalized as a driving force for convergence and motivation of residents' participation intentions mainly through the normative pressure and exchange of experiences between acquaintances and that the danwei system reinforces this extrinsic-intrinsic facilitation process through the danwei's "physical presence." These findings provide revelatory countermeasures for exploring the factors that motivate residents to participate actively in neighborhood regeneration and encourage their involvement at the intervention level.

Abstract Titanium and its alloys have been widely applied in many biomedical fields because of its excellent mechanical properties, corrosion resistance and good biocompatibility. However, problems such as rejection, shedding and infection will occur after titanium alloy implantation due to the low biological activity of titanium alloy surface. The structures with specific functions, which can enhance osseointegration and antibacterial properties, are fabricated on the surface of titanium implants to improve the biological activity between the titanium implants and human tissues. This paper presents a comprehensive review of recent developments and applications of surface functional structure in titanium and titanium alloy implants. The applications of surface functional structure on different titanium and titanium alloy implants are introduced, and their manufacturing technologies are summarized and compared. Furthermore, the fabrication of various surface functional structures used for titanium and titanium alloy implants is reviewed and analyzed in detail. Finally, the challenges affecting the development of surface functional structures applied in titanium and titanium alloy implants are outlined, and recommendations for future research are presented.

Damage to the substrate hinders the application of laser paint stripping (LPS) on carbon fiber reinforced polymers (CFRP), but the damage mechanism is currently unknown. In this paper, the LPS characteristics of CFRP, such as paint stripping depth, surface morphology and dynamic behavior, are firstly obtained. Subsequently, the surface damage mechanism of CFRP is discussed in detail by theoretical analysis and finite element method, and the effect of substrate damage on adhesive properties is investigated. The results show that it is difficult for LPS to obtain a complete surface free of paint residue. The strong laser plasma impact and resin pyrolysis pressure cause the resin to crack and flake before the paint is fully ablated. The carbon fiber then breaks and are thrown outward by heat and forces, and the surface with slightly fracture of the fiber will facilitate bonding with the paint.

To explore the differences in the composition, content and comprehensive quality of free amino acids (FAA) in millet from Longzhong area in Gansu Province，12 different cultivars of millet were used as research objects, the types and contents of FAA were determined by liquid chromatography-tandem mass spectrometry. Comprehensive evaluation of FAA quality was performed by principal component analysis (PCA) and hierarchical cluster analysis (HCA). The results showed that 19~20 kinds of FAA were detected in all kinds of millet, and the total content of FAA ranged from 1046.80~1773.85 mg/kg, asparagine (Asn), aspartic acid (Asp), glutamic acid (Glu) and glycine (Gly) were the four main FAA in millet. There were significant differences in the contents of FAA (Pbitter amino acids>sweet amino acids>aromatic amino acids. 9 Medicinal amino acids and 3 branched chain amino acids were found in millet, the average content of medicinal amino acids was 706.34 mg/kg, the percentages of medicinal amino acids to total FAA was 53.63%, so millet had many potential medicinal values. There was a significant relation with FAA in different cultivars of millet, five principal components were extracted after PCA, and the cumulative contribution ratio of the five components was 86.20%, the FAA comprehensive scores of LG-23、LG-11 and YG-18 were ranked as the top three. The 12 different cultivars millet were divided into four groups by HCA, FAA comprehensive quality performances of groups Ⅰ (LG-23) and Ⅲ (LG-11 and YG-18) were optimal, the content of total FAA was significantly higher than the other two groups (P

Abstract Objective Melanoma, with its high degree of malignancy, stands as one of the most dangerous skin cancers and remains the primary cause of death from skin cancer. With studies demonstrating the potential of traditional Chinese medicine to intervene and treat melanoma, we turned our attention to celastrol. Celastrol is a triterpene compound extracted from the traditional Chinese medicine derived from Tripterygium wilfordii. Previous studies have shown that celastrol exerts inhibitory effects on various malignant tumors, including melanoma. Hence, our goal was to clarify the impact of celastrol on cell viability, apoptosis, and cell cycle progression by elucidating its effects on the PI3K/AKT/mTOR pathway. Methods CCK-8 and wound healing assays were used to determine the effect of celastrol on the viability and migration of B16-F10 cells. Changes in cell apoptosis, cell cycle, reactive oxygen species (ROS), and mitochondrial membrane potential were detected by flow cytometry. PI3K/AKT/mTOR pathway proteins and HIF-α mRNA expression in B16-F10 cells were detected by western blotting and qPCR. Moreover, the addition of a PI3K activator demonstrated that celastrol could inhibit the function of B16-F10 cells via the PI3K/AKT/mTOR pathway. Results Celastrol inhibited the viability and migration of B16-F10 cells. Through the inhibition of the PI3K/AKT/mTOR pathway down-regulates the expression of HIF-α mRNA, thereby causing an increase of ROS in cells and a decrease in the mitochondrial membrane potential to promote cell apoptosis and cell cycle arrest. The inhibitory effect of celastrol on B16-F10 cells was further demonstrated by co-culturing with a PI3K activator. Conclusion Celastrol inhibits the function of B16-F10 cells by inhibiting the PI3K/AKT/mTOR cellular pathway and regulating the expression of downstream HIF-α mRNA.

Abstract We use families of circular null geodesics as probes of a family of microstate geometries, known as (1, 0, n) superstrata. These geometries carry a left-moving momentum wave and the behavior of some of the geodesic probes is very sensitive to this background wave. The left-moving geodesics behave like BPS particles and so can be placed in circular orbits anywhere in the geometry and actually “float” at fixed radius and angle in the three-dimensional “capped BTZ” geometry. The right-moving geodesics behave like non-BPS particles. We show that they provide a simple geometric characterization of the black-hole bound: when the momentum charge of the geometry is below this bound, such geodesics can be placed anywhere, but exceeding the bound, even by a small amount, means these geodesics are restricted to the deep interior of the geometry. We also show that for left-moving string probes, the tidal forces remain comparable with those of global AdS3. Nevertheless, for some of these probes, the “bumps” in the geometry induce an oscillatory mass term and we discuss how this can lead to chaotic scrambling of the state of the string.

Although different damage-coupled physically based models have been proposed, those damage models are established based on the isothermal uniaxial or multi-axial tensile condition. However, the influence of the stress state on ductile failure strain is not adequately considered in the thermal damage models. It is widely recognized that the stress state has significant effect on damage evolution and ductility fracture for metallic materials. Actually, the current damage-coupled physically based models are not suitable for complex hot forming and the applications of these damage-coupled models are mainly focused on sheet hot stamping forming to date. Therefore, a modified damage-coupled unified model considering a broad range of stress states was established to figure out the complex damage behavior and microstructure evolution of metallic materials during the thermal deformation process. In this study, the Mg-6Gd-5Y-0.3Zr alloy was used as the experimental material. First, the flow behavior of the alloy was explored using a series of experiments under various stress states (i.e., uniaxial tensile, shear and compression) under various combinations of strain rates and temperatures. On this basis, a modified damage-coupled physics-based model was developed, in which the dynamic recrystallization, damage, stress triaxiality and Lode parameter were included as internal state variables. Furthermore, the model was integrated into ABAQUS to verify the applicability using hot spinnability test because the stress state was very complex during the forming process. The comparison between the calculated results and experiments is carried out. According to the simulation result, the predicted ultimate thinning rate is 71.14%, with an error of only 7.85% from the experimentally measured ultimate thinning rate of 77.2%, and the correlation coefficient and error for thickness and profile between the predicted values and experimental values are 0.9980 and 5.05%, respectively. These demonstrate that the developed model is reliable.

Abstract Bacterial resistance and excessive inflammation are common issues that hinder wound healing. Antimicrobial peptides (AMPs) offer a promising and versatile antibacterial option compared to traditional antibiotics, with additional anti-inflammatory properties. However, the applications of AMPs are limited by their antimicrobial effects and stability against bacterial degradation. TFNAs are regarded as a promising drug delivery platform that could enhance the antibacterial properties and stability of nanodrugs. Therefore, in this study, a composite hydrogel (HAMA/t-GL13K) was prepared via the photocross-linking method, in which tFNAs carry GL13K. The hydrogel was injectable, biocompatible, and could be instantly photocured. It exhibited broad-spectrum antibacterial and anti-inflammatory properties by inhibiting the expression of inflammatory factors and scavenging ROS. Thereby, the hydrogel inhibited bacterial infection, shortened the wound healing time of skin defects in infected skin full-thickness defect wound models and reduced scarring. The constructed HAMA/tFNA-AMPs hydrogels exhibit the potential for clinical use in treating microbial infections and promoting wound healing.

Abstract Background The gastric conduit is the most commonly used replacement organ for reconstruction after minimally invasive McKeown esophagectomy. Although the optimal route of gastric conduit remains controversial, the posterior mediastinal route is physiologically preferable but is not without disadvantages. Here, we report the safety and efficacy of a method of gastric conduit reconstruction via the anterior of the pulmonary hilum route. Methods We have used the anterior of the pulmonary hilum route since 2021. This procedure involves pulling the gastric conduit up through a substernal tunnel between the right thoracic cavity and the abdominal cavity and passing it into the neck via the anterior of the pulmonary hilum route. In this retrospective study, we compared the clinical outcomes between 20 patients who underwent this procedure and 20 patients who underwent the posterior mediastinal route from 2021 to 2022. Results No mortality was reported in either group. No significant differences were observed between the two groups in duration of surgery, blood loss, incidence of postoperative complications, and postoperative hospital stay. As a result of the anterior of the pulmonary hilum route, the primary tumor bed and lymph node drainage area were effectively bypassed, which facilitates postoperative adjuvant radiotherapy or chemoradiotherapy. The distance of the gastric conduit accompanying the airway was significantly shorter in the anterior of the pulmonary hilum route group. Conclusions Our method is considered to be a safe and useful technique for the reconstruction of gastric conduit.

Abstract The bound state of one NS5 brane (wrapped on a 𝕋4) and N NS1-branes has two dual descriptions: its low-energy dynamics is described by the symmetric orbifold of 𝕋4, while the near horizon geometry is captured by string theory on AdS3 × S3 × 𝕋4 with one unit of NS flux. The latter theory is exactly solvable in the hybrid formalism, and this allows one to prove the equivalence of the two descriptions. In this paper we extend this duality to ℤ k orbifolds of this AdS3 × S3 background. In particular, we show that the corresponding worldsheet spectrum reproduces exactly the perturbative excitations on top of a certain non-perturbative state in the dual symmetric orbifold theory. Since the AdS/CFT duality map is exact for these models, we obtain an interesting picture of how the duality relates boundary and bulk descriptions.

Currently, the application scope of big data (BD for short here) technology is relatively narrow, mostly used in the medical field, and the degree of application is relatively superficial, mostly for data statistical record analysis. Therefore, By combining the literature review, this article has decided to construct a system based on BD technology for analyzing the advanced neural activity status of athletes. The system is mainly divided into two parts, one is the biological information collection part. As an important source of system data, it is necessary to use professional equipment to collect ECG and EEG data and ensure the accuracy of the data through signal filtering, Gaussian noise elimination, salt and pepper noise, and exponential noise de-noising technology. The other is the algorithm problem of BD systems. Considering that the traditional algorithm can not deal with a large amount of data effectively, this paper chooses the BD spectral clustering algorithm based on core points as the main algorithm to cluster the data. By evaluating the efficiency of system learning, data collection and classification, system scheme construction, and error rate, this article ultimately determined the practical feasibility and effectiveness of the system. After completing the construction of the system, considering the gap between the system's performance and traditional data, this article analyzed the improvement data of various aspects of sports training. This paper compares the performance differences between the system based on BD technology and the traditional data analysis method under different indicators. In terms of data collection and classification, the accuracy of the system based on BD technology in the collection and classification of ECG and EEG data reached 100 % and 90 %, respectively, which was significantly higher than 60 % and 30 % of the traditional methods. By comparing the data from five training courses, it is found that the training efficiency of the conventional method has increased by 60 % in the first course, while the efficiency of the training method based on the BD system has increased by 85 % in the fifth course. For the activation efficiency of nerve function, the activation efficiency of brain nerve function reached 60 % and 90 % respectively in the two nerve function activation training based on the BD system, which was much higher than 30 % and 45 % of the traditional methods. Through a series of tests and comparative analysis of data, the effectiveness of the BD system is finally determined, which can achieve the goal of improving athletes' training efficiency.

Abstract Background Sirtuin 7 (SIRT7) is pivotal in diverse diseases progression. Importantly, SIRT7 is associated with melanin production. However, whether SIRT7 regulates vitiligo is unclear. Therefore, we aimed to investigate the effects of SIRT7 on pigmentation and the modification of glucose 6‐phosphate dehydrogenase (G6PD). Methods After knockdown SIRT7 and G6PD, pigmentation of melanocytes was evaluated using commercial kits, immunofluorescence, and Western blot analysis. The succinylation of G6PD mediated by SIRT7 was analyzed using co‐immunoprecipitation, immunofluorescence, Western blot analysis, and cycloheximide‐chase experiment. Results We found that SIRT7 was highly expressed in vitiligo skin lesions. Knockdown of SIRT7 increased tyrosinase activity, melanin content, and the levels of α‐melanocyte‐stimulating hormone, MITF, TYR, TRP1, and TRP2. Additionally, SIRT7 directly interacted with G6PD. Silenced SIRT7 promoted the succinylation of G6PD and enhanced its protein stability. G6PD knockdown reversed the effect of reduced SIRT7 expression on melanin production. Conclsuion Silencing of SIRT7 promotes pigmentation of melanocytes by succinylating G6PD, suggesting that SIRT7‐mediated G6PD desuccinylation may promote vitiligo progression.

Abstract In the D1D5 CFT the twist operator of order 2 can twist together two copies in the untwisted sector into a single joined copy in the twisted sector. Traditionally, this effect is computed by using the covering map method. Recently, a new method was developed using the Bogoliubov ansatz and conformal symmetry to compute this effect in a toy model of one free boson. In this paper, we use this method with superconformal symmetry to compute the effect of the twist operator in the D1D5 CFT. This may provide more effective tools for computing correlation functions of twist operators in this system.

Abstract Endodontic diseases are a kind of chronic infectious oral disease. Common endodontic treatment concepts are based on the removal of inflamed or necrotic pulp tissue and the replacement by gutta-percha. However, it is very essential for endodontic treatment to debride the root canal system and prevent the root canal system from bacterial reinfection after root canal therapy (RCT). Recent research, encompassing bacterial etiology and advanced imaging techniques, contributes to our understanding of the root canal system’s anatomy intricacies and the technique sensitivity of RCT. Success in RCT hinges on factors like patients, infection severity, root canal anatomy, and treatment techniques. Therefore, improving disease management is a key issue to combat endodontic diseases and cure periapical lesions. The clinical difficulty assessment system of RCT is established based on patient conditions, tooth conditions, root canal configuration, and root canal needing retreatment, and emphasizes pre-treatment risk assessment for optimal outcomes. The findings suggest that the presence of risk factors may correlate with the challenge of achieving the high standard required for RCT. These insights contribute not only to improve education but also aid practitioners in treatment planning and referral decision-making within the field of endodontics.

Electrically assisted forming has been a reliable method for enhancing the formability of metal components for decades. This study investigates the mechanical properties and microstructures of an equiatomic CoCrFeNiMn high-entropy alloy (HEA) under electrically assisted tensile (EAT). The results indicate that the CoCrFeNiMn HEA exhibits lower flow stress and elongation under EAT compared to samples deformed at room temperature (RT). The sample's temperature increases with current density, and the primary factor influencing the HEA's mechanical properties during EAT is the Joule heating effect. A model about yield strength (YS) increment is established to predict the YS of the HEA under EAT at different temperatures. As the amount of Joule heating rises, the dislocation width increases, reducing the lattice friction stress and resulting in an exponential decay of YS. Increased Joule heating caused by current leads to a higher dynamic recovery rate, resulting in a reduced proliferation rate of geometrically necessary dislocations. However, the change in dislocation recovery coefficients is little affected by the current density in CoCrFeNiMn HEA when the dynamic recovery produced by the current is not sufficient to increase the fracture strain. Deformation twins (DTs) form during deformation at RT and 10 A/mm2. However, as the current density surpasses 20 A/mm2, the flow stress becomes insufficient to induce the formation of DTs, leading to a decrease in strain-hardening ability and elongation. This study provides an experimental and theoretical foundation for forming HEA components.

As a common agricultural intensification, the winter wheat and summer maize rotation cropping pattern (wheat–maize) plays a crucial role in achieving sustainable food security in China. Reliable regional wheat–maize maps are of great importance to ensure the sustainability of agro-ecosystems. However, conventional previous studies typically depended on vegetation index time-series for detecting wheat–maize, which was challenging for rapid wheat–maize mapping. This study proposed a simpler phenology index-based method for mapping wheat–maize from multitemporal Sentinel-2 data. To better explore the mapping performance, two indices [i.e., normalized difference vegetation index (NDVI) and two-band enhanced vegetation index (EVI2)] and two mathematical combinations (i.e., multiplication and addition) were introduced to generate four uncorrelated indices. The wheat–maize maps obtained using phenology indices were evaluated using samples and high-precision maps derived from random forest. The results showed that the resulting maps achieved high overall accuracy of above 94% and F1-score of over 0.95, as well as agreed well with random forest derived maps (overall accuracy ≥ 91%, F1-score ≥ 0.88). In addition, this study found that EVI2 was better suited for designing phenology difference-based index than NDVI; concerning combination approaches, multiplication performed better than addition in enhancing spectral differences. Our results demonstrated the advantages of index-based method in mapping wheat–maize and its potential to be applied over larger regions. We hope that this study will advance our understanding of phenology-based methods in agriculture mapping.

Abstract Predictive maintenance has emerged as an effective tool for curbing maintenance costs, yet prevailing research predominantly concentrates on the abnormal phases. Within the ostensibly stable healthy phase, the reliance on anomaly detection to preempt equipment malfunctions faces the challenge of sudden anomaly discernment. To address this challenge, this paper proposes a dual-task learning approach for bearing anomaly detection and state evaluation of safe regions. The proposed method transforms the execution of the two tasks into an optimization issue of the hypersphere center. By leveraging the monotonicity and distinguishability pertinent to the tasks as the foundation for optimization, it reconstructs the SVDD model to ensure equilibrium in the model's performance across the two tasks. Subsequent experiments verify the proposed method's effectiveness, which is interpreted from the perspectives of parameter adjustment and enveloping trade-offs. In the meantime, experimental results also show two deficiencies in anomaly detection accuracy and state evaluation metrics. Their theoretical analysis inspires us to focus on feature extraction and data collection to achieve improvements. The proposed method lays the foundation for realizing predictive maintenance in a healthy stage by improving condition awareness in safe regions.

Abstract Background Osteoporosis is the most common metabolic bone disease in humans. Exploring the expression difference of iron metabolism-related genes in osteoporosis can provide a new target for diagnosis and treatment. Methods First, we used online databases to identify differentially expressed genes (DEGs) related to iron metabolism in patients with osteoporosis. The differential genes were comprehensively analyzed by bioinformatics method (GO, KEGG, GSEA, immune infiltration analysis, PPI). The expression levels of hub genes and important signaling pathways were verified by qRT-PCR and Western blotting. Results A total of 23 iron metabolism-related genes with significant differences were identified, which were enriched in “regulation of protein dephosphorylation” and “negative regulation of protein dephosphorylation”. The GSEA results, heme metabolism and Myc targets v1 were among the top two pathways, both upregulated. The immune infiltration analysis revealed that the expressions of genes such as ABCA5, D2HGDH, GNAI2, and CTSW were correlated with the infiltration degree of significantly different cells. The PPI network contained 12 differentially expressed iron metabolism-related genes. Additionally, YWHAE, TGFB1, PPP1R15A, TOP2A, and CALR were mined as hub genes using the Cytoscape software. qRT PCR showed that the expression of TGF-β1, YWHAE, TOP2A and CALR increased. We also verified the expression of related proteins and genes in the oxidative stress signaling pathway by qRT PCR and Western blotting. The results showed that Mob1, YAP and TAZ molecules were highly expressed at the gene and protein levels. Conclusions These differentially expressed iron metabolism-related genes could provide new potential targets for the diagnosis and treatment of osteoporosis.

In order to improve aerodynamic deceleration efficiency, deep space reentry capsules generally adopt large blunt windward shape and ablative heat protection system. However, factors such as the flat forebody shape and the sharp increase in surface roughness caused by aerothermodynamic heating and ablation easily lead to the instability of the windward flowfield of the capsule, resulting in the transition or even evolution into turbulence, which greatly changes the distribution of the surface heat flux and brings great challenges to the safety of the capsule. Formerly the studies on the instability mechanism and simulation for the transition of hypersonic boundary layer under the change of microscopic morphology of large blunt heat shield are relatively unexplored. Using the γ-Reθ transition model and k-ω-γtransition model based on hypersonic and rough element correction, the intermittent factors of rough element equivalent roughness height, incoming Reynolds number, angle of attack and chemical non-equilibrium basic flow on the windward surface of the large blunt heat shield were analyzed. The development law of hypersonic boundary layer transition and aerothermodynamic effect on ablative rough surfaces of deep space reentry capsules were studied.

Abstract The two-dimensional 𝒩 = 4 superconformal algebra has a free field realization with four bosons and four fermions. There is an automorphism of the algebra called spectral flow. Under spectral flow, the four fermions are transformed together. In this paper, we study partial spectral flow where only two of the four fermions are transformed. Partial spectral flow is applied to the D1D5 CFT where a marginal deformation moves the CFT away from the free point. The partial spectral flow is broken by the deformation. We show that this effect can be studied due to a transformation of the deformation which is well-defined under partial spectral flow. As a result in the spectrum, we demonstrate how to compute the second-order energy lift of a D1D5P state through its partial spectral flowed state. We find that D1D5P states related by partial spectral flow do not have the same lift in general.

The stress drop and strain localization behaviors of Ti–6Al–4V titanium alloy under the action of single pulse were investigated using electrically-assisted (EA) tension tests in this study. It is found that the flow stress drop gradually increases with the increase of current density and pulse width during EA tension. The digital image correlation (DIC) technology was adopted to analyze the strain distribution evolution and fracture regulation in EA micro-tension process. It turn out that the EA tensile sample will suddenly form two new intersecting high-strain bands at the moment of applying a pulse. With the increase of strain, the two high-strain bands converge toward the center and gradually evolve into a crossed localized flow zone, which makes the EA tensile sample exhibit a high local plastic deformation compared with room temperature tension. Furthermore, with the increase of current density, the temperature gradient in the tensile direction of the sample increases gradually, resulting in the narrowing of localized flow zone. The transformation of the localized flow zone eventually leads to the increase of fracture angle and the formation of a sawtooth shape fracture morphology. Finally, a material flow model for the single-pulse EA tension process was established. The calculation results show that about 11 % of the stress drop comes from the contribution of non-thermal electroplastic, the main mechanism of stress drop is thermal softening and thermal expansion induced by Joule heat during EA tension.

Abstract Hypercholesterolaemia is a systemic metabolic disease, but the role of organs other than liver in cholesterol metabolism is unappreciated. The phenotypic characterization of the Tsc1Dmp1 mice reveal that genetic depletion of tuberous sclerosis complex 1 (TSC1) in osteocytes/osteoblasts (Dmp1‐Cre) triggers progressive increase in serum cholesterol level. The resulting cholesterol metabolic dysregulation is shown to be associated with upregulation and elevation of serum amyloid A3 (SAA3), a lipid metabolism related factor, in the bone and serum respectively. SAA3, elicited from the bone, bound to toll‐like receptor 4 (TLR4) on hepatocytes to phosphorylate c‐Jun, and caused impeded conversion of cholesterol to bile acids via suppression on cholesterol 7 α‐hydroxylase (Cyp7a1) expression. Ablation of Saa3 in Tsc1Dmp1 mice prevented the CYP7A1 reduction in liver and cholesterol elevation in serum. These results expand the understanding of bone function and hepatic regulation of cholesterol metabolism and uncover a potential therapeutic use of pharmacological modulation of SAA3 in hypercholesterolaemia.

The Internet of Things is based on the traditional Internet and its purpose is to achieve information exchange between users and devices, as well as between devices. The rapid development of sensor technology, communication network technology, and computer technology has enriched the coverage of the Internet of Things, including a wide range of intelligent applications such as healthcare, smart cities, and smart homes. The development of high-performance computing and machine learning technologies has promoted the wide application of intelligent auxiliary systems in sports medicine. With the rapid development of yoga in the field of sports, athletes can play the various functions of yoga, improve their physical strength and quality, and improve their strength, flexibility, etc., cultivate positive, optimistic, and healthy emotions, and these are conducive to rehabilitation treatment after sports injuries. Therefore, it is feasible and feasible to introduce yoga training into the monitoring of the exercise load of athletes. In this paper, neural network technology was used to break the traditional training method based on experience. Based on yoga training data, through experimental exercise research, it could explore a new effective way to monitor exercise load and rehabilitation treatment, and build an exercise load monitoring model of the Ant Colony Optimization (ACO) neural network. By sorting out the data, statistics and analysis of the data, this article confirmed the effect of yoga training on reducing fatigue after exercise. The experimental results showed that the prediction value obtained by the ACO neural network model was 9.106, and the error was only −0.003 compared to the actual detection value of 9.109. This result showed that the ACO neural network model can perfectly fit the functional relationship between yoga training level and exercise load and has high prediction accuracy. This also marked that the development of high-performance computing systems has entered a new journey in the field of sports and health.

Diabetic neuropathy (DN) represents a common and debilitating complication of diabetes, affecting a significant proportion of patients. Despite available treatments focusing on symptom management, there remains an unmet need for therapies that address the underlying pathophysiology. In pursuit of novel interventions, this study evaluated the therapeutic effects of caffeic acid—a natural phenolic compound prevalent in various foods—on diabetic neuropathy using a mouse model, particularly examining its interaction with the Insulin-like Growth Factor 1 (IGF-1) signaling pathway. Caffeic acid was administered orally at two dosages (5 mg/kg and 10 mg/kg), and a comprehensive set of outcomes including fasting blood glucose levels, body weight, sensory behavior, spinal cord oxidative stress markers, inflammatory cytokines, and components of the IGF-1 signaling cascade were assessed. Additionally, to determine the specific contribution of IGF-1 signaling to the observed benefits, IGF1R inhibitor Picropodophyllin (PPP) was co-administered with caffeic acid. Our results demonstrated that caffeic acid, at both dosages, effectively reduced hyperglycemia and alleviated sensory behavioral deficits in diabetic mice. This was accompanied by a marked decrease in oxidative stress markers and an increase in antioxidant enzyme activities within the spinal cord. Significantly lowered microglial activation and inflammatory cytokine expression highlighted the potent antioxidative and anti-inflammatory effects of caffeic acid. Moreover, increases in both serum and spinal levels of IGF-1, along with elevated phosphorylated IGF1R, implicated the IGF-1 signaling pathway as a mediator of caffeic acid's neuroprotective actions. The partial reversal of caffeic acid's benefits by PPP substantiated the pivotal engagement of IGF-1 signaling in mediating its effects. Our findings delineate the capability of caffeic acid to mitigate DN symptoms, particularly through reducing spinal oxidative stress and inflammation, and pinpoint the integral role of IGF-1 signaling in these protective mechanisms. The insights gleaned from this study not only position caffeic acid as a promising dietary adjunct for managing diabetic neuropathy but also highlight the therapeutic potential of targeting spinal IGF-1 signaling as part of a strategic treatment approach.

Abstract Purpose Obsessive‐compulsive disorder (OCD) is a complex psychiatric disorder. Genetic and broad environmental factors are common risk factors for OCD. The purpose of this study is to explore the molecular mechanism of OCD and to find new molecular targets for the diagnosis and management of OCD. Methods All data were downloaded from public dataset. Key modules and candidate key mRNAs were identified based on weighted gene co‐expression network analysis (WGCNA). The “limma” R package was used for differential expression analysis of mRNAs. Subsequently, functional enrichment analysis of differentially expressed mRNAs (DEmRNAs) was also carried out. In addition, a diagnostic model was constructed. Finally, the infiltration level of immune cells in OCD and its correlation with multicentric key DEmRNAs were analyzed. Results Green and red modules were selected as the hub modules. A total of 447 mRNAs were considered candidate key mRNAs according to GS > 0.2 and MM > 0.3. A total of 26 DEmRNAs in the same direction were identified in the GSE60190 and GSE78104 datasets. A total of 26 DEmRNAs were intersected with candidate key mRNAs in WGCNA to obtain 10 intersection DEmRNAs (HSPB1, ITPK1, CBX7, PPP1R10, TAOK1, PISD, MKNK2, RWDD1, PPA1, and RELN). However, only four DEmRNAs (HSPB1, TAOK1, MKNK2, and PPA1) predicted related drugs. Subsequently, receiver operating characteristic analysis shows that the diagnostic model has high diagnostic value. Moreover, six multicentric key DEmRNAs (SNRPF, SNRNP70, PRPF8, NOP56, EPRS, and CCT2) were screened by UpSet package. Finally, six multicentric key DEmRNAs were found to be associated with immune cells. Conclusion The key molecules obtained in this study lay a foundation for further research on the molecular mechanism of OCD.

Pitaya (Hylocereus undatus) is a typical tropical cash crop that is not chilling-tolerant. Low temperature stress seriously affects the quality and yield of pitaya. It is an efficient and safe method to apply exogenous natural substances to improve the chilling tolerance of plants. Salicylic acid (SA) not only regulates many physiological and biochemical processes such as seed germination, growth, fruiting and senescence, but also helps plants to cope with biotic and abiotic stresses. However, the role of exogenous SA in chilling tolerance of pitaya has not been reported. To explore the effect of exogenous SA on the morphology structure and physiology of pitaya seedlings under low temperature, the leaves of ‘Zihonglong’ seedlings were sprayed with SA at four concentrations (0.1, 0.3, 0.5, 0.7 mmol·L-1). after spraying for 48 h, seedlings were incubated at 4℃. The change in the morphology and leaf tissue structure of pitaya seedlings were observed on 0, 3, 6, 9 d. Physiological indexes such as relative electrical conductivity, contents of malondialdehyde, contents of osmotic regulators (soluble sugar, soluble protein, proline) and antioxidant enzyme (superoxide dismutase, peroxidase, catalase, glutathione S-transferase) activities in leaves were measured. The results were as follows: (1) Under low temperature stress, pitaya seedlings showed chilling injury of Grade 0, Grade Ⅰ and Grade Ⅱ. The leaf shape, color and cell structure of pitaya with different chilling injury symptoms were quite different. The percentages of Grade Ⅰ and Grade Ⅱ chilling injury of pitaya seedlings treated with SA were significantly reduced. (2) Compared with the low temperature control, SA treatment could reduce the relative conductivity and malondialdehyde contents of pitaya leaves, and increase the contents of osmotic regulators and antioxidant enzyme activities. (3) After comparing with different SA treatments, SA at 0.3 mmol·L-1 had the best effects on relieving chilling injury symptoms, reducing the relative conductivity and malondialdehyde content, increasing the soluble sugar and proline content, and increasing the activities of superoxide dismutase and glutathione S-transferase. The optimal SA concentrations for increasing soluble protein content, peroxidase activity and catalase activity were 0.7, 0.1 and 0.5 mmol·L-1, respectively. In summary, exogenous SA could alleviate chilling injury of pitaya seedlings under 4℃, and has a positive physiological effect on improving chilling tolerance of seedlings, and exogenous SA at 0.3 mmol·L-1 is more suitable.

Abstract Introduction Lung adenocarcinoma (LUAD) is the major type of non‐small cell lung cancer with low a survival rate caused by metastasis. SCN4B encoding voltage‐gated sodium channel β subunit is regarded as a metastasis‐suppressor gene. We aim to explore how SCN4B influences the progression and prognosis of LUAD. Methods The gene expression profiles of 585 LUAD samples in TCGA and GSE31210, GSE116959, and GSE72094 datasets from the GEO database were downloaded for analysis. Differentially expressed genes were obtained through the “limma” package. The “clusterProfiler” package was used to conduct GSEA. Survival analysis was conducted via “survival” and “survminer” packages. Transcription factors regulating SCN4B expression were screened by correlation analysis and further predicted by FIMO. Infiltration of immune cells was analyzed by CIBERSORT. ESTIMATE algorithm was used to evaluate the immune‐related scores. Results SCN4B expressed higher in normal samples than in LUAD samples and higher in female samples than male samples. One hundred and twenty‐six pathways were significantly enriched between high and low SCN4B expression groups. Six transcription factors' expressions were positively related to SCN4B expression, and ChIP‐seq data from “Cistrome” verified that TAL1 and ERG might bind to the upstream sequence of SCN4B. SCN4B expression was significantly correlated with activated memory CD4 T cells, resting mast cells, and monocytes. TMB status, three scores based on ESTIMATE algorithm, and expression of three immune checkpoints showed significant differences between SCN4B high‐ and low‐expression groups. SCN4B could be considered as an independent prognostic signature of LUAD patients that higher expression represents a better prognosis. Conclusion SCN4B expresses higher in normal samples, and SCN4B is able to be an independent prognostic signature for LUAD patients. TAL1 and ERG may regulate the expression of SCN4B by binding its upstream sequences. Our research is valuable in improving the effectiveness of treatment in LUAD.

Located in the city of Xianyang in Shaanxi Province, the Hanyang Mausoleum is the first fully closed underground museum in China and in the world. The fissure disease of its outer pit is developing, which seriously endangers the safety of the pit wall and the pit bottom cultural relics, and it is urgent to protect and strengthen the pit. In the past, more was learned about the disease and prevention of the ruins in the open air and semi-closed environment, while the completely closed environment was seldom examined. This paper takes the outer pit K21 of the Hanyang Mausoleum as the research object. The number and distribution characteristics of cracks are determined through field investigation. On this basis, the causes of cracks are studied and classified. The stability of pit wall and its influencing factors are analyzed by numerical simulation methods. The research results show that there are 53 cracks in the K21 outer pit, mainly occurring on the south and north sides of the surface and the pit wall. The surface longitudinal cracks are unloading cracks, the surface transverse cracks are dry shrinkage cracks, and the pit wall cracks are mainly structural cracks. The longitudinal unloading crack is the main reason for the reduction of pit wall stability. The earthquake, artificial load or the further development of cracks will lead to the pit wall to be unstable. It is recommended to use anchor bolts to reinforce the pit wall, and reset and pre-tighten the unloading cracks by applying prestress. This study is of important guiding significance for the investigation and protection of the fissure disease in the museum sites.

Surface microstructures can endow materials with excellent functions such as enhanced heat transfer. However, with the continuous improvement of function enhancement, it is urgent to develop the manufacturing technology of more complex multiscale functional microstructures. Herein, an exhaust hot embossing based on a novel multi-block assembled punch is developed to fabricate micro-array structures, and the microformability of conventional process and exhaust process is compared. The combined processing technology of slow-feeding wire cut electrical discharge machining and micro electrical discharge machining is adopted to manufacturing the assembled exhaust punch with numerous micro-holes and complex multiscale features. The processing quality of the assembled punch is better than the integrated punch, and the surface roughness of each position of the assembled punch is Ra ＜ 0.2 μm. During hot embossing experiments, it is found that the exhaust process could significantly improve the filling performance. At 300 °C, the exhaust process realizes complete filling of the microstructures under the maximum load of 25 kN, whereas the conventional process requires 50 kN. Meanwhile, it is also found that the exhaust process can significantly improve warping and surface coarsening defects compared to the conventional process. The pool boiling test was carried out on the fabricated micro-array structures, and it was found that its heat transfer performance is significantly enhanced compared with other tested surfaces, which will be applied in enhanced heat transfer.

Abstract As the unique cell type in articular cartilage, chondrocyte senescence is a crucial cellular event contributing to osteoarthritis development. Here we show that clathrin-mediated endocytosis and activation of Notch signaling promotes chondrocyte senescence and osteoarthritis development, which is negatively regulated by myosin light chain 3. Myosin light chain 3 (MYL3) protein levels decline sharply in senescent chondrocytes of cartilages from model mice and osteoarthritis (OA) patients. Conditional deletion of Myl3 in chondrocytes significantly promoted, whereas intra-articular injection of adeno-associated virus overexpressing MYL3 delayed, OA progression in male mice. MYL3 deficiency led to enhanced clathrin-mediated endocytosis by promoting the interaction between myosin VI and clathrin, further inducing the internalization of Notch and resulting in activation of Notch signaling in chondrocytes. Pharmacologic blockade of clathrin-mediated endocytosis-Notch signaling prevented MYL3 loss-induced chondrocyte senescence and alleviated OA progression in male mice. Our results establish a previously unknown mechanism essential for cellular senescence and provide a potential therapeutic direction for OA.

Background: Diffusion-weighted imaging (DWI), a pivotal component of multiparametric magnetic resonance imaging (mpMRI), plays a pivotal role in the detection, diagnosis, and evaluation of gastric cancer. Despite its potential, DWI is often marred by substantial anatomical distortions and sensitivity artifacts, which can hinder its practical utility. Presently, enhancing DWI’s image quality necessitates reliance on cutting-edge hardware and extended scanning durations. The development of a rapid technique that optimally balances shortened acquisition time with improved image quality would have substantial clinical relevance. Objectives: This study aims to construct and evaluate the unsupervised learning framework called attention dual contrast vision transformer cyclegan (ADCVCGAN) for enhancing image quality and reducing scanning time in gastric DWI. Methods: The ADCVCGAN framework, proposed in this study, employs high b-value DWI (b = 1200 s/mm2) as a reference for generating synthetic b-value DWI (s-DWI) from acquired lower b-value DWI (a-DWI, b = 800 s/mm2). Specifically, ADCVCGAN incorporates an attention mechanism CBAM module into the CycleGAN generator to enhance feature extraction from the input a-DWI in both the channel and spatial dimensions. Subsequently, a vision transformer module, based on the U-net framework, is introduced to refine detailed features, aiming to produce s-DWI with image quality comparable to that of b-DWI. Finally, images from the source domain are added as negative samples to the discriminator, encouraging the discriminator to steer the generator towards synthesizing images distant from the source domain in the latent space, with the goal of generating more realistic s-DWI. The image quality of the s-DWI is quantitatively assessed using metrics such as the peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), feature similarity index (FSIM), mean squared error (MSE), weighted peak signal-to-noise ratio (WPSNR), and weighted mean squared error (WMSE). Subjective evaluations of different DWI images were conducted using the Wilcoxon signed-rank test. The reproducibility and consistency of b-ADC and s-ADC, calculated from b-DWI and s-DWI, respectively, were assessed using the intraclass correlation coefficient (ICC). A statistical significance level of p < 0.05 was considered. Results: The s-DWI generated by the unsupervised learning framework ADCVCGAN scored significantly higher than a-DWI in quantitative metrics such as PSNR, SSIM, FSIM, MSE, WPSNR, and WMSE, with statistical significance (p < 0.001). This performance is comparable to the optimal level achieved by the latest synthetic algorithms. Subjective scores for lesion visibility, image anatomical details, image distortion, and overall image quality were significantly higher for s-DWI and b-DWI compared to a-DWI (p < 0.001). At the same time, there was no significant difference between the scores of s-DWI and b-DWI (p > 0.05). The consistency of b-ADC and s-ADC readings was comparable among different readers (ICC: b-ADC 0.87–0.90; s-ADC 0.88–0.89, respectively). The repeatability of b-ADC and s-ADC readings by the same reader was also comparable (Reader1 ICC: b-ADC 0.85–0.86, s-ADC 0.85–0.93; Reader2 ICC: b-ADC 0.86–0.87, s-ADC 0.89–0.92, respectively). Conclusions: ADCVCGAN shows excellent promise in generating gastric cancer DWI images. It effectively reduces scanning time, improves image quality, and ensures the authenticity of s-DWI images and their s-ADC values, thus providing a basis for assisting clinical decision making.

Arbuscular mycorrhizal (AM) fungi are well known for enhancing phosphorus uptake in plants; however, their regulating roles in cation transporting gene family, such as natural resistance-associated macrophage protein (NRAMP), are still limited. Here, we performed bioinformatics analysis and quantitative expression assays of tomato SlNRAMP 1 to 5 genes under nutrient deficiency and cadmium (Cd) stress in response to AM symbiosis. These five SlNRAMP members are mainly located in the plasma or vacuolar membrane and can be divided into two subfamilies. Cis-element analysis revealed several motifs involved in phytohormonal and abiotic regulation in their promoters. SlNRAMP2 was downregulated by iron deficiency, while SlNRAMP1, SlNRAMP3, SlNRAMP4, and SlNRAMP5 responded positively to copper-, zinc-, and manganese-deficient conditions. AM colonization reduced Cd accumulation and expression of SlNRAMP3 but enhanced SlNRAMP1, SlNRAMP2, and SlNRMAP4 in plants under Cd stress. These findings provide valuable genetic information for improving tomato resilience to nutrient deficiency and heavy metal stress by developing AM symbiosis.

China’s greenhouse industry has undergone thousands of years of development history, although the development of modern greenhouses arrived late. After decades of development in China, its greenhouse industry is at the global forefront. China’s greenhouse industry is experiencing rapid development, transformation, and upgrading. China ranks first in the world in terms of the greenhouse industry. These greenhouses are mainly used for vegetable cultivation, playing an important role in the utilization of agricultural resources and food production. In 2023, the cumulative area of greenhouses nationwide was 1835.87 million ha. In this paper, we present the latest developments in the greenhouse sector. More specifically, we present an overview of the development of the greenhouse market, greenhouse production, the greenhouse industry, and technology development. Current problems are underpinned, development opportunities and prospects are analyzed, and measures and specific proposals are detailed for the technological development of the greenhouse sector, both for increasing product quantity and quality.

The Lower Jurassic Reservoir (LJR) in the Lenghu area on the northern margin of the Qaidam Basin (NMoQB) has become the most promising target for hydrocarbon exploration. The reservoir has experienced complex diagenesis; however, the porosity evolution and the influence of different diagenesis events on reservoir densification remains unclear. In this study, various analytical methods was first used to clarify the diagenetic stage and sequence, establish a porosity evolution model, quantitatively analyze the time and influence of different diagenesis events on reservoir densification, and illustrate the densification mechanism of tight sandstone reservoir in the Lenghu area. The results showed that the dominant rock types in the LJR were feldspathic litharenite, followed by litharenite, lithic arkose, and a small amount of subarkose and sublitharenite. The reservoir is a typical tight sandstone reservoir (TSR), with average porosity and permeability of 5.5% and 0.08 mD, respectively. The pore types were primarily secondary pores, followed by residual intergranular pores and occasional fractures. Diagenesis of LJR has entered the meso-diagenetic stage A, with minor progression into meso-diagenetic stage B. Quantitative calculation showed that the initial porosity of LJR is 32.2%. In eo-diagenetic stage A, compaction is the main factor for porosity reduction. In eo-diagenetic stage B, the porosity loss rates caused by compaction and cementation were 81.5% and 11.8%, respectively. In this stage, the LJR in the Lenghu area has almost been densified, mainly affected by compaction, calcite cementation and clay minerals cementation. Additionally, cementation is an important factor causing reservoir heterogeneity and is dominated by calcite and clay mineral cementation. After entering the meso-diagenetic stage A, dissolution is the main diagenesis event, which can increase porosity by 6.0%. This stage is the critical period for forming high-quality reservoir of LJR in the Lenghu area, mainly in the 4,400 m depth. In meso-diagenetic stage B, the influence of dissolution gradually decreased. Simultaneously, in this stage, the cementation of iron-bearing calcite further strengthened the densification of the LJR in the Lenghu area.

Introduction: Against the background of rapid global urbanization, the urban space expansion has led to increasingly acute land-use conflicts. Accurately understanding the spatial and temporal evolution characteristics of land-use conflict patterns and measuring the level of spatial conflicts are crucial for intensifying sustainable use and management of land resources. Existing research focuses on analyzing the current status of land-use conflicts, while there is limited discussion on tracking spatial-temporal dynamic patterns and simulating future conflict trends.Method: In this paper, the level of spatial conflict was measured by constructing a spatial comprehensive conflict index (SCCI) model, and the spatio-temporal evolution characteristics of land use conflict in Harbin-Changchun urban agglomeration from 2000 to 2020 are discussed. In addition, the PLUS model is used to simulate and predict the pattern of land use conflict in 2030, finally put forward the control strategy.Results: Result shows that: (1) Over the past 20 years, urban space has expanded rapidly with two provincial capitals as growth poles. Land-use conflicts generally exhibit a distribution pattern of “high in the west and low in the east, high in the core and low in the periphery.” (2) During the past 20 years, conflicts have intensified initially and then eased. Severe uncontrolled conflicts are concentrated in the transition zone between urban and rural areas of urban agglomerations. (3) Agricultural space is the core resource and key area contested by different interest subjects in the process of land development and utilization.Discussion: The agricultural space priority scenario proves to be the most effective in controlling spatial conflicts. However, a single space priority scenario cannot adequately address multiple spatial rights and interests. Therefore, different spatial management modes should be implemented in different areas. The purpose of this paper is to provide scientific strategies and suggestions for controlling land-use conflicts in urban agglomerations and achieving sustainable development of regional land use.

BackgroundIntravascular leiomyomatosis (IVL) is often a non-malignant condition that grows inside the blood vessels and does not invade surrounding tissues. However, its presence within the blood vessels can lead to obstructions. The majority of IVL cases manifest symptoms related to blockage.Case presentationWe present a case of a 50-year-old female patient who was referred to our institution due to the presence of a common non-cancerous tumor in the uterus, known as a benign uterine leiomyoma. The tumor was identified during an ultrasound examination during a routine physical examination. Postoperative pathology established the existence of intrapelvic IVL.ConclusionIntrapelvic IVL often not present with complications when it is confined to the pelvic cavity. Furthermore, the imaging features of intrapelvic IVL resemble those of typical benign uterine leiomyomas. This can often result in the clinical misdiagnosis of the tumor as a typical benign uterine leiomyoma.

Land use regression (LUR) models are widely used in epidemiological and environmental studies to estimate humans’ exposure to air pollution within urban areas. However, the early models, developed using linear regressions and data from fixed monitoring stations and passive sampling, were primarily designed to model traditional and criteria air pollutants and had limitations in capturing high-resolution spatiotemporal variations of air pollution. Over the past decade, there has been a notable development of multi-source observations from low-cost monitors, mobile monitoring, and satellites, in conjunction with the integration of advanced statistical methods and spatially and temporally dynamic predictors, which have facilitated significant expansion and advancement of LUR approaches. This paper reviews and synthesizes the recent advances in LUR approaches from the perspectives of the changes in air quality data acquisition, novel predictor variables, advances in model-developing approaches, improvements in validation methods, model transferability, and modeling software as reported in 155 LUR studies published between 2011 and 2023. We demonstrate that these developments have enabled LUR models to be developed for larger study areas and encompass a wider range of criteria and unregulated air pollutants. LUR models in the conventional spatial structure have been complemented by more complex spatiotemporal structures. Compared with linear models, advanced statistical methods yield better predictions when handling data with complex relationships and interactions. Finally, this study explores new developments, identifies potential pathways for further breakthroughs in LUR methodologies, and proposes future research directions. In this context, LUR approaches have the potential to make a significant contribution to future efforts to model the patterns of long- and short-term exposure of urban populations to air pollution.

Understanding changes in industrial water use at finer spatial scales is critical for regional water allocation and sustainability. This study employs a top-down method based on multi-source data to estimate the industrial water use at 1 km × 1 km resolution in the Beijing-Tianjin-Hebei (BTH) region during 2000–2019. Statistical data from municipalities and prefectures are used to assess the accuracy of simulated industrial water use. During the validation period, all accuracy validation indices (R, NSE, |RE|, RMSE) have achieved good results, indicating that the method is credible. In addition, industrial water use at the county level in BTH has a strong spatial correlation with 99% confidence. Spatiotemporal change pattern mainly depends on the industrial scale and technical level of prefecture-level cities, and the economic environment will also contribute to changes in the annual industrial water use in BTH. The method provides a reference for high-resolution estimation of industrial water use and can also be applied to regional water management and allocation.

In the EAST (Experimental Advanced Superconducting Tokamak), the manifolds play an important role in the blow-out process, which directly affects the dryness of the plasma facing components (PFCs) and the entire drying system. This will cause corrosion of PFCs and coolant leakage, which will seriously affect the safe operation of the device. Therefore, it is necessary to study the gas–liquid​ two-phase flow characteristics of the manifold during the blowout process. In this paper, the CFD (Computational Fluid Dynamics) method was used to simulate the gas–liquid blowout process of the manifold with different header-diameters, and to discuss the influence mechanism of the change of header-diameter on the blowout effect. Under the boundary condition of a gas supply with a certain pressure difference, it can be found that enlarging the header-diameter can enhance the uniformity of the flow of branches, improve the inlet gas flow rate of manifold, which conductively improve the dryness of the manifold. The research results in this paper will provide reference for improving the dryness of internal components and drying systems, and also for the construction of future fusion reactor drying systems.

Abstract It was demonstrated that a string probe falling radially within a superstratum geometry would experience tidal forces. These tidal forces were shown to excite the string by converting its kinetic energy into stringy excitations. Using the AdS/CFT correspondence we seek to understand this behavior from the perspective of the dual D1D5 CFT. To study this process we turn on an interaction of the theory which is described by a deformation operator. We start with an initial state which is dual to a graviton probe moving within the superstratum geometry. We then use two deformation operators to compute transition amplitudes between this state and a final state that corresponds to stringy excitations. We show that this amplitude grows as t 2 with t being the amount of time for which the deformation operators are turned on. We argue that this process in the CFT is suggestive of the tidal effects experienced by the probe propagating within the dual superstratum geometry.

Abstract In this study, we aimed to investigate the causal associations of brain structure with bone mineral density (BMD). Based on the genome-wide association study (GWAS) summary statistics of 1 325 brain imaging-derived phenotypes (BIDPs) of brain structure from the UK Biobank and GWAS summary datasets of 5 BMD locations, including the total body, femoral neck, lumbar spine, forearm, and heel from the GEFOS Consortium, linkage disequilibrium score regression (LDSC) was conducted to determine the genetic correlations, and Mendelian randomization (MR) was then performed to explore the causal relationship between the BIDPs and BMD. Several sensitivity analyses were performed to verify the strength and stability of the present MR outcomes. To increase confidence in our findings, we also performed confirmatory MR between BIDPs and osteoporosis. LDSC revealed that 1.93% of BIDPs, with a false discovery rate (FDR)

Abstract Recently, ammonia (NH3), which has a higher energy density than hydrogen, has gained attention for zero-carbon emission goals in the transportation sector. However, in a conventional internal combustion engine (ICE), NH3 combustion mechanism is still under investigation. In this paper, to further expand the knowledge on the adoption of NH3 in ICEs, authors conducted NH3/gasoline co-combustion experiments in a modified, 17.7:1 compression ratio, naturally aspirated spark-assisted CI engine with sub-chamber. The sub-chamber was chosen in order to enhance the combustion speed of NH3. In addition, the sub-chamber was equipped with glow and spark plugs to overcome the high auto-ignition temperature of NH3. Engine performance and NOX emissions were studied under three different intake air temperatures. During the experiments, NH3 content was increased gradually where the engine was run under lean conditions. Although higher NH3 content was achieved compared to our previous work, increasing the intake air temperature resulted in decreased charging efficiency. In addition, corrosion was found on the piston ring after 120 h of operation, negatively affecting the engine performance. Furthermore, NH3/gasoline co-combustion duration was shortened drastically with the influence of the sub-chamber, where the longest combustion duration under the present conditions was found to be 17°CA.

As an environmentally friendly new method for coating removal, laser cleaning has been widely used in aircraft skin paint removal recently. However, due to the thermal damage sensitivity of composite materials, current laser cleaning is still mainly used in aluminum alloy skins. In this work, we demonstrate a method for cleaning the surface paint of honeycomb sandwich structures by ultraviolet picosecond laser. The method achieves layer-by-layer and non-destructive removal of paint from composite surfaces. The results show that the top coat is selectively removed when the laser power is 8 W and the scanning speed is 1750 mm/s. When the laser power is 8 W and the scanning speed is 750 mm/s, both top coat and primer are completely removed without any morphological damage for the glass fiber. The temperature monitoring results show that the UV picosecond laser exhibits low-temperature paint removal. The paint removal mechanism of UV picoseconds is dominated by photochemical effects.

Currently, brain tumors are extremely harmful and prevalent. Deep learning technologies, including CNNs, UNet, and Transformer, have been applied in brain tumor segmentation for many years and have achieved some success. However, traditional CNNs and UNet capture insufficient global information, and Transformer cannot provide sufficient local information. Fusing the global information from Transformer with the local information of convolutions is an important step toward improving brain tumor segmentation. We propose the Group Normalization Shuffle and Enhanced Channel Self-Attention Network (GETNet), a network combining the pure Transformer structure with convolution operations based on VT-UNet, which considers both global and local information. The network includes the proposed group normalization shuffle block (GNS) and enhanced channel self-attention block (ECSA). The GNS is used after the VT Encoder Block and before the downsampling block to improve information extraction. An ECSA module is added to the bottleneck layer to utilize the characteristics of the detailed features in the bottom layer effectively. We also conducted experiments on the BraTS2021 dataset to demonstrate the performance of our network. The Dice coefficient (Dice) score results show that the values for the regions of the whole tumor (WT), tumor core (TC), and enhancing tumor (ET) were 91.77, 86.03, and 83.64, respectively. The results show that the proposed model achieves state-of-the-art performance compared with more than eleven benchmarks.

Incorporating iron tailings (ITs) into asphalt represents a new method for waste-to-resource conversion. The objective of this study is to evaluate the fatigue performance of ITs as fillers in asphalt mastic and investigate the interaction and interfacial adhesion energy between asphalt and ITs. To achieve that, the particle size distributions of two ITs and limestone filler (LF) were tested through a laser particle size analyzer; the morphology and structure characteristics were obtained by scanning electronic microscopy (SEM), the mineral compositions were conducted through X-ray diffraction (XRD), and the chemical compositions were tested through X-ray Fluorescence Spectrometer (XRF). Furthermore, the fatigue properties of asphalt mastic and the interaction between asphalt binder and mineral fillers (ITs and LFs) were evaluated by Dynamic Shear Rheometer (DSR). The interfacial adhesion energy between ITs and asphalt binder were calculated through molecular dynamics simulation. In the end, the correlation between the test results and the fatigue life is established based on the gray correlation analysis, the environmental and economic benefits of iron tailings asphalt pavement are further evaluated. The results show that the particle size distribution of ITs is concentrated between 30 μm and 150 μm, and the main component is quartz. ITs have rich angularity and a higher interaction ability with asphalt. The adhesion energy of iron tailings filler to asphalt is less than that of limestone. The correlation degree of the interfacial adhesion energy and interaction between asphalt and mineral filler with asphalt mastic fatigue life is close to 0.58. Under the combined action of interaction ability and interfacial adhesion energy, the fatigue life of IT asphalt mastic meets the requirements. ITs as a partial replacement for mineral fillers in asphalt pavement have great environmental and social effectiveness.

High-entropy alloys (HEAs) have garnered significant attention for their exceptional properties, with eutectic high-entropy alloys (EHEAs) emerging as particularly notable due to their incorporation of eutectic structures comprising soft and hard phases. This study investigated the influence of shear strain on the microstructural refinement and mechanical properties of AlCoCrFeNi2.1 EHEAs, which were subjected to high-pressure torsion (HPT) at room temperature under a pressure of 6 GPa across 0.5 to 3 turns, compared to the initial material. After HPT treatment, significant grain refinement occurred due to strong shear strain, evidenced by the absence of B2 phase peaks in X-ray diffraction (XRD) analysis. Microhardness increased substantially post-HPT, reaching a saturation point at approximately 575 HV after three turns, significantly higher than that of the original sample. Moreover, the ultimate tensile strength of HPT-treated specimens reached around 1900 MPa after three revolutions, compared to approximately 1100 MPa for the as-cast alloy, with a mixed fracture mode maintained. This investigation underscores the efficacy of HPT in enhancing the mechanical properties of AlCoCrFeNi2.1 EHEAs through microstructural refinement induced by shear deformation, offering insights into the design and optimization of advanced HEAs for various engineering applications.

Cable-driven parallel robots (CDPRs) offer significant advantages, such as the lightweight design, large workspace, and easy reconfiguration, making them essential for various spatial applications and extreme environments. However, despite their benefits, CDPRs face challenges, notably the uncertainty in terms of the post-reconstruction parameters, complicating cable coordination and impeding mechanism parameter identification. This is especially notable in CDPRs with redundant constraints, leading to cable relaxation or breakage. To tackle this challenge, this paper introduces a novel approach using reinforcement learning to drive redundant constrained cable-driven robots with uncertain parameters. Kinematic and dynamic models are established and applied in simulations and practical experiments, creating a conducive training environment for reinforcement learning. With trained agents, the mechanism is driven across 100 randomly selected parameters, resulting in a distinct directional distribution of the trajectories. Notably, the rope tension corresponding to 98% of the trajectory points is within the specified tension range. Experiments are carried out on a physical cable-driven device utilizing trained intelligent agents. The results indicate that the rope tension remained within the specified range throughout the driving process, with the end platform successfully maneuvered in close proximity to the designated target point. The consistency between the simulation and experimental results validates the efficacy of reinforcement learning in driving unknown parameters in redundant constraint-driven robots. Furthermore, the method’s applicability extends to mechanisms with diverse configurations of redundant constraints, broadening its scope. Therefore, reinforcement learning emerges as a potent tool for acquiring motion data in cable-driven mechanisms with unknown parameters and redundant constraints, effectively aiding in the reconstruction process of such mechanisms.

Efficient magnetic resonance imaging (MRI) segmentation, which is helpful for treatment planning, is essential for identifying brain tumors from detailed images. In recent years, various convolutional neural network (CNN) structures have been introduced for brain tumor segmentation tasks and have performed well. However, the downsampling blocks of most existing methods are typically used only for processing the variation in image sizes and lack sufficient capacity for further extraction features. We, therefore, propose SARFNet, a method based on UNet architecture, which consists of the proposed SLiRF module and advanced AAM module. The SLiRF downsampling module can extract feature information and prevent the loss of important information while reducing the image size. The AAM block, incorporated into the bottleneck layer, captures more contextual information. The Channel Attention Module (CAM) is introduced into skip connections to enhance the connections between channel features to improve accuracy and produce better feature expression. Ultimately, deep supervision is utilized in the decoder layer to avoid vanishing gradients and generate better feature representations. Many experiments were performed to validate the effectiveness of our model on the BraTS2018 dataset. SARFNet achieved Dice coefficient scores of 90.40, 85.54, and 82.15 for the whole tumor (WT), tumor core (TC), and enhancing tumor (ET), respectively. The results show that the proposed model achieves state-of-the-art performance compared with twelve or more benchmarks.

Deep neural networks must address the dual challenge of delivering high-accuracy predictions and providing user-friendly explanations. While deep models are widely used in the field of time series modeling, deciphering the core principles that govern the models’ outputs remains a significant challenge. This is crucial for fostering the development of trusted models and facilitating domain expert validation, thereby empowering users and domain experts to utilize them confidently in high-risk decision-making contexts (e.g., decision-support systems in healthcare). In this work, we put forward a deep prototype learning model that supports interpretable and manipulable modeling and classification of medical time series (i.e., ECG signal). Specifically, we first optimize the representation of single heartbeat data by employing a bidirectional long short-term memory and attention mechanism, and then construct prototypes during the training phase. The final classification outcomes (i.e., normal sinus rhythm, atrial fibrillation, and other rhythm) are determined by comparing the input with the obtained prototypes. Moreover, the proposed model presents a human–machine collaboration mechanism, allowing domain experts to refine the prototypes by integrating their expertise to further enhance the model’s performance (contrary to the human-in-the-loop paradigm, where humans primarily act as supervisors or correctors, intervening when required, our approach focuses on a human–machine collaboration, wherein both parties engage as partners, enabling more fluid and integrated interactions). The experimental outcomes presented herein delineate that, within the realm of binary classification tasks—specifically distinguishing between normal sinus rhythm and atrial fibrillation—our proposed model, albeit registering marginally lower performance in comparison to certain established baseline models such as Convolutional Neural Networks (CNNs) and bidirectional long short-term memory with attention mechanisms (Bi-LSTMAttns), evidently surpasses other contemporary state-of-the-art prototype baseline models. Moreover, it demonstrates significantly enhanced performance relative to these prototype baseline models in the context of triple classification tasks, which encompass normal sinus rhythm, atrial fibrillation, and other rhythm classifications. The proposed model manifests a commendable prediction accuracy of 0.8414, coupled with macro precision, recall, and F1-score metrics of 0.8449, 0.8224, and 0.8235, respectively, achieving both high classification accuracy as well as good interpretability.