Linking the assessment of ecological engineering construction with zoning management in the typical agro-pastoral area of China: A perspective from quantity, quality and function.

Combatting land damage has become a global priority, and China has adopted a series of ecological engineering measures, especially in the agro-pastoral area with fragile ecological environment. The effectiveness of ecological engineering construction (EEC), from a comprehensive recognition encompassing its quality, quantity, and function, has remained largely unknown. To this end, Zhangbei County, a typical agro-pastoral ecotone of northern China, was chosen as our focal area. After summarizing the timelines, aims and results of the EEC during various periods in Zhangbei, the linear spectral mixture analysis was employed to process Landsat 5 TM images in 2000 and 2010, as well as Landsat 8 OLI images in 2020. Then, a comprehensive evaluation framework of EEC was established from the perspective of "quantity-quality-function", and the ecological effectiveness of EEC was evaluated from 2000 to 2020 in Zhangbei. Results revealed that EEC played a critical role in enhancing quantity, quality and function, in spite of that, there were still numerous regions showing varying degrees of degradation in terms of these aspects. Then, by extending the three-dimensional cube as the theoretical basis for the zoning management of EEC, we merged four zones according to the space matching relationship among quantity, quality and function of EEC, namely, Ecological conservation area, Ecological improvement area, Ecological restoration area and Ecological remodeling zone. More targeted ecological measures were required for specific matching relationship among quantity, quality and function of EEC. This study is expected to present an empirical case for assessing the ecological effectiveness of EEC in areas or countries with similar restoration demand and support regional management.

Evidence that robot-assisted gait training modulates neuroplasticity after stroke: An fMRI pilot study based on graph theory analysis.

OBJECTIVES: To investigate alterations of whole-brain network after stroke and therapeutic mechanisms of robot-assisted gait training (RAGT). METHODS: 21 S patients and 20 healthy subjects were enrolled, with the stroke patients randomized to either control group (n = 11) or robot group (n = 10), and resting-state functional magnetic resonance imaging data were collected. The global network metrics were obtained using graph theory analysis and compared between stroke patients and healthy subjects, and the effect of the RAGT on the whole-brain networks was explored. RESULTS: Compared to healthy subjects, area under the curve (AUC) for small-worldness (σ), clustering coefficient (Cp), global efficiency (Eg) and mean local efficiency (Eloc) were significantly lower in stroke patients, whereas AUC for characteristic path length (Lp) were significantly higher. Compared with the control group, patients in robot group showed significant improvement in lower limb motor function, balance function and walking function after intervention, with a significant reduction in the AUC of Cp. Moreover, the improvement of walking function was positively correlated with the changes of AUC of σ and Eg, and negatively correlated with the changes of AUC of Cp. CONCLUSIONS: Small-worldness and network efficiency were significantly reduced after stroke, whereas RAGT decreased characteristic path length and promoted normalization of the whole-brain network, and this change was associated with improvement in walking function. Our findings reveal the mechanism by which RAGT regulates network reorganization and neuroplasticity after stroke.

A new evaluation system for drug-microbiota interactions.

The drug response phenotype is determined by a combination of genetic and environmental factors. The high clinical conversion failure rate of gene-targeted drugs might be attributed to the lack of emphasis on environmental factors and the inherent individual variability in drug response (IVDR). Current evidence suggests that environmental variables, rather than the disease itself, are the primary determinants of both gut microbiota composition and drug metabolism. Additionally, individual differences in gut microbiota create a unique metabolic environment that influences the in vivo processes underlying drug absorption, distribution, metabolism, and excretion (ADME). Here, we discuss how gut microbiota, shaped by both genetic and environmental factors, affects the host's ADME microenvironment within a new evaluation system for drug-microbiota interactions. Furthermore, we propose a new top-down research approach to investigate the intricate nature of drug-microbiota interactions in vivo. This approach utilizes germ-free animal models, providing foundation for the development of a new evaluation system for drug-microbiota interactions.

FF3D: A Rapid and Accurate 3D Fruit Detector for Robotic Harvesting.

This study presents the Fast Fruit 3D Detector (FF3D), a novel framework that contains a 3D neural network for fruit detection and an anisotropic Gaussian-based next-best view estimator. The proposed one-stage 3D detector, which utilizes an end-to-end 3D detection network, shows superior accuracy and robustness compared to traditional 2D methods. The core of the FF3D is a 3D object detection network based on a 3D convolutional neural network (3D CNN) followed by an anisotropic Gaussian-based next-best view estimation module. The innovative architecture combines point cloud feature extraction and object detection tasks, achieving accurate real-time fruit localization. The model is trained on a large-scale 3D fruit dataset and contains data collected from an apple orchard. Additionally, the proposed next-best view estimator improves accuracy and lowers the collision risk for grasping. Thorough assessments on the test set and in a simulated environment validate the efficacy of our FF3D. The experimental results show an AP of 76.3%, an AR of 92.3%, and an average Euclidean distance error of less than 6.2 mm, highlighting the framework's potential to overcome challenges in orchard environments.

Causal associations between platelet count, alcohol consumption, and the risk of liver hepatocellular carcinoma based on a Mendelian randomization study.

Background and aims: Liver hepatocellular carcinoma (LIHC) exhibits a multifactorial etiology, insidious onset, and a significantly low 5-year survival rate. We aimed to evaluate the causal impact of exposure factors (Alzheimer's disease, platelet count, ambidextrousness, cigarettes smoked per day, alcohol consumption, and endocarditis) on the risk of LIHC using a two-sample Mendelian randomization (MR) study. Methods: Independent single nucleotide polymorphisms (SNPs) strongly associated with Alzheimer's disease, platelet count, ambidextrousness, daily cigarette consumption, alcohol intake, and endocarditis were selected as instrumental variables (IVs) from the corresponding genome-wide association studies (GWAS). Genetic summary statistics for LIHC came from a GWAS that included 168 cases and 372,016 controls of European individuals. Multivariable MR analyses were performed to find the causal association between 6 exposure factors and LIHC risk. The inverse-variance weighted (IVW)-MR was employed as the primary analysis, and the MR-Egger regression, LASSO regression, and weighted Median approaches were performed as complementary analyses. Results: Multivariable MR analysis showed causal association between Alzheimer's disease [Odds ratio (OR) = 0.9999, 95% confidence intervals (CI) = 0.9998-0.9999, p = 0.0010], platelet count (OR = 0.9997, 95% CI = 0.9995-0.9999, p = 0.0066), alcohol consumption (OR = 0.9994, 95% CI = 0.9990-0.9999, p = 0.0098) and the LIHC outcome. After IVW-MR, MR-Egger and LASSO tests, the results are still significant. Next, we used different MR Methods to analyze platelet count, alcohol consumption, and Alzheimer's disease separately. Moreover, both funnel plots and MR-Egger intercepts provided compelling evidence to refute the presence of directional pleiotropy in the association between platelet count, alcohol consumption, Alzheimer's disease and the risk of LIHC. The IVW-MR analysis revealed a significant causal association between an elevated platelet count and a reduced risk of LIHC (OR = 0.9996, 95% CI= 0.9995-0.9998, p = 0.0005). Similarly, the analysis of weighted median revealed a negative correlation between platelet count and the risk of LIHC (OR = 0.9995, 95% CI = 0.9993-0.9999; p = 0.0160). Conversely, we observed a positive causal effect of alcohol consumption on the incidence of LIHC (OR = 1.0004, 95% CI = 0.9999-1.0009). However, no significant causal relationship was found between alcohol assumption, Alzheimer's disease, and LIHC susceptibility. Conclusions: A significant causal relationship exists between platelet count, alcohol consumption, Alzheimer's disease, and an increased risk of LIHC. The study presents compelling evidence for a genetically predicted decreased susceptibility to LIHC based on platelet count. The research implies that elevated platelet count may serve as a protective mechanism against LIHC. These findings may inform clinical strategies for LIHC prevention.

Dynamic analysis and optimal control of stochastic information cross-dissemination and variation model with random parametric perturbations.

Information dissemination has a significant impact on social development. This paper considers that there are many stochastic factors in the social system, which will result in the phenomena of information cross-dissemination and variation. The dual-system stochastic susceptible-infectious-mutant-recovered model of information cross-dissemination and variation is derived from this problem. Afterward, the existence of the global positive solution is demonstrated, sufficient conditions for the disappearance of information and its stationary distribution are calculated, and the optimal control strategy for the stochastic model is proposed. The numerical simulation supports the results of the theoretical analysis and is compared to the parameter variation of the deterministic model. The results demonstrate that cross-dissemination of information can result in information variation and diffusion. Meanwhile, white noise has a positive effect on information dissemination, which can be improved by adjusting the perturbation parameters.

Temperature fluctuation in soil alters the nanoplastic sensitivity in wheat.

Despite the wide acknowledgment that plastic pollution and global warming have become serious agricultural concerns, their combined impact on crop growth remains poorly understood. Given the unabated megatrend, a simulated soil warming (SWT, +4 °C) microcosm experiment was carried out to provide a better understanding of the effects of temperature fluctuations on wheat seedlings exposed to nanoplastics (NPs, 1 g L-1 61.71 ± 0.31 nm polystyrene). It was documented that SWT induced oxidative stress in wheat seedlings grown in NPs-contaminated soil, with an 85.56 % increase in root activity, while decreasing plant height, fresh weight, and leaf area by 8.72 %, 47.68 %, and 15.04 % respectively. The SWT also resulted in reduced photosynthetic electron-transfer reaction and Calvin-Benson cycle in NPs-treated plants. Under NPs, SWT stimulated the tricarboxylic acid (TCA) metabolism and bio-oxidation process. The decrease in photosynthesis and the increase in respiration resulted in an 11.94 % decrease in net photosynthetic rate (Pn). These results indicated the complicated interplay between climate change and nanoplastic pollution in crop growth and underscored the potential risk of nanoplastic pollution on crop production in the future climate.

Polystyrene nanoplastics in soil impair drought priming-induced low temperature tolerance in wheat.

Drought priming is known to enhance plant low temperature tolerance, whereas polystyrene nanoplastic contamination exerts detrimental effects on plant growth. This study investigates the less-explored influence of nanoplastic contamination on cold stress tolerance in drought-primed plants. We compared the photosynthetic carbon assimilation, carbohydrate metabolism, reactive oxygen species metabolism, and grain yield between the non-primed and drought-primed wheat grown in both nanoplastic-contaminated and healthy soils. Our results reveal that the beneficial effects of drought priming on photosynthetic carbon assimilation and the efficiency of the "water-water" cycle were compromised in the presence of nanoplastics (nPS). Additionally, nPS exposure disturbed carbohydrate metabolism, which impeded source-to-sink transport of sugar and resulted in reduced grain yield in drought-primed plants under low temperature conditions. These findings unveil the suppression of nPS on drought-primed low-temperature tolerance (DPLT) in wheat plants, suggesting an intricate interplay between the induction of stress tolerance and responses to nPS contamination. The study raises awareness about a potential challenge for future crop production.

cGAS: action in the nucleus.

As a canonical cytoplasmic DNA sensor, cyclic GMP-AMP synthase (cGAS) plays a key role in innate immunity. In recent years, a growing number of studies have shown that cGAS can also be located in the nucleus and plays new functions such as regulating DNA damage repair, nuclear membrane repair, chromosome fusion, DNA replication, angiogenesis and other non-canonical functions. Meanwhile, the mechanisms underlying the nucleo-cytoplasmic transport and the regulation of cGAS activation have been revealed in recent years. Based on the current understanding of the structure, subcellular localization and canonical functions of cGAS, this review focuses on summarizing the mechanisms underlying nucleo-cytoplasmic transport, activity regulation and non-canonical functions of cGAS in the nucleus. We aim to provide insights into exploring the new functions of cGAS in the nucleus and advance its clinical translation.

Poly-(lactic acid) composite films comprising carvacrol and cellulose nanocrystal-zinc oxide with synergistic antibacterial effects.

Herein, carvacrol (CRV) and modified cellulose nanocrystal-zinc oxide (CNC-ZnO) were incorporated into a poly (lactic acid) (PLA) matrix to prepare a PLA-based composite film using a simple solution casting method to achieve antimicrobial effects for application in antimicrobial food packaging. Compared with films obtained from neat PLA, the PLA@CRV20%@CNC-ZnO3% composite film shows better performance in terms of mechanical properties, ultraviolet (UV) blocking, and antimicrobial effects. The PLA composites containing CRV and 3 wt% CNC-ZnO blends exhibit improved tensile strength (21.8 MPa) and elongation at break (403.1 %) as well as excellent UV resistance. In particular, CRV and the CNC-ZnO hybrid endow the obtained PLA composite films with a synergistic antibacterial effect, resulting in good antibacterial properties for microbes, such as Escherichia coli, Staphylococcus aureus and Aspergillus niger. The diameters of the inhibition zone of the PLA@CRV20%@CNC-ZnO3% composite films against E. coli, S. aureus, and A. niger were 4.9, 5.0, and 3.4 cm, respectively. Appling the PLA@CRV20%@CNC-ZnO3% composite film as an antibacterial food packaging material, the storage period for strawberries was considerably extended. This study provides a theoretical basis for developing new organic/inorganic composite antimicrobial film materials from PLA.

Predictors of Cognitive Functions After Stroke Assessed Using the Wechsler Adult Intelligence Scale: A Retrospective Study.

Background: The mechanism(s) of cognitive impairment remains complex, making it difficult to confirm the factors influencing poststroke cognitive impairment (PSCI). Objective: This study quantitatively investigated the degree of influence and interactions of clinical indicators of PSCI. Methods: Information from 270 patients with PSCI and their Wechsler Adult Intelligence Scale (WAIS-RC) scores, totaling 18 indicators, were retrospectively collected. Correlations between the indicators and WAIS scores were calculated. Multiple linear regression model(MLR), genetic algorithm modified Back-Propagation neural network(GA-BP), logistic regression model (LR), XGBoost model (XGB), and structural equation model were used to analyze the degree of influence of factors on the WAIS and their mediating effects. Results: Seven indicators were significantly correlated with the WAIS scores: education, lesion side, aphasia, frontal lobe, temporal lobe, diffuse lesions, and disease course. The MLR showed significant effect of education, lesion side, aphasia, diffuse lesions, and frontal lobe on the WAIS. The GA-BP included five factors: education, aphasia, frontal lobe, temporal lobe, and diffuse lesions. LR predicted that the lesion side contributed more to mild cognitive impairment, while education, lesion side, aphasia, and course of the disease contributed more to severe cognitive impairment. XGB showed that education, side of the lesion, aphasia, and diffuse lesions contributed the most to PSCI. Aphasia plays a significant mediating role in patients with severe PSCI. Conclusions: Education, lesion side, aphasia, frontal lobe, and diffuse lesions significantly affected PSCI. Aphasia is a mediating variable between clinical information and the WAIS in patients with severe PSCI.

Protective Effect of the Polyphenol Ligustroside on Colitis Induced with Dextran Sulfate Sodium in Mice.

Dietary polyphenols are reported to alleviate colitis by interacting with gut microbiota which plays an important role in maintaining the integrity of the intestinal barrier. As a type of dietary polyphenol, whether ligustroside (Lig) could alleviate colitis has not been explored yet. Here, we aimed to determine if supplementation of ligustroside could improve colitis. We explored the influence of ligustroside intake with different dosages on colitis induced with dextran sulfate sodium (DSS). Compared to the DSS group, supplementation of ligustroside could reduce body weight (BW) loss, decrease disease activity indices (DAI), and relieve colon damage in colitis mice. Furthermore, ligustroside intake with 2 mg/kg could decrease proinflammatory cytokine concentrations in serum and increase immunoglobulin content and antioxidant enzymes in colon tissue. In addition, supplementation of ligustroside (2 mg/kg) could reduce mucus secretion and prevent cell apoptosis. Also, changes were revealed in the bacterial community composition, microbiota functional profiles, and intestinal metabolite composition following ligustroside supplementation with 2 mg/kg using 16S rRNA sequencing and non-targeted lipidomics analysis. In conclusion, the results showed that ligustroside was very effective in preventing colitis through reduction in inflammation and the enhancement of the intestinal barrier. Furthermore, supplementation with ligustroside altered the gut microbiota and lipid composition of colitis mice.

"Back to the future" projections for COVID-19 surges.

We argue that information from countries who had earlier COVID-19 surges can be used to inform another country's current model, then generating what we call back-to-the-future (BTF) projections. We show that these projections can be used to accurately predict future COVID-19 surges prior to an inflection point of the daily infection curve. We show, across 12 different countries from all populated continents around the world, that our method can often predict future surges in scenarios where the traditional approaches would always predict no future surges. However, as expected, BTF projections cannot accurately predict a surge due to the emergence of a new variant. To generate BTF projections, we make use of a matching scheme for asynchronous time series combined with a response coaching SIR model.

The effects of rTMS on motor recovery after stroke: a systematic review of fMRI studies.

Repetitive transcranial magnetic stimulation (rTMS) has been widely used in motor rehabilitation after stroke, and functional magnetic resonance imaging (fMRI) has been used to investigate the neural mechanisms of motor recovery during stroke therapy. However, there is no review on the mechanism of rTMS intervention for motor recovery after stroke based on fMRI explicitly. We aim to reveal and summarize the neural mechanism of the effects of rTMS on motor function after stroke as measured by fMRI. We carefully performed a literature search using PubMed, EMBASE, Web of Science, and Cochrane Library databases from their respective inceptions to November 2022 to identify any relevant randomized controlled trials. Researchers independently screened the literature, extracted data, and qualitatively described the included studies. Eleven studies with a total of 420 poststroke patients were finally included in this systematic review. A total of 338 of those participants received fMRI examinations before and after rTMS intervention. Five studies reported the effects of rTMS on activation of brain regions, and four studies reported results related to brain functional connectivity (FC). Additionally, five studies analyzed the correlation between fMRI and motor evaluation. The neural mechanism of rTMS in improving motor function after stroke may be the activation and FCs of motor-related brain areas, including enhancement of the activation of motor-related brain areas in the affected hemisphere, inhibition of the activation of motor-related brain areas in the unaffected hemisphere, and changing the FCs of intra-hemispheric and inter-hemispheric motor networks.

Lactobacillus and Allobaculum mediates the improvement of vascular endothelial dysfunction during hypertension with TaohongSiwu decoction combined with Dubosiella newyorkensis.

Background: Previous study confirmed that both TaohongSiwu decoction (THSWD) and Dubosiella newyorkensis improved hypertension-induced endothelial dysfunction. However, the mechanism of THSWD combined with Dubosiella newyorkensis remains unclear. Purpos: e: We aimed to investigate the microecological mechanism underlying the THSWD combined with Dubosiella newyorkensis for the prevention of hypertensive vascular endothelial dysfunction. Methods: Eight percent high-salt diet was applied to induce hypertension in a mouse model for 4 weeks. THSWD, Dubosiella newyorkensis and THSWD combined with Dubosiella newyorkensis were used to intervene in the model mice to observe the changes of systolic blood pressure (SBP), body weight, blood routine, endothelial function, gut contents microbiota and bile acid metabolites. Results: Results revealed that THSWD combined with Dubosiella newyorkensis significantly restored blood pressure and regulated body weight, and markedly downregulating serum and vascular levels of endothelin-1 (ET-1), thrombin regulatory protein (TM), vascular hemophilia factor (vWF) and vascular endothelial growth factor (VEGF), and upregulating nitric oxide (NO) levels compared with the model group. Notably, It altered the diversity and community structure of gut contents microbiota in mice. Lactobacillus and Allobaculum was enormously up-regulated at the genus level. Serum bile acid differential metabolites cholic acid and chenodeoxycholic acid were markedly altered. Futhermore, there was a close relationship between Lactobacillus, Allobaculum and endothelial function indexes in mice. Conclusion: Lactobacillus and Allobaculum play important roles in the prevention of vascular endothelial dysfunction in hypertension during the THSWD combined with Dubosiella newyorkensis.

Gender Identity Stigma in Transgender Women Is Higher After Gender-Affirming Vaginoplasty.

Gender affirmation may reduce stigma and gender-based discrimination that drive increased behaviors that can lead to HIV in transgender women (TW). For many TW, vaginoplasty is gender affirming, yet has not been previously evaluated with regard to likelihood of HIV. This pilot study of TW aimed to evaluate the influence of gender-affirming vaginoplasty on stigma and the drivers of HIV acquisition. Adult TW without HIV were recruited. Interviewer-administered surveys were used to assess demographics, gender identity stigma, psychosocial factors, importance of and satisfaction with gender affirmation, and behaviors that increase the likelihood of HIV in TW who had either undergone gender-affirming vaginoplasty (TWWV) or who had not (TWWOV). Statistical analysis was conducted using descriptive statistics, Fisher's exact tests, and Wilcoxon rank-sum tests. Thirty TW without HIV (19-83 years old) participated (TWWV = 10; TWWOV = 20). The majority identified with ethnic minority groups (n = 21, 70%) and on gender-affirming hormone therapy (n = 25, 83%). Gender identity stigma (38.0; 32.15, p = .03) and social oppression (53.6; 39.4, p = .05) scores were significantly higher among TWWV compared with TWWOV. Satisfaction with body (3.10; 1.95, p = .01), appearance (3.10; 2.10, p = .02), and femininity (3.40; 2.25, p = .001) were higher among TWWV than TWWOV. Present (n = 8, 27%) and past (n = 16, 53%) survival sex work, multiple sex partners (n = 16, 53%), and receptive condomless anal intercourse (n = 10, 33%) were reported but did not vary significantly between groups. Behaviors that may lead to HIV acquisition and their underlying drivers, including gender identity stigma, are present after gender-affirming vaginoplasty. As this procedure continues to increase among TW, interventions to mitigate chances of HIV acquisition are critically needed in this population.

Integrating Chlorophyll a Fluorescence and Enzymatic Profiling to Reveal the Wheat Responses to Nano-ZnO Stress.

It has been shown that increased concentrations of zinc oxide nanoparticles (nano-ZnO) in the soil are harmful to plant growth. However, the sensitivity of different wheat cultivars to nano-ZnO stress is still unclear. To detect the physiological response process of wheat varieties with different tolerance to nano-ZnO stress, four wheat cultivars (viz., cv. TS1, ZM18, JM22, and LM6) with different responses to nano-ZnO stress were selected, depending on previous nano-ZnO stress trials with 120 wheat cultivars in China. The results found that nano-ZnO exposure reduced chlorophyll concentrations and photosynthetic electron transport efficiency, along with the depressed carbohydrate metabolism enzyme activities, and limited plant growth. Meanwhile, the genotypic variation in photosynthetic carbon assimilation under nano-ZnO stress was found in wheat plants. Wheat cv. JM22 and LM6 possessed relatively lower Zn concentrations and higher leaf nitrogen per area, less reductions in their net photosynthetic rate, a maximum quantum yield of the PS II (Fv/Fm), electron transport flux per cross-section (ETo/CSm), trapped energy flux per cross-section (TRo/CSm), and total soluble sugar and sucrose concentrations under nano-ZnO stress, showing a better tolerance to nano-ZnO stress than wheat cv. TS1 and ZM18. In addition, the chlorophyll a fluorescence parameters Fv/Fm, ETo/CSm, and TRo/CSm could be used to rapidly screen wheat varieties resistant to nano-ZnO stress. The results here provide a new approach for solving the issues of crop yield decline in regions polluted by heavy metal nanoparticles and promoting the sustainable utilization of farmland with heavy metal pollution.

Different doses of intermittent theta burst stimulation for upper limb motor dysfunction after stroke: a study protocol for a randomized controlled trial.

Background: Upper limb motor recovery is one of the important goals of stroke rehabilitation. Intermittent theta burst stimulation (iTBS), a new type of repetitive transcranial magnetic stimulation (rTMS), is considered a potential therapy. However, there is still no consensus on the efficacy of iTBS for upper limb motor dysfunction after stroke. Stimulus dose may be an important factor affecting the efficacy of iTBS. Therefore, we aim to investigate and compare the effects and neural mechanisms of three doses of iTBS on upper limb motor recovery in stroke patients, and our hypothesis is that the higher the dose of iTBS, the greater the improvement in upper limb motor function. Methods: This prospective, randomized, controlled trial will recruit 56 stroke patients with upper limb motor dysfunction. All participants will be randomized in a 1:1:1:1 ratio to receive 21 sessions of 600 pulses active iTBS, 1,200 pulses active iTBS, 1,800 pulses active iTBS, or 1,800 pulses sham iTBS in addition to conventional rehabilitation training. The primary outcome is the Fugl-Meyer Assessment of the Upper Extremity (FMA-UE) score from baseline to end of intervention, and the secondary outcomes are the Wolf Motor Function Test (WMFT), Grip Strength (GS), Modified Barthel Index (MBI), and Stroke Impact Scale (SIS). The FMA-UE, MBI, and SIS are assessed pre-treatment, post-treatment, and at the 3-weeks follow-up. The WMFT, GS, and resting-state functional magnetic resonance imaging (rs-fMRI) data will be obtained pre- and post-treatment. Discussion: The iTBS intervention in this study protocol is expected to be a potential method to promote upper limb motor recovery after stroke, and the results may provide supportive evidence for the optimal dose of iTBS intervention.

Integrated Optimal Control for Electrolyte Temperature With Temporal Causal Network and Reinforcement Learning.

The electrowinning process is a critical operation in nonferrous hydrometallurgy and consumes large quantities of power consumption. Current efficiency is an important process index related to power consumption, and it is vital to operate the electrolyte temperature close to the optimum point to ensure high current efficiency. However, the optimal control of electrolyte temperature faces the following challenges. First, the temporal causal relationship between process variables and current efficiency makes it difficult to estimate the current efficiency accurately and set the optimal electrolyte temperature. Second, the substantial fluctuation of influencing variables of electrolyte temperature leads to difficulty in maintaining the electrolyte temperature close to the optimum point. Third, due to the complex mechanism, building a dynamic electrowinning process model is intractable. Hence, it is a problem of index optimal control in the multivariable fluctuation scenario without process modeling. To get around this issue, an integrated optimal control method based on temporal causal network and reinforcement learning (RL) is proposed. First, the working conditions are divided and the temporal causal network is used to estimate current efficiency accurately to solve the optimal electrolyte temperature under multiple working conditions. Then, an RL controller is established under each working condition, and the optimal electrolyte temperature is placed into the controller's reward function to assist in control strategy learning. An experiment case study of the zinc electrowinning process is provided to verify the effectiveness of the proposed method and to show that it can stabilize the electrolyte temperature within the optimal range without modeling.