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Compared with most dynamic tests, point load test is widely used in engineering practice because of its wide requirements for test conditions. In offshore mining engineering, the surrounding rock is affected by dynamic load impact and corrosion of various aqueous solutions for a long time. Therefore, it is of great significance to study the influence of hydrochemical corrosion on dynamic mechanical properties of rock to ensure the stability of surrounding rock. In this paper, a large number of dynamic point load and dynamic uniaxial compression tests were carried out on the granite mined from a large mine by using the Split Hopkinson pressure bar test device after the corrosion of pH values of 2, 5, and 7 solutions, respectively. Based on the energy theory, the crushing energy consumption in the test process is analyzed, and finally the fitting formula of the dynamic compressive strength and the crushing energy consumption in the dynamic point load test is obtained through fitting analysis. The results show that when the crushing energy consumption in the dynamic point load test is used to estimate the dynamic compressive strength, a certain crushing energy consumption (the final value of this test is 70 J in this paper) is more accurate, and it can estimate the dynamic compressive strength under various corrosion conditions under this crushing energy consumption. However, with the change of crushing energy consumption in the dynamic point load test, this transformation relationship is no longer accurate, and it is necessary to modify this transformation relationship with corrosion condition as the influencing factor. This conclusion can provide reference for obtaining the dynamic compressive strength of rocks under different corrosion conditions in engineering field in the future.

As one of the core components of the transport medium in the energy pile system, the circulating working fluid is crucial for the enhancement of its heat transfer efficiency. In this study, based on the heat transfer enhancement theory of nanofluids, deionized water was used as the base solution to prepare the corresponding 0, 0.5, 1, and 1.5 vol% nanofluids by introducing nanoparticles SiO2, Al2O3, CuO, and Cu. The laws of thermal conductivity and specific heat capacity with the volume fraction of different nanofluids are studied by the comparison. The results of thermal conductivity research illustrate that the specific heat capacity of nanofluids decreases linearly with the increase of the volume concentration of nanoparticles, but the thermal conductivity increases linearly. The fluid with the highest thermal conductivity and specific heat capacity is Cu–water nanofluids. In addition, it is proposed to directly apply all kinds of nanofluids with 1 vol% as circulating fluid to self-made miniature model box of energy pile to simulate the working conditions in summer. The influence laws of the nanofluids on the flow rate and heat transfer efficiency in the energy pile were calculated through the temperature difference between the inlet and outlet of the heat exchange tube. The results reveal that the nanofluids used in the experiment exert a optimization influence on the heat transfer of energy pile but the mass flow rate of the nanofluids during the circulation is decreased compared with that of the deionized water circulation liquid. Among them, the temperature difference between inlet and outlet of Cu–water nanofluid is the largest, which has the best effect on improving the heat transfer efficiency of the energy pile but its mass flow loss is also the largest. The research results can provide a reliable reference for the improvement of heat transfer efficiency of energy pile engineering in the future.

Thermal power plants play a crucial role in the power system as critical lifeline infrastructure. In order to meet the production process requirements, the main building of a thermal power plant is often connected to a coal conveyor trestle. This study focuses on investigating the seismic interaction between the common three-row reinforced concrete frame-bent main building and the steel trestle in a circulating fluidized bed (CFB) unit. The objective is to assess the influence of the trestle on the main building and understand the failure mode of the trestle structure. The seismic interaction is analyzed through fragility analysis based on Incremental Dynamic Analysis (IDA). The results indicate that the trestle has minimal influence on the main building, except during the large deformation stage. The study identifies the failure mode of the coal conveyor trestle as excessive relative displacement along the longitudinal direction at the connection points, leading to collisions or falls. A seismic demand model based on longitudinal relative displacement is developed to obtain the fragility curve for the trestle structure. These findings offer valuable insights for assessing the seismic performance of thermal power plants.

The in situ stress measurement technique can be used in long-term monitoring of induced stress to obtain three-dimensional stress states in slope engineering. In the monitoring, the ambient temperature fluctuation, “zero” drift of the logging data, and stable power supply should be considered. A dual temperature compensation circuit and experimental calibration techniques are proposed to increase accuracy based on the principle of the CSIRO method and considering the effect of a long-term disturbance of temperature in slope engineering. In view of the characteristics of the stress field distribution of the slope rock, the strain gauge layout scheme for induced stress monitoring of slope rock is modified to achieve the acquisition of three parallel measurements at one measurement and a stress–strain relationship equation for multilayer elastic layers is derived. An in situ stress logging system with the function of transient logging and data-connection in power cut condition is introduced to achieve a continuous correlation of measurement data under power cut conditions. An online cloud platform is established for the slope engineering of Au Mountain Iron Mine in Maanshan City. The results show that the data deviation of logging system is ±14 με with 24 days’ power off, and errors with amount of 15% were corrected by the dual temperature compensation method. The remotely transmitted data reflect the effect of temperature changes and the evolution of strain (induced stress) in real time to satisfy the demand of long-term monitoring of slope engineering.

ObjectiveLeukocytes telomere length (LTL) was reported to be associated with cellular aging and aging related disease. Urine metal also might accelerate the development of aging related disease. We aimed to analyze the association between LTL and urinary metals.MethodsIn this research, we screened all cycles of National Health and Nutrition Examination Survey (NHANES) dataset, and download the eligible dataset in NHANES 1999–2002 containing demographic, disease history, eight urine metal, and LTL. The analysis in this research had three steps including baseline difference comparison, multiple linear regression (MLR) for hazardous urine metals, and artificial neural network (ANN, based on Tensorflow framework) to make LTL prediction.ResultsThe MLR results showed that urinary cadmium (Cd) was negatively correlated with LTL in the USA population [third quantile: −9.36, 95% confidential interval (CI) = (−19.7, −2.32)], and in the elderly urinary molybdenum (Mo) was positively associated with LTL [third quantile: 24.37, 95%CI = (5.42, 63.55)]. An ANN model was constructed, which had 24 neurons, 0.375 exit rate in the first layer, 15 neurons with 0.53 exit rate in the second layer, and 7 neurons with 0.86 exit rate in the third layer. The squared error loss (LOSS) and mean absolute error (MAE) in the ANN model were 0.054 and 0.181, respectively, which showed a low error rate.ConclusionIn conclusion, in adults especially the elderly, the relationships between urinary Cd and Mo might be worthy of further research. An accurate prediction model based on ANN could be further analyzed.

Objective: To investigate the effect of indirubin on the expression of proinflammatory cytokines in HaCaT cells, and to elucidate the mechanisms of Diqing ointment in the treatment of psoriasis. Methods: The human immortalized keratinocyte cell line, HaCaT cells, were used to observe the changes in the expression levels of IL-1β, IL-6, and TNF-α in HaCaT cells after treatment with different concentrations of indirubin. HaCaT cells were divided into 4 groups. The secretion levels of IL-1β, IL-6, and TNF-α in the culture supernatants were detected by enzyme-linked immunosorbent assay ELISA, and the expression levels of IL-1β, IL-6, and TNF-α mRNA were detected by real-time PCR (RT-qPCR). Results: Expression levels of both mRNA and protein of IL-1β, IL-6, and TNF-α were significantly and dose-dependently decreased after treatment with indirubin. Conclusion: Indirubin, the main component of Qingdai ointment, can lower expression levels of pro-inflammatory cytokines such as IL-1β, IL-6, and TNF-α in keratinocytes, leading to the improvements of psoriasis.

Abstract Ischemia-reperfusion (IR) injury to the renal epithelia is associated with endoplasmic reticulum stress (ERS) and mitochondria dysfunction, which lead to oxidative stress-induced acute kidney injury (AKI). X-box binding protein 1 (XBP1), an ERS response protein, could play a prominent role in IR-induced AKI. In this study, we revealed that XBP1 and its downstream target HRD1 participated in the crosstalk between ERS and mitochondrial dysfunction via regulation of NRF2/HO-1-mediated reactive oxidative stress (ROS) signaling. Mice with reduced expression of XBP1 (heterozygous Xbp1±) were resistant to IR-induced AKI due to the enhanced expression of NRF2/HO-1 and diminished ROS in the kidney. Downregulation of XBP1 in renal epithelial cells resulted in reduced HRD1 expression and increased NRF2/HO-1 function, accompanied with enhanced antioxidant response. Furthermore, HRD1 served as an E3-ligase to facilitate the downregulation of NRF2 through ubiquitination-degradation pathway, and the QSLVPDI motif on NRF2 constituted an active site for its interaction with HRD1. Thus, our findings unveil an important physiological role for XBP1/HRD1 in modulating the antioxidant function of NRF2/HO-1 in the kidney under stress conditions. Molecular therapeutic approaches that target XBP1-HRD1-NRF2 pathway may represent potential effective means to treat renal IR injury.

ObjectiveHeavy metals are present in many environmental pollutants, and have cumulative effects on the human body through water or food, which can lead to several diseases, including osteoarthritis (OA). In this research, we aimed to explore the association between heavy metals and OA.MethodsWe extracted 18 variables including age, gender, race, education level, marital status, smoking status, body mass index (BMI), physical activity, diabetes mellitus, hypertension, poverty level index (PLI), Lead (Pb), cadmium (Cd), mercury (Hg), selenium (Se), manganese (Mn), and OA status from National Health and Nutrition Examination Survey (NHANES) 2011-2020 datasets.ResultsIn the baseline data, the t test and Chi-square test were conducted. For heavy metals, quartile description and limit of detection (LOD) were adopted. To analyze the association between heavy metals and OA among elderly subjects, multivariable logistic regression was conducted and subgroup logistic by gender was also carried out. Furthermore, to make predictions based on heavy metals for OA, we compared eight machine learning algorithms, and XGBoost (AUC of 0.8, accuracy value of 0.773, and kappa value of 0.358) was the best machine learning model for prediction. For interactive use, a shiny application was made (https://alanwu.shinyapps.io/NHANES-OA/).ConclusionThe overall and gender subgroup logistic regressions all showed that Pb and Cd promoted the prevalence of OA while Mn could be a protective factor of OA prevalence among the elderly population of the United States. Furthermore, XGBoost model was trained for OA prediction.

ObjectiveTo explore the association between depression and blood metal elements, we conducted this machine learning model fitting research.MethodsDatasets from the National Health and Nutrition Examination Survey (NHANES) in 2017–2018 were downloaded (https://www.cdc.gov/nchs/nhanes). After screening, 3,247 aging samples with 10 different metals [lead (Pb), mercury (Hg), cadmium (Cd), manganese (Mn), selenium (Se), chromium (Cr), cobalt (Co), inorganic mercury (InHg), methylmercury (MeHg) and ethyl mercury (EtHg)] were included. Eight machine learning algorithms were compared for analyzing metal and depression. After comparison, XGBoost showed optimal effects. Poisson regression and XGBoost model (a kind of decision tree algorithm) were conducted to find the risk factors and prediction for depression.ResultsA total of 344 individuals out of 3247 participants were diagnosed with depression. In the Poisson model, we found Cd (β = 0.22, P = 0.00000941), EtHg (β = 3.43, P = 0.003216), and Hg (β=-0.15, P = 0.001524) were related with depression. XGBoost model was the suitable algorithm for the evaluation of depression, the accuracy was 0.89 with 95%CI (0.87, 0.92) and Kappa value was 0.006. Area under the curve (AUC) was 0.88. After that, an online XGBoost application for depression prediction was developed.ConclusionBlood heavy metals, especially Cd, EtHg, and Hg were significantly associated with depression and the prediction of depression was imperative.

Abstract Coaxial fiber-shaped supercapacitors are a promising class of energy storage devices requiring high performance for flexible and miniature electronic devices. Yet, they are still struggling from inferior energy density, which comes from the limited choices in materials and structure used. Here, Zn-doped CuO nanowires were designed as 3D framework for aligned distributing high mass loading of MnO2 nanosheets. Zn could be introduced into the CuO crystal lattice to tune the covalency character and thus improve charge transport. The Zn–CuO@MnO2 as positive electrode obtained superior performance without sacrificing its areal and gravimetric capacitances with the increasing of mass loading of MnO2 due to 3D Zn–CuO framework enabling efficient electron transport. A novel category of free-standing asymmetric coaxial fiber-shaped supercapacitor based on Zn0.11CuO@MnO2 core electrode possesses superior specific capacitance and enhanced cell potential window. This asymmetric coaxial structure provides superior performance including higher capacity and better stability under deformation because of sufficient contact between the electrodes and electrolyte. Based on these advantages, the as-prepared asymmetric coaxial fiber-shaped supercapacitor exhibits a high specific capacitance of 296.6 mF cm−2 and energy density of 133.47 μWh cm−2. In addition, its capacitance retention reaches 76.57% after bending 10,000 times, which demonstrates as-prepared device’s excellent flexibility and long-term cycling stability.

The phenomenon of surrounding rock damage and rupture caused by high temperatures is widespread, and has become a potential threat to the safety of nuclear waste disposal repositories. In order to reveal the energy distribution pattern of fractured granite during the failure process under different confining pressures, triaxial compression tests were carried out on rocks with different initial thermal damage. Firstly, the rock was treated at a high temperature to analyze the change rule of the porosity of the rock after high-temperature treatment, define the equivalent damage coefficient, and analyze the influence of confining pressure and equivalent damage coefficient on the peak stress and peak strain of the rock. The results show that, after high-temperature treatment, the porosity increases with the increase in temperature. The peak stress and corresponding strain of rock samples with similar equivalent damage factors increase with the increase in confining pressure. By comparing the rock samples with the same confining pressure and different initial thermal damage, the larger the confining pressure, the smaller the difference of peak stress of different initial thermal damage specimens. Then, the energy density of rock in a triaxial compression test is quantitatively analyzed by energy theory. The results show that, as long as the confining pressure is the same, the proportion of the dissipated energy of the specimen has a similar evolution trend with the strain. When the confining pressure is the same, the proportion of dissipated energy decreases rapidly with the change of strain due to the increase in equivalent damage factor, but the rate of decline will gradually slow down; however, when the confining pressure increases, the difference caused by the equivalent damage factor will gradually decrease, because the fracture is bound by the confining pressure. Finally, we analyze the maximum dissipated energy during rock deformation and failure. According to the inflection point of maximum dissipated energy, the optimum time for critical support of the key rock mass is determined.

Psoriasis is a chronic inflammatory skin disease. Although miRNAs are reported to be associated with the pathogenesis of psoriasis, the contribution of individual microRNAs toward psoriasis remains unclear. The miR-17-92 cluster regulates cell growth and immune functions that are associated with psoriasis. miR-17-3p is a member of miR-17-92 cluster; however, its role in dermatological diseases remains unclear. Our study aims at investigating the effects of miR-17-3p and its potential target gene on keratinocytes proliferation and secretion of pro-inflammatory cytokine and their involvement in psoriasis. Initially, we found that miR-17-3p was upregulated in psoriatic skin lesions, and bioinformatic analyses suggested that CTR9 is likely to be a target gene of miR-17-3p. Quantitative reverse-transcriptase PCR and immunohistochemical analysis revealed that CTR9 expression was downregulated in psoriatic lesions. Using dual-luciferase reporter assays, we identified CTR9 as a direct target of miR-17-3p. Further functional experiments demonstrated that miR-17-3p promoted the proliferation and pro-inflammatory cytokine secretion of keratinocytes, whereas CTR9 exerted the opposite effects. Gain-of-function studies confirmed that CTR9 suppression partially accounted for the effects of miR-17-3p in keratinocytes. Furthermore, Western blot revealed that miR-17-3p activates the downstream STAT3 signaling pathway while CTR9 inactivates the STAT3 signaling pathway. Together, these findings indicate that miR-17-3p regulates keratinocyte proliferation and pro-inflammatory cytokine secretion partially by targeting the CTR9, which inactivates the downstream STAT3 protein, implying that miR-17-3p might be a novel therapeutic target for psoriasis.

Point load test is a simple and fast method to obtain the compressive strength of rock. According to the maximum load at failure and the distance between two cone ends, the compressive strength of specimens can be calculated by the empirical formula. Because the test process does not need to process the sample into laboratory size type, so it is widely used. At the same time, with the rapid development of rock dynamics, the dynamic strength index of rock becomes more and more important under dynamic load. But dynamic point load is seldom mentioned by scholars. In order to explore the correlation between dynamic point load test and dynamic compressive strength, a large number of dynamic point load and uniaxial dynamic compressive strength tests were carried out using a split Hopkinson pressure bar for granite. Based on the energy theory, the crushing energy consumption during dynamic point load and uniaxial dynamic compressive strength tests were statistically analyzed, and the transformational relation between uniaxial dynamic compressive strength and crushing energy consumption during the dynamic point load test was determined. At the same time, the influence of the cone angle on crushing energy consumption during the dynamic point load test was investigated by changing the conical angle. The results show that with the increase in conical angle, the energy consumption of rock crushing decreases gradually during the dynamic point load test. And the decreasing trend tends to be gentle. The conclusion can provide a reference for obtaining the numerical value of the dynamic compressive strength of the rock in the future.

Implantable brain electrophysiology electrodes are valuable tools in both fundamental and applied neuroscience due to their ability to record neural activity with high spatiotemporal resolution from shallow and deep brain regions. Their use has been hindered, however, by the challenges in achieving chronically stable operations. Furthermore, implantable depth neural electrodes can only carry out limited data sampling within predefined anatomical regions, making it challenging to perform large-area brain mapping. Minimizing inflammatory responses and associated gliosis formation, and improving the durability and stability of the electrode insulation layers are critical to achieve long-term stable neural recording and stimulation. Combining electrophysiological measurements with simultaneous whole-brain imaging techniques, such as magnetic resonance imaging (MRI), provides a useful solution to alleviate the challenge in scalability of implantable depth electrodes. In recent years, various carbon-based materials have been used to fabricate flexible neural depth electrodes with reduced inflammatory responses and MRI-compatible electrodes, which allows structural and functional MRI mapping of the whole brain without obstructing any brain regions around the electrodes. Here, we conducted a systematic comparative evaluation on the electrochemical properties, mechanical properties, and MRI compatibility of different kinds of carbon-based fiber materials, including carbon nanotube fibers, graphene fibers, and carbon fibers. We also developed a strategy to improve the stability of the electrode insulation without sacrificing the flexibility of the implantable depth electrodes by sandwiching an inorganic barrier layer inside the polymer insulation film. These studies provide us with important insights into choosing the most suitable materials for next-generation implantable depth electrodes with unique capabilities for applications in both fundamental and translational neuroscience research.

Background: Aerobic training has been used as one of the common treatments for type 2 diabetes; however, further research on the individualized exercise program with the optimal intensity is still necessary. The purpose of this study was to investigate the effects of supervised exercise training at the maximal fat oxidation (FATmax) intensity on body composition, glycemic control, lipid profile, and physical capacity in older people with type 2 diabetes. Methods: Twenty-four women and 25 men with type 2 diabetes, aged 60–69 years. The exercise groups trained at the individualized FATmax intensity for 1 h/day for 3 days/week over 16 weeks. No dietary intervention was introduced during the experimental period. Whole body fat, abdominal fat, oral glucose tolerance test, lipid profile, and physical capacity were measured before and after the interventions. Results: FATmax intensity was at 41.3 ± 3.2% VO2max for women and 46.1 ± 10.3% VO2max for men. Exercise groups obtained significant improvements in body composition, with a special decrease in abdominal obesity; decreased resting blood glucose concentration and HbA1c; and increased VO2max, walking ability, and lower body strength, compared to the non-exercising controls. Daily energy intake and medication remained unchanged for all participants during the experimental period. Conclusion: Beside the improvements in the laboratory variables, the individualized FATmax training can also benefit daily physical capacity of older people with type 2 diabetes. Keywords: Type 2 diabetes, Exercise training, Maximal fat oxidation rate, Physical capacity, Older people

Secreted proteins from malaria protozoa play a critical role in the research and development of antimalarial drugs. Therefore, the precise identification of secreted proteins from malaria protozoa is invaluable. Though biochemical experiments can be used to address this task, this method is time-consuming and costly. By extracting the feature vector of a protein, machine learning technology can be used to forecast the functional and structural properties of the protein. Because high-dimensional features may result in increased redundant information and high-dimensional disasters or over-fitting, to train the machine learning model using initial high-dimensional features performs unsatisfactorily in practice. To address this problem, the three features of postivecharger.postivecharger.gap2, Xc1, and Chydrophobicity_ENGD860101.1.residue50 were used to classify random forests. The accuracy was 86.111% in 10-fold cross-validation. The prediction accuracy of adjusting parameters c and g by a support vector machine was 88.8889%.

Deep neural networks (DNNs) have achieved great success in the field of computer vision. The high requirements for memory and storage by DNNs make it difficult to apply them to mobile or embedded devices. Therefore, compression and structure optimization of deep neural networks have become a hot research topic. To eliminate redundant structures in deep convolutional neural networks (DCNNs), we propose an efficient filter pruning framework via deep reinforcement learning (DRL). The proposed framework is based on a deep deterministic policy gradient (DDPG) algorithm for filter pruning rate optimization. The main features of the proposed framework are as follows: (1) AA tailored reward function considering both accuracy and complexity of DCNN is proposed for the training of DDPG and (2) a novel filter sorting criterion based on Taylor expansion is developed for filter pruning selection. To illustrate the effectiveness of the proposed framework, extensive comparative studies on large public datasets and well-recognized DCNNs are conducted. The experimental results demonstrate that the Taylor-expansion-based filter sorting criterion is much better than the widely used minimum-weight-based criterion. More importantly, the proposed filter pruning framework can achieve over 10× parameter compression and 3× floating point operations (FLOPs) reduction while maintaining similar accuracy to the original network. The performance of the proposed framework is promising compared with state-of-the-art DRL-based filter pruning methods.

Water pipe cooling is mainly used to control temperature in the construction of mass concrete structures. It is important to reveal how to accurately stimulate the temperature field of mass concrete under action of this water pipe cooling. This paper presents a new method for this purpose. In this method, the contact surface of the water pipe and the concrete is used as the heat dissipation surface into the control equation and the composite Multiquadrics radial basis function (MQ-RBF) and low-order linear polynomial combination are used to discrete the spatial domain. The heat dissipation surface of the water pipe is included in the boundary conditions so that there is no need to build the refined water pipe modeling. This new method not only reduces the calculation cost but also ensures calculation accuracy. Through four calculation examples, this paper show that the algorithm has advantages in the numerical simulation of the concrete temperature field with water pipe cooling.

Floating catalytic chemical vapor deposition (FCCVD) is an attractive method for synthesizing carbon nanotube (CNT) fibers of high strength, toughness and electrical conductivity. During the process of CNT fibers synthesis, the assembly structure, such as the CNT orientation, CNT length, and the inter-tube particle impurity inside the CNT fibers, are key factors to determine the mechanical properties of CNT fibers. However, the regulation mechanism of the assembly structure during the process of CNT fiber synthesis is still unclear. Herein, in order to obtain high-strength CNT fibers, we demonstrated the synergistic relationship between the orientation and length of CNT inside the CNT fibers during the FCCVD growth process by adjusting the winding rate (5–30 m/min) and the length of the high-temperature reaction zone (660–1060 mm). It also revealed that the particle impurities inside the fibers could greatly reduce mechanical strength of CNT fibers. By optimizing the assembly structure of CNT fibers, the stable and continuous synthesis was realized, with the specific tensile strength of 3.1 N/tex (~ 3.5 GPa) without any post-treatment process.

In deep mining, much elastic energy is stored in rock mass due to the high geostress. Rockburst will be induced by accumulated energy during excavation. Meanwhile, because of blasting vibration energy in the host rock, there will be an obvious superimposed effect on the probability and intensity of rockburst. To explore the most reasonable and effective method for understanding rockburst problem under blasting, a deep roadway of Sanshandao gold mine was studied. On the basis of in situ geostress data, the accumulated energy of three-centered arch roadway after quasi-static excavation was derived. Then, a series of in situ blasting vibration were monitored, and the blasting vibration energy was calculated by employing the equivalent theory of elastic vibration boundary. Finally, the tendentiousness of rockburst was evaluated qualitatively with the superimposed energy. The results indicated that the disaster-driven energy was increased by 45.1% and 28.2% on different places of roadway. Also, the probability and intensity of rockburst would be raised.

In the past 30 years, because of built-in advantages, energy saving, pollution control, and sustainability, the energy pile system has had a rapid development around the world. Many scholars did numerous researches on the parameters’ optimization, heat exchange efficiency, and structure-soil response. Also, the researches of evolutional GSHP system using high temperature in deep mine and lager collection surface of tunnel lining were learned. At present, most of researchers are discussing the geothermal collection for the heating or cooling the building, and plenteous and significant research achievements have been obtained. It is a novel attempt to apply energy pile to geotechnical engineering, and good results have been achieved in engineering practice in Northern China. The area of northern China is a typical seasonal frozen region: the high temperature in summer and the cold weather and accumulated snow in winter will result in huge challenge and resource consumption of maintaince on highway tunnel, pavement, and other geotechnical engineering facilities. In this paper, taking example of using the geothermal heat exchanger to melt snow, the novel idea of using energy piles to prevent track in summer and crack in winter of pavement, and guaranteeing the safety of frost crack on tunnel lining were discussed. Also, through simulation research, we propose a buried pipe form with good heat transfer uniformity-spiral buried pipe, which has better engineering applicability. This shows us that the application of energy pile in geotechnical engineering will provide solutions to geotechnical problems, which will have a brilliant future.

Cancer is still a severe health problem globally. The therapy of cancer traditionally involves the use of radiotherapy or anticancer drugs to kill cancer cells, but these methods are quite expensive and have side effects, which will cause great harm to patients. With the find of anticancer peptides (ACPs), significant progress has been achieved in the therapy of tumors. Therefore, it is invaluable to accurately identify anticancer peptides. Although biochemical experiments can solve this work, this method is expensive and time-consuming. To promote the application of anticancer peptides in cancer therapy, machine learning can be used to recognize anticancer peptides by extracting the feature vectors of anticancer peptides. Nevertheless, poor performance usually be found in training the machine learning model to utilizing high-dimensional features in practice. In order to solve the above job, this paper put forward a 19-dimensional feature model based on anticancer peptide sequences, which has lower dimensionality and better performance than some existing methods. In addition, this paper also separated a model with a low number of dimensions and acceptable performance. The few features identified in this study may represent the important features of anticancer peptides.

Multiple organ dysfunction syndrome can follow severe infection or injury, but its relationship to exercise is not well understood. Previous studies have observed that prolonged strenuous exercise can lead to transiently increased level and/or activity of markers for systemic inflammatory response and multiple organ damage. However, few studies have analyzed the pathogenesis of the inflammatory response and subsequent multi-organ injury in exhaustive exercise conditions. In this study, we established a rat model of repetitive bouts of exhaustive running (RBER) and investigated its effects on multiple organ damage. Rats were subjected to RBER in either uphill or downhill running modes daily for a period of 7 days. Morphologically, RBER causes tissue structural destruction and infiltration of inflammatory cells in the skeletal muscles and many visceral organs. RBER also causes sustained quantitative changes in leukocytes, erythrocytes, and platelets, and changes in the concentration of blood inflammatory factors. These inflammatory alterations are accompanied by increases in serum enzyme levels/activities which serve as functional markers of organ damage. In general, RBER in the downhill mode seemed to cause more damage evaluated by the above-mentioned measures than that produced in the uphill mode. A period of rest could recover some degree of damage, especially for organs such as the heart and kidneys with strong compensatory capacities. Together, our data suggest that, as a result of multi-organ interactions, RBER could cause a sustained inflammatory response for at least 24 h, resulting in tissue lesion and ultimately multiple organ dysfunction.

Highly conducting and lightweight wires can be created based on carbon nanotube (CNT) assembly materials, where the inter-tube electron transport plays a key role. Here we report a gas infiltration of bromine to improve the electrical properties of CNT fibers, owing to the enhanced inter-tube electron hopping. Although Br infiltration is mainly a physical absorption process, with just a little fraction to form covalent bonding with the defect of CNTs, it can induce electron transfer from CNT to Br. Together with the densification effect, there are more pathways for interfacial electron transport between the CNTs. As a result, the infiltration efficiently increases the electrical conductivity from 2.66 × 105 to 1.63 × 106 S/m, by 6-fold. Based on the high performance stability, the composite fiber can be used as lightweight and functional conductor for wearable smart devices. Keywords: Carbon nanotube, Fiber, Bromine, Gas infiltration, Electrical conductivity

The complexity of scene images makes the research on remote-sensing image scene classification challenging. With the wide application of deep learning in recent years, many remote-sensing scene classification methods using a convolutional neural network (CNN) have emerged. Current CNN usually output global information by integrating the depth features extricated from the convolutional layer through the fully connected layer; however, the global information extracted is not comprehensive. This paper proposes an improved remote-sensing image scene classification method based on a global self-attention module to address this problem. The global information is derived from the depth characteristics extracted by the CNN. In order to better express the semantic information of the remote-sensing image, the multi-head self-attention module is introduced for global information augmentation. Meanwhile, the local perception unit is utilized to improve the self-attention module’s representation capabilities for local objects. The proposed method’s effectiveness is validated through comparative experiments with various training ratios and different scales on public datasets (UC Merced, AID, and NWPU-NESISC45). The precision of our proposed model is significantly improved compared to other methods for remote-sensing image scene classification.

As one of the dynamic disasters of deep mining, rockburst significantly affects the safety of underground environment especially at great depth. First, the elastic energy and dissipative energy are deduced to characterize rockburst process separately employing the theoretical analysis and test technique. Then, a series of split-Hopkinson pressure bar system tests are conducted. After calculation, the percentage of fractured dissipative energy occupied in total input dynamic energy is obtained. Subsequently, the dynamic mechanical parameters of rock specimens and dynamic impact factors are fitted. Finally, a three-dimensional model is developed using the mechanical property of the host rock, constitutive model, and in situ geostress. The contours of energy and the damage conditions of host rock are predicted, and the tendentiousness of rockburst is estimated.

Peripheral nerve injury is a common neurological condition that often leads to severe functional limitations and disabilities. Research on the pathogenesis of peripheral nerve injury has focused on pathological changes at individual injury sites, neglecting multilevel pathological analysis of the overall nervous system and target organs. This has led to restrictions on current therapeutic approaches. In this paper, we first summarize the potential mechanisms of peripheral nerve injury from a holistic perspective, covering the central nervous system, peripheral nervous system, and target organs. After peripheral nerve injury, the cortical plasticity of the brain is altered due to damage to and regeneration of peripheral nerves; changes such as neuronal apoptosis and axonal demyelination occur in the spinal cord. The nerve will undergo axonal regeneration, activation of Schwann cells, inflammatory response, and vascular system regeneration at the injury site. Corresponding damage to target organs can occur, including skeletal muscle atrophy and sensory receptor disruption. We then provide a brief review of the research advances in therapeutic approaches to peripheral nerve injury. The main current treatments are conducted passively and include physical factor rehabilitation, pharmacological treatments, cell-based therapies, and physical exercise. However, most treatments only partially address the problem and cannot complete the systematic recovery of the entire central nervous system–peripheral nervous system–target organ pathway. Therefore, we should further explore multilevel treatment options that produce effective, long-lasting results, perhaps requiring a combination of passive (traditional) and active (novel) treatment methods to stimulate rehabilitation at the central–peripheral–target organ levels to achieve better functional recovery.

Abstract Purpose: To investigate the role of PI3k/Akt signal pathway in the protective effects of propofol on intestinal and lung injury induced by intestinal ischemia/reperfusion(I/R). Methods: Male Sprague-Dawley rats were subjected to 45 min of ischemia by occluding the superior mesenteric artery and to 2h of reperfusion to establish the model of I/R. Twenty four rats were randomly divided into four groups: Sham, intestinal I/R (II/R), propofol (P), wortmannin (W). In groups P, W, propofol was injected intravenously and continuously at the onset of reperfusion via infusion pump. PI3K inhibitor (wortmannin) was administered intravenously in group W 25 min before ischemia. Intestinal tissues and lung tissues were obtained for determination of histologic injury, wet/dry weight ratio, malondialdehyde (MDA) levels, superoxide dismutase (SOD) and myeloperoxidase (MPO) activities. Meanwhile, the expressions of caspase-3 and phosphorylated Akt (p-Akt) in intestines and lungs were detected by western blot. Results: Propofol treatment alleviated intestinal and lung morphological changes which were observed in II/R group, Moreover, wet/dry weight ratio, the MDA level, MPO activity and expression of caspase-3 were significantly decreased whereas the SOD activity and p-Akt expression were significantly increased. Notably, the protections were significantly reversed by pretreatment of wortmannin. Conclusion: PI3K/Akt pathway activation play a critical role in the protective effects of propofol on intestinal and lung injury induced by ischemia/reperfusion.

Increased serum prostate-specific antigen (PSA) level is closely associated with prostate cancer; however, there is still no reliable method for distinguishing prostate cancer from benign prostatic hyperplasia (BPH) when the PSA level is between 4 and 10 ng/mL. In this study, we detected the inflammatory cell counts in serum and prostate tissues in prostate cancer and BPH patients. The results showed that the monocyte counts in both serum and prostate tissues were obviously less in patients with prostate cancer than that in those with BPH, which indicates that monocyte may be associated with development of prostate cancer and it is possible to increase positive finding for prostate cancer with 4–10 ng/mL PSA concentration by detecting and analyzing monocyte count in serum and tissue simultaneously.

Deep mining involves complex geological environments. Moreover, along with strong disturbance, rockbursts and other severe dynamic hazards can occur frequently. Energy theory is widely regarded as the most appropriate method for understanding the mechanism of deep dynamic problems. When modeling dynamic disasters, energy theory includes the energy storage, energy accumulation, and energy transfer. To study the energy transfer characteristics in rock, a series of split-Hopkinson pressure bar (SHPB) impact tests were conducted with long granite specimens (400 mm in length and 50 mm in diameter) and modified incidence bars (having the same cross-sectional area but different shapes). The test results indicate that the impact energy decays exponentially with an energy attenuation coefficient of −0.42. For the scattering characteristics of energy in the rock, the scattering distance is found to be approximately three times the specimen diameter, which is very similar to Saint-Venant’s principle in elastic mechanics.

With the increase in mining depth, the deep hard rock mass is under threat of rockburst under high geostress, high temperature, high osmotic pressure, and strong disturbance. To reduce the probability and strength of rockburst, a new energy-absorbing bolt for guaranteeing the stability of deep hard rock mass was developed utilizing the energy absorption characteristic of high-damping rubber. To analyze the practicability and obtain the quantified behaviors of this new energy-absorbing bolt, a series of impact tests on specimens of high-damping rubber, granite, and granite–rubber composite specimens was carried out by a split Hopkinson pressure bar (SHPB) method. Further, considering the different working depths with different rock temperatures, the dynamic energy-absorbing characteristics of high-damping rubber under different temperatures were tested. The testing results show that the new energy-absorbing bolt can consume the storage energy in host rock effectively, and the environmental temperature will produce certain effects on the energy-consuming rate. In addition, the optimal energy-absorbing thickness–diameter ratio of high-damping rubber was confirmed by SHPB tests.

The latest research on energy piles demonstrates that most scholars are focusing their attention on optimization by designing more efficient heat exchanger coils, analyzing the heat pump matching parameters, and so on. However, after more than 20 years of development, these traditional methods for improving the heat transfer efficiency of energy piles have reached a bottleneck, and a new approach for the continued enhancement of this technology must be investigated. In this study, powdered graphite with high heat transfer characteristics was included in a concrete mix to create graphite concrete piles with enhanced heat transfer characteristics. The results from theoretical analysis, laboratory testing, and numerical simulation indicate that using graphite to improve the heat transfer efficiency of a concrete material is an effective method for enhancing the thermal efficiency of an energy pile system. The research results also show that the heat transfer coefficient of the concrete exhibits greater improvement when the graphite content is greater than 15% under the same environmental temperature. After studying the performance of the proposed graphite concrete energy pile under different environmental temperatures (10°C, 20°C, 30°C, and 40°C), the results indicate that the working efficiency of the energy pile is better in the summer than in the winter. Finally, parameters such as the cast-in pipe configuration and pile spacing are optimized.

Energy pile is one of the promising areas in the burgeoning green power technology; it is gradually gaining attention and will have wide applications in the future. Because of its specific structure, the energy pile has the functions of both a structural element and a heat exchanger. However, most researchers have been paying attention to only the heat transfer process and its efficiency. Very few studies have been done on the structural interaction between the energy pile and its host soil. As the behavior of the host soil is complicated and uncertain, thermal stresses appear with inhomogeneous distribution along the pile, and the peak value and distribution of stress will be affected by the thermal and physical properties and thermal conductivities of the structure and the host soil. In view of the above, it is important to determine thermal-mechanical coupled behavior under these conditions. In this study, a comprehensive method using theoretical derivations and numerical simulation was adopted to analyze the structural interaction between the energy pile and its host soil. The results of this study could provide technical guidance for the construction of energy piles.

The carbon dioxide geological storage is one of the most effective ways to slow down the earth's climate warming. The ideal location for storage is in the deep scrap mines. Because of the characteristics of the deep underground condition, the long-term mechanical stability must have close relationship with the geostress fields and permeability, whose development can determine and reflect the mechanical behaviors of carbon dioxide geological storage. The permeability of host rock is affected by existing joints and discontinuity surfaces. Furthermore, as the liquid carbon dioxide is injected into the geological storage, the injection pressure and buoyancy force will change the state of geostress obviously. In this paper, based on mechanical properties of the host rock (granite), coupled brittle shear constitutive model was adopted and the analysis module was implemented in software FLAC3D. Then, with the in situ survey of joints in the host rock and the monitoring of in situ geostress, the permeability characteristics and geostress inverse analysis were input in FLAC3D. At last, fluid-solid coupled model was used to analyze the seepage characteristics of each phase after the injection and long-term storage of liquid carbon dioxide. Therefore, the systematic analysis of the storage stability of carbon dioxide geological could be carried out.

The settlement control is critical for the safety of road based on high filled embankment. The traditional construction methods have the characteristic with less soil thickness compacted at a time. There are many advantages to compact the gravel soil with blasting. The cavity in soil is formed by blasting and its fillings to form a composite foundation for the embankment. The field data show this composite foundation can meet the requirement of loading and settlement control with less construction time. In geotechnical blasting, the high temperature due to blasting will swell the material around, so its worthy to do the coupled analysis with thermal mechanics (TM) and blasting compaction in the high filled embankment. In this paper, a 3D model is built with FLAC3D to simulate a single hole to predict the range and degree of thermal propagation. Then, the thermal strains got from the model are used to estimate the displacement of surrounding soil to predict the degree of compaction and optimize the distribution of blast holes in plan.

In the tunnel and underground space engineering, the blasting wave will attenuate from shock wave to stress wave to elastic seismic wave in the host rock. Also, the host rock will form crushed zone, fractured zone, and elastic seismic zone under the blasting loading and waves. In this paper, an accurate mathematical dynamic loading model was built. And the crushed zone as well as fractured zone was considered as the blasting vibration source thus deducting the partial energy for cutting host rock. So this complicated dynamic problem of segmented differential blasting was regarded as an equivalent elastic boundary problem by taking advantage of Saint-Venant’s Theorem. At last, a 3D model in finite element software FLAC3D accepted the constitutive parameters, uniformly distributed mutative loading, and the cylindrical attenuation law to predict the velocity curves and effective tensile curves for calculating safety criterion formulas of surrounding rock and tunnel liner after verifying well with the in situ monitoring data.

Objective: To compare the clinical anesthetic effects of ultrasound-guided traditional erector spinae plane block (ESPB) with those of modified ESPB (layer-by-layer infiltration erector spinae plane block) in elderly spinal fracture surgery. Methods: From January to December 2023, eighty patients diagnosed with geriatric spinal fractures underwent ESPB surgery at Guangzhou University of Chinese Medicine’s Shenzhen Hospital (Futian). The patients were randomly divided into the ESPB layer-by-layer infiltration group (Group M) and the traditional ESPB group (Group E), with 40 participants in each. The study compared ESPB operation time and percutaneous kyphoplasty (PKP) procedure time between the groups, as well as the intraoperative administration of additional intravenous analgesic medicines and the assessment of blood oxygen, mean arterial pressure (MAP), heart rate (HR), and pain scores at before anesthesia (T0), 20 minutes after blockade (T1), skin incision (T2), and following bone cement implantation (T3). Results: The use of additional intraoperative sufentanil in ESPB revealed significant differences between the groups (p < 0.001). From T0 to T3, there were statistically significant differences in HR, MAP, and numerical rating scale scores between the groups (p < 0.05). There were also significant differences in MAP and NRS scores between the traditional and modified ESPB groups (p < 0.05). Conclusion: Modified ESPB builds upon traditional ESPB by continuing to infiltrate anesthesia layer by layer along the direction of the erector spinae fascia after the puncture needle reaches the ultrasoundguided nerve block plane. This method effectively enhances intraoperative analgesia and sedation in spinal compression surgery, improving the quality of anesthesia in senior spinal surgery. [ABSTRACT FROM AUTHOR]

Aqueous Mg-ion batteries (AMIBs) featuring advantages of good safety, low cost, and high specific energy have been recognized as a promising energy-storage technology. However, the performance of AMIBs is consistently limited by sluggish diffusion kinetics and structural degradation of cathode materials arising from the strong electrostatic interactions between high-charge-density Mg2+ and host materials. Here, layered-structured NiOOH, as traditional cathodes for alkaline batteries, is initially demonstrated to realize proton-assisted Mg-(de)intercalation chemistry with a high discharge platform (0.57 V) in neutral aqueous electrolytes. Benefiting from the unique core/shell structure, the resulting NiOOH/CNT cathodes achieve a high capacity of 122.5 mAh g-1 and long cycle stability. Further theoretical calculations reveal that the binding energy of hydrated Mg2+ is higher than that of Mg2+ with NiOOH, resulting in that Mg2+ is easily intercalated/de-intercalated into/from NiOOH. Benefiting from the freestanding design, the assembled fiber-shaped "rocking-chair" NaTi2(PO4)3//NiOOH AMIB shows a high energy density and satisfactory mechanical flexibility, which could be woven into a commercial fabric and power for fiber-shaped photoelectric sensors. [ABSTRACT FROM AUTHOR]

Artificial neuromorphic devices can emulate dendric integration, axonal parallel transmission, along with superior energy efficiency in facilitating efficient information processing, offering enormous potential for wearable electronics. However, integrating such circuits into textiles to achieve biomimetic information perception, processing, and control motion feedback remains a formidable challenge. Here, we engineer a quasi-solid-state iontronic synapse fiber (ISF) comprising photoresponsive TiO2, ion storage Co-MoS2, and an ion transport layer. The resulting ISF achieves inherent short-term synaptic plasticity, femtojoule-range energy consumption, and the ability to transduce chemical/optical signals. Multiple ISFs are interwoven into a synthetic neural fabric, allowing the simultaneous propagation of distinct optical signals for transmitting parallel information. Importantly, IFSs with multiple input electrodes exhibit spatiotemporal information integration. As a proof of concept, a textile-based multiplexing neuromorphic sensorimotor system is constructed to connect synaptic fibers with artificial fiber muscles, enabling preneuronal sensing information integration, parallel transmission, and postneuronal information output to control the coordinated motor of fiber muscles. The proposed fiber system holds enormous promise in wearable electronics, soft robotics, and biomedical engineering. [ABSTRACT FROM AUTHOR]