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Purposes The economic dispatch of Integrated Energy Systems (IES) is a key research topic of energy technology reform, inherently a complex Mixed-Integer Nonlinear Programming problem. Traditional optimization methods have high computational complexity and struggle to adapt to the source-load uncertainty in IES coupled with renewable energy systems. Utilizing Deep Reinforcement Learning to decompose and accelerate the original problem enhances the efficiency of the IES economic dispatch model. Methods To address these issues, in this paper, an IES optimization dispatch framework based on an improved Proximal Policy Optimization (PPO) algorithm is proposed. The PPO algorithm is used to approximate some variables of the nonlinear constraints in the original model, converting them into linear constraints to speed up the solution. Findings The effectiveness and efficiency of this method over others are validated through case studies, predicting significant computational advantages in large-scale IES optimization problems.

C16H16N2O2, orthorhombic, P212121 (no. 19), a = 9.370(2) Å, b = 10.265(2) Å, c = 15.863(4) Å, V = 1525.8(6) Å3, Z = 4, R gt(F) = 0.0753, wRref (F 2) = 0.198, T = 273 K.

Regeneration of adsorption saturated activated carbon by traditional electrochemical technology has the advantages of high regeneration efficiency and no mass loss of activated carbon, but it has defects such as low mineralization efficiency, generation of toxic by-products, and high energy consumption. Electrochemical advanced oxidation(E-AOP) regeneration technology can effectively overcome the problems of traditional electrochemical regeneration. In this paper, the regeneration efficiency and mechanism of activated carbon by traditional electrochemical are briefly described, and the effects of operating parameters (current, electrolyte type and concentration, regeneration location,anode material, etc.) on the desorption-adsorption balance and the mineralization efficiency of pollutants are analyzed. The mechanism and application of three types of E-AOP regeneration technologies(electro-Fenton regeneration, electro-peroxone regeneration, and electro-persulfate regeneration) in the process of activated carbon regeneration are summarized. The electric-Fenton regeneration technology has better regeneration effect, and the problem of metal ion pollution in the system can be effectively overcome by new regeneration. The electro-peroxone regeneration technology does not require the addition of any chemicals and catalysts, which is conducive to the control of reaction conditions and automation of the regeneration process. The electro-persulfate regeneration technology is convenient in operation with low energy consumption and wide applicability. Finally, the problems and development prospects of E-AOP regeneration technology are proposed. This review provides theoretical basis for the development of new efficient and environmentally friendly activated carbon regeneration technologies.

Objective To investigate the effect of intensive phototherapy for neonatal hyperbilirubinemia on cellular immune function and short-term immune-related adverse effects. Methods Totally 180 infants with hyperbilirubinemia were treated with different light intensity, the efficacy, cellular immune function and immune adverse effects were followed up for six months after discharge. Results After phototherapy, serum interleukin-6 (IL-6) in both groups were decreased and CD4+ (%) and CD4+/CD8+ were increased than that before phototherapy. The decrease rate of total bilirubin in the intensive phototherapy group was significantly faster than that in the conventional phototherapy group, at the same time, the total duration of phototherapy and hospital stay were significantly shorter than that in the conventional phototherapy group (P＜0.05). No statistical significance in the incidence of diarrhea, rash, fever and hypo-calcemia during hospitalization and no immune-related adverse effects in 6 months after discharge were recorded. Conclusions Compared with conventional phototherapy, intensive phototherapy reduces serum bilirubin level more quickly and shorten the duration of phototherapy and hospital stay. No common adverse effects nor immune-related adverse effects are recorded during hospitalization and the period of six months after discharge.

NHX proteins are transmembrane antiporters belonging to the cation/proton antiporter gene family, with a conserved Na+ (K+)/H+ exchange (PF00999) protein domain. NHXs play a prominent role in plant growth, development, and defense. However, the role of NHX gene family in potato (Solanum tuberosum L.) is yet to be known. In this study, we conducted a genome-wide analysis of the potato NHX gene family. A total of 25 StNHX family members were identified to be unevenly distributed on 10 chromosomes. The proteins ranged in length from 252 to 1,153 amino acids, with molecular masses ranging from 27516.32 to 127860.87 kD, and isoelectric points (pI) ranging from 4.96 to 9.3. Analyses of gene structures and conserved motifs indicated that StNHX genes in the same phylogenetic cluster are conserved. Phylogenetic analysis divided the StNHX genes into three subfamilies (Classes I, II, and III). Synteny analysis indicated that StNHX gene family Class III of NHX and all Arabidopsis thaliana NHXs shared a close evolutionary relationship. Analysis of cis-acting elements in the upstream 1,500 bp promoter region of potato NHX genes showed that these genes could be regulated by light, stress, and hormones such as abscisic acid and gibberellic acid. Protein-protein interaction network analysis indicated that StNHX proteins may participate in the regulation of potato growth and stress response. Besides, To determine a potential role of these genes in tissue development and drought response, we analyzed the RNA-seq data of different DM potato tissues. The results showed that NHX genes exhibited distinct tissue-specific expression patterns. We further examined the expression patterns of StNHX in different tissues (leaves, roots, shoots, tubers, stolons, and flowers) during the flowering stage in ‘Jizhangshu NO.8.’ potato. The qRT-PCR results further confirmed the importance of StNHX genes in potato plant growth and development. We further analyzed the RNA-seq data (DM potato) under different abiotic stresses (salt, drought, and heat), and found that the expression of StNHX genes was induced under abiotic stress. qRT-PCR analysis of shoots and roots of ‘Jizhangshu NO.8.’ potato treated for 0, 6, 12, and 24 h with 15% PEG6000 confirmed that the 25 StNHX genes are involved in the response to drought stress in potato. The results of this study may be useful for selecting appropriate candidate genes for the breeding of new drought-tolerant potato varieties. Furthermore, this study lays a foundation for prospective analysis of StNHX gene functions.

[Objective] Factors impacting the demand of natural gas vary across regions in China, resulting in distinct data characteristics within corresponding datasets. The availability of adequate sample data for long-term forecasting is limited. Therefore, the development of a generalized demand forecasting model applicable to diverse regions remains a significant challenge. [Methods] This study focused on analyzing eleven prefecture-level cities in Shandong Province. Data from these regions, spanning multiple time periods, were gathered to establish a general database, incorporating key factors influencing natural gas demand, such as annual consumption, GDP, and population. Pearson’s correlation coefficient was initially employed to preliminarily screen and identify sample characteristics, followed by the utilization of the K-means clustering algorithm for data clustering. Subsequently, three sample points exhibiting a similar energy consumption structure were selected, and their corresponding natural gas demands at the next time points were used as new sample characteristics. Furthermore, forecast outputs derived from the grey theory were utilized as input samples for a Back Propagation (BP) neural network. As a result, a combined forecasting model was developed by integrating the new sample data with the BP neural network.[Results] The proposed forecasting method, which integrated K-means clustering, the grey theory, and a BP neural network, leveraged the historical natural gas demands of the cities with similar energy structures. By taking advantage of the grey theory’s high robustness in dealing with small sized sample data, the proposed forecasting method kept the mean absolute percentage errors of the resulting long-term natural gas demand forecasts for the 11 prefecture-level cities in Shandong Province within the range from 0.57% to 6.41%. Comparative analysis with traditional grey forecasting models, BP neural network models, and K-means clustering + BP neural network models revealed the superiority of the proposed approach, yielding improved prediction results with smaller errors and higher stability. [Conclusion] The proposed forecasting method proves effective in providing technical support for analyzing future natural gas demands in cities across China, surpassing regional limitations. Moreover, it serves as a valuable tool for assisting governments and enterprises at all levels in making decisions on allocation plans of natural gas resources.

The preparation, purification and application of fullerene were reviewed. The advantages and disadvantages of the preparation and purification methods of fullerene were compared by analyzing the factors such as yield and cost. The application status of fullerene materials in lubrication, catalysis, biomedicine and other fields were summarized. It was also pointed out that the preparation and purification methods of fullerene should be further optimized and improved in the direction of low cost and high yield. At the same time, it was supposed to strengthen the theoretical research on the reaction mechanism of fullerene application in order to develop fullerene materials from the perspective of design.

Gas chromatography-mass spectrometry combines the advantages of efficient and rapid gas chromatography and accurate identification by mass spectrometry. Gas chromatography-mass spectrometry has been widely used in the separation and analysis of volatile components in food recently. This paper reviewed the application progress of GC in food analysis, introduces the separation mechanism of GC, the types of GC columns and the classification of detectors. The application progress of GC-MS in food analysis was reviewed, and the separation process of gas chromatography, the classification of chromatographic columns and the classification of detectors were introduced. Moreover, the applications of gas chromatography-mass spectrometry in food nutrition, food safety and food traceability were discussed in detail with specific examples.

The vertical electronic and optoelectronic devices based on 2D materials have shown great advantages over lateral devices, such as higher current density, faster switch speed, and superior short-channel control. However, it is difficult to fabricate vertical device with conventional metal deposition methods due to the aggressive process usually results in damage to the contact region. Here, we develop a simple and effective metal transfer technique and fabricate p-type and n-type WSe2 transistors by using metals with different work functions and subsequently create a vertical WSe2 transistors with a 18-nm-thick channel, which retain good gate coupling effect. Furthermore, a vertical WSe2 photodiode is constructed with graphene and Pt as asymmetric van der Waals (vdW) contacts. The work-function difference between graphene and Pt generates a built-in electric filed, leading to a high current rectification over 105. Under 405 nm laser illumination, the device exhibits excellent self-powered photodetection properties, including a high responsivity of 0.28 A W−1, fast response speed of 24 μs, and large light on/off ratio exceeding 105 at zero bias, which surpass most of the vdW photodiodes. This work demonstrates that the metal transfer technique is a promising strategy for the construction of high-performance vertical optoelectronic devices.

In order to make the temporary support force better adapt to the mine pressure and improve the support capacity of the support, taking the dual self-moving temporary support as the research object, an adaptive control method of temporary support force based on particle swarm optimization (PSO) - BP neural network is proposed. The initial weights of the BP neural network are optimized by using the global search capability and fast convergence features of the PSO algorithm to improve the rate of convergence of the BP neural network. Then, the optimized BP neural network is used to achieve online self-adjustment of PID parameters. The PSO-BP neural network is constructed to optimize the PID controller. This enables the temporary support force to reach the predetermined value more quickly and accurately, achieving adaptive control of the temporary support force. It avoids damage to the roof due to the mismatch between support force and roof pressure. The expected initial support force of the temporary support is simulated using unit step signals for experimental verification. The results show that compared with the BP neural network optimized PID controller and traditional PID controller, the PSO-BP neural network optimized PID controller can achieve the expected initial support force faster and more accurately. The adjustment time is only 0.5 s and there is almost no overshoot. Based on actual geological conditions, the roof pressure on the support during excavation support is simulated. The adaptive control effect of three controllers for support force is studied. The results show that under the control of the PSO-BP neural network optimized PID controller, the system error is only 0.02 MPa, with the smallest error and the best control effect.

The management of water resources must be based on accurate models of the river discharge in the context of the water flow alteration due to anthropic influences and climate change. Therefore, this article addresses the challenge of detecting the best model among three artificial intelligence techniques (AI)—backpropagation neural networks (BPNN), long short-term memory (LSTM), and extreme learning machine (ELM)—for the monthly data series discharge of the Buzău River, in Romania. The models were built for three periods: January 1955–September 2006 (S1 series), January 1955–December 1983 (S2 series), and January 1984–December 2010 (S series). In terms of mean absolute error (MAE), the best performances were those of ELM on both Training and Test sets on S2, with MAETraining = 5.02 and MAETest = 4.01. With respect to MSE, the best was LSTM on the Training set of S2 (MSE = 60.07) and ELM on the Test set of S2 (MSE = 32.21). Accounting for the R2 value, the best model was LSTM on S2 (R2Training = 99.92%, and R2Test = 99.97%). ELM was the fastest, with 0.6996 s, 0.7449 s, and 0.6467 s, on S, S1, and S2, respectively.

Intelligent design is a trend in geotechnical engineering. However, a middle link between demand identification and intelligent design is missing in anchor engineering, resulting in lower efficiency in terms of the interaction between the anchor components, geological body and modeling information. To address this challenge, this paper proposes a method for modeling a three-dimensional anchor engineering information model based on sparse boreholes. This method includes three parts: modeling the geological body, integrated modeling of the anchor components and the geological body, and multiple information assignments based on the anchor model. The feasibility was validated in actual engineering scenarios by using neural networks and rendering engines. The results showed that the prediction accuracy of the strata improved by 17.69%, the modeling efficiency increased by double, and engineering information was fit to the model well. This paper has the application potential to achieve intelligent design in anchor engineering.

Objective To construct and validate a prognosis prediction model and a risk stratification tool for more precise and individualized evaluation of prognosis for patients following resection of esophageal squamous cell carcinoma (ESCC), and provide real-world evidence for informing optimal decision-making about adjuvant therapy. Methods The comprehensive clinical data and follow-up data were collected from consecutive patients with ESCC in the Anyang Cancer Hospital (Anyang center) from May 31, 2011 to July 31, 2018, and in the Cancer Hospital of Shantou University Medical College (Shantou center) from August 1, 2009 to December 31, 2018. Patients from the Anyang center formed the training cohort, and a two-phase selection based on backward stepwise multivariable Cox proportional hazard regression and minimization of AIC was used to construct prediction model for overall survival (OS). Bootstrap with 1 000 resamples was used for internal validation, and cohort from the Shantou center was used for external validation. Furthermore, a risk stratification tool was constructed according to the tertiles of the total points derived from nomogram in the training cohort. Results A total of 4 171 eligible patients were included in the training cohort, and 1 895 patients were included in the validation cohort. The final model incorporated nine variables: age, sex, primary tumor location, T stage, N stage, number of lymph nodes harvested, tumor size, adjuvant treatment, and preoperative hemoglobin level. A significant interaction was observed between N stage and adjuvant treatment (P < 0.001), which means that N+ stage patients were likely to benefit from addition of adjuvant therapy as opposed to surgery alone, but adjuvant therapy did not improve OS for N0 stage patients. The C-index of the model was 0.728 (95% CI: 0.713-0.742) in the training cohort, 0.722 (95% CI: 0.711-0.739) after bootstrapping, and 0.679 (95% CI: 0.662-0.697) in the external validation cohort. Calibration plots demonstrated favorable agreement between model prediction and actual observation for 1-, 3- and 5-year OS. In both training and validation cohorts, this model outperformed the seventh edition of the AJCC TNM (tumor, lymph node, and metastasis) staging system in terms of the accuracy of prognostic prediction (P < 0.05). Moreover, within each TNM staging group, this model achieved ideal risk stratification. Conclusions The prediction model constructed in this study may provide individualized survival prediction for patients with resected ESCC in China. This study also demonstrated that the N stage may be a fundamental determinant in planning postoperative adjuvant therapy for ESCC patients.

Uranium is the heaviest naturally occurring radioactive element in nature, and it is widely distributed in the earth’s crust. With the improvement of the technical accuracy of mass spectrometry to measure uranium isotope ratios, it is gradually recognized that uranium isotopes in the natural environment also have fractionation effects. In this paper, the recent research results on uranium isotope fractionation is reviewed and the geochemical behavior of uranium in nature and the analytical methods of uranium isotopes is introduced. The natural uranium isotope fractionation is related to the nuclear volume effect, which leads to a greater tendency for heavy uranium isotopes to be enriched in the reductant equivalent, and the δ238U of U(Ⅵ) reduction to U(Ⅳ) reaches 1.0‰. The isotopic fractionation mechanism of uranium in redox exchange reactions is revealed by the sensitivity of uranium isotopes to the oxidation-reduction environment, and it is found that δ238U is significantly isotopically fractionated between deposits formed in different oxidation-reduction environments, and moreover, it is shown that the bioreduction-induced isotopic fractionation of uranium is greater. Therefore, uranium isotope fractionation has an important tracer role in the inversion of uranium ore formation environment and the study of radioactive environmental chemistry and environmental remediation in the in-situ leaching of uranium mining. Finally, how to better address the environmental remediation of groundwater in the in-situ leaching of uranium mining is suggested, thus promoting the research and application of uranium isotope systems in the field of earth sciences.

The Jiangmen Underground Neutrino Observatory (JUNO) experiment is designed to measure the neutrino mass ordering (NMO) using a 20-kton liquid scintillator (LS) detector. Besides the precise measurement of the reactor neutrino’s oscillation spectrum, an atmospheric neutrino oscillation measurement in JUNO offers independent sensitivity for NMO, which can potentially increase JUNO’s total sensitivity in a joint analysis. In this contribution, we present a novel multi-purpose reconstruction method for atmospheric neutrinos in JUNO at few-GeV based on a machine learning technique. This method extracts features related to event topology from PMT waveforms and uses them as inputs to machine learning models. A preliminary study based on the JUNO simulation shows good performances for event directionality reconstruction and neutrino flavor identification. This method also has a great application potential for similar LS detectors.

The article analyses the influencing factors of the anti-fouling properties of road traffic markings and researches a double-coated, anti-fouling road marking with good heat stability and high coating density. The anti-fouling performance of the road marking during its use period was experimentally analysed using SPSS software. The results indicate that the anti-fouling performance of the double-coated road marking is significantly better than that of thermoplastic markings and two-component markings, and it has a promising prospect for widespread application.

In the dynamic and rapid detection of retroreflection coefficient in road traffic markings, different factors may affect the detection results. This study investigates the significance of different levels of environmental light intensity and vehicle speed on the detection results of retroreflection coefficient in road markings using one-way ANOVA analysis. The results show that within a 95% confidence interval, there is no statistically significant difference in the detection results of retroreflection coefficient under different levels of environmental light intensity and vehicle speed. The variance effect size calculation indicates that for the detection of retroreflection coefficient in road markings, vehicle speed control is more important than light intensity. To obtain more reliable detection results, it is recommended to maintain a stable and uniform speed of no more than 80 km/h during the detection process.

Modeling and forecasting the river flow is essential for the management of water resources. In this study, we conduct a comprehensive comparative analysis of different models built for the monthly water discharge of the Buzău River (Romania), measured in the upper part of the river’s basin from January 1955 to December 2010. They employ convolutional neural networks (CNNs) coupled with long short-term memory (LSTM) networks, named CNN-LSTM, sparrow search algorithm with backpropagation neural networks (SSA-BP), and particle swarm optimization with extreme learning machines (PSO-ELM). These models are evaluated based on various criteria, including computational efficiency, predictive accuracy, and adaptability to different training sets. The models obtained applying CNN-LSTM stand out as top performers, demonstrating a superior computational efficiency and a high predictive accuracy, especially when built with the training set containing the data series from January 1984 (putting the Siriu Dam in operation) to September 2006 (Model type S2). This research provides valuable guidance for selecting and assessing river flow prediction models, offering practical insights for the scientific community and real-world applications. The findings suggest that Model type S2 is the preferred choice for the discharge forecast predictions due to its high computational speed and accuracy. Model type S (considering the training set recorded from January 1955 to September 2006) is recommended as a secondary option. Model type S1 (with the training period January 1955–December 1983) is suitable when the other models are unavailable. This study advances the field of water discharge prediction by presenting a precise comparative analysis of these models and their respective strengths

ObjectiveTo investigate the safety and efficacy of endovascular embolization for ruptured posterior inferior cerebellar artery （PICA） aneurysms. MethodsThe clinical data of 18 patients with ruptured PICA aneurysms admitted in Nanjing First Hospital from June 2014 to August 2021 were retrospectively analyzed. ResultsImmediate postoperative angiography showed that 14 patients （77.78%） had Raymond grade Ⅰ dense embolism, 2 patients （11.11%） had Raymond grade Ⅱ residual tumor neck, and 2 patients （11.11%） had Raymond grade Ⅲ residual tumor. Perioperative complications occurred in 2 cases （11.11%）, and cerebral stem and cerebellar infarction resulted in death in 1 case （5.56%）. One patient （5.56%） with ruptured aneurysm ruptured again during the operation. Except for 1 died patient, the mRS scores of 17 patients were all ≤3 points, and the good prognosis rate was 94.44% （17/18）. Seventeen patients were followed up for 6-12 months after operation, 2 patients with PICA tumor neck recurrence after simple coil embolization, the recurrence rate was 11.11% （2/18）, one of them was cured by LVIS double stent treatment. ConclusionEndovascular embolization is a safe and effective method for the treatment of PICA aneurysms. The design of treatment strategy should be based on the location and morphological characteristics of the aneurysm and parent artery.

A pre-cooled combined engine based on a closed helium (He) cycle offers high specific thrust and high specific impulse. Therefore, evaluation of the performance of such an engine is crucial for engine applications and key technology research. This study employs an analytical approach to investigate the effects of key parameters on the performance of a pre-cooled core engine, assuming a perfect gas model. The findings revealed that the specific thrust and specific impulse of the pre-cooled core engine are related to the pressurized coefficient of the airflow passage and equivalence ratio (ER). An increase in the pressurized coefficient leads to an increase in both specific thrust and specific impulse. However, within a certain range, although the specific thrust is positively correlated with the ER, the specific impulse is greatly reduced. With specific component parameters and a fixed thermodynamic cycle, a minimum ER exists, which satisfies the cycle-matching requirement. Moreover, the value of the minimum ER is related to the closed-cycle efficiency. For a pre-cooled core engine with a simple closed He cycle, the minimum ER is approximately 2.5–3.5.

Phosphatidylinositol 3-kinase(PI3K) signaling pathway is involved in the occurrence and development of atherosclerosis, tumor and immune system diseases. Regulation of PI3K can regulate apoptosis, autophagy, inflammatory response and other pathophysiological processes, which provides a new idea for the treatment of diseases.

Intrinsic structural phase is a crucial foundation for the fundamental physical properties, and for creating innovative devices with unprecedented performances and unique functionalities. Long-range ferromagnetic orders of van der Waals CrI3 are strongly tied with interlayer stacking orders. However, the intrinsic structure of few-layer CrI3 still remains elusive; the predicted monoclinic phase has not yet been experimentally detected in bare few-layer CrI3. Here we uncover the intrinsic structure of few-layer CrI3 with interlayer antiferromagnetic coupling, which unambiguously show monoclinic stacking in both bare and hBN-encapsulated bilayer and tri-five-layer CrI3 throughout an entire temperature range from 300 to 10 K. An exotic spring damping effect from hBN encapsulation layers is experimentally observed in hBN/CrI3/hBN heterostructures, which partly hinders interlayer sliding of CrI3. This work demonstrates the intrinsic monoclinic crystal phase of few-layer CrI3 and associated correlation with magnetic orders, opening up numerous opportunities for creating magnetic texture by stacking design.

In view of the problem of coal spontaneous combustion and re-ignition by reducing the oxidation of coal with inert gas, most of the existing studies are related to the coal low-temperature oxidation process and the coal re-ignition process. The spontaneous combustion characteristics of coal secondary oxidation after reducing inert gas temperature are less covered. In order to solve the above problems, taking coking coal as an example, the spontaneous combustion characteristics of coking coal oxidized at different temperatures after CO2 cooling and secondary oxidation are explored through the low-temperature oxidation experiment. The coking coal is pre-oxidized by GC-4000A temperature-programmed equipment at 70, 110, 150 ℃ respectively. The oxygen consumption rate, CO production rate, CO2 concentration and apparent activation energy of coking coal during the secondary oxidation process are analyzed after cooling to 30 ℃ with CO2 gas and dry air respectively. The experimental results show that at the same pre-oxidation temperature, compared with the dry air cooling, the change rule of related parameters of coking coal cooled by CO2 is basically the same. In the early stage of secondary oxidation, because of coking coal absorbs a lot of CO2, CO2 hinders the contact between coal and O2, the oxygen consumption rate and CO production rate decrease. The apparent activation energy increases, and the oxidation of coking coal decreases. As the CO2 resolves, CO2 cooling also affects the later reaction of pre-oxidized coking coal, which reduces the spontaneous combustion risk of pre-oxidized coking coal during the whole reaction process. When the pre-oxidation temperature is different, the pre-oxidation coking coal at 70 ℃ and 110 ℃ has a small amount of CO2 adsorption in the early stage. This leads to no change in oxygen consumption rate, CO production rate and apparent activation energy. When the pre-oxidized coking coal at 150 ℃ is cooled to 30 ℃, the coking coal has more CO2 adsorption, resulting lower the oxygen consumption rate and CO production rate. With the increase of activation energy, more energy is required. The coal oxygen reaction is more difficult. The risk of spontaneous combustion is also reduced. Therefore, when there is a danger of oxidation and spontaneous combustion of coal in the coal mine, it is necessary to inject CO2 for a long time to reduce the possibility of secondary oxidation and re-ignition when the mining area is reopened.

Spinal cord injury (SCI) induced catastrophic neurological disability is currently incurable, especially in elderly patients. Due to the limited axon regeneration capacity and hostile microenvironment in the lesion site, essential neural network reconstruction remains challenging. Owing to the blood–spinal cord barrier (BSCB) created immune cells and cytokines isolation, the immune elements were incorrectly recognized as innocent bystanders during the SCI pathological process traditionally. Emerging evidence demonstrated that the central nervous system (CNS) is an “immunological quiescent” rather than “immune privileged” area, and the CNS-associated immune response played mixed roles which dedicate beneficial and detrimental contributions throughout the SCI process. Consequently, coordinating double-edged immunomodulation is vital to promote tissue repair and neurological recovery post-SCI. The comprehensive exploration and understanding of the immune landscape post-SCI are essential in establishing new avenues for further basic and clinical studies. In this context, this review summarizes the recent significant breakthroughs in key aspects of SCI-related immunomodulation, including innate and adaptive immune response, immune organ changes, and holistic immune status modification. Moreover, the currently existing immune-oriented therapies for SCI will be outlined.

Based on the engineering background of Hequ Open-pit Mine, this paper analyzes the bottom slope displacement cloud map, the maximum shear strain increment cloud image at different tracking distances, and the different pressure feet in Hequ Open-pit Mine. The slope stability changes at the lower end of the tracking distance. The research results show that under different tracking distances of the inner row presser foot, the end side slope forms different areas of dangerous areas and settlement areas. With the continuous reduction of the inner row presser foot tracking distance, the end side slope danger area and settlement area gradually migrate to the working side, close to the dumping yard and the bottom of the end side slope to form a bottom drum area, the end side slope sliding form is approximately “convex”; the inner row tracking distance and the end side slope stability coefficient obey the Boltzmann function relation. When the tracking distance is reduced from 150 m to 100 m, the stability coefficient of the end slope has a cliff-like change. Therefore, a reasonable tracking distance of the inner row presser foot can not only improve the stability of the side slope, but also improve the economic benefits of the mine. The use of the inner row presser foot measure to improve the stability of the end side slope is also a kind of both appropriate and economical method.

As categorical attributes cannot be utilized directly in some regression models like the linear regression,SVR and most multivariate regression trees,a multivariate split method dealing with multiple types of data is prompted in this paper.We define the centers of the sample sets on the categorical attributes and the distances from the samples to the centers in order that thecate-gorical attributes can also participate in the clustering process like the numerical attributes.Then a reasonable ensemble scheme is selected for the decision trees generated by the method to get the ensemble called cluster regression forest(CRF).Finally,we use CRF and other 9 regression models to compare regression mean absolute error (MAE) and root mean square error (RMSE) on 12 UCI public data sets.The experimental results show that CRF has the best performance among the 10 regression models.

Depression is the most common non⁃motor symptom of Parkinson's disease. However, the pathogenesis of depression in Parkinson's disease (DPD) remains undetermined. In order to further standardize and improve clinical diagnosis and treatment of DPD, relevant domestic experts of traditional Chinese and Western medicine from Jiangsu, Anhui, Shandong, Guangdong and Tianjin, Beijing, Shanghai jointly developed "Expert consensus on diagnosis and treatment of depression in Parkinson's disease with integrated traditional Chinese and Western medicine (2021 edition)" after detailed discussions both online and offline. With integrated traditional Chinese and Western medicine, the consensus sorts out diagnosis, evaluation tools and treatment of Western medicine according to the diagnostic criteria of Parkinson's disease and depression, and traditional Chinese medicine diagnosis and treatment system based on syndrome differentiation of Parkinson's disease according to the traditional Chinese medicine diagnosis of tremor syndrome and depression syndrome. Different treatment methods are provided for the early and advanced stages of Parkinson's disease according to the treatment principles of integrated traditional Chinese and Western medicine. The expert consensus is superior in clinic and relatively safe, which can be used as a reference for clinicians.

The application of a no-touch technique to create an autologous radiocephalic arteriovenous fistula might improve the patency rate. In the present report, we have expanded the concept of the no-touch technique by introducing a modified no-touch technique in which we preserve the perivenous vascular tissue, followed by a functional end-to-side anastomosis to create a radiocephalic arteriovenous fistula with early maturation for hemodialysis.

The goals of this paper are to study the frost resistance of steel slag concrete (SSC), research the damage mechanisms, and predict the service life of SSC in cold regions. First, the stability of steel slag (SS) was tested, and then SS samples with different treatment dosages were used as aggregates to replace natural aggregates of equal volumes in the preparation of C40 concrete. The microstructures of concrete and micro properties of cement hydration products were investigated in nanospace in this research. In addition, rapid frost resistance durability tests were carried out under laboratory conditions. The results revealed that the ordinary concrete (OC) exhibited a more serious damage phenomenon, and the mass loss and relative dynamic elastic modulus of OC were changed by 5.27 and 62.30%, respectively. However, with increases in the SS content, the losses in mass were lowered. Furthermore, the relative dynamic elastic modulus decreased less, and the frost resistance of the specimens was stronger. The range of mass loss rate was between 2.233 and 3.024%, and the relative dynamic elastic modulus range was between 74.92 and 91.09%. A quadratic function with a good fitting degree was selected to establish a freezing-thawing damage calculation model by taking the relative dynamic elastic modulus as the variable. Then, the freezing-thawing durability lifespan of concrete in the colder regions of northern China was successfully predicted by using the damage calculation model. The results of SSC20–60 showed the better frost resistance durability when the content of SS sand was 20% and the dosage of SS stone was 60%. Its frost resistance lifespan was more than twice that of OC, which demonstrated that SS as an aggregate could effectively improve the frost resistance lifespan of concrete to a certain extent.

Due to its functional、nutritional and ornamental characteristics,the special colored grains are increasingly favored and become an important direction of high-end crop industry.These natural pigments can not only increase the color of food,but also have special functions such as antioxidant,anti-cancer,and improving vision etc.This paper focuses on the biosynthesis,main functions and related products of anthocyanins,tricin and carotenoids in special color crops,and then focuses on wheat,an important food crop,and introduced two newly cultivated pigments functional wheat including “Shannong lanmai 1” and“Shannong 101”.This paper provides a reference for the research and variety creation of special color crops.