Search

Abstract Enhancing the efficacy of CD19 CAR-T cell therapy can significantly improve patient outcomes by reducing relapse rates in CD19 + B cell malignancies. Exogenous or transgenic cytokines are often used to boost the expansion and durability of CAR-T cells but pose risks of severe toxicities. A promising approach to address these limitations is to immobilize cytokines on the surface of CAR-T cells using transmembrane (TM) anchor domains. Given IL-7 can enhance T-cell proliferation and antitumor activity, our study developed membrane-bound IL-7 constructs using different TM anchor domains (CD8, CD28 and B7-1). We primarily found that the CD8 TM provided superior anchoring for IL-7 compared to CD28 and B7-1. Moreover, the IL-7 construct with a CD8 TM (IL7/CD8) enhanced naïve T cell proliferation and effector functions, and improved the in vitro and in vivo antitumor activity of CD19 CAR-T cells. Importantly, although IL7/CD8 could promote T-cell proliferation, it did not sustain long-term autonomous expansion, which could ensure the safety of CD19 CAR-T cells expressing IL7/CD8 in clinical applications. Collectively, the IL7/CD8 construct represents a promising strategy for enhancing the therapeutic potential of CD19 CAR-T cell therapy.

Abstract The on-chip measurement of polarization states plays an increasingly crucial role in modern sensing and imaging applications. While high-performance monolithic linearly polarized photodetectors have been extensively studied, integrated circularly polarized light (CPL) photodetectors are still hindered by inadequate discrimination capability. This study presents a broadband CPL photodetector utilizing achiral all-dielectric nanostructures, achieving an impressive discrimination ratio of ~107 at a wavelength of 405 nm. Our device shows outstanding CPL discrimination capability across the visible band without requiring intensity calibration. It functions based on the CPL-dependent near-field modes within achiral structures: under left or right CPL illumination, distinct near-field modes are excited, resulting in asymmetric irradiation of the two electrodes and generating a photovoltage with directions determined by the chirality of the incident light field. The proposed design strategy facilitates ultra-compact CPL detection across diverse materials, structures, and spectral ranges, presenting a novel avenue for achieving high-performance monolithic CPL detection.

Abstract Introduction Semantic fluency is the ability to name items from a given category within a limited time, which relies on semantic knowledge, working memory, and executive function. Similar to patients with Parkinson's disease (PD), patients with progressive supranuclear palsy (PSP) scored lower than healthy adults in the well‐established semantic fluency test. However, it is unclear how unique are the produced words. This study examined the relationship between semantic fluency and words’ uniqueness in patients with PSP. Methods Twenty‐seven patients with PSP Richardson's syndrome (PSP‐RS), 37 patients with PD, and 41 healthy controls (HC) performed a standard semantic fluency test (animals), and their verbal responses were audio‐recorded. We used the uniqueness to reflect the ability to produce both original and effective work, that is, creativity. Results The PSP‐RS group produced fewer correct words and fewer unique words than the PD and HC groups. Moreover, the correlation between fluency and uniqueness was positive in the HC and PD groups but negative in the PSP‐RS group. Importantly, the actual levodopa dose was positively correlated with the fluency but negatively correlated with the uniqueness in PSP‐RS. The PSP‐RS patients who took a greater dose of levodopa tended to produce more correct words but fewer unique words. Conclusions These results suggested that levodopa may modulate semantic fluency and uniqueness in the early stages of PSP‐RS.

Deep carbonate reservoirs are attractive targets for gas development. These reservoirs are deeply buried, and commonly possess strong heterogeneity and poor seismic data quality, making the identification of favorable production areas (“sweet spots”) challenging. Furthermore, sedimentary facies and fault systems markedly impact reservoir quality, and identifying these features in seismic data is also crucial for sweet spot identification. To solve these problems, we propose a dual-factor-controlled sweet spot identification method with two steps. First, sedimentary facies and faults are identified separately at different seismic scales using different attributes by the steerable pyramid (SP) method. The SP method decomposes the original seismic data into high-frequency and low-frequency data. The amplitude attributes from high-frequency data are used to identify sedimentary facies, and coherence attributes based on low-frequency data are used to characterize the fault systems. Second, after separately identifying the sedimentary facies and faults, the two attribute volumes are merged together to identify reservoir sweet spots. The results are verified by using well production data. The results of a field study in the Dengying Formation deep carbonate reservoir in the central Sichuan Basin, China, indicate that reservoir sweet spots are primarily developed in ideal sedimentary facies along strike-slip fault systems. Sedimentary facies generally control the type and distribution of reservoirs, whereas strike-slip fault systems control the migration and accumulation of gas. In addition, the fault systems serve as karst channels that further improve the reservoir properties. The proposed dual-factor method might help to maximize exploration potential in deep carbonate reservoirs with similar settings.

Abstract Purpose Sequential working memory is the ability to maintain and manipulate sequential information at a second time scale. Patients with progressive supranuclear palsy (PSP) or Parkinson's disease (PD) perform poorly in tests that require the flexible arrangement of thoughts or actions. This study investigated whether sequential working memory is differently impaired in patients with PSP versus PD. Method Twenty‐nine patients with PSP Richardson's syndrome (PSP‐RS), 36 patients with PD, and 36 healthy controls (HC) completed 3 well‐established neuropsychological tests, including digit span forward (DST‐F), digit span backward (DST‐B), and adaptive digit ordering tests (DOT‐A). The DST‐F required maintaining digit sequences, and the DST‐B and DOT‐A required maintaining and manipulating digit sequences. Finding The PSP‐RS group scored lower than the PD and HC groups in the DST‐B and DOT‐A but not in the DST‐F, indicating that the ability to manipulate sequences was impaired, but the maintenance ability was preserved in PSP‐RS patients. Moreover, in PSP‐RS, the DST‐B score negatively correlated with the severity of motor symptoms. The actual levodopa dose positively correlated with the DST‐B ordering cost (DST‐F score vs. DST‐B score). The PSP patients who took a greater dose of levodopa tended to have higher DST‐B ordering cost. There was no effect of levodopa on DST‐B or DOT‐A in PD. Conclusion These results suggested that the ability to manipulate sequence was already reduced in patients with PSP‐RS and was worse than in patients with PD.

This paper proposes a multi-level operation method designed to enhance the resilience of power systems under extreme weather conditions by utilizing preventive control and virtual oscillator (VO) technology. Firstly, a novel model for predicting time intervals between successive failures of the power system during extreme weather is introduced. Based on this, this paper proposes a preventive control method considering the system ramping and transmission constraints prior to failures so as to ensure the normal electricity demand within the system. Further, a VO-based adaptive frequency control strategy is designed to accelerate the regulation speed and eliminate the frequency deviation. Finally, the control performance is comprehensively compared under different experimental conditions. The results verify that the method accurately predicted the time of the line fault occurrence, with a maximum error not exceeding 3 min compared to the actual occurrence; also, the virtual oscillator control (VOC) strategy outperformed traditional droop control in frequency stabilization, achieving stability within 2 s compared to the droop control’s continued fluctuations beyond 20 s. These results highlight VOC’s superior effectiveness in frequency stability and control in power systems.

Exploration in the Lishui West Sag of the East China Sea Basin is limited by the scarcity of offshore drilling sites, and the prediction of deep, high-quality reservoirs is challenging using only geophysical methods. This study introduces a quantitative approach to diagenetic facies division in individual wells based on logging data, providing a new method and perspective for the prediction of deep, high-quality reservoirs. We employed comprehensive data from core, logging, thin-section casting, cathodoluminescence, scanning electron microscopy, and X-ray diffraction analyses from five wells to study the petrology, physical properties, diagenetic types and strength, and diagenetic minerals of the Paleocene sandstone reservoirs in the Lishui West Sag. Apparent compaction rate, apparent cementation rate, and other quantitative characterization parameters were used to calculate the comprehensive diagenetic coefficient (Cg), and the diagenetic facies were divided into compaction, cementation, and dissolution facies. A logging calculation model for the comprehensive diagenetic coefficient (Cg) and a quantitative identification method for diagenetic facies in individual well reservoirs were established through a fitting analysis between Cg and logging curve parameters. Continuous quantitative identification of vertical diagenetic facies in the five wells in the study area showed that the high-quality reservoirs in wells L1, L2, and L3 within the L1 gas field are characterized by extensive development of dissolution facies, while wells L4 and L5 are dominated by compaction and cementation facies, with poor reservoir properties and no industrial gas flow output. The results demonstrate the reliability of the model method. The establishment of this quantitative characterization method for diagenetic facies using logging data provides guidance for the prediction of favorable reservoirs.

ObjectiveTo analyze the risk factors of lower extremity deep venous thrombosis (DVT) detachment in orthopedic patients, and to establish a risk nomogram prediction model.MethodsThe clinical data of 334 patients with orthopedic DVT admitted to the Third Hospital of Hebei Medical University from January 2020 to July 2021 were retrospectively analyzed. General statistics included gender, age, BMI, thrombus detachment, inferior vena cava filter window type, filter implantation time, medical history, trauma history, operation, use of tourniquet, thrombectomy, anesthesia mode, anesthesia grade, operative position, blood loss during operation, blood transfusion, immobilization, use of anticoagulants, thrombus side, thrombus range, D-dimer content before filter implantation and during removal of inferior vena cava filter. Logistic regression was used to perform univariate and multivariate analysis on the possible factors of thrombosis detachment, screen out independent risk factors, establish a risk nomogram prediction model by variables, and internally verify the predictability and accuracy of the model.ResultsBinary logistic regression analysis showed that Short time window filter (OR = 5.401, 95% CI = 2.338–12.478), lower extremity operation (OR = 3.565, 95% CI = 1.553–8.184), use of tourniquet (OR = 3.871, 95% CI = 1.733–8.651), non-strict immobilization (OR = 3.207, 95% CI = 1.387–7.413), non-standardized anticoagulation (OR = 4.406, 95% CI = 1.868–10.390), distal deep vein thrombosis (OR = 2.212, 95% CI = 1.047–4.671) were independent risk factors for lower extremity DVT detachment in orthopedic patients (P

In addressing the critical need to understand the geological and diagenetic factors affecting Paleogene sandstone reservoirs in the Baiyun Sag—a region vital for oil and gas exploration—this study delves into the Paleogene Zhuhai and Enping formations. Advanced methodologies, including petrographic thin-section analysis, scanning electron microscopy, wavelet analysis, and carbon and oxygen isotope analysis, were employed to evaluate their petrological characteristics, pore structures, physical properties, and key diagenetic processes. The results indicate that the Zhuhai Formation is primarily composed of feldspathic quartz sandstones with prevalent intergranular dissolution pores, while the Enping Formation consists mainly of feldspathic sandstones with intragranular solution pores. The diagenetic temperatures across both formations ranged from 42.6 to 116.3 °C. The studied reservoirs have experienced porosity alterations due to mechanical compaction (23.07% reduction), carbonate cementation (9.02% reduction), and dissolution (5.09% enhancement). Notably, feldspar dissolution emerged as a significant contributor to high-quality reservoirs, particularly in the upper Enping Formation. These findings offer invaluable insights into the diagenetic evolution of sandstone reservoirs in the Baiyun Sag and hold significant implications for guiding future oil and gas exploration efforts in the region.

The well-established semantic fluency test measures the ability to produce a sequence of spoken words from a particular category within a limited period of time. Like patients with Parkinson’s disease (PD), patients with progressive supranuclear palsy (PSP) tend to produce fewer correct words than age-matched healthy adults. This study further examined the difference between patients with PSP and PD in their semantic fluency performance using a graph theory-based approach. Twenty-nine patients with PSP Richardson’s syndrome (PSP-RS), thirty-eight patients with PD, and fifty-one healthy controls (HC) were recruited. All participants completed a standard semantic fluency test (animals). Their verbal responses were recorded, transcripted, and transformed into directed speech graphs. The speech graphs of the PSP-RS group showed higher density, shorter diameter, and shorter average shortest path than those of the PD and HC groups. It indicates that the PSP-RS group produced smaller and denser speech graphs than the PD and HC groups. In the PSP-RS group, moreover, the average shortest paths of the speech graphs correlated with the severity of motor symptoms. This study shows the potential of the graph theory-based approach in distinguishing the semantic fluency performance of nondemented patients with PSP-RS and PD.

Abstract To screen the key genes in the development of gastric cancer and their influence on prognosis. The GEO database was used to screen gastric cancer-related gene chips as a training set, and the R packages limma tool was used to analyze the differential genes expressed in gastric cancer tissues compared to normal tissues, and then the selected genes were verified in the validation set. The String database was used to calculate their Protein–protein interaction (PPI) network, using Cytoscape software's Centiscape and other plug-ins to analyze key genes in the PPI network. The DAVID database was used to enrich and annotate gene functions of differential genes and PPI key module genes, and further explore correlation between expression level and clinical stage and prognosis. Based on clinical data and patient samples, differential expression of key node genes was verified by immunohistochemistry. The 63 characteristic differential genes screened had good discrimination between gastric cancer and normal tissues, and are mainly involved in regulating extracellular matrix receptor interactions and the PI3k-AKT signaling pathway. Key nodes in the PPI network regulate tumor proliferation and metastasis. Analysis of the expression levels of key node genes found that relative to normal tissues, the expression of ITGB1 and COL1A2 was significantly increased in gastric cancer tissues, and patients with late clinical stages of tumors had higher expression of ITGB1 and COL1A2 in tumor tissues, and their survival time was longer (P

The physical and chemical properties of tissue engineering scaffolds have considerable effects on the inflammatory response at the implant site in soft tissue repair. The development of inflammation-modulating polymer scaffolds for soft tissue repair is attracting increasing attention. In this study, in order to regulate the inflammatory response at the implant site, a series of waterborne polyurethane (WPU) scaffolds with different properties were synthesized using polyethylene glycol (PEG), polycaprolactone (PCL) and poly (lactic acid)–glycolic acid copolymers (PLGAs) with three lactic acid/glycolic acid (LA/GA) ratios as the soft segments. Then, scaffolds were obtained using freeze-drying. The WPU scaffolds exhibited a porous cellular structure, high porosity, proper mechanical properties for repairing nerve tissue and an adjustable degradation rate. In vitro cellular experiments showed that the degradation solution possessed high biocompatibility. The in vitro inflammatory response of C57BL/6 mouse brain microglia (immortalized) (BV2) cells demonstrated that the LA/GA ratio of the PLGA in WPU scaffolds can regulate the external inflammatory response by altering the secretion of IL-10 and TNF-α. Even the IL-10/TNF-α of PU5050 (3.64) reached 69 times that of the control group (0.053). The results of the PC12 culture on the scaffolds showed that the scaffolds had positive effects on the growth, proliferation and differentiation of nerve cells and could even promote the formation of synapses. Overall, these scaffolds, particularly the PU5050, indeed prevent BV2 cells from differentiating into a pro-inflammatory M1 phenotype, which makes them promising candidates for reducing the inflammatory response and repairing nerve tissue. Furthermore, PU5050 had the best effect on preventing the transformation of BV2 cells into the pro-inflammatory M1 phenotype.

Semantic fluency is the ability to name items from a given category within a limited time, which relies on semantic memory, working memory, and executive function. Semantic disfluency is a common problem in Parkinson’s disease (PD) and Alzheimer’s disease (AD). We demonstrated a graph theoretical analysis of semantic fluency in patients with PD (N=86), patients with AD (N=40), and healthy controls (HC, N=88). All participants completed a standard animal fluency test. Their verbal responses were recorded, transcripted, and transformed into directed speech graphs. Patients with PD generated fewer correct words than HC and more correct words than patients with AD. Patients with PD showed higher density, shorter diameter, and shorter average shortest path length than HC, but lower density, longer diameter, and longer average shortest path length than patients with AD. It suggests that patients with PD produced relatively smaller and denser speech graphs. Moreover, in PD, the densities of speech graphs correlated with the severity of non-motor symptoms, but not the severity of motor symptoms. The graph theoretical analysis revealed new features of semantic disfluency in patients with PD.

Abstract Acoustofluidics has emerged as a promising method for submicron particle manipulation. However, ultrahigh‐frequency or focused sound waves are usually required to generate sufficient acoustic radiation force or localized streaming vortex for trapping nanoscale objects, which is more challenging in device fabrication. This work presents a novel method using a low‐frequency acoustic field actuated micro‐pillar array (APA) chip to efficiently enable programmable and parallel trapping of nanoparticles. Driven by the acoustic waves, each arrayed vibrating micropillar generates a highly localized acoustic field with enhanced acoustic radiation forces and well‐confined vortex streaming around the pillar. The APA chip is demonstrated with geometric tuning ability of regulating the trapping limit by altering the pillar size. Micropillar arrays with a diameter of 5 µm are demonstrated to trap 112 nm particles efficiently. Thanks to the convenience of using ultrasounds and arraying micropillars of different geometric sizes, the APA chip provides an alternative of submicron particle manipulation technique for programmable and high‐throughput trapping and patterning of particles, with potential for “lab‐on‐a‐chip” sample preparations.

Manipulator is a kind of commonly used multi-degree-of-freedom nonlinear system. There is a strong coupling between the links, and the movement of each link constraints and affects each other, which increases the difficulty of motion analysis of the system and reduces its trajectory planning efficiency under specific task targets. To solve this problem, a direct trajectory planning method based on an improved particle swarm optimization (PSO) algorithm, called IEPSO, and the fuzzy rewards and punishment theory is proposed in this paper. First, on the basis of preserving the local search ability of PSO, the global search ability of the population is improved by increasing a population exchange item. At the same time, in order to avoid the population falling into the local optimal value, the last elimination principle is incorporated into the standard PSO algorithm. Second, the fuzzy rewards and punishment theory is introduced to reduce the redundant decoupling operation, which can not only ensure the accuracy of manipulator trajectory planning but also effectively reduce the calculation amount of the trajectory planning for the multi-degree-of-freedom manipulator, to improve the optimization efficiency. Finally, the direct trajectory planning method of the multi-degree-of-freedom manipulator is compared and tested. It can be seen that the efficiency scalar and accuracy of the proposed direct trajectory planning method are significantly higher than those of other optimization methods.

Multi-agent combat scenarios often appear in many real-time strategy games. Efficient learning for such scenarios is an indispensable step towards general artificial intelligence. Multi-agent reinforcement learning (MARL) algorithms have attracted much interests, but few of them have been shown effective for such scenarios. Most of previous research is focused on revising the learning mechanism of MARL algorithms, for example, trying different types of neural networks. The study of training techniques for improving the performance of MARL algorithms has not been paid much attention. In this paper we propose three efficient training techniques for a multi-agent combat problem which is originated from an unmanned aerial vehicle (UAV) combat scenario. The first one is the scenario-transfer training, which utilizes the experience obtained in simpler combat tasks to assist the training for complex tasks. The next one is the self-play training, which can continuously improve the performance by iteratively training agents and their counterparts. Finally, we consider using combat rules to assist the training, which is named as the rule-coupled training. We combine the three training techniques with two popular multi-agent reinforcement learning methods, multi-agent deep q-learning and multi-agent deep deterministic policy gradient (proposed by Open AI in 2017), respectively. The results show that both the converging speed and the performance of the two methods are significantly improved through the three training techniques.

The ability to sequence thoughts and actions is impaired in Parkinson’s disease (PD). In PD, a distinct error pattern has been found in the offline performance of sequential working memory. This study examined how PD’s performance of sequential working memory unfolds over time using mouse tracking techniques. Non-demented patients with mild PD (N = 40) and healthy controls (N = 40) completed a computerized digit ordering task with a computer mouse. We measured response dynamics in terms of the initiation time, ordering time, movement time, and area under the movement trajectory curve. This approach allowed us to distinguish between the cognitive processes related to sequence processing before the actual movement (initiation time and ordering time) and the execution processes of the actual movement (movement time and area under the curve). PD patients showed longer initiation times, longer movement times, and more constrained movement trajectories than healthy controls. The initiation time and ordering time negatively correlated with the daily exposure to levodopa and D2/3 receptor agonists, respectively. The movement time positively correlated with the severity of motor symptoms. We demonstrated an altered temporal profile of sequential working memory in PD. Stimulating D1 and D2/3 receptors might speed up the maintenance and manipulation of sequences, respectively.

Mitochondrial chronic progressive external ophthalmoplegia (CPEO) is a major manifestation of human mitochondrial encephalomyopathies. Previous studies have shown cognitive deficits in patients with mitochondrial diseases. However, these studies often included patients with heterogeneous subtypes of mitochondrial diseases. Here, we aimed to provide a better cognitive profile of patients with CPEO by applying a comprehensive battery of neuropsychological assessments in a pure sample of patients with CPEO. We recruited 28 patients with CPEO (19 women, age 16–62 years) and 38 age- and education-matched healthy control subjects (25 women, age 16–60 years). The neuropsychological assessments covered global cognition and five cognitive domains (executive functions, language, working memory, memory, and visuospatial functions). We found that the patients were impaired in global cognition [Montreal Cognitive Assessment (MoCA)], executive functions [Trail Making Test Part B (TMT-B)], and language [Boston Naming Test (BNT)], but not in working memory, memory or visuospatial functions. Moreover, individual patients' performances in the TMT-B (completion time) were predicted by the severity of non-ophthalmoplegia mitochondrial symptoms/signs [Newcastle Mitochondrial Disease Adult Scale (NMDAS)] and duration of the mitochondrial disease (years). Namely, patients with more severe non-ophthalmoplegia mitochondrial symptoms/signs and a longer disease duration took a longer time to complete the TMT-B. No clinical measures predicted individual patients' performances in the BNT.

Summary: Hepatocytes are the primary functional cells of the liver, performing its metabolic, detoxification, and endocrine functions. Functional hepatocytes are extremely valuable in drug discovery and evaluation, as well as in cell therapy for liver diseases. However, it has been a long-standing challenge to maintain the functions of hepatocytes in vitro. Even freshly isolated hepatocytes lose essential functions after short-term culture for reasons that are still not well understood. In the present study, we find that mechanical tension-induced yes-associated protein activation triggers hepatocyte dedifferentiation. Alleviation of mechanical tension by confining cell spreading is sufficient to inhibit hepatocyte dedifferentiation. Based on this finding, we identify a small molecular cocktail through reiterative chemical screening that can maintain hepatocyte functions over the long term and in vivo repopulation capacity by targeting actin polymerization and actomyosin contraction. Our work reveals the mechanisms underlying hepatocyte dedifferentiation and establishes feasible approaches to maintain hepatocyte functions. : It has been a long-standing challenge to maintain the functions of hepatocytes in vitro. Sun et al. find that mechanical tension-induced Yap activation triggers hepatocyte dedifferentiation. Alleviation of mechanical tension by confining cell spreading or treatment with a small molecule cocktail targeting actin/actomyosin dynamics could maintain hepatocyte functions. Keywords: hepatocytes, dedifferentiation, small molecules, mechanical tension

Myelin sheaths are essential in maintaining the integrity of axons. Development of the platform for in vitro myelination would be especially useful for demyelinating disease modeling and drug screening. In this study, a fiber scaffold with a core–shell structure was prepared in one step by the coaxial electrospinning method. A high-molecular-weight polymer poly-L-lactic acid (PLLA) was used as the core, while the shell was a natural polymer material such as hyaluronic acid (HA), sodium alginate (SA), or chitosan (CS). The morphology, differential scanning calorimetry (DSC), Fourier transform infrared spectra (FTIR), contact angle, viability assay, and in vitro myelination by oligodendrocytes were characterized. The results showed that such fibers are bead-free and continuous, with an average size from 294 ± 53 to 390 ± 54 nm. The DSC and FTIR curves indicated no changes in the phase state of coaxial brackets. Hyaluronic acid/PLLA coaxial fibers had the minimum contact angle (53.1° ± 0.24°). Myelin sheaths were wrapped around a coaxial electrospun scaffold modified with water-soluble materials after a 14-day incubation. All results suggest that such a scaffold prepared by coaxial electrospinning potentially provides a novel platform for oligodendrocyte myelination.

We, the authors, wish to make the following corrections to our paper [...]

Vehicles are developing in the direction of energy-saving and electrification. suspension has been widely developed in the field of vehicles as a key component. Traditional hydraulic energy-supply suspensions dissipate vibration energy as waste heat to suppress vibration. This part of the energy is mainly generated by the vehicle engine. In order to effectively utilize the energy of this part, the energy-regenerative suspension with energy recovery converts the vibrational energy into electrical energy as the vehicle’s energy supply equipment. This article reviews the hydraulically powered suspension of vehicles with energy recovery. The importance of such suspension in vehicle energy recovery is analyzed. The main categories of energy-regenerative suspension are illustrated from different energy recovery methods, and the research status of hydraulic energy-regenerative suspension is comprehensively analyzed. Important factors that affect the shock-absorbing and regenerative characteristics of the suspension system are studied. In addition, some unresolved challenges are also proposed, which provides a reference value for the development of energy-regenerative suspension systems for hybrid new energy vehicles

The electromechanical system of a crawler is a multi-input, multioutput strongly coupled nonlinear system. In this study, an adaptive inverse control method based on kriging algorithm and Lyapunov theory is proposed to improve control accuracy during adaptive driving. The electromechanical coupling model of the electromechanical system is established on the basis of the dynamic analysis of the crawler. In accordance with the kriging algorithm, the inverse model of the electromechanical system of the crawler is established by offline data. The adaptive travel control law of the crawler is obtained on the basis of Lyapunov theory. Combined with the kriging algorithm, the adaptive driving reverse control method is designed, and the online system is used to update and perfect the inverse system model in real time. Finally, the virtual prototype model of the crawler is established, and the control effect of the adaptive inverse control method is verified by theoretical analysis and virtual prototype simulation.

Efficient conversion of cellulosic sugars in cellulosic hydrolysates is important for economically viable production of biofuels from lignocellulosic biomass, but the goal remains a critical challenge. The present study reports a new approach for simultaneous fermentation of cellobiose and xylose by using the co-culture consisting of recombinant Saccharomyces cerevisiae specialist strains. The co-culture system can provide competitive advantage of modularity compared to the single culture system and can be tuned to deal with fluctuations in feedstock composition to achieve robust and cost-effective biofuel production. This study characterized fermentation kinetics of the recombinant cellobiose-consuming S. cerevisiae strain EJ2, xylose-consuming S. cerevisiae strain SR8, and their co-culture. The motivation for kinetic modeling was to provide guidance and prediction of using the co-culture system for simultaneous fermentation of mixed sugars with adjustable biomass of each specialist strain under different substrate concentrations. The kinetic model for the co-culture system was developed based on the pure culture models and incorporated the effects of product inhibition, initial substrate concentration and inoculum size. The model simulations were validated by results from independent fermentation experiments under different substrate conditions, and good agreement was found between model predictions and experimental data from batch fermentation of cellobiose, xylose and their mixtures. Additionally, with the guidance of model prediction, simultaneous co-fermentation of 60 g/L cellobiose and 20 g/L xylose was achieved with the initial cell densities of 0.45 g dry cell weight /L for EJ2 and 0.9 g dry cell weight /L SR8. The results demonstrated that the kinetic modeling could be used to guide the design and optimization of yeast co-culture conditions for achieving simultaneous fermentation of cellobiose and xylose with improved ethanol productivity, which is critically important for robust and efficient renewable biofuel production from lignocellulosic biomass.

There are many and complex big data in digital power grid regulation, which leads to the difficulty of big data asset management. Therefore, a model of big data asset management system in digital power grid regulation is constructed. The model consists of three parts: data acquisition, data safe storage and data index. The data acquisition architecture is designed, and the data acquisition results are filled with missing values and corrected with grey prediction method. Using AR-Tree index organization to realize the digital power grid regulation big data index, and achieve the goal of high-quality management of digital power grid regulation big data assets. Store the filled and corrected data in the blockchain to ensure data security. The experimental results show that the average recall and precision of this method are 96.9% and 97.9%, and the data acquisition quality is high. After the application of this method, there is almost no unsafe data, and the proportion of safe data is higher, which shows that this method can ensure the security of big data storage. The response time of digital power grid regulation big data index is below 0.21s, and the index efficiency is higher. [ABSTRACT FROM AUTHOR]