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Abstract We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.

To explore the usefulness of neutrophil-to-lymphocyte count ratio (NLR), procalcitonin (PCT), and interleukin-6 (IL-6) for the severity assessment of bacterial sepsis.

Grid-forming （GFM） converters， known for their superior inertia damping characteristics， have emerged as a center research focus in the renewable energy sector. As a result， the damping characteristics of GFM wind power converters are first examined. The analysis centers on their equivalent external characteristics from an impedance standpoint， and the Bode stability criterion is utilized to study their stability during grid connection. Subsequently， the frequency support characteristics of GFM wind power converters are examined in terms of inertia. A comparative investigation is undertaken via simulation analysis to gauge the supportive capability of GFM and grid-following （GFL） wind power converters during alterations in grid frequency and power fluctuation on the wind turbine side. The findings reveal that the external impedance characteristics of GFM wind power converters not only display inductive properties but also maintain commendable stability throughout grid integration. In response to a grid malfunction， GFM wind power converters can furnish a significant measure of power support， equating to a rise in system inertia， thereby indicating favorable grid integration characteristics.

Abstract Background The systematic status of sect. Tuberculata and its taxonomy have recently attracted considerable attention. However, the different bases for defining the characteristics of sect. Tuberculata has led to many disagreements among the plants in this group. Camellia neriifolia and Camellia ilicifolia have been the subject of taxonomic controversy and have been treated as different species or varieties of the same species. Therefore, it is important to use multiple methods, i.e., integrative taxonomy, to determine the taxonomic status of C. neriifolia and C. ilicifolia. This is the first study to systematically explore the taxonomic position of these two plants on the basis of Morphology, Anatomy, Palynology and Molecular Systematics. Results Extensive specimen reviews and field surveys showed that many differences exist in C. neriifolia and C. ilicifolia, such as the number of trunk (heavily debarked vs. slightly peeling), leaf type (smooth thin leathery, shiny vs. smooth leathery, obscure or slightly shiny), leaf margin (entire vs. serrate), flower type (subsessile vs. sessile), number of styles (3–4 vs. 3), and sepal (ovate vs. round). Moreover, C. neriifolia has a more distinctive faint yellow flower color, and trunk molting was more severe in C. neriifolia than that in C. ilicifolia. In addition, micromorphological analysis of the leaf epidermis showed that the two species differed in the anticlinal wall, stomatal apparatus, and stomatal cluster, and pollen morphology analyses based on pollen size, germination furrow, and polar and equatorial axes showed that they are both distinct from each other. The results of the phylogenetic tree constructed based on the whole chloroplast genome, protein-coding genes, and ITS2 showed that both C. ilicifolia and C. neriifolia were clustered in different branches and gained high support. Conclusions The results combine morphology, anatomy, palynology, and molecular systematics to treat both C. neriifolia and C. ilicifolia as separate species in the sect. Tuberculata, and the species names continue to be used as they were previously. In conclusion, clarifying the taxonomic status of C. neriifolia and C. ilicifolia deepens our understanding of the systematic classification of sect. Tuberculata.

Abstract Sect. tuberculata plant belongs to the Camellia genus and is named for the “tuberculiform protuberance on the surface of the ovary and fruit”. It is a species of great ornamental value and potential medicinal value. However, little has been reported on the metabolites of C. tuberculata seeds. Therefore, this study was conducted to investigate the metabolites of C. tuberculata seeds based on UPLC/ESI-Q TRAP-MS/MS with extensively targeted metabolomics. A total of 1611 metabolites were identified, including 107 alkaloids, 276 amino acids and derivatives, 283 flavonoids, 86 lignans and coumarins, 181 lipids, 68 nucleotides and derivatives, 101 organic acids, 190 phenolic acids, 10 quinones, 4 steroids, 17 tannins, 111 terpenoids, and 177 other metabolites. We compared the different metabolites in seeds between HKH, ZM, ZY, and LY. The 1311 identified different metabolites were classified into three categories. Sixty-three overlapping significant different metabolites were found, of which lignans and coumarins accounted for the largest proportion. The differentially accumulated metabolites were enriched in different metabolic pathways between HKH vs. LY, HKH vs. ZM, HKH vs. ZY, LY vs. ZY, ZM vs. LY and ZM vs. ZY, with the most abundant metabolic pathways being 4, 2, 4, 7, 7 and 5, respectively (p

Panax japonicus has long been utilized as an herbal remedy in Chinese traditional medicine for treating various diseases. In this investigation, we present the environmentally friendly silver nanoparticle (AgNP) synthesis by the aqueous extract of P. japonicas to follow its cardioprotective effects. Through various analytical methods, we identified the nanoparticles (NPs). Our XRD findings revealed the formation of Ag@P. japonicus, while FE-SEM imagery indicated a spherical shape, with NPs measuring less than 40 nm. The UV–Vis and FT-IR spectroscopy confirm the green synthesis of Ag@P. japonicus. In the medicinal section, 45 Wistar rats were utilized. These groups consisted of a normal group, a group that was solely treated with isoproterenol for inducing myocardial infarction, and two groups that were pretreated with AgNPs at different doses for 14 days. These pretreated groups were then challenged with isoproterenol. The expression of PI3K/Akt/mTOR and other downstream inflammatory and apoptotic mediators were followed. Additionally, the expression of Keap1, Nrf2, ECG, cardiac markers, and other downstream antioxidant enzymes were assessed. Treatment with AgNPs ameliorated the apoptosis, inflammation, and myocardial autophagy, regulated the PI3K/Akt/mTOR pathway, increased the antioxidant enzyme efficacies, and activated the Keap1/Nrf2/HO-1 pathway. The findings suggest that AgNPs may have a cardioprotective efficacy on myocardial infarction by mitigating the Keap1/Nrf2 pathway, GST, GPx, GSH, SOD, IL-1β, IL-6, TNF-α, NF-κB, Bax, Bcl2, caspase-9, caspase-3, and PI3K/Akt/mTOR pathway. Furthermore, the treatment decreased the infarct region size, attenuated the cardiac indicators levels, and mitigated immune cell infiltration and myocardial necrosis.

Abstract The T-cell receptor (TCR) repertoires exhibits distinct signatures associated with COVID-19 severity. However, the precise identification of vaccine-induced SARS-CoV-2-specific TCRs and T-cell immunity mechanisms are unknown. We developed a machine-learning model that can differentiate COVID-19 patients from healthy individuals based on TCR sequence features with an accuracy of 95.7%. Additionally, we identified SARS-CoV-2-specific T cells and TCR in HLA-A*02 vaccinated individuals by peptide stimulation. The SARS-CoV-2-specific T cells exhibited higher cytotoxicity and prolonged survival when targeting spike-pulsed cells in vitro or in vivo. The top-performing TCR was further tested for its affinity and cytotoxic effect against SARS-CoV-2-associated epitopes. Furthermore, single-cell RNA sequencing (scRNA-seq), immune repertoire sequencing (IR-seq) and flow cytometry were used to access vaccine-induced cellular immunity, which demonstrated that robust T cell responses (T cell activation, tissue-resident memory T cell (Trm) generation, and TCR clonal expansion) could be induced by intranasal vaccination. In summary, we identified the SARS-CoV-2-associated TCR repertoires profile, specific TCRs and T cell responses. This study provides a theoretical basis for developing effective immunization strategies.

In order to solve the oscillatory heat transfer problem of gas-liquid two-phase flow of cooling oil gallery of piston, a reciprocating oscillatory experimental device reformed by diesel engine was designed and established. The oscillatory flow process of gas-liquid two-phase flow in a test piece was visualized by high-speed camera technology, and the oscillatory flow patterns of gas-liquid two-phase flow in the test piece at initial and full oscillation stage under different rotation speed and liquid filling rate were analyzed respectively. The results show that at initial oscillation stage, the interface between gas and liquid is obvious, and there is no intense turbulent mixing motion. At full oscillation stage, the movement law and flow pattern of liquid change periodically. Rotational speed mainly affects the turbulence intensity of gas-liquid two-phase flow, while the liquid filling rate mainly affects the flow pattern of gas-liquid two-phase flow. The research results reveal the oscillatory flow rules of gas-liquid two-phase flow in cooling oil gallery, and also provide a reference for the structural optimization design of the highly-intensified piston in the future.

The exothermic behaviors of butanol, butyraldehyde, butanone, and butyric acid with nitric acid were studied by adiabatic accelerating rate calorimeter(ARC), and the test results were compared and analyzed, and the system risk was evaluated by THI index method. The results show that under the condition of the zero oxygen balance, butyraldehyde-HNO3 system has the most obvious self-exothermic. When the butyraldehyde content is only 0.14 g, the adiabatic temperature of the system rises to 118.4 ℃ and the heat release amount is 776.6 J/g; butanol-HNO3 system begins to emit heat at about 40.2 ℃, and the highest temperature in the exothermic stage of self-reaction reaches 145.7 ℃ and the maximum pressure reaches about 34 bar(1 bar=105 Pa). Butanone-HNO3 system releases heat from 50 ℃ to 136 ℃, and the amount of heat released is 564.0 J/g. No exothermic point is observed in butyric acid-HNO3 system in the temperature range of less than 140.0 ℃. With the increase of nitric acid concentration(2.0→6.0 mol/L), the risk of butanol-HNO3 system increases from medium to high level. The risks of reaction systems of butanol, butyraldehyde, butanone and butyric acid with 4.0 mol/L HNO3 are at higher, higher, middle and middle levels.

Abstract Background Predictive biomarkers of immune checkpoint inhibitor (ICI) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti–PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. Methods Participants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. Results A total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression–based signatures. The best-performing models showed improved predictive power over reference variables, including TMB or PD-L1. Conclusions This DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICI clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICI efficacy. Trial registration: CheckMate 026; NCT02041533, registered January 22, 2014. CheckMate 227; NCT02477826, registered June 23, 2015.

Abstract The fast-growing terahertz technologies require high-performance terahertz absorber for suppressing electromagnetic interference. Since the dissipation mechanism in terahertz band usually focuses on electronic conduction loss, almost all terahertz absorbers are constructed with electronically conducting materials being opaque, which limits their applications in scenarios requiring high visible transmittance. Here, we demonstrate a transparent terahertz absorber based on permittivity-gradient elastomer-encapsulated-organohydrogel. Our organohydrogel-based terahertz absorber exhibits a high absorbing property (average reflection loss of 49.03 dB) in 0.5–4.5 THz band with a thin thickness of 700 μm and a high average visible transmittance of 85.51%. The terahertz absorbing mechanism mainly derives from the ionic conduction loss of the polar liquid in organohydrogel. Besides, the hydrophobic and adhesive elastomer coating endows this terahertz absorber high absorbing stability and interfacial adhesivity. This work paves a viable way to designing transparent terahertz absorbers.

Abstract Background Interindividual variation characterizes the relief experienced by constipation-predominant irritable bowel syndrome (IBS-C) patients following linaclotide treatment. Complex bidirectional interactions occur between the gut microbiota and various clinical drugs. To date, no established evidence has elucidated the interactions between the gut microbiota and linaclotide. We aimed to explore the impact of linaclotide on the gut microbiota and identify critical bacterial genera that might participate in linaclotide efficacy. Methods IBS-C patients were administered a daily linaclotide dose of 290 µg over six weeks, and their symptoms were then recorded during a four-week posttreatment observational period. Pre- and posttreatment fecal samples were collected for 16S rRNA sequencing to assess alterations in the gut microbiota composition. Additionally, targeted metabolomics analysis was performed for the measurement of short-chain fatty acid (SCFA) concentrations. Results Approximately 43.3% of patients met the FDA responder endpoint after taking linaclotide for 6 weeks, and 85% of patients reported some relief from abdominal pain and constipation. Linaclotide considerably modified the gut microbiome and SCFA metabolism. Notably, the higher efficacy of linaclotide was associated with enrichment of the Blautia genus, and the abundance of Blautia after linaclotide treatment was higher than that in healthy volunteers. Intriguingly, a positive correlation was found for the Blautia abundance and SCFA concentrations with improvements in clinical symptoms among IBS-C patients. Conclusion The gut microbiota, especially the genus Blautia, may serve as a significant predictive microbe for symptom relief in IBS-C patients receiving linaclotide treatment. Trial registration: This trial was registered with the Chinese Clinical Trial Registry (Chictr.org.cn, ChiCTR1900027934).

Abstract Background Sect. Tuberculata belongs to Camellia, and its members are characterized by a wrinkled pericarp and united filaments. All the plants in this group, which are endemic to China, are highly valuable for exploring the evolution of Camellia and have great potential for use as an oil source. However, due to the complex and diverse phenotypes of these species and the difficulty of investigating them in the field, their complex evolutionary history and interspecific definitions have remained largely unelucidated. Results Therefore, we newly sequenced and annotated 12 chloroplast (cp) genomes and retrieved the published cp genome of Camellia anlungensis Chang in sect. Tuberculata. In this study, comparative analysis of the cp genomes of the thirteen sect. Tuberculata species revealed a typical quadripartite structure characterized by a total sequence length ranging from 156,587 bp to 157,068 bp. The cp.genome arrangement is highly conserved and moderately differentiated. A total of 130 to 136 genes specific to the three types were identified by annotation, including protein-coding genes (coding sequences (CDSs)) (87–91), tRNA genes (35–37), and rRNA genes (8). The total observed frequency ranged from 23,045 (C. lipingensis) to 26,557 (C. anlungensis). IR region boundaries were analyzed to show that the ycf1 gene of C. anlungensis is located in the IRb region, while the remaining species are present only in the IRa region. Sequence variation in the SSC region is greater than that in the IR region, and most protein-coding genes have high codon preferences. Comparative analyses revealed six hotspot regions (tRNA-Thr(GGT)-psbD, psbE-petL, ycf15-tRNA-Leu(CAA), ndhF-rpl32, ndhD, and trnL(CAA)-ycf15) in the cp genomes that could serve as potential molecular markers. In addition, the results of phylogenetic tree construction based on the cp genomes showed that the thirteen sect. Tuberculata species formed a monophyletic group and were divided into two evolutionarily independent clades, confirming the independence of the section. Conclusions In summary, we obtained the cp genomes of thirteen sect. Tuberculata plants and performed the first comparative analysis of this group. These results will help us better characterize the plants in this section, deepen our understanding of their genetic characteristics and phylogenetic relationships, and lay the theoretical foundation for their accurate classification, elucidation of their evolutionary changes, and rational development and utilization of this section in the future.

Gut microbiota dysbiosis is involved in cholestatic liver diseases. However, the mechanisms remain to be elucidated. The purpose of this study was to examine the effects and mechanisms of Lactobacillus acidophilus (L. acidophilus) on cholestatic liver injury in both animals and humans. Bile duct ligation (BDL) was performed to mimic cholestatic liver injury in mice and serum liver function was tested. Gut microbiota were analyzed by 16S rRNA sequencing. Fecal bacteria transplantation (FMT) was used to evaluate the role of gut microbiota in cholestasis. Bile acids (BAs) profiles were analyzed by targeted metabolomics. Effects of L. acidophilus in cholestatic patients were evaluated by a randomized controlled clinical trial (NO: ChiCTR2200063330). BDL induced different severity of liver injury, which was associated with gut microbiota. 16S rRNA sequencing of feces confirmed the gut flora differences between groups, of which L. acidophilus was the most distinguished genus. Administration of L. acidophilus after BDL significantly attenuated hepatic injury in mice, decreased liver total BAs and increased fecal total BAs. Furthermore, after L. acidophilus treatment, inhibition of hepatic Cholesterol 7α-hydroxylase (CYP7α1), restored ileum Fibroblast growth factor 15 (FGF15) and Small heterodimer partner (SHP) accounted for BAs synthesis decrease, whereas enhanced BAs excretion was attributed to the increase of unconjugated BAs by enriched bile salt hydrolase (BSH) enzymes in feces. Similarly, in cholestasis patients, supplementation of L. acidophilus promoted the recovery of liver function and negatively correlated with liver function indicators, possibly in relationship with the changes in BAs profiles and gut microbiota composition. L. acidophilus treatment ameliorates cholestatic liver injury through inhibited hepatic BAs synthesis and enhances fecal BAs excretion.

Objective: The substantial prevalence of nonadherence to analgesic medication among individuals diagnosed with cancer imposes a significant strain on both patients and healthcare resources. The objective of this study is to develop and authenticate a nomogram model for assessing nonadherence to analgesic medication in cancer patients. Methods: Clinical information, demographic data, and medication adherence records of cancer pain patients were gathered from the Affiliated Hospital of Chengde Medical University between April 2020 and March 2023. The risk factors associated with analgesic medication nonadherence in cancer patients were analyzed using the least absolute selection operator (LASSO) regression model and multivariate logistic regression. Additionally, a nomogram model was developed. The bootstrap method was employed to internally verify the model. Discrimination and accuracy of the nomogram model were evaluated using the Concordance index (C-index), area under the receiver Operating characteristic (ROC) curve (AUC), and calibration curve. The potential clinical value of the nomogram model was established through decision curve analysis (DCA) and clinical impact curve. Results: The study included a total of 450 patients, with a nonadherence rate of 43.33%. The model incorporated seven factors: age, address, smoking history, number of comorbidities, use of nonsteroidal antiinflammatory drugs (NSAIDs), use of opioids, and PHQ-8. The C-index of the model was found to be 0.93 (95% CI: 0.907–0.953), and the ROC curve demonstrated an AUC of 0.929. Furthermore, the DCA and clinical impact curves indicate that the built model can accurately predict cancer pain patients' medication adherence performance. Conclusions: A nomogram model based on 7 risk factors has been successfully developed and validated for long-term analgesic management of cancer patients.

Abstract Temporal variation and fluctuation in environmental contamination in Futaba town and Okuma town, the location of the Fukushima Daiichi Nuclear Power Plant (FDNPP), were evaluated based on a car-borne survey conducted from October 2021 to November 2022. Although the environmental radioactivity in the interim storage facility area (ISF) was higher than that in open areas (i.e., the evacuation order lifted areas in Futaba town and the Specific Reconstruction and Regeneration Base area [SRRB] in Okuma town), only minor temporal changes were seen in the ambient dose and detection rate of radiocesium (the proportion of radiocesium detected points per all measuring points) in those areas, respectively. These findings suggest that the observed variations may result from physical decay and environmental remediation. Resuspension caused by human activities and weather could also affect the detection rate of radiocesium. The annual external effective doses in Futaba town and Okuma town were estimated to be at a limited level (< 1 mSv/year). Nevertheless, to help ensure the safety and future prosperity of residents and communities in the affected areas around the FDNPP, long-term follow-up monitoring of temporal exposure dose levels during the recovery and reconstruction phases is extremely important.

Abstract Background As a part of the decontamination process after the Fukushima Daiichi Nuclear Power Plant accident of 2011, 1.32 million tonnes of tritium-containing water will be discharged from the power plant into the Pacific Ocean. Although radiobiological impacts of the treated water discharge on the public and the environment were reported to be minimal, Tomioka and Okuma locals expressed unease regarding the long-term recovery of their towns, which are economically dependent on the agricultural, fishery, and tourism sectors. This study presents thoughts, perceptions and concerns of Tomioka and Okuma locals regarding the discharge of FDNPP-treated water containing tritium into the Pacific Ocean to facilitate a more inclusive decision-making process that respects local stakeholder interests. Methods Conducted from November to December 2022, surveys were mailed to current residents and evacuees aged 20 years or older registered with the town councils. Results Out of 1268 included responses, 71.5% were from those > 65 years. 65.6% were unemployed, 76.2% routinely visited hospitals, and 85.5% did not live with children. 61% did not want to return to Okuma/Tomioka. Anxiety about radiation-related health effects (38.7%), consuming food produced in Okuma/Tomioka (48.0%) and genetic effects (45.3%) were low. >50% reported poor physical and mental health. 40% were acceptive, 31.4% were unsure, and 29.7% objected to the discharge plans. Multinomial regression analysis revealed that, compared to acceptive responders, those who objected were more likely to be female, unemployed, and have anxiety about radiation-related genetic effects and poor mental health. Unsure responders were similarly more likely to be female, anxious about radiation-related genetic effects and have poor mental health. Conclusion The poor mental health of the locals, connected to high levels of risk perception and anxiety about the loss of economic opportunities related to the discharge plans, must be addressed. The 30-year discharge process could handicap local industries and hamper post-disaster socioeconomic recovery due to the circulation of false rumours among consumers. These results highlight the need to actively involve residents in the towns’ recovery process to address local concerns. The focus should be on the judicious combination of transparent science with the human aspect of recovery and narratives highlighting dialogues between local stakeholders and experts to enable the locals and the general public to make informed decisions about their protection and future.

Abstract Peutz–Jeghers Syndromeis a rare autosomal dominant genetic disease characterized by gastrointestinal hamartomatous polyps and skin and mucous membrane pigmentation. The pathogenesis of PJS remains unclear; however, it may be associated with mutations in the STK11 gene, and there is currently no effective treatment available. The gut microbiota plays an important role in maintaining intestinal homeostasis in the human body, and an increasing number of studies have reported a relationship between gut microbiota and human health and disease. However, relatively few studies have been conducted on the gut microbiota characteristics of patients with PJS. In this study, we analyzed the characteristics of the gut microbiota of 79 patients with PJS using 16 S sequencing and measured the levels of short-chain fatty acids in the intestines. The results showed dysbiosis in the gut microbiota of patients with PJS, and decreased synthesis of short-chain fatty acids. Bacteroides was positively correlated with maximum polyp length, while Agathobacter was negatively correlated with age of onset. In addition, acetic acid, propionic acid, and butyric acid were positively correlated with the age of onset but negatively correlated with the number of polyps. Furthermore, the butyric acid level was negatively correlated with the frequency of endoscopic surgeries. In contrast, we compared the gut microbiota of STK11-positive and STK11-negative patients with PJS for the first time, but 16 S sequencing analysis revealed no significant differences. Finally, we established a random forest prediction model based on the gut microbiota characteristics of patients to provide a basis for the targeted diagnosis and treatment of PJS in the future.

Abstracts AF6, a known polarity protein, contributes to the maintenance of homeostasis while ensuring tissue architecture, repair, and integrity. Mice that lack AF6 display embryonic lethality owing to cell–cell junction disruption. However, we show AF6 promotes necroptosis via regulating the ubiquitination of RIPK1 by directly interact with the intermediate domain of RIPK1, which was mediated by the deubiquitylase enzyme USP21. Consistently, while injection of mice with an adenovirus providing AF6 overexpression resulted in accelerated TNFα-induced necroptosis-mediated mortality in vivo, we observed that mice with hepatocyte-specific deletion of AF6 prevented hepatocytes from necroptosis and the subsequent inflammatory response in various liver diseases model, including non-alcoholic steatohepatitis (NASH) and the systemic inflammatory response syndrome (SIRS).Together, these data suggest that AF6 represents a novel regulator of RIPK1-RIPK3 dependent necroptotic pathway. Thus, the AF6-RIPK1-USP21 axis are potential therapeutic targets for treatment of various liver injuries and metabolic diseases.

By applying a microwave drive to a specially designed Josephson circuit, we have realized a double-well model system: a Kerr oscillator submitted to a squeezing force. We have observed, for the first time, the spectroscopic fingerprint of a quantum double-well Hamiltonian when its barrier height is increased: a pairwise level kissing (coalescence) corresponding to the exponential reduction of tunnel splitting in the excited states as they sink under the barrier. The discrete levels in the wells also manifest themselves in the activation time across the barrier which, instead of increasing smoothly as a function of the barrier height, presents steps each time a pair of excited states is captured by the wells. This experiment illustrates the quantum regime of Arrhenius’s law, whose observation is made possible here by the unprecedented combination of low dissipation, time-resolved state control, 98.5% quantum nondemolition single shot measurement fidelity, and complete microwave control over all Hamiltonian parameters in the quantum regime. Direct applications to quantum computation and simulation are discussed.

In order to meet the demand of the intelligent and efficient picking of fresh citrus fruit in a natural environment, a flexible and independent picking method of fresh citrus fruit based on picking pattern recognition was proposed. The convolutional attention (CA) mechanism was added in the YOLOv7 network model. This makes the model pay more attention to the citrus fruit region, reduces the interference of some redundant information in the background and feature maps, effectively improves the recognition accuracy of the YOLOv7 network model, and reduces the detection error of the hand region. According to the physical parameters of the citrus fruit and stem, an end-effector suitable for picking citrus fruit was designed, which effectively reduced the damage during the picking of citrus fruit. According to the actual distribution of citrus fruits in the natural environment, a citrus fruit-picking task planning model was established, so that the adaptability of the flexible handle can make up for the inaccuracy of the deep learning method to a certain extent when the end-effector picks fruits independently. Finally, on the basis of integrating the key components of the picking robot, a production test was carried out in a standard citrus orchard. The experimental results show that the success rate of the citrus-picking robot arm is 87.15%, and the success rate of picking in the natural field environment is 82.4%, which is better than the success rate of 80% of the market picking robot. In the picking experiment, the main reason for the unsuccessful positioning of citrus fruits is that the position of citrus fruits is beyond the picking range of the end-effector, and the motion parameters of the robot arm joint will produce errors, affecting the motion accuracy of the robot arm, leading to the failure of picking. This study can provide technical support for the exploration and application of the intelligent fruit-picking mode.

The lack of spatial pose information and the low positioning accuracy of the picking target are the key factors affecting the picking function of citrus-picking robots. In this paper, a new method for automatic citrus fruit harvest is proposed, which uses semantic segmentation and rotating target detection to estimate the pose of a single culture. First, Faster R-CNN is used for grab detection to identify candidate grab frames. At the same time, the semantic segmentation network extracts the contour information of the citrus fruit to be harvested. Then, the capture frame with the highest confidence is selected for each target fruit using the semantic segmentation results, and the rough angle is estimated. The network uses image-processing technology and a camera-imaging model to further segment the mask image of the fruit and its epiphyllous branches and realize the fitting of contour, fruit centroid, and fruit minimum outer rectangular frame and three-dimensional boundary frame. The positional relationship of the citrus fruit to its epiphytic branches was used to estimate the three-dimensional pose of the citrus fruit. The effectiveness of the method was verified through citrus-planting experiments, and then field picking experiments were carried out in the natural environment of orchards. The results showed that the success rate of citrus fruit recognition and positioning was 93.6%, the average attitude estimation angle error was 7.9°, and the success rate of picking was 85.1%. The average picking time is 5.6 s, indicating that the robot can effectively perform intelligent picking operations.

The accuracy and interpretability of artificial intelligence (AI) are crucial for the advancement of optical coherence tomography (OCT) image detection, as it can greatly reduce the manual labor required by clinicians. By prioritizing these aspects during development and application, we can make significant progress towards streamlining the clinical workflow. In this paper, we propose an explainable ensemble approach that utilizes transfer learning to detect fundus lesion diseases through OCT imaging. Our study utilized a publicly available OCT dataset consisting of normal subjects, patients with dry age-related macular degeneration (AMD), and patients with diabetic macular edema (DME), each with 15 samples. The impact of pre-trained weights on the performance of individual networks was first compared, and then these networks were ensemble using majority soft polling. Finally, the features learned by the networks were visualized using Grad-CAM and CAM. The use of pre-trained ImageNet weights improved the performance from 68.17% to 92.89%. The ensemble model consisting of the three CNN models with pre-trained parameters loaded performed best, correctly distinguishing between AMD patients, DME patients and normal subjects 100% of the time. Visualization results showed that Grad-CAM could display the lesion area more accurately. It is demonstrated that the proposed approach could have good performance of both accuracy and interpretability in retinal OCT image detection.

Liver transplantation is the most effective treatment for end-stage liver diseases. However, the shortage of donor livers severely restricts the application of liver transplantation, and the impairments of liver function caused by intraoperative ischemia reperfusion injury and postoperative immune rejection also significantly affect the therapeutic efficacy. In order to improve the shortage of donor livers and further improve the efficacy of liver transplantation, a variety of cell therapies based on stem cells or somatic cells have been tried to repair and improve donor liver function. At present, the time points for cell therapy can be divided into the stage before procurement of donor livers, machine perfusion stage and stage after reperfusion of donor livers. In this review, we summarize the efficacy and the underlying mechanisms of cell therapy in the preservation and function repair of donor livers, so as to facilitate the application and promotion of cell therapy in the field of liver transplantation.

Cu–Al2O3–TiB2 is an important high-performance dual-phase dispersion strengthened copper alloy. The problem of serious coarseness and agglomeration of TiB2 and Al2O3 particles is a bottleneck that restricts the preparation of high-performance Cu–Al2O3–TiB2 alloys by traditional liquid-phase in-situ reaction method. In this paper, an idea of combining the split cavity melting of complex reactants and efficient solidification of melt was proposed, and a new liquid phase in-situ reaction technology for dual-phase strengthened metal matrix composites was invented. Compared with the traditional liquid phase in-situ reaction method, the strengthening particles in the Cu-0.75Al2O3-0.75TiB2 (wt.%, nominal composition) prepared by the new liquid phase in-situ reaction technology were more uniform, and the tensile strength and hardness were significantly improved. Large-deformation cold rolling can improve distribution of particles. With the increase of deformation, the main deformation mode of the composite changed from matrix plastic deformation to matrix-particle shear deformation, with the main fracture mechanism changing from particle-matrix interface fracture to particle shear fracture. The new liquid phase in-situ reaction technology effectively solved the problem of particle coarsening and agglomeration in Cu–Al2O3–TiB2 composites. The new liquid phase in-situ reaction technology combined with large deformation is a new process with high efficiency and short flow for preparing dual-phase dispersion strengthened copper alloys.

Abstract Proteolysis is the rate-limiting step in the mineralization of organic nitrogen into ammonium (NH4 +) and thereby the ammonia (NH3) released during the composting. However, the dynamics of bacterial proteolytic communities related to NH3 emissions during the composting systems are mostly unknown. This study aimed to examine and compare the effects of hyperthermophilic pretreatment composting (HPC) and traditional composting (TC) methods on (i) the difference of NH3 loss and nitrogenous compounds; (ii) the dynamics of the proteolytic bacterial community involved in the proteolysis and (iii) the correlation between the proteolytic bacterial community, biophysiochemical characteristics and NH3 loss. Results revealed that the HPC decreased NH3 loss by 42% as compared to TC during 60-day composting period. This was accompanied with an inhibitory effect on protease activity in the HPC where the relative abundances of the proteolytic bacteria (Bacillus megaterium and Staphylococcus cohnii) were reduced significantly as compared to TC. Partial least-squares path modeling suggested that various physicochemical properties such as higher temperature as well as lower C/N ratio during composting played a dominant role in affecting the abundance of proteolytic bacteria, which may have been an important factor contributing to the lower NH3 loss in HPC. All these findings lead us to conclude that the HPC can significantly reduce NH3 loss by inhibiting the proteolytic bacteria and protease activity responsible for NH3 release. Graphical Abstract

The optimal combination of the nitrogen fertilizer application and planting density with reference to the silage maize yield and quality remains unclear. We hypothesized that increasing both would increase yields following the law of diminishing returns. Yayu26, a silage maize cultivar, was used in a split-plot experiment to investigate the effects of nitrogen fertilizer and planting density on growth, nutrient characteristics, and chlorophyll fluorescence. The main plots were assigned to three planting densities: 60,000 (A1), 75,000 (A2), and 90,000 (A3) plants hm−2, and the subplots were assigned to four nitrogen fertilizer rates: 0 (B1), 120 (B2), 240 (B3), and 360 (B4) kg hm−2. The results showed that increasing the nitrogen application rate and planting density both enhanced silage maize yield. Nitrogen accumulation and agronomic use efficiency peaked at a planting density of 75,000 hm−2. Structural equation modeling showed that the nitrogen application rate and planting density affected nitrogen accumulation and nutrient properties by influencing chlorophyll fluorescence parameters and nitrogen agronomic efficiency, ultimately resulting in a positive effect on the yield. The A3 × B2 treatments exhibited higher nitrogen accumulation, potentially compensating for any deficiencies in the dry-matter yield. Therefore, the A3 × B2 treatment was evaluated as the optimal treatment to achieve sustainable and economically feasible silage maize production.

This study was envisaged to identify a strain of bacteria isolated from the gill of mandarin fish. Identification and characterization of the bacterial strain were performed using morphological characteristics, growth temperature, physiological and biochemical tests, antibiotic sensitivity tests, artificial infection tests, and 16S rRNA gene sequencing homology analysis. The results showed that the bacterium was Gram-negative, with flagella at the end and the side. The bacterium exhibited a light brownish-gray colony on the Luria-Bertani culture and white colony on the blood agar plate without hemolytic ring. Normal growth was achieved at 42°C, and growth could be delayed in 7% NaCl broth medium. By homology comparison and analysis, the phylogenetic tree was constructed using MEGA7.0, and the bacterium was preliminarily identified as Achromobacter. The antibiotic sensitivity test showed that the strain was sensitive to piperacillin, carbenicillin, cefoperazone, cefazolin, ofloxacin, gentamicin, kanamycin, amikacin, neomycin, erythromycin, minocycline, doxycycline, polymyxin B, tetracycline, chloramphenicol, and other drugs. However, it was resistant to penicillin, ampicillin, oxacillin, ceftriaxone, cefradine, cefalexin, cefuroxime sodium, ciprofloxacin, norfloxacin, vancomycin, compound sulfamethoxazole, clindamycin, medimycin, and furazolidone.

Objective To investigate the effect of isoprene cysteine carboxymethyltransferase (ICMT) gene on the migration and invasion of salivary adenoid cystic cancer cells (SACC) and the related mechanism, to provide experimental evidence for molecular targeted therapy of SACC. Methods Adenoid cystic cancer cells SACC-LM and SACC-83 were cultured in vitro, and siRNA was transfected into human SACC-LM and SACC-83 cells (experimental group) by transient transfection of a liposome vector. A blank control group and negative control group were set up respectively (transfected NC-siRNA). qRT-PCR was peformed to measure the mRNA expression of ICMT and RhoA in each group after transfection and to determine the silencing efficiency. The expression of ICMT, membrane RhoA, total RhoA, matrix metalloproteinase-2 (MMP-2), matrix metalloproteinase-9 (MMP-9) and Rho associated with coiled helical binding protein kinase 1 (ROCK1) in each group was detected by Western blot. The proliferation abilityies of SACC cells was detected by CCK-8 assay. The migration and invasion ability of SACC cells were detected by comparing the relative healing area of cell scratch assay and the number of Transwell assay cells. Results After transfection of ICMT-siRNA into SACC-LM and SACC-83 cells, the expression of ICMT gene and protein in the experimental group was significantly decreased compared with the negative control group and blank control group (P0.05). The expression of RhoA membrane proteins, ROCK1, MMP-2, MMP-9 in the experimental group was significantly decreased compared with that in the negative control group and blank control group (P

Objectives To assess the current evidence on the potential of digital health interventions (DHIs) to improve adherence to oral antipsychotics among patients with schizophrenia by assessing the methodologies, feasibility and effectiveness of DHIs as well as the perceptions of relevant stakeholders.Design The scoping review was conducted based on the methodologies outlined by Levac et al and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines.Data sources PubMed, Embase, Web of Science, Scopus, CINAHL, PsycINFO and the Cochrane Library were searched in August 2023 to identify relevant publications from the previous decade.Eligibility criteria Studies published in English focused on improving medication adherence among adult patients with schizophrenia or schizoaffective disorder via DHIs were selected. Protocols, editorials, comments, perspectives, reviews, correspondence and conference abstracts were excluded.Data extraction and synthesis The extracted data included general information about the study, framework, participants, features and strategies of DHIs, measurement tools for adherence used, and main findings.Results In total, 64 studies were included in the qualitative synthesis. Features used in DHIs to improve medication adherence included phone calls, text messages, mobile apps, sensors, web-based platforms and electronic devices. Strategies included medication reminders and monitoring, providing medication-related information and suggestions, other illness management suggestions and individual support. Texting and mobile apps were commonly used as medication reminders and monitoring methods. Additionally, the use of sensors combined with other digital technologies has garnered significant attention. All the interventions were considered acceptable and feasible, and several were assessed in pilot trials. Preliminary findings suggest that DHIs could enhance medication adherence in patients with schizophrenia. However, further validation of their effectiveness is required.Conclusion DHIs are a promising approach to enhancing medication adherence among patients with schizophrenia. Future interventions should be interactive, focusing on user preference, experience and privacy.

Non-steroidal anti-inflammatory drugs (NSAIDs) are widely used in human and animal health care to reduce persistent inflammation, pain and fever because of their anti-inflammatory, analgesic and antipyretic effects. However, the improper discharge and disposal make it becomes a major contaminant in the environment, which poses a big threat to the ecosystem. For this reason, accurate, sensitive, effective, green, and economic techniques are urgently required and have been rapidly developed in recent years. This review summarizes the advancement of sample preparation technologies for NSAIDs involving solid-phase extraction, solid-phase microextraction, liquid-phase microextraction, QuEChERS, and matrix solid-phase dispersion. Meanwhile, we overview and compare analytical technologies for NSAIDs, including liquid chromatography-based methods, gas chromatography-based methods, capillary electrophoresis, and sensors, particularly the development of liquid chromatography-based methods. Furthermore, we focus on their progress and conduct a comparison between their advantages and disadvantages.

Abstract Lung cancer is one of the most prevalent malignant tumors worldwide, with lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) accounting for the majority of cases. Cuproptosis, tumor immune microenvironment (TIME) and long non-coding RNA (lncRNA) have been demonstrated to be associated with tumorigenesis. The objective of the present study was to develop a novel cuproptosis-related lncRNA signature to assess the association between cuproptosis and TIME in patients with LUAD or LUSC and to predict prognosis. Based on the outputs of the least absolute shrinkage and selection operator regression model, a cuproptosis-related lncRNA signature was developed. Kaplan–Meier survival curves were generated to confirm the predictive ability of the signature. Univariate and multivariate analysis was also performed to determine the association between overall survival and this signature and other clinical characteristics, and a nomogram was created. Additionally, the relationship between the signature, TIME, tumor mutation burden and m6A methylation was established. The results of the present study revealed that 8 cuproptosis-related lncRNAs were associated with the prognosis of patients with LUAD and LUSC. This novel cuproptosis-related lncRNA signature is associated with TIME and m6A methylation in LUAD and LUSC and can predict prognosis with accuracy.

Parametric gates and processes engineered from the perspective of the static effective Hamiltonian of a driven system are central to quantum technology. However, the perturbative expansions used to derive static effective models may not be able to efficiently capture all the relevant physics of the original system. In this work, we investigate the conditions for the validity of the usual low-order static effective Hamiltonian used to describe a Kerr oscillator under a squeezing drive. This system is of fundamental and technological interest. In particular, it has been used to stabilize Schrödinger cat states, which have applications for quantum computing. We compare the states and energies of the effective static Hamiltonian with the exact Floquet states and quasi-energies of the driven system and determine the parameter regime where the two descriptions agree. Our work brings to light the physics that is left out by ordinary static effective treatments and that can be explored by state-of-the-art experiments.

Nasopharyngeal carcinoma is one of the common malignant tumors that the pathogenesis has not yet been completely defined. SETD1A (histone lysine methyltransferase SET domain-containing 1A) is related to the occurrence of various cancers. However, the role of SETD1A in nasopharyngeal carcinoma remains unclear. The SETD1A overexpression vector, si-NC, si-SETD1A#1, and si-SETD1A#2 were transfected into nasopharyngeal carcinoma cells to overexpress or knockdown SETD1A expression. The assay of biofunction was used to explore the role of SETD1A in nasopharyngeal carcinoma cells. The assay of glucose uptake, lactate release, ATP level, western blot, cell proliferation, and cellular apoptosis analysis were performed to investigate the potential mechanism of SETD1A regulation in nasopharyngeal carcinoma. This study was the first to show that SETD1A was upregulated in nasopharyngeal carcinoma cells and the overexpression of SETD1A significantly promoted the cell proliferation and glycolysis and suppressed the cellular apoptosis. Moreover, SETD1A enhances aerobic glycolysis and cell biological function of nasopharyngeal carcinoma cells via PI3K/AKT signaling pathway. SETD1A induced PI3K/AKT activation and subsequently prevented cellular apoptosis. In conclusion, this study identified overexpressed SETD1A as a positive regulator of proliferation that induced nasopharyngeal carcinoma cells’ aerobic glycolysis via PI3K/AKT signaling activation in vitro. This study laid a strong foundation for unveiling the precise anticancer mechanism of SETD1A. The SETD1A may become a novel biomarker for further inhibitor design to obstruct the PI3K/AKT-dependent nasopharyngeal carcinoma progression.

Interlayer spacing and termination are important for controlling the physical and chemical properties of MXenes, largely affecting their potential applications. Here authors present a general approach for simultaneously tuning the interlayer spacing and termination of MXenes using Lewis-basic halides.

Percolation, describing critical behaviors of phase transition in a geometrical context, prompts wide investigations in natural and social networks as a fundamental model. The introduction of quantum coherence and superposition brings percolation into quantum regime with more fascinating phenomena and unique features, which, however, has not been experimentally explored yet. Here we successfully map these large-scale porous structures into a photonic chip using femtosecond laser direct writing techniques and present an experimental demonstration of quantum transport in hexagonal percolation lattices, probed by coherent light. A quantum percolation threshold of 80% is observed in the prototyped laser-written lattices with up to 1,600 waveguides, which is significantly larger than the classical counterpart of 63%. We also investigate the spatial confinement by localization parameters and exhibit the transition from ballistic to diffusive propagation with the decrease of the occupation probability. Direct observation of quantum percolation may deepen the understanding of the relation among materials, quantum transport, geometric quenching, disorder and localization, and inspire applications for quantum technologies.

Xiao, Guo et al. use imaging mass cytometry to evaluate the spatial composition of the tumor microenvironment in melanoma. The authors identify features of the microenvironment associated with response to anti-PD-1 immunotherapy.

A major challenge for the effective use of Ti-based MXenes in applications with harsh environmental conditions is their poor resistance to oxidation. Here, authors report an air-stable Ti3C2T x composite with extracted bentonite able to endure high-temperature annealing in air by an oxygen adsorption competition mechanism.

Abstract Brain metastasis (BM) frequently occurs in advanced non-small cell lung cancer (NSCLC) and is associated with poor clinical prognosis. Due to the location of metastatic lesions, the surgical resection is limited and the chemotherapy is ineffective because of the existence of the blood brain barrier (BBB). Therefore, it is essential to enhance our understanding about the underlying mechanisms associated with brain metastasis in NSCLC. In the present study, we explored the RNA-Seq data of brain metastasis cells from the GEO database, and extracted RNA collected from primary NSCLC tumors as well as paired brain metastatic lesions followed by microRNA PCR array. Meanwhile, we improved the in vivo model and constructed a cancer stem cell-derived transplantation model of brain metastasis in mice. Our data indicated that the level of miR-596-3p is high in primary NSCLC tumors, but significantly downregulated in the brain metastatic lesion. The prediction target of microRNA suggested that miR-596-3p was considered to modulate two genes essential in the brain invasion process, YAP1 and IL-8 that restrain the invasion of cancer cells and permeability of BBB, respectively. Moreover, in vivo experiments suggested that our model mimics the clinical aspect of NSCLC and improves the success ratio of brain metastasis model. The results demonstrated that miR-596-3p significantly inhibited the capacity of NSCLC cells to metastasize to the brain. Furthermore, these finding elucidated that miR-596-3p exerts a critical role in brain metastasis of NSCLC by modulating the YAP1-IL8 network, and this miRNA axis may provide a potential therapeutic strategy for brain metastasis.

To clarify the soil nutrient status and identify the safety risks of heavy metals in Camellia oleifera planting regions, the integrated soil fertility status was assessed using the improved Nemero composite index method, weighted average method, and coefficient of variation (CV) method, and the impact of heavy metals in the soil on human health was evaluated with a health risk assessment model using the Qianyu C. oleifera planting base in Yuping County, Guizhou Province, as the study object. The results showed the following: (1) The soil pH levels were 4.12–6.17, with CV values of 0.04–0.66, and no significant differences were observed among the plots. The soil was rich in organic matter, alkali-hydrolyzed nitrogen, and available phosphorus, with a high total potassium content, total phosphorus content, and rapidly available potassium, indicating a high level of comprehensive soil fertility. (2) The total carcinogenic risk (CR) index of the arsenic (As), cadmium (Cd), and chromium (Cr) in the soil was 1.92 × 10−7, and among these elements, the CR index of the As was the highest (1.3–8.0 × 10−7), but all were below the highest acceptable level (10−6) recommended by the United States Environmental Protection Agency (USEPA). (3) The redundancy analysis (RDA) between the soil fertility and trace elements revealed that the soil organic matter content was positively correlated with the contents of lead (Pb), manganese (Mn), and Cr and negatively correlated with the contents of zinc (Zn), iron (Fe), Cd, mercury (Hg), As, and copper (Cu). The soil pH was positively correlated with the contents of Cr, Fe, and Cu and negatively correlated with the contents of Mn, Pb, Zn, Cd, Hg, and As. In the study area, the soil was slightly acidic with overall high fertility without any CR. The quality of the C. oleifera was degraded by soil acidification, but the slightly acidic soil facilitated the absorption of trace elements by C. oleifera. Soil acidification could be relieved by taking appropriate measures, such as the addition of biochar or CaCO3. This study determined the soil fertility of the Qianyu C. oleifera planting base and assessed the health risk of heavy metals in the soil, providing a theoretical reference for enhancing C. oleifera quality, preventing the excessive accumulation of soil heavy metals, and improving the soil in this planting base.

Metabolic syndromes (Mets) is a high-risk factor for a series of cardiovascular diseases. Changes in iodine nutritional status can directly mediate the occurrence of insulin resistance, affect glucose and lipid metabolism and the regulation of blood pressure and also,may contribute to the pathogenesis of Mets by regulating thyroid function. Exploring the role of iodine in the occurrence and development of Mets can provide new ideas for the prevention and treatment of Mets.

The ever-growing demands for renewable energy sources motivate the development of energy storage systems. Among them, supercapacitors are received increasing attention due to their high power density, long cycle life, fast recharge rate, and almost no maintenance. Nevertheless, their application is hindered by severe self-discharge behaviors, especially in wearable and energy storage devices. In recent years, tremendous excellent works have been reported to conquer this shortcoming through various creative strategies. Herein, we gives a timely spotlight on breakthroughs in the self-discharge mechanism investigations of supercapacitors and the corresponding suppression strategies. The self-discharge mechanisms of various supercapacitors were introduced first, followed by a summary of the strategies from materials (i.e., electrode, electrolyte, and separator) to system and protocol optimization, furthermore, the connection between them, existing issues, and possible directions for future research are discussed.

Geodorum eulophioides is a unique and endangered species belonging to the Orchidaceae family in China. It has great potential as an ornamental horticultural plant. However, little is known about its genetic diversity and reasons for being endangered due to its narrow distribution and few populations in the wild. To effectively evaluate and conserve available resources, the genetic diversity and population structure of G. eulophioides were analyzed in this study. A total of 94 individuals from 10 natural populations were studied using site-specific amplified fragment sequencing (SLAF-seq). Based on the 76,340 SNPs detected by SLAF-seq, genetic diversity analysis was performed and markers associated with environmental variables were determined. The results showed that the level of genetic diversity in the 10 natural populations studied was low, with PIC values ranging from 0.1874 to 0.2156. FIS values ranged from −0.2376 to 0.2658, with excess and deficiency in heterozygotes. FST values ranged from 0.0482 to 0.3144, with genetic variation among populations. AMOVA results showed that the genetic variation among populations accounted for 21.35% of the total variation, and the remaining genetic variation among individuals within populations was 78.65%. The results of the population structure analysis showed that 94 individuals were classified into three major groups and two subgroups. Environmental association analysis using Bayenv2 and LFMM yielded thirty and eighteen putative adaptive loci, respectively, and five specific functional genes were annotated. In summary, this study provides further insight into the genetic structure of G. eulophioides and provides a reference for protection and restoration.

A self-tuning fuzzy PID grab force control algorithm was designed to solve the problems of linear elastic deformation and reduced grab force of rope driven robot hand, which easily causes shake and slip of grab target. Firstly, the mathematical models of rope driven manipulator and DC motor based on force control were established, and the order of the control system model was reduced by Padé algorithm. Secondly, the fuzzy technology was combined with PID control, and a self-tuning fuzzy PID controller was designed through the fuzzy control toolbox of Matlab. Finally, the simulation models of PID control, fuzzy control and self-tuning fuzzy PID control were established by using Simulink environment, and the grasping force control simulation of different algorithms was realized. The simulation results show that the algorithm can make the system reach a stable state within 0.5 s, and the steady-state error is less than 0.5%. When the rope rebounds, it can compensate the grasping force within 0.3 s, and has good dynamic performance, which meets the requirements of stable grasping of the target.

In recent years, deep-learning detection algorithms based on automatic feature extraction have become the focus of defect detection. However, limited by industrial field conditions, the insufficient number of images in the collected dataset restricts the detection effect of deep learning. In this paper, an algorithm of strip steel defect classification using the improved GAN and EfficientNet was proposed. First, the label deconvolution network is constructed, where the image labels were deconvolved layer by layer to obtain the conditional masks that were superimposed into the generator and discriminator to form Mask-CGAN. Then, the mode-seeking generative adversarial networks (MSGAN) were improved and used to solve the problem of mode collapse. Finally, the EfficientNet was improved and trained on the dataset expanded by Mask-CGAN, which achieved the classification of strip steel defects. Experiments showed that Mask-CGAN proposed in this paper can generate true-to-life images and solve the problem of insufficient samples in deep learning. The improved EfficientNet with fewer parameters can accurately and efficiently classify strip steel defects.

ABSTRACT In order to provide the basis for the design and control of a citrus picking robot clamp and cutter, and find the optimal combination of cutting parameters, this study used a self-made citrus stem cutting test-bed to study the effects of the citrus stem diameter, blade cutting speed, blade cutting clearance, and tool sliding cutting angle on the peak cutting force of citrus stems through a single-factor experiment. Based on the single-factor test, the blade cutting speed, blade cutting clearance, and tool sliding angle are selected as the influencing factors, and a multi-factor test is carried out with the target of the peak cutting force, and the regression model is established. The results showed that the peak cutting force increased linearly with the diameter of the fruit stalk, decreased with the increase of the blade cutting speed and sliding cutting angle, and first decreased and then increased with the increase of the blade cutting clearance. Through the optimisation analysis of the regression model, it is found that the optimal cutting parameter combination is the blade cutting speed of 40 mm/min, blade cutting gap of 1 mm, tool sliding cutting angle of 20°, and the peak cutting force under this combination is 168.23 N. The deviation between the predicted value of the peak cutting force and the measured value is less than 2%, and the optimisation result of the cutting parameters is reliable. This study provides a theoretical basis for the optimal design and control of the clamping and cutting mechanism of the citrus picking robot.

The current forensic research on heaps mainly extracts information from the heap of Linux and the NT heap of Windows. However, the study of how to extract the information on the segment heap in the Windows 10 from dump files is not sufficient. To reproduce the internal information on the segment heap, this paper proposes a method for locating and extracting the internal information on the segment heap in the Windows 10 according to the field offset in the vtype description information of memory object. The method uses the pool scanning technology to locate the process object, obtains the starting position of the process heap and scans the process heap according to the structural information on the process object and the process environment block object. Then it locates the position of the segment heap with its feature values, thereby extracting its internal information. Based on the analysis results, five forensic plugins for extracting the information on the segment heap were developed on the Volatility framework. The experimental results show that this method can effectively extract the information on the address of each segment heap and its internal components in the memory and on the size of committed memory, etc. The information can help investigators to analyze the digital traces left in the memory by cyber criminals or cyber attackers.

Camellia leyeensis Chang ＆ Y. C. Zhong is a plant belonging to the genus Camellia. To determine its correct taxonomic status and better understand its molecular phylogenetic and genetic diversity, we studied the chloroplast genome of this species. Here, we report and characterize the complete chloroplast (cp) genome of C. leyeensis by using Illumina paired-end sequencing data. The chloroplast genome was determined to be 157,063 bp in length with a GC content of 37.30%. The genome contained 136 genes, including 91 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. The sequence contained a large single-copy region (LSC, 86,661 bp), a small single-copy region (SSC, 18,284 bp), and two inverted repeat sequences (IRs, 26,059 bp, each). The GC content of the IR regions (42.96%) was higher than that of the SSC region (30.6%) and LSC region (35.31%). Phylogenetic analysis suggested that Camellia leyeensis is closely related to C. anlungensis with 96% bootstrap support. This chloroplast genome would be helpful for the phylogeny and conservation of Camellia.