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BackgroundLarge language models (LLMs) are advanced artificial neural networks trained on extensive datasets to accurately understand and generate natural language. While they have received much attention and demonstrated potential in digital health, their application in mental health, particularly in clinical settings, has generated considerable debate. ObjectiveThis systematic review aims to critically assess the use of LLMs in mental health, specifically focusing on their applicability and efficacy in early screening, digital interventions, and clinical settings. By systematically collating and assessing the evidence from current studies, our work analyzes models, methodologies, data sources, and outcomes, thereby highlighting the potential of LLMs in mental health, the challenges they present, and the prospects for their clinical use. MethodsAdhering to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, this review searched 5 open-access databases: MEDLINE (accessed by PubMed), IEEE Xplore, Scopus, JMIR, and ACM Digital Library. Keywords used were (mental health OR mental illness OR mental disorder OR psychiatry) AND (large language models). This study included articles published between January 1, 2017, and April 30, 2024, and excluded articles published in languages other than English. ResultsIn total, 40 articles were evaluated, including 15 (38%) articles on mental health conditions and suicidal ideation detection through text analysis, 7 (18%) on the use of LLMs as mental health conversational agents, and 18 (45%) on other applications and evaluations of LLMs in mental health. LLMs show good effectiveness in detecting mental health issues and providing accessible, destigmatized eHealth services. However, assessments also indicate that the current risks associated with clinical use might surpass their benefits. These risks include inconsistencies in generated text; the production of hallucinations; and the absence of a comprehensive, benchmarked ethical framework. ConclusionsThis systematic review examines the clinical applications of LLMs in mental health, highlighting their potential and inherent risks. The study identifies several issues: the lack of multilingual datasets annotated by experts, concerns regarding the accuracy and reliability of generated content, challenges in interpretability due to the “black box” nature of LLMs, and ongoing ethical dilemmas. These ethical concerns include the absence of a clear, benchmarked ethical framework; data privacy issues; and the potential for overreliance on LLMs by both physicians and patients, which could compromise traditional medical practices. As a result, LLMs should not be considered substitutes for professional mental health services. However, the rapid development of LLMs underscores their potential as valuable clinical aids, emphasizing the need for continued research and development in this area. Trial RegistrationPROSPERO CRD42024508617; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=508617

Abstract Background First-line chemotherapy combined with bevacizumab is one of the standard treatment modes for patients with advanced non-small cell lung cancer (NSCLC). Thoracic radiotherapy (TRT) can provide significant local control and survival benefits to patients during the treatment of advanced NSCLC. However, the safety of adding TRT has always been controversial, especially because of the occurrence of radiation pneumonia (RP) during bevacizumab treatment. Therefore, in this study, we used an expanded sample size to evaluate the incidence of RP when using bevacizumab in combination with TRT. Patients and methods Using an institutional query system, all medical records of patients with NSCLC who received TRT during first-line chemotherapy combined with bevacizumab from 2017 to 2020 at Shandong Cancer Hospital and Institute were reviewed. RP was diagnosed via computed tomography and was classified according to the RTOG toxicity scoring system. The risk factors for RP were identified using univariate and multivariate analyses. The Kaplan–Meier method was used to calculate progression-free survival (PFS) and overall survival (OS). Results Ultimately, 119 patients were included. Thirty-eight (31.9%) patients developed Grade ≥ 2 RP, of whom 27 (68.1%) had Grade 2 RP and 11 (9.2%) had Grade 3 RP. No patients developed Grade 4 or 5 RP. The median time for RP occurrence was 2.7 months (range 1.2–5.4 months). In univariate analysis, male, age, KPS score, V20 > 16.9%, V5 > 33.6%, PTV (planning target volume)-dose > 57.2 Gy, and PTV-volume > 183.85 cm3 were correlated with the occurrence of RP. In multivariate analysis, male, V20 > 16.9%, and PTV-volume > 183.85 cm3 were identified as independent predictors of RP occurrence. The mPFS of all patients was 14.27 (95% CI, 13.1–16.1) months. The one-year and two-year PFS rates were 64.9% and 20.1%, respectively. The mOS of all patients was 37.09 (95% CI, 33.8–42.0) months. The one-year survival rate of all patients was 95%, and the two-year survival rate was 71.4%. Conclusions The incidence of Grade ≥ 2 RP in NSCLC patients who received both bevacizumab and TRT was 31.9%. Restricting factors such as V20 and PTV will help reduce the risk of RP in these patients. For patients who receive both bevacizumab and TRT, caution should be exercised when increasing TRT, and treatment strategies should be optimized to reduce the incidence of RP.

Abstract Conventional endoscopy is widely used in the diagnosis of early gastric cancers (EGCs), but the graphical features were loosely defined and dependent on endoscopists’ experience. We aim to establish a more accurate predictive model for infiltration depth of early gastric cancer including a standardized colorimetric system, which demonstrates promising clinical implication. A retrospective study of 718 EGC cases was performed. Clinical and pathological characteristics were included, and Commission Internationale de l’Eclariage (CIE) standard colorimetric system was used to evaluate the chromaticity of lesions. The predicting models were established in the derivation set using multivariate backward stepwise logistic regression, decision tree model, and random forest model. Logistic regression shows location, macroscopic type, length, marked margin elevation, WLI color difference and histological type are factors significantly independently associated with infiltration depth. In the decision tree model, margin elevation, lesion located in the lower 1/3 part, WLI a*color value, b*color value, and abnormal thickness in enhanced CT were selected, which achieved an AUROC of 0.810. A random forest model was established presenting the importance of each feature with an accuracy of 0.80, and an AUROC of 0.844. Quantified color metrics can improve the diagnostic precision in the invasion depth of EGC. We have developed a nomogram model using logistic regression and machine learning algorithms were also explored, which turned out to be helpful in decision-making progress.

Ti–Mo–Zr alloys have attracted increasing interest for biomedical applications, due to their outstanding properties such as low elastic modulus. To improve the bioactivity of alloys, this study utilized the anodic oxidation method to fabricate porous micro/nano structures on the surface of a series of Ti–Mo–Zr alloys, including the Ti–12Mo-AO, Ti–10Zr-AO, and Ti–12Mo–10Zr-AO groups. The morphology, composition, phase, microhardness, roughness, wettability, adhesion strength, corrosion resistance, bioactivity, and biocompatibility of each group were systematically investigated. The formation mechanism of surfaces was discussed from the perspective of thermodynamics. Our results demonstrated that, Ti–12Mo-AO showed the structure of single-layer regularly arranged nanotubes, while Ti–10Zr-AO and Ti–12Mo–10Zr-AO exhibited a double-layer porous structure with a nano-filamentous upper layer and a densely arranged nanotube lower layer. With low crystallinity, these surfaces showed an amorphous structure and were composed of the oxides of corresponding matrix element. After anodizing, the microhardness and wettability of surfaces increased, while their corrosion resistance decreased. Compared with Ti–12Mo-AO, Ti–10Zr-AO and Ti–12Mo–10Zr-AO possessed a higher degree of roughness, better wettability, stronger interface bonding, and higher apatite forming ability. Furthermore, the biocompatibility of Ti–12Mo–10Zr-AO was superior to that of the other groups. Taken together, our results revealed that, under the same anodic oxidation condition, Ti–Mo–Zr alloys formed different porous micro/nano structures on the surface. Particularly, due to its favorable properties, Ti–12Mo–10Zr-AO is very attractive for future biomedical application.

Abstract Interleukin 12 (IL-12) is a potent immunostimulatory cytokine mainly produced by antigen-presenting cells (e.g., dendritic cells, macrophages) and plays an important role in innate and adaptive immunity against cancers. Therapies that can synergistically modulate innate immunity and stimulate adaptive anti-tumor responses are of great interest for cancer immunotherapy. Here we investigated the lipid nanoparticle-encapsulated self-replicating RNA (srRNA) encoding IL-12 (referred to as JCXH-211) for the treatment of cancers. Both local (intratumoral) and systemic (intravenous) administration of JCXH-211 in tumor-bearing mice induced a high-level expression of IL-12 in tumor tissues, leading to modulation of tumor microenvironment and systemic activation of antitumor immunity. Particularly, JCXH-211 can inhibit the tumor-infiltration of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs). When combined with anti-PD1 antibody, it was able to enhance the recruitment of T cells and NK cells into tumors. In multiple mouse solid tumor models, intravenous injection of JCXH-211 not only eradicated large preestablished tumors, but also induced protective immune memory that prevented the growth of rechallenged tumors. Finally, intravenous injection of JCXH-211 did not cause noticeable systemic toxicity in tumor-bearing mice and non-human primates. Thus, our study demonstrated the feasibility of intravenous administration of JCXH-211 for the treatment of advanced cancers.

Angelica sinensis is a long-standing medicine used by Chinese medical practitioners and well-known for its blood-tonic and blood-activating effects. Ferulic acid, ligustilide, and eugenol in Angelica sinensis activate the blood circulation; however, the material basis of their blood-tonic effects needs to be further investigated. In this study, five homogeneous Angelica sinensis polysaccharides were isolated, and their sugar content, molecular weight, monosaccharide composition, and infrared characteristics determined. Acetylphenylhydrazine (APH) and cyclophosphamide (CTX) were used as inducers to establish a blood deficiency model in mice, and organ indices, haematological and biochemical parameters were measured in mice. Results of in vivo hematopoietic activity showed that Angelica sinensis polysaccharide (APS) could elevate erythropoietin (EPO), granulocyte colony-stimulating factor (G-CSF), and interleukin-3 (IL-3) serum levels, reduce tumor necrosis factor-α (TNF-α) level in mice, and promote hematopoiesis in the body by regulating cytokine levels. Biological potency test results of the in vitro blood supplementation indicated strongest tonic activity for APS-H2O, and APS-0.4 has the weakest haemopoietic activity. The structures of APS-H2O and APS-0.4 were characterized, and the results showed that APS-H2O is an arabinogalactan glycan with a main chain consisting of α-1,3,5-Ara(f), α-1,5- Ara(f), β-1,4-Gal(p), and β-1,4-Gal(p)A, and two branched chains of β-t-Gal(p) and α-t-Glc(p) connected to each other in a (1→3) linkage to α-1,3,5-Ara(f) on the main chain. APS-0.4 is an acidic polysaccharide with galacturonic acid as the main chain, consisting of α-1,4-GalA, α-1,2-GalA, α-1,4-Gal, and β-1,4-Rha. In conclusion, APS-H2O can be used as a potential drug for blood replenishment in patients with blood deficiency, providing a basis for APS application in clinical treatment and health foods, as well as research and development of new polysaccharide-based drugs.

Ophthalmic and many systemic diseases may damage the eyes, resulting in changes in the composition and content of biomolecules in ocular biofluids such as aqueous humor and tear. Therefore, the biomolecules in biofluids are potential biomarkers to reveal pathological processes and diagnose diseases. Raman spectroscopy is a non-invasive, label-free, and cost-effective technique to provide chemical bond information of biomolecules and shows great potential in the detection of ocular biofluids. This review demonstrates the applications of Raman spectroscopy technology in detecting biochemical components in aqueous humor and tear, then summarizes the current problems encountered for clinical applications of Raman spectroscopy and looks forward to possible approaches to overcome technical bottlenecks. This work may provide a reference for wider applications of Raman spectroscopy in biofluid detection and inspire new ideas for the diagnosis of diseases using ocular biofluids.

Introduction: Cadonilimab (AK104) is an innovative human programmed cell death-1 (PD-1)/cytotoxic T lymphocyte antigen-4 (CTLA-4) bispecific antibody. Compared with the combination therapy of PD-1 and CTLA-4 blockers, less cellular toxicity of cadonilimab was significantly manifested. As one of the characteristic adverse effects of cadonilimab, infusion-related reactions (IRRs) represent fever, chills, rash, decreased blood pressure, and other symptoms. Case Presentation: Here, we documented seven cases of IRRs after the administration of cadonilimab. The symptoms of IRRs were relieved after the discontinuation of cadonilimab and the administration of diphenhydramine, dexamethasone, and cimetidine. Notably, 3 patients were able to tolerate the subsequent cadonilimab therapy under the pretreatment. Conclusion: In this study, we discovered that cadonilimab-related IRRs might be lessened or prevented by administering medication and the proper pretreatment and lowering the infusion rate.

This research develops a simulation model, aiming to study the breakdown process of the tri-post insulator when exposed to electric field and mechanical loadings. The insulator is subjected to external forces of varying magnitudes and directions, along with an applied 1100 kV AC voltage. Results show that the breakdown process is driven by the electrostatic energy density (Wele) under an AC voltage. As the length of the breakdown channel increases, Wele, also rises, thereby accelerating the extension of the breakdown channel. After applying a straight tension along the insulator post, the tensile stress and the corresponding strain energy density become concentrated near the tips of the lateral branches, thus promoting their expansion and even causing a transverse fracture under the condition of 100 kN. In the case of a small straight compression below 25 kN, the breakdown process can be restrained. But when it comes to 75 kN, the breakdown process is promoted again, and a shear fracture can be caused above 100 kN. Under diagonal tensile or compressive stress, the breakdown channel deviates towards the applied force due to asymmetric strain energy density distribution. The objective of this research is to improve the comprehension and forecasting of breakdown in dielectric materials.

Purposes Users’ abnormal power consumption behaviors need to be distinguished quickly and accurately. Methods An abnormal state detection model is proposed on the basis of smart meter data and data decomposition and random matrix theory, realizing the identification of users’ abnormal power consumption behaviors. The variational mode decomposition (VMD) algorithm is used to eliminate the noise of power data and the influence of noise data. The Random Matrix Theory (RMT) is combined with the Auto-Regressive Moving Average Model (ARMA) to improve the applicability of RMT to time series and realize the judgment of abnormal state of electricity consumption. Findings Taking the actual power consumption data of a certain area as an example, the method conveniency and efficiency for the case of large data samples and non-Gaussian distribution have been verified, which provides a new direction for the identification of abnormal power consumption behavior.

In this article, a new kind of neural network model named multi-scale convolutional echo state network (MCESN) is proposed for solar irradiance prediction, which integrates the strong feature extraction capability of convolutional neural network (CNN) and the fast yet efficient prediction ability of echo state network (ESN). Firstly, the feature information at different time scales of solar irradiance (one dimensional series) data are extracted and selected by multi-scale CNN (MCNN) in the pre-training stage. Then, the trained features extracted above are concatenated and passed to ESN module as the input signal, which can be further encoded into high-dimensional state space; Meanwhile, the target solar irradiance value is fitted and predicted by ESN in the prediction phase. Finally, the effectiveness of MCESN is evaluated by hourly solar irradiance prediction. In experiment, RMSE, MAE, MAPE and R are chosen as four metrics to evaluate the performance of the proposed model. Simulation results demonstrate that the proposed MCESN perform better than classical ESN, MCNN, backpropagation (BP) random forest (RF), long short time memory (LSTM) and deep ESN (DESN) algorithms.

Abstract To investigate the occurrence and 90-day mortality of cancer patients following unplanned admission to the intensive care unit (ICU), as well as to develop a risk prediction model for their 90-day prognosis. We prospectively analyzed data from cancer patients who were admitted to the ICU without prior planning within the past 7 days, specifically between May 12, 2021, and July 12, 2021. The patients were grouped based on their 90-day survival status, and the aim was to identify the risk factors influencing their survival status. A total of 1488 cases were included in the study, with an average age of 63.2 ± 12.4 years. The most common reason for ICU admission was sepsis (n = 940, 63.2%). During their ICU stay, 29.7% of patients required vasoactive drug support (n = 442), 39.8% needed invasive mechanical ventilation support (n = 592), and 82 patients (5.5%) received renal replacement therapy. We conducted a multivariate COX proportional hazards model analysis, which revealed that BMI and a history of hypertension were protective factors. On the other hand, antitumor treatment within the 3 months prior to admission, transfer from the emergency department, general ward, or external hospital, high APACHE score, diagnosis of shock and respiratory failure, receiving invasive ventilation, and experiencing acute kidney injury (AKI) were identified as risk factors for poor prognosis within 90 days after ICU admission. The average length of stay in the ICU was 4 days, while the hospital stay duration was 18 days. A total of 415 patients died within 90 days after ICU admission, resulting in a mortality rate of 27.9%. We selected 8 indicators to construct the predictive model, which demonstrated good discrimination and calibration. The prognosis of cancer patients who are unplanned transferred to the ICU is generally poor. Assessing the risk factors and developing a risk prediction model for these patients can play a significant role in evaluating their prognosis.

Due to the difficulty in distinguishing transparent and white foreign fibers from seed cotton in RGB images and in order to improve the recognition ability of deep learning (DL) algorithms for white, transparent, and multi-class mixed foreign fibers with different sizes in seed cotton, this paper proposes a method of combining hyperspectral imaging technology with a multi-module joint hierarchical residue network (MJHResNet). Firstly, a series of preprocessing methods are performed on the hyperspectral image (HSI) to reduce the interference of noise. Secondly, a double-hierarchical residual (DHR) structure is designed, which can not only obtain multi-scale information, but also avoid gradient vanishing to some extent. After that, a squeeze-and-excitation network (SENet) is integrated to reduce redundant information, improve the expression of model features, and improve the accuracy of foreign fiber identification in seed cotton. Finally, by analyzing the experimental results with advanced classifiers, this method has significant advantages. The average accuracy is 98.71% and the overall accuracy is 99.28%. This method has great potential for application in the field of foreign fiber identification in seed cotton.

Stress annealing is utilized for enhancing the magnetic softness of Fe83–xCoxB10Si3C3P1 (x = 0–16) amorphous alloys with saturation polarization up to 1.75 T. All of the stress-annealed alloys exhibit improved soft-magnetic properties, including low coercivity of 1.8–2.2 A/m, low core loss of 0.09–0.11 W/kg at 1.0 T and 50 Hz, and high permeability of 27,000–33,200 at 5 A/m and 1 kHz. Stress annealing induces longitudinal magnetic anisotropy and facilitates the annihilation of free volume, leading to pinning-free domain wall motion, and thus the enhanced magnetic softness. The induced magnetic anisotropy relates to the constrained elastic elongation introduced by stress annealing.

Abstract As one of the common complications of radiotherapy, radiation pneumonia (RP) limits the prognosis of patients. Therefore, better identifying the high-risk factors that lead to RP is essential to effectively prevent its occurrence. However, as lung cancer treatment modalities are being replaced and the era of immunotherapy has arrived, literature that reviews the parameters and mode of radiotherapy, chemotherapy drugs, targeted drugs and current hot immune checkpoint inhibitors related to RP is lacking. This paper summarizes the risk factors for radiation pneumonia by retrieving and analysing previously published literature and the results of large clinical trials. The literature primarily included retrospective analyses, including clinical trials in different periods and a part of the literature review. A systematic literature search of Embase, PubMed, Web of Science, and Clinicaltrials.gov was performed for relevant publications up to 6 Dec. 2022. Search keywords include, but are not limited to, “radiation pneumonia”, “pneumonia”, “risk factors”, “immunotherapy”, etc. The factors related to RP in this paper include physical parameters of radiotherapy, including V5, V20, and MLD; chemoradiotherapy mode and chemotherapy drugs, including paclitaxel and gemcitabine; EGFR-TKI; ALK inhibitors; antiangiogenic drugs; immune drugs and the underlying disease of the patient. We also introduce the possible mechanism of RP. In the future, we hope that this article not only sounds the alarm for clinicians but also helps to identify a method that can effectively intervene and reduce the occurrence of RP, significantly improve the quality of life and prognosis of patients, and more effectively improve the therapeutic effect of radiation therapy.

Titanium (Ti) alloys have been widely used as bone implants, but challenges such as the stress shielding effect still compromise long-term clinical successes. To improve the mechanical properties of Ti, non-toxic alloying elements zirconium (Zr) and molybdenum (Mo) were added either alone or in combination to produce Ti–Mo–Zr alloys. The influence of Zr or Mo addition on the alloy properties, such as the microstructure and the corrosion resistance, were investigated. The cytocompatibility and osteointegration of prepared alloys were evaluated to determine the potential for bone repair. The results showed that Ti–10Zr displayed an acicular α′ phase, while Ti–12Mo and Ti–12Mo–10Zr comprised a metastable β phase. Due to the solid solution and phase precipitation strengthening effect of Zr and Mo elements, the prepared alloys showed higher microhardness and compressive yield strength when compared with commercially pure Ti (CP–Ti). Ti–12Mo–10Zr possessed the lowest Young's modulus, while CP-Ti and Ti–10Zr showed a comparable Young's modulus. The corrosion resistance was in the order of Ti–12Mo–10Zr > Ti–12Mo > CP-Ti > Ti–10Zr. Notably, all alloys showed good cytocompatibility and osteointegration, which were similar to those of CP-Ti. Taken together, due to excellent material and biological performance, Ti–12Mo–10Zr presents a promising material for bone repair.

Background Imbalances in bile acid (BA) synthesis and metabolism are involved in the onset of diabetes and depression in humans and rodents. However, the role of BAs and the farnesoid X receptor (FXR)/fibroblast growth factor (FGF) 15 signaling pathway in the development of diabetes and depression is still largely unknown. Therefore, we investigated the potential molecular mechanisms of BAs that may be associated with glucolipid metabolism disorders in diabetic mice subjected to chronic stress. Methods The type 2 diabetes mellitus (T2DM) mouse model was induced by feeding mice a high-fat diet and administering an intraperitoneal injection of streptozotocin (STZ). The chronic unpredictable mild stress (CUMS) procedure was performed by introducing a series of mild stressors. Forty mice were randomly divided into the regular chow feeding group and the high-fat diet feeding group. After two weeks of feeding, the mice were randomly divided into four groups: the Control group, CUMS group, T2DM group, and T2DM+CUMS group. The T2DM group and T2DM+CUMS group received an intraperitoneal injection of STZ to induce the T2DM model. The CUMS and T2DM+CUMS groups were exposed to CUMS to induce depressive-like phenotypes. Blood and tissue samples were obtained for pertinent analysis and detection. Results Compared with the T2DM mice, T2DM+CUMS mice had higher blood glucose and lipid levels, insulin resistance, inflammation of the liver and pancreas, impaired liver function, and increased total bile acids. These changes were accompanied by attenuated FXR signaling. Chronic stress was found to attenuate FXR expression and its downstream target, FGF15, in the ileum when compared with the T2DM group. Conclusion FXR may play a role in the diabetic disorder of glucolipid metabolism when aggravated by chronic stress. FXR and its downstream target, FGF15, may be therapeutic targets for treating comorbid T2DM and depression.

To reduce the working resistance and soil adhesion in the process of soil tillage or engineering construction, this paper takes the bulldozing plate as the research object and takes the cutting angle and the directrix form of the Soil engaging surface as the design variables and designs 15 groups of bulldozing plate models for the soil bin experiments. The test results show that compared with the conventional circular bulldozing plate, the horizontal working resistance of the bionic bulldozing plate with 50 degrees, 55 degrees, and 60 degrees cutting angles is reduced by 44.46 %, 39.74 %, and 10.32 %, respectively. 55 degrees cutting angle bionic bulldozing plate to reduce adhesion and front soil fluctuations best; each performance index of the parabolic bulldozing plate is relatively balanced and stable. An entropy-weighted grey relational analysis method is proposed to quantitatively analyze and sort the comprehensive performance of bulldozing plates. Then, the influence law between the horizontal resistance, vertical resistance, and the total resistance of the bulldozer during stable operation and soil adhesion and soil fluctuation state is studied. The hypothesis of the internal influence relationship between the intrinsic micro-geometric characteristics and the macroscopic comprehensive mechanical properties of the soil engaging surface of the bulldozing plate is proposed, and it is pointed out that the essence of the change of the cutting angle and the directrix form of the soil engaging part is the change of the directrix curvature of the soil engaging surface and the soil. It is proposed to optimize and edit the directrix curvature trend of the soil engaging surface and then reverse the directrix equation so as to realize the optimal design of the soil engaging surface. The research in this paper provides a reference for the design and optimization of reducing adhesion and resistance of soil engaging components.

Innovation and entrepreneurship are being widely promoted and made popular as new job strategies for university graduates to relieve the pressure of employment. Colleges and universities in ethnically diverse places are significant components of higher education institutions in our nation and offer special advantages for instructing in innovation and entrepreneurship due to their national cultures. As a result, educating university students from many ethnic backgrounds about innovation and entrepreneurship has become crucial and integral to our nation's innovation and entrepreneurship strategy. This paper proposes strategies to enhance the innovation and entrepreneurship capacity of university graduate students in ethnic minority areas combing with the research and analysis of the innovation and entrepreneurship capacity of university graduate students majoring in food science and engineering in the college of agriculture, Yanbian university. These strategies includ: Improving the comprehensive quality and awareness of innovation and entrepreneurship capacity of university graduate students in ethnically diverse areas, strengthening teaching staff of innovation and entrepreneurship in minority areas and also completing the curriculum system of innovation and entrepreneurship education as well as socially responsible support policies.

The determination of the aflatoxin B1 (AFB1) content has received widespread attention in the context of food safety, which is a global public health issue. Accordingly, a label-free and turn-on fluorescent AFB1 determination method is developed herein with an ss-DNA aptamer as the recognition element, 4, 4-(1E,1E)-2, 2-(anthracene-9, 10-diyl) bis(ethene-2, 1-diyl) bis(N, N, N-trimethylbenzenaminium iodide) (DSAI) as the aggregation-induced emission (AIE) fluorescent probe, and single-walled carbon nanohorns (SWCNHs) as the selective part with a fluorescence quenching effect. In the presence of AFB1, the AFB1-specific aptamer undergoes a structural transformation and switches from being a random helix to a folded structure. DSAI’s fluorescence is protected as a result of the resistance of the transformed aptamer adsorbed on the SWCNHs’ surface. Because DSAI’s fluorescence is not quenchable, the fluorescence intensity is calculated as a function of the AFB1 concentration. By simply mixing DSAI, aptamer, AFB1 samples, and SWCNHs, the method can be carried out in 2 h, with a limit of detection (LOD) of 1.83 ng/mL. It has a high selectivity in the presence of other mycotoxins, and its performance is confirmed in soybean sauce with a known concentration of AFB1. The LOD was 1.92 ng/mL in the soy sauce samples and the recovery ranged from 95 to 106%, implying that the presented aptasensor has great potential for food analysis.

Abstract Listeria monocytogenes is a food-borne pathogen. Pediocin is a group IIα bacteriocin with anti-listeria activity that is naturally produced by Pediococcus acidilactic and Lactobacillus plantarum. The pedA/papA gene encodes pediocin/plantaricin. In native hosts, the expression and secretion of active PedA/PapA protein rely on the accessory protein PedC/PapC and ABC transporter PedD/PapD on the same operon. The excretion machines were also necessary for pediocin protein expression in heterologous hosts of E. coli, Lactobacillus lactis, and Corynebacterium glutamicum. In this study, two vectors carrying the codon sequence of the mature PapA peptide were constructed, one with and one without a His tag. Both fragments were inserted into the plasmid pHT43 and transformed into Bacillus subtilis WB800N. The strains were induced with IPTG to secrete the fused proteins PA1 and PA2. Supernatants from both recombinant strains can inhibit Listeria monocytogenes ATCC54003 directly. The fused protein possesses inhibition activity as a whole dispense with removal of the leading peptide. This is the first report of active pediocin/PapA expression without the assistance of PedCD/PapCD in heterogeneous hosts. In addition, the PA1 protein can be purified by nickel-nitrilotriacetic acid (Ni-NTA) metal affinity chromatography.

In view of the time-consuming and laborious manual picking and sorting of strawberries, the direct impact of image recognition accuracy on automatic picking and the rapid development of deep learning(DL), a Faster Regions with Convolutional Neural Network features (R-CNN) strawberry recognition method that combines Mixup data augmentation, a ResNet(Residual Network)50 backbone feature extraction network and a Soft-NMS (Non-Maximum Suppression) algorithm, named the MRS Faster R-CNN, is proposed. In this paper, the transfer learning backbone feature extraction network VGG (Visual Geometry Group) 16 and ResNet50 are compared, and the superior ResNet50 is selected as the backbone network of MRS Faster R-CNN. The data augmentation method of Mixup image fusion is used to improve the learning and generalization ability of the model. The redundant bboxes (bounding boxes) are removed through Soft-NMS to obtain the best region proposal. The freezing phase is added to the training process, effectively reducing the occupation of video memory and shortening the training time. After experimental verification, the optimized model improved the AP (Average Precision) values of mature and immature strawberries by 0.26% and 5.34%, respectively, and the P(Precision) values by 0.81% and 6.34%, respectively, compared to the original model (R Faster R-CNN). Therefore, the MRS Faster R-CNN model proposed in this paper has great potential in the field of strawberry recognition and maturity classification and improves the recognition rate of small fruit and overlapping occluded fruit, thus providing an excellent solution for mechanized picking and sorting.

We explore the mechanism and law of reducing the resistance of soil cutting tools by achieving the self-excited vibration mode through the modification of the soil-engaging surface spectrum. Around the fundamental resonance point of the soil, and superimposing geometric waveforms of different spatial frequencies and amplitudes on the basis of the circular arc surface base directrix, 18 bulldozing plate models with different soil-engaging surface spectrum structures were designed and manufactured. By conducting a discrete element method (DEM) simulation of the working process of the bulldozing plate and comparing the working resistance of the soil-engaging components with the results of the soil bin test, the microscopic process of soil disturbance was further revealed from the perspective of simulation. The results indicate that the self-excited vibrating circular arc-surface bulldozing plate could effectively improve the resistance reduction effect during the operation around the resonance point. With this model, the average error of the horizontal working resistance was 7.52%, and the average error of the vertical working resistance was 21.71%. The analysis of the soil microscopic disturbance process by DEM simulation further verified the correctness of the macroscopic test results. The research work has an important reference value for both the vibration resistance reduction design of soil cutting tools and resistance reduction design of soil-engaging surfaces’ geometric structure modification.

Abstract Aiming at the issues of slow convergence, phase delay, and chattering in the sensorless vector control system of permanent magnet synchronous motor (PMSM) controlled by sliding mode observer (SMO), a fuzzy adaptive super‐twisting (ST) SMO sensorless control algorithm is proposed. The fuzzy adaptive algorithm is used to estimate the uncertain boundary and adaptively adjust sliding mode gain, which is used in the ST algorithm to accelerate the convergence speed of sliding mode gain, and eliminate the system delay caused by phase locked loop and phase compensation, and improve the estimation accuracy of speed and rotor position. In this algorithm, the sigmoid function is used instead of the signum function in the traditional SMO to suppress system chattering. Lyapunov stability theorem is used to obtain the stable conditions of position and speed observer at motoring mode. The saturated ST‐SMO algorithm is verified by Matlab/Simulink. The simulation results show that compared with the traditional SMO, the fuzzy ST‐SMO algorithm proposed in this paper has faster convergence speed in the variable speed and the variable load of PMSM sensorless control system, which has significantly reduced chattering, obtained more accurate speed and rotor position and has better dynamic response and robustness.

Backgrounds Chronic stress could induce depression-like phenotype in animal models. Previous data showed that sex differences exist after chronic stress model establishment, however, the detailed information about the difference of blood biochemical indexes is not clear. In this study, we aim to supply comparison of monoamine transmitters and related hormone markers in serum between male and female depressed mice, and in order to better understand the sex difference in transmitters and hormone levels in depression occurrence and development. Methods Sixty C57BL/6 mice (both male and female) were divided into two groups by gender. Same gender mice were then divided randomly into the non-treated control group and chronic stress group which was exposed to 8 weeks of chronic unpredictable mild stress (CUMS). Depression-like behavior was assessed with open-field test and sucrose preference test. Blood sample was collected and monoamine transmitter and related hormone in serum were measured by ELISA. Results The depression-like phenotype mice model was established successfully after 8 weeks of chronic stress. The locomotion activity scores in male stressed mice declined more than that in female stressed mice, while the exploratory behavior scores in female stressed mice declined more than that in male stressed mice. Compared to non-treated control group mice, mice in the chronic stress group in response to stress showed greater declines in monoamine transmitters (5-HT, dopamine, norepinephrine) and sex hormones (androgen, estrogen, oxytocin and prolactin), while stress hormones (adrenaline, corticosterone and ACTH) were significantly increased. The decrease of norepinephrine, androgen and estrogen in female stressed mice was greater than in male stressed mice, whereas the 5-HT and oxytocin in male stressed mice decreased more than in female stressed mice, and the corticosterone in male stressed mice increased more than in female stressed mice. Conclusion Sex differences of monoamine transmitter and related hormone levels in serum occurred in chronic stress induced depression-like phenotype mice model. It may provide a useful reference to guide precise antidepressant treatment in different gender population in clinical care.

Aflatoxin B1 (AFB1) is one of the most contaminated fungal toxins worldwide and is prone to cause serious economic losses, food insecurity, and health hazards to humans. The rapid, on-site, and economical method for AFB1 detection is need of the day. In this study, an AFB1 aptamer (AFB1-Apt) sensing platform was established for the detection of AFB1. Fluorescent moiety (FAM)-modified aptamers were used for fluorescence response and quenching, based on the adsorption quenching function of single-walled carbon nanohorns (SWCNHs). Basically, in our constructed sensing platform, the AFB1 specifically binds to AFB1-Apt, making a stable complex. This complex with fluorophore resists to be adsorbed by SWCNHs, thus prevent SWCNHs from quenching of fluorscence, resulting in a fluorescence response. This designed sensing strategy was highly selective with a good linear response in the range of 10–100 ng/mL and a low detection limit of 4.1 ng/mL. The practicality of this sensing strategy was verified by using successful spiking experiments on real samples of soybean oil and comparison with the enzyme-linked immunosorbent assay (ELISA) method.

Background: Chemotherapy-induced nausea and vomiting severely impairs the treatment and prognosis of cancer patients. Depressive mood disorder might aggravate nausea and vomiting in cancer patients; however, the role of neurotransmitters and receptors involved in the mediation of emesis and nausea is still not well elaborated.Methods: The study was carried out based on the chronic unpredictable mild stress–induced depression-like phenotype rat model and cisplatin-induced pica rat model establishment. Forty male Sprague–Dawley rats were randomized into the non-treated control group and the chronic stress group, which were exposed to 8 weeks of stress. Each group was then sub-divided into vehicle subgroups (n = 10) and cisplatin subgroups (n = 10) which were given cisplatin to induce pica behavior. Kaolin and food intake were recorded after administration. The medulla oblongata and ileum tissues were obtained. Neurotransmitters involved in the mediation of emesis and nausea (5-HT, DA, SP, and AEA) were detected using an ELISA kit. Vomit-related receptors (5-HT3R, DA2R, NK1R, and CB1R) in tissues were assayed for mRNA and protein expression by RT-qPCR and Western blotting.Results: Behavioral test and sucrose preference validated that depression-like phenotype rat models were established successfully. The kaolin consumption test confirmed that chronic stress pretreatment aggravated anorexia and pica behavior. Vomiting-related molecules’ data showed that chronic stress exposure increased 5-HT and SP levels in the medulla oblongata. Vomiting-related receptor expression data showed that chronic stress pretreatment upregulated 5-HT3R, DA2R, and NK1R expressions and downregulated the CB1R expression in the medulla oblongata. However, chronic stress pretreatment downregulated 5-HT3R, DA2R, and NK1R expressions and upregulated the CB1R expression in the ileum.Conclusion: Chronic stress pretreatment aggravates anorexia and vomiting progress, which might be via altering neurotransmitters and receptors involved in the mediation of emesis and the nausea level and expression in the central nervous system.

In this study we explored the methods and effects of spectral resistance reduction for soil-engaging surface of self-excited resonant bulldozing plates with a plane base on the basis of resonance effects. In the acquisition of the low-order vibration frequency f0 of the bin soil, centering around frequency point f0, eight spatial geometric wave frequency points ni of soil-engaging surfaces and three amplitudes were selected; by superimposing with soil-engaging surfaces of plane-based bulldozing plates, 24 spectral structures of the soil-engaging surface of bulldozing plates and model samples were combinatorically designed. Resistance reduction characteristics of each model sample were tested using an indoor soil bin test. Near the resonance point f0, the structures of the self-excited vibrating frequency spectrum of the soil-engaging surface obtain a preferable inhibitory effect on working resistance. At a 4 mm amplitude resonance point, model samples achieved the best resistance reduction effect, with a maximum relative resistance reduction rate of 22.67%, and the soil desorption effect of the relevant model sample was also good. On the other hand, away from the resonance point, whether the frequency increased or decreased, the corresponding working resistance of the model sample surfaces increased relatively. This is in good agreement with the law that the resonance point amplitude of the theoretical resonance curve is higher and the amplitude on both sides is lower. This paper provides a reference for the parameter design and related product development for various forced or self-excited vibration soil cutting tools.

Accurate solar irradiance prediction plays an important role in ensuring the security and stability of renewable energy systems. Solar irradiance modeling is usually a time-dependent dynamic model. As a new kind of recurrent neural network, echo state network (ESN) shows excellent performance in the field of time series prediction. However, the memory length of classical ESN is fixed and finite, which makes it hard to map sufficient features of solar irradiance with long-range dependency. Therefore, a novel deep echo state network with variable memory pattern (VMP-DESN) is proposed in this brief. VMP-DESN consists of multiple connected reservoirs in series, and there exist different types of memory modes in VMP-DESN. To remember more input history information in the states, the time delay links are added in each reservoir and between every two reservoirs. The VMP-DESN is more flexible to deal with different input signals due to its variable memory modes in the reservoir states. Additionally, the effect of different memory patterns on the VMP-DESN performance is discussed in detail, including the antidisturbance ability, memory capacity, and prediction accuracy. Finally, the effectiveness of VMP-DESN is evaluated by predicting the real solar irradiance task.

Background. Jujuboside B (JUB) is a saponins isolated from the seeds of Zizyphi jujuba var. spinosi, which is used to treat mental illness and is reported recently to induce cancer cell apoptosis. As our previous research showed chronic stress promoted tumor growth, this work aims to investigate whether JUB exert antitumor effect in addition to its antidepressant effect and possible mechanism. Methods. 56 female C57BL/6 mice were grouped into 7 groups: A (blank control), B (tumor-bearing control), C (tumor-bearing + JUB), D (CUMS control), E (CUMS + JUB), F (tumor-bearing + CUMS), and G (tumor-bearing + CUMS + JUB). Groups C, E, G, B, D, and F were administered, respectively, with JUB (40 mg/kg/day) or vehicle for 2 weeks. Serum 5-HT, Trp (tryptophane), inflammatory cytokines TNF-α, IL-4, -6, and -10 levels were detected by ELISA. The tumors in groups B and F were isolated for RNA-seq sequencing. Protein and mRNA expression of Bax, Bcl-2, p-PI3K, p-Akt, p-MAPK, p-ERK, and p-CREB in tumor tissues were detected. In vitro, A549 cells were stimulated with JUB (60 μmol/L), in which proliferation rate and colony formation rate were detected. The PI3K/Akt and, MAPK/ERK pathway were measured. Results. Chronic stress successfully induced the depression-like phenotype (group D vs. A) and promoted tumor growth (group B vs. F). JUB significantly ameliorated the depression-like phenotype and increased 5-HT, Trp levels (group D vs. E), and reversing CUMS-induced tumor progression. Meanwhile, JUB decreased inflammatory cytokine levels. Chronic stress upregulated the phosphorylation levels of PI3K/Akt/MAPK/ERK/CREB; JUB reversed this regulation. JUB significantly inhibited cell viability, colony formation rate, and downregulated the phosphorylation levels of PI3K/Akt/MAPK/ERK/CREB in vitro. Conclusions. JUB reverses CUMS-promoted tumor progression in tumor-bearing mice with depression-like phenotype. JUB exerts the dual beneficial effect on tumor growth and depression-like phenotype by blocking the signal transduction pathway of PI3K/Akt, MAPK/ERK, and dephosphorylating the downstream signaling regulator CREB.

Bioactive wound dressings that are capable of regulating the local wound microenvironment have attracted a very large interest in the field of regenerative medicine. Macrophages have many critical roles in normal wound healing, and the dysfunction of macrophages significantly contributes to impaired or non-healing skin wounds. Regulation of macrophage polarization towards an M2 phenotype provides a feasible strategy to enhance chronic wound healing, mainly by promoting the transition of chronic inflammation to the proliferation phase of wound healing, upregulating the level of anti-inflammatory cytokines around the wound area, and stimulating wound angiogenesis and re-epithelialization. Based on this, modulation of macrophage functions by the rational design of bioactive scaffolds has emerged as a promising way to accelerate delayed wound healing. This review outlines current strategies to regulate the response of macrophages using bioactive materials, with an emphasis on extracellular matrix-based scaffolds and nanofibrous composites.

To solve the technical problem that wheeled vehicles are prone to skidding on complex ground, due to poor adhesion performance, a tire-tread-structure design method based on the bionic principle is proposed in this paper. The 3D model of a goat’s foot was obtained using reverse engineering technology, and the curve equation was fitted by extracting the contour data of its outer-hoof flap edge, which was applied to the tire-tread-structure design. The bionic and herringbone-pattern rubber samples were manufactured, and a soil-tank test was carried out using an electronic universal tensile-testing machine, in order to verify the simulation results. The results showed that the overall adhesion of the bionic tread-pattern was greater than that of the normal tread-pattern with the same load applied and the same height and angle of the tread-pattern structure, and the maximum adhesion was increased by 14.23%. This research will provide a reference for optimizing the pattern structure and thus improving the passing performance of wheeled vehicles.

As a kind of clean energy, the exploration and development of coalbed methane (CBM) are of great importance and significance. In this paper, the CBM reservoir parameters of a working area in Western Guizhou Province, China, were predicted by using 3D seismic exploration technology, and the sweet-spot area was evaluated based on the prediction results. In terms of data interpretation, while the traditional technology is extended to the study of CBM, new technologies and methods suitable for CBM were also actively explored, especially in the quantitative prediction methods of parameters such as coal seam thickness, CBM content, coal body structure, in situ stress, etc., and a three-highs quantitative prediction technology of CBM sweet spots characterized by high precision, high resolution, and high coincidence was explored, which is based on logging evaluation and petrophysics. In addition, in the comprehensive evaluation of multiparameter sweet spots, the multiparameter weighted step-by-step evaluation method based on inversion was innovatively proposed, which made the prediction of CBM sweet spots more focused, effective, and practical, and the distribution law of sweet spots was more consistent with the geological law, providing enough basis for subsequent well location deployment. Based on this method, the C409 coal seam was selected as the sweet spot.

First of all, the explosion-welding method was adopted to prepare steel fiber-reinforced steel-aluminum composite plates. Secondly, the smooth particle hydrodynamic (SPH) method was used to investigate the effect of introducing steel fibers to a vortex region created at the bonding interface of the steel-aluminum composite plate. Thirdly, the following conclusions were drawn through an analysis of the vortex region with the assistance of scanning electron microscopy and energy-dispersive X-ray spectroscopy. A brittle intermetallic compound FeAl was produced in the vortex region in an environment characterized by high temperature, high pressure, and high strain rate, resulting in cracks, holes and pores. In addition, the hardness of the vortex area was less than the estimated value, which is mainly because the main element in the vortex area was 2A12 aluminum with low hardness, and there were cracks, holes, pores and other defects that caused hardness reduction. Although the addition of steel fibers caused defects at the bond interface, the addition of steel fibers was effective in improving the tensile resistance performance of steel-aluminum composite panels to a certain extent. In addition, the larger the fiber diameter, the more significant the increase in tensile resistance.

In order to improve the slope movement stability and flexibility of quadruped robot, a theoretical design method of a flexible spine of a robot that was based on bionics was proposed. The kinematic characteristics of the spine were analyzed under different slopes with a Saanen goat as the research object. A Qualisys track manager (QTM) gait analysis system was used to obtain the trunk movement of goats under multiple slopes, and linear time normalization (LTN) was used to calibrate and match typical gait cycles to characterize the goat locomotion gait under slopes. Firstly, the spatial angle changes of cervical thoracic vertebrae, thoracolumbar vertebrae, and lumbar vertebrae were compared and analyzed under 0°, 5°, 10°, and 15° slopes, and it was found that the rigid and flexible coupling structure between the thoraco–lumbar vertebrae played an obvious role when moving on the slope. Moreover, with the increase in slope, the movement of the spine changed to the coupling movement of thoraco–lumbar coordination movement and a flexible swing of lumbar vertebrae. Then, the Gaussian mixture model (GMM) clustering algorithm was used to analyze the changes of the thoraco–lumbar vertebrae and lumbar vertebrae in different directions. Combined with anatomical knowledge, it was found that the motion of the thoraco–lumbar vertebrae and lumbar vertebrae in the goat was mainly manifested as a left–right swing in the coronal plane. Finally, on the basis of the analysis of the maximin and variation range of the thoraco–lumbar vertebrae and lumbar vertebrae in the coronal plane, it was found that the coupling motion of the thoraco–lumbar cooperative motion and flexible swing of the lumbar vertebrae at the slope of 10° had the most significant effect on the motion stability. SSE, R2, adjusted-R2, and RMSE were used as evaluation indexes, and the general equations of the spatial fitting curve of the goat spine were obtained by curve fitting of Matlab software. Finally, Origin software was used to obtain the optimal fitting spatial equations under eight movements of the goat spine with SSE and adjusted-R2 as indexes. The research will provide an idea for the bionic spine design with variable stiffness and multi-direction flexible bending, as well as a theoretical reference for the torso design of a bionic quadruped robot.

In this work, a facile direct current atmospheric pressure micro-plasma (APM) technology was deployed for the synthesis of functional gold nanoparticle/chitosan (AuNP/CS) nanocomposites for the first time. Different experimental parameters, such as metal salt precursor concentration and chitosan viscosity, have been investigated to understand their effects on the resulting nanocomposite structures and properties. The nanocomposites were fully characterized using a wide range of material characterization techniques such as UV–vis, transmission electron microscope (TEM), Fourier transform infrared (FTIR) spectra and X-ray photoelectron spectroscopy (XPS) analyses. Potential reaction pathways have been proposed for the nanocomposite synthesis process. Finally, potential of the synthesized nanocomposites towards photothermal conversion and bacteria eradiation applications has been demonstrated. The results show that APM is a facile, rapid and versatile technique for the synthesis of AuNP/CS functional nanocomposites. Through this work, a more in-depth understanding of the multi-phase system (consisting of gas, plasma, liquid and solid) has been established and such understanding could shine a light on the future design and fabrication of new functional nanocomposites deploying the APM technique.

To obtain the discrete element simulation model parameters suitable for the interaction between cinnamon soil and soil-engaging components, the Hertz–Mindlin with JKR contact model in EDEM simulation software was used to calibrate the relevant model parameters of cinnamon soil. Firstly, the particle size distribution, moisture content, volume density, Poisson’ s ratio, shear modulus, and other parameters of the cinnamon soil were measured with cinnamon soil as the research object. Further, taking the stacking angle as the response value, the Plackett–Burman test, the steepest climbing test, and the Box–Behnken were designed by using the Design-Expert software to calibrate and optimize the physical parameters of soil simulation. The optimal parameter combination was obtained: cinnamon soil–cinnamon soil rolling friction coefficient was 0.08, soil JKR surface energy was 0.37 J/m−2, and cinnamon soil–steel static friction coefficient was 0.64. Finally, the discrete element simulation verification test of stacking angle and cutting resistance was carried out under the calibrated parameters. The comparative calculation showed that the relative error between the simulated stacking angle and the measured stacking angle was 0.253%, and the maximum relative error between the simulated cutting resistance and the measured cutting resistance was 10.32%, which was within the acceptable range, indicating the high accuracy and reliability for the calibration parameters. The research results have important reference value for the energy-saving and consumption-reducing design of soil tillage components and provide basic data for the simulation of cutting resistance research of cinnamon-soil-engaging components.

Due to the time-varying topology and possible disturbances in a conflict environment, it is still challenging to maintain the mission performance of flying Ad hoc networks (FANET), which limits the application of Unmanned Aerial Vehicle (UAV) swarms in harsh environments. This paper proposes an intelligent framework to quickly recover the cooperative coverage mission by aggregating the historical spatio-temporal network with the attention mechanism. The mission resilience metric is introduced in conjunction with connectivity and coverage status information to simplify the optimization model. A spatio-temporal node pooling method is proposed to ensure all node location features can be updated after destruction by capturing the temporal network structure. Combined with the corresponding Laplacian matrix as the hyperparameter, a recovery algorithm based on the multi-head attention graph network is designed to achieve rapid recovery. Simulation results showed that the proposed framework can facilitate rapid recovery of the connectivity and coverage more effectively compared to the existing studies. The results demonstrate that the average connectivity and coverage results is improved by 17.92% and 16.96%, respectively compared with the state-of-the-art model. Furthermore, by the ablation study, the contributions of each different improvement are compared. The proposed model can be used to support resilient network design for real-time mission execution. [ABSTRACT FROM AUTHOR]