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In this paper, a nodal detection method for the detection and optimization of barrel helix offsets is proposed. The barrel used in this experiment is a 6-helix barrel. Moreover, the special properties of the film of Polyetheretherketone (PEEK) material are used to cover the surface of the barrel helix with a virtual in-mold decoration (IMD) film, and the unique nature of the film die offset in the IMD is utilized to detect the position of the barrel helix. The area with a large die index is the area with a large helix offset in the barrel, and the IMD die index is introduced to quantify the data. The IMD die index is used to determine the helix offset of the damaged barrel. The novelty of this work is that each node can use the die index to efficiently detect the position of the barrel helix deviation, carry out subsequent optimization and repair work through the optimization of the injection molding parameters and the design optimization of the barrel and verify the experiment by comparing the results. Through the steady-state simulation research mode, different permutations and combinations of the two process parameters are simulated to study their effects. Quantitative reference indicators include but are not limited to dependent variables such as the fluid flow velocity, shear rate, temperature distribution and phase transition, and the shear heating process of the injection screw is taken into account in the mold flow analysis to ensure that the die index value is more accurate. It can be seen from the analysis results that the temperature of the barrel changes after the groove depth and groove width are changed, and the effect ratio of the groove depth is lower than that of the groove width in the same degree of size change.

The emergence of super-resolution (SR) fluorescence microscopy has rejuvenated the search for new cellular sub-structures. However, SR fluorescence microscopy achieves high contrast at the expense of a holistic view of the interacting partners and surrounding environment. Thus, we developed SR fluorescence-assisted diffraction computational tomography (SR-FACT), which combines label-free three-dimensional optical diffraction tomography (ODT) with two-dimensional fluorescence Hessian structured illumination microscopy. The ODT module is capable of resolving the mitochondria, lipid droplets, the nuclear membrane, chromosomes, the tubular endoplasmic reticulum, and lysosomes. Using dual-mode correlated live-cell imaging for a prolonged period of time, we observed novel subcellular structures named dark-vacuole bodies, the majority of which originate from densely populated perinuclear regions, and intensively interact with organelles such as the mitochondria and the nuclear membrane before ultimately collapsing into the plasma membrane. This work demonstrates the unique capabilities of SR-FACT, which suggests its wide applicability in cell biology in general.Microscopy: New tool furthers our understanding of living cellsScientists from China have developed a new microscopy tool that could help to further expand our understanding of cell biological processes in live cells. Although the emergence of superresolution (SR) fluorescence microscopy is revolutionising the life sciences, the technique can only be used to observe a handful of biomolecules simultaneously and cannot provide a holistic map of the cellular landscape. Furthermore, the imaging of live cells in three dimensions (3D) over time also remains very challenging. By combining two different techniques, a team of Chinese researchers led by Liangyi Chen and Kebin Shi from Peking University has created a novel dual-mode high-speed SR microscopy technique. The tool is capable of revealing previously unseen sub-cellular structures and dynamic processes, allowing both the cellular landscape and molecular identity in live cells to be observed in 3D over prolonged periods.

This study evaluates the effects of Self-Myofascial Release (SMR) through foam rolling (FR), aerobic recovery (AR), and passive recovery (PAS) on muscle recovery following high-intensity exercise in elite volleyball athletes. A total of 33 participants were randomly assigned to the FR, AR, or PAS groups. Recovery was assessed using deep squat jump performance, blood lactate levels, creatine kinase (CK), and Visual Analog Scale (VAS) scores. Results showed that FR and AR facilitated recovery, with FR improving jump performance by 23% ( p  = 0.03), reducing lactate by 15% ( p  = 0.01), and significantly lowering VAS scores ( p  = 0.02). The AR group showed a 19% improvement ( p  = 0.05) in jump performance and a 14% reduction in lactate ( p  = 0.04), but showed no significant improvement in VAS scores ( p  > 0.05). For CK clearance, FR demonstrated the greatest reduction in CK levels (from 415.4 U/L to 280.6 U/L at 72 h), while AR also showed a marked reduction (from 410.3 U/L to 300.2 U/L at 72 h). In contrast, PAS showed minimal changes across all measures. Thermal imaging revealed faster normalization of muscle temperature in FR and AR groups ( p  = 0.04), supporting enhanced circulation and recovery. These findings suggest that FR and AR are effective recovery strategies, with FR demonstrating the greatest improvements in muscle recovery metrics, while PAS showed less pronounced effects. Deep squat jumps and VAS scores are useful for monitoring recovery progress, but for a full assessment of muscle regeneration, additional biochemical markers are recommended. Further investigation into the long-term impact of these recovery strategies in high-intensity sports is warranted.

If the Higgs boson discovered at the Large Hadron Collider (LHC) is not exactly the one in the Standard Model, an alternative mechanism is needed to restore unitarity in the scattering amplitude of longitudinal gauge bosons, and new resonances may appear. This paper presents a search for new heavy neutral resonances (R) produced through vector boson fusion process (ℓ = e, μ) using 3.2 fb−1 of data at √s = 13 TeV recorded by the ATLAS detector at the LHC. No excess above the Standard Model background expectation is observed. Limits are set on the production of five types of neutral resonances with different spin and isospin quantum numbers using a K-matrix unitarization of the vector boson scattering process.

Under the influence of climate change, extreme heat events are becoming more frequent and intense. Understanding the response mechanisms of public building spaces, such as atriums, during extreme heat events is of great significance for developing effective design strategies to enhance the thermal resilience of buildings. This study investigated the effect of atrium spaces on the thermal resilience of buildings during heatwaves, focusing on their ability to mitigate high temperatures under two states: closed and open. The research monitored the indoor and outdoor temperature and humidity data of the atrium of a university building in Shanghai during a typical heatwave, and used statistical methods to analyze the relationships between the thermal resilience indicators and various environmental parameters, including the indoor and outdoor temperatures and ventilation states, to evaluate the thermal performance of the atrium. The results indicate that the atrium demonstrated robust thermal resilience under both closed and open conditions. In the closed phase, the indoor temperature was, on average, approximately 7 °C lower than the outdoor temperature, with the maximum difference reaching 11 °C, and the peak temperature delay was up to 4 h. In the open phase, despite exhibiting larger thermal fluctuations and an increase in temperature non-uniformity, the thermal resilience index improved significantly, from 0.231 in the closed phase to 0.047. The analytical framework developed in this study shows great potential for understanding the thermal resilience mechanisms of buildings during extreme heat events. Additionally, the data-driven insights are invaluable for informing the design strategies of public building spaces, especially in regions prone to extreme heat.

Background Despite hip function typically deteriorating in the post-collapse stage of osteonecrosis of the femoral head (ONFH), some patients can still demonstrate long-term favorable hip function, a state termed “survival with collapse”. This study aims to identify the characteristics of patients suitable for “survival with collapse” in cases of ONFH. Methods This cross-sectional study included 65 patients (87 hips) diagnosed with post-collapse ONFH for ≥ 3 years (average 9.1 years, range 3–23 years). Hip function was assessed using the Harris Hip Score (HHS). Demographic, clinical, and radiographic data were compared between the favorable group (HHS > 80) and the poor group (HHS ≤ 80). Independent protective factors for hip function were identified by multivariate analysis and receiver operating characteristic (ROC) curve analysis was further applied to evaluate these factors’ diagnostic efficacy. Results The favorable and poor groups included 46 and 41 hips, respectively. Significant differences were found in body mass index (BMI), Association Research Circulation Osseous (ARCO) stage, collapse degree, Japanese Investigation Committee (JIC) classification, necrotic size, and hip subluxation between the two groups ( p  < 0.05). Multivariate logistic regression identified collapse < 3 mm(OR:14.49, 95%CI: 3.52–59.68, p  < 0.001), JIC types B (OR: 11.08, 95% CI: 1.07-115.12, p  < 0.05) and C1(OR: 5.18, 95% CI: 1.47–18.20, p  < 0.05) as independent protective factors for hip function, while BMI (OR: 0.76, 95% CI: 0.59–0.97, p  = 0.029) was an independent risk factor. ROC curve analysis demonstrated that both collapse degree (AUC = 0.798, sensitivity = 91.3%, specificity = 68.3%, p  < 0.0001) and JIC classification (AUC = 0.787, sensitivity = 80.4%, specificity = 73.2%, p  < 0.0001) had satisfactory diagnostic value for hip function. Combining JIC classification and collapse degree (AUC = 0.868, sensitivity = 76.1%, specificity = 85.4%, p  < 0.0001) significantly enhanced diagnostic efficacy compared to using either alone ( p  < 0.05). Conclusion In ONFH, femoral head collapse does not necessarily determine a poor prognosis. Patients with mild collapse (< 3 mm) and preserved anterolateral wall are more likely to retain satisfactory hip function, making them candidates for “survival with collapse.”

Decision trees are popular classification models, providing high accuracy and intuitive explanations. However, as the tree size grows the model interpretability deteriorates. Traditional tree-induction algorithms, such as C4.5 and CART, rely on impurity-reduction functions that promote the discriminative power of each split. Thus, although these traditional methods are accurate in practice, there has been no theoretical guarantee that they will produce small trees. In this paper, we justify the use of a general family of impurity functions, including the popular functions of entropy and Gini-index, in scenarios where small trees are desirable, by showing that a simple enhancement can equip them with complexity guarantees. We consider a general setting, where objects to be classified are drawn from an arbitrary probability distribution, classification can be binary or multi-class, and splitting tests are associated with non-uniform costs. As a measure of tree complexity, we adopt the expected cost to classify an object drawn from the input distribution, which, in the uniform-cost case, is the expected number of tests. We propose a tree-induction algorithm that gives a logarithmic approximation guarantee on the tree complexity. This approximation factor is tight up to a constant factor under mild assumptions. The algorithm recursively selects a test that maximizes a greedy criterion defined as a weighted sum of three components. The first two components encourage the selection of tests that improve the balance and the cost-efficiency of the tree, respectively, while the third impurity-reduction component encourages the selection of more discriminative tests. As shown in our empirical evaluation, compared to the original heuristics, the enhanced algorithms strike an excellent balance between predictive accuracy and tree complexity.

To reveal the effects of thermal hydrolysis (TH) pretreatment (THPT) on anaerobic digestion (AD) of protein-rich substrates, discarded tofu was chosen as the object, and its batch AD tests of tofu before and after being subjected to TH at gradually increasing organic loads were carried out and the AD process characteristics were compared; furthermore, its continuous AD tests without and with THPT were also conducted and the difference of the microbial community structures was investigated. The results showed that, during AD of protein-rich tofu with increase in the organic load, inhibition from severe acidification prior to accumulation of ammonia nitrogen (AN) occurred. THPT helped overcome the acidification inhibition present in batch AD of tofu at such a high TS content of 3.6%, to obtain the maximum methane yield rate of 589.39 ml·(gVS) −1 . Continuous AD of protein-rich tofu heavily depended on ammonia-tolerant hydrogenotrophic methanogens and bacteria. The continuous AD processes acclimated by HT substrates seemed to be resistant to severe organic loads, by boosting growth of ammonia-tolerant microorganisms, above all methylotrophic methanogens such as the genera RumEnM2 and methanomassiliicoccus. The process response of continuous AD of HT tofu was hysteretic, suggesting that a sufficiently long adaptation period was required for stabilizing the AD system.

The digestibility of lignocellulosic biomass is limited by its high content of refractory components. The objective of this study is to investigate hydrothermal pretreatment and its effects on anaerobic digestion of sorted organic waste with submerged fermentation. Hydrothermal pretreatment (HT) was performed prior to anaerobic digestion, and three agents were examined for the HT: hot compressed water, alkaline solution, and acidic solution. The concentrations of glucose and xylose were the highest in the sample pretreated in acidic solution. Compared with that of the untreated sample, the biogas yields from digesting the samples pretreated in alkaline solution, acidic solution, and hot water increased by 364, 107, and 79 %, respectively. The decrease of chemical oxygen demand (COD) in liquid phase followed the same order as for the biogas yield. The initial ammonia content of the treated samples followed the order sample treated in acidic solution > sample treated in alkaline solution > sample treated in hot water. The concentrations of volatile fatty acids (VFAs) were low, indicating that the anaerobic digestion process was running at continuously stable conditions.

Published papers highlight the roles of the catalysts in plasma catalysis systems, and it is essential to provide deep insight into the mechanism of the reaction. In this work, a coaxial dielectric barrier discharge (DBD) reactor packed with γ-MnO2 and CeO2 with similar nanorod morphologies and particle sizes was used for methanol oxidation at atmospheric pressure and room temperature. The experimental results showed that both γ-MnO2 and CeO2 exhibited good performance in methanol conversion (up to 100%), but the CO2 selectivity of CeO2 (up to 59.3%) was much higher than that of γ-MnO2 (up to 28.6%). Catalyst characterization results indicated that CeO2 contained more surface-active oxygen species, adsorbed more methanol and utilized more plasma-induced active species than γ-MnO2. In addition, in situ Raman spectroscopy and Fourier transform infrared spectroscopy (FT-IR) were applied with a novel in situ cell to reveal the major factors affecting the catalytic performance in methanol oxidation. More reactive oxygen species (O22−, O2−) from ozone decomposition were produced on CeO2 compared with γ-MnO2, and less of the intermediate product formate accumulated on the CeO2. The combined results showed that CeO2 was a more effective catalyst than γ-MnO2 for methanol oxidation in the plasma catalysis system.