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Summary: Background: Surgical treatment for a benign or low-grade malignant tumor in the pancreatic head remains a challenge at present. As an organ-sparing procedure, enucleation is ideal. However, it is still controversial whether laparoscopic enucleation (LapEN) can be safely performed for a pancreatic head tumor, especially a deeply embedded one. Methods: The cases who underwent LapEN of a pancreatic tumor from January 2014 to September 2022 in our hospital were collected and analyzed. Results: A total of 151 cases were collected. The incidence of pancreatic fistula (PF, grade B) was 21.9 %. No patient developed PF (grade C) or died. Compared with enucleating a tumor in the distal pancreas (N = 98), enucleating a tumor in the pancreatic head (N = 53) showed a longer operation time and a higher incidence of conversion. The cases with a tumor in the pancreatic head were then divided into the group with a deeply embedded tumor (N = 32) and the group with a superficial tumor (N = 21). The embedded group had a smaller tumor size and a higher proportion of insulinoma. There were no statistical differences in the parameters of operation time, blood loss and incidence of complications between the two groups. The outcomes of enucleating a tumor deeply embedded in the proximal and distal pancreas were further analyzed, which indicated no statistical differences in clinical parameters between the two groups. Conclusion: LapEN of a tumor in the pancreatic head is feasible and safe, even for a deeply embedded tumor.

Abstract A large-scale shaking table test of a living stump slope with a geometric similarity ratio of 1:7 was designed and completed. The peak acceleration, acceleration amplification factor, and displacement response patterns of living stumps slopes under different types of seismic waves and excitation intensities were obtained. The time-frequency and energy variation characteristics were analyzed using the Hilbert-Huang Transform (HHT). The results showed that: (1) Regardless of the type of seismic wave, the peak acceleration and acceleration amplification factor of the living stumps slope surface are positively correlated with relative height and seismic excitation intensity. When the excitation intensity is ≤ 0.4 g, the acceleration amplification effect is more pronounced; when the excitation intensity is > 0.4 g, the acceleration amplification effect weakens. (2) Under the action of different seismic waves, the peak displacement of slope surface shows amplification effect along the elevation, and increases with the increase of excitation intensity. In addition, the incremental displacement gradually decreases from the toe to the top of the slope, which is expressed as D2 > D3 > D1 > D4 > D5. The peak displacement at the top of the slope is the greatest, but the incremental displacement is the smallest; the peak displacement at the toe of the slope is the smallest, but the incremental displacement is relatively large. (3) Regardless of the type of seismic wave, living stumps slope shows the characteristics of filtering the low-frequency components of the seismic waves and amplifying their high-frequency components. At the same time, the seismic Hilbert energy gradually accumulates along the elevation. PSHEA and PMSA significantly increase with elevation and excitation intensity, and they reach the maximum at the top of the slope. (4) The seismic Hilbert energy is positively correlated with the relative height and excitation intensity, and reaches the maximum at the top of the slope. With the accumulation of seismic Hilbert energy increases, the dynamic response parameters such as peak acceleration, acceleration amplification coefficient and displacement also increase synchronously, reaching the maximum at the top of the slope. The research conclusions can provide an experimental basis for the seismic design of living stumps slopes.

The global-scale production of plastics has led to a significant accumulation in the environment, and it has become a major stressor to environmental sustainability, agricultural crops, and human health. Here we report the particle size effect of polystyrene (PS, typically microplastic) on the impact on rice suspension cells. This study used PS of different particle sizes (30 nm, 200 nm, and 2 μm) in a three-day co-culture experiment, the results showed that 30 nm, 200 nm, and 2 μm PS at the same concentration (100 μg/mL) caused 4.6 %, 55.8 %, and 66.4 % decrease in rice suspension cell viability, respectively. Furthermore, a substantial reduction in protein content, amounting to 26.53 % and 48.47 %, was observed in cells treated with 200 nm and 2 μm PS, and the DNA and RNA content of rice suspension cells also decreased substantially at 100 μg/mL PS. Non-targeted metabolomics analyses showed that PS disrupted fatty acid biosynthesis with a clear size effect, wherein 2 μm PS caused a decrease of 64.9 % in hexadecanoic acid content. Consequently, this finding provides valuable perspectives on the potential ecotoxicity of microplastics at the single-cell level of rice and will facilitate the formulation of an environmental management program specifically tailored for addressing the challenges posed by microplastics.

Chilled chicken is inevitably contaminated by microorganisms during slaughtering and processing, resulting in spoilage. Cutting parts of chilled chicken, especially wings, feet, and other skin-on products, are abundant in collagen, which may be the primary target for degradation by spoilage microorganisms. In this work, a total of 17 isolates of spoilage bacteria that could secrete both collagenase and lipase were determined by raw-chicken juice agar (RJA) method, and the results showed that 7 strains of Serratia, Aeromonas, and Pseudomonas could significantly decompose the collagen ingredients. The gelatin zymography showed that Serratia liquefaciens (F5) and Pseudomonas saponiphila (G7) had apparent degradation bands around 50 kDa, and Aeromonas veronii (G8) and Aeromonas salmonicida (H8) had a band around 65 and 95 kDa, respectively. The lipase and collagenase activities were detected isolate-by-isolate, with F5 showing the highest collagenase activity. For spoilage ability on meat in situ, F5 performed strongest in spoilage ability, indicated by the total viable counts, total volatile basic nitrogen content, sensory scores, lipase, and collagenase activity. This study provides a theoretical basis for spoilage heterogeneity of strains with high-producing collagenase in meat.

Abstract Domesticated herbivores are an important agricultural resource that play a critical role in global food security, particularly as they can adapt to varied environments, including marginal lands. An understanding of the molecular basis of their biology would contribute to better management and sustainable production. Thus, we conducted transcriptome sequencing of 100 to 105 tissues from two females of each of seven species of herbivore (cattle, sheep, goats, sika deer, horses, donkeys, and rabbits) including two breeds of sheep. The quality of raw and trimmed reads was assessed in terms of base quality, GC content, duplication sequence rate, overrepresented k-mers, and quality score distribution with FastQC. The high-quality filtered RNA-seq raw reads were deposited in a public database which provides approximately 54 billion high-quality paired-end sequencing reads in total, with an average mapping rate of ~93.92%. Transcriptome databases represent valuable resources that can be used to study patterns of gene expression, and pathways that are related to key biological processes, including important economic traits in herbivores.

Enzyme-induced carbonate precipitation (EICP) technology was used to cement calcareous sand. Consolidated drained triaxial compression tests were conducted to investigate the mechanical properties of EICP-cemented calcareous sand (EICP-S) and EICP-cemented calcareous sand mixed with coir fiber (EICP-FS) under varying levels of cementation and confining pressures. Based on the stress-strain curves, a brittleness evaluation index (BEICP) suitable for cemented calcareous sand was developed. The research results indicate: (1) The EICP technique exhibits a pronounced cementation effect on calcareous sand. With the number of grouting operations escalating from 1 to 9, or the confining pressure incrementing from 100 kPa to 300 kPa, the peak deviatoric stress of the cemented mass progressively improves. Furthermore, the EICP-FS specimens display a higher strain at failure and demonstrate a more gradual post-peak stress reduction characteristic. (2) At low cementation levels, coir fiber can effectively enhance the peak deviatoric stress of the samples. However, the enhancement effect diminishes at high cementation levels, and the peak deviatoric stress of the EICP-FS samples can even be lower than that of the EICP-S samples without fiber. (3) At low cementation levels, coir fiber can effectively mitigate the post-peak strength loss of the cemented body. However, this mitigating effect diminishes at high cementation levels. (4) Parameters such as the pre-peak elastic energy ratio, failure strain, maximum post-peak average modulus, peak deviatoric stress, and residual stress of the cemented calcareous sand highly correlate with its brittleness characteristics. The brittleness evaluation index (BEICP) constructed based on these parameters can effectively evaluate its brittleness properties. (5) Under different confining pressures, the BEICP of EICP-FS samples is generally lower than that of EICP-S samples. However, under higher confining pressure conditions, the BEICP values of both types of samples are similar. The research results can provide a theoretical basis for a deeper understanding of the brittleness characteristics of calcareous sand treated with EICP technology and can serve as a reference for brittleness evaluation in related engineering applications.

BackgroundMore and more patients with pancreatic cancer (PC) received neoadjuvant therapy (NAT) and then underwent radical pancreatectomy. However, the benefit of adjuvant chemotherapy (AC) for these patients is still controversial. This study is designed to determine the benefits of postoperative AC for patients with PC undergoing NAT and radical resection.MethodsWe conducted a comprehensive search of the PubMed, Embase, Web of Science, and Cochrane Library databases, covering the period from their inception until 10 September 2023. Our analysis focused on the assessment of overall survival (OS) and recurrence-free survival (RFS) through meta-analysis. The fixed-effects model and the random-effects model were used to process the data. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were employed to determine the necessary of administering AC for patients with PC who have undergone NAT and radical resection. We retrieved 3,063 search results, of which 3,048 were excluded because of duplication or after applying our inclusion and exclusion criteria.ResultsA total of 15 studies with 21,113 patients (7,794 patients in the AC group and 13,319 in the non-AC group) were included, all of which reported OS, and three studies reported disease-free survival (DFS)/tumor-specific survival (CSS)/RFS. The final results showed that AC significantly improved OS and DFS/CSS/RFS in patients with PC who underwent pancreatectomy after NAT [OS: HR = 0.80, 95% CI (0.75∼0.86), P < 0.00001, I2 = 48%; DFS/CSS/RFS: HR = 0.53, 95% CI (0.41~0.69), P < 0.00001, I2 = 0%]. Furthermore, we performed subgroup analyses and demonstrated that AC provided a significant survival benefit for patients with PC after NAT and resection regardless of the tumor size [

In the development of new electrochemical concepts for the fabrication of high-energy-density batteries, fluoride-ion batteries (FIBs) have emerged as one of the valid candidates for the next generation electrochemical energy storage technologies, showing the potential to match or even surpass the current lithium-ion batteries (LIBs) in terms of energy density, safety without dendritic grains, and elimination of dependence on scarce lithium and cobalt resources. However, the development of FIBs is still in its infancy and their performance is far from satisfactory, with issues such as the lower fluoride-ion conductivity of the electrolytes and the reversibility of the electrodes hindering their commercialization. Previous reviews have mainly focused on inorganic solid electrolytes with a brief emphasis on the development of various fluoride-ion conductors and their ion-conducting properties. Therefore, this review summarizes the current developments in various electrolytes, a systematic overview of the current progress for various fluoride-ion electrolytes is presented by beginning with the history, structure and classification of FIBs, ion-transport mechanisms are briefly discussed. Recent advances in different classes of fluoride-ion electrolytes are described. The methods for optimizing the ionic conductivity characteristics of the fluoride-ion electrolytes are highlighted. Finally, an outlook on the future research direction of FIBs is given by highlighting some critical issues, challenges and prospects of fluoride-ion electrolytes.

The intricate failure modes and the yet unclear rate dependency of carbon fiber reinforced plain weave composite materials pose a challenge to mechanics researchers. This study establishes an energy-based evolution mechanism for the compressive failure modes of plain weave composite materials as the strain rate varies. This mechanism illustrates how the rate dependency of failure modes arises from the competitive relationship between strain potential energy and deformation kinetic energy. At low loading rates, the specimen exhibits a progressive crushing failure mode characterized by low peak stress and significant geometric deformation. As the loading strain rate increases, the energy required for this geometric deformation also increases. When the energy expenditure surpasses that needed to elevate the stress level of the specimen, it transitions to an instantaneous failure mode with high peak stress. In this mode, the specimen fractures into multiple small fragments immediately upon failure, lacking the large geometric deformations observed at lower rates. Through calculating this energy mechanism, a transition strain rate of 180 s−1 was determined for both failure modes. The accuracy of this mechanism was further verified by tests conducted near the critical strain rate. The energy-based evolution mechanism for failure modes provides a simplified and concise framework for simplifying complex models of composite material failures.

BackgroundIn recent years, with the development of society, children's daily exposure to screen time has gradually increased. Screen exposure and sedentary behavior have brought a host of harms to children's lives. The aim of this study was to explore the effects of screen exposure and sedentary behavior on precocious puberty and early development.MethodsThis is a cross-sectional study in the school-based population. A total of 3,560 children were recruited from Qufu City, Shandong province using multistage stratified cluster random sampling. All study subjects had a physical examination by professional pediatricians in October 2019, and were investigated with health questionnaires. Precocious puberty is defined as development of secondary sexual signs in boys before 9 years or in girls before 8 years. Screen time was calculated as the average of screen time on weekdays and weekend days, and sedentary time was calculated as the average of sedentary time on weekdays and weekend days. After adjusting for potential confounders, logistic regression was used to examine the association between screen exposure and sedentary behavior and early puberty and precocious puberty.ResultsSedentary time was a risk factor for precocious puberty and early development (OR = 1.428, 95% CI = 1.087–1.876) in girls without adjustment. No significant association was found between screen exposure and early puberty and early development both in girls and boys.ConclusionsExcessive sedentary behavior was associated with an increased risk of early puberty, especially in girls, while there was no significant association between screen exposure and early puberty and early development. In addition, further longitudinal investigations are needed to determine the causal relationship between screen exposure, sedentary behavior and precocious puberty.

The energy consumption of a large-scale industrial hydrogen liquefaction system is primarily determined by the hydrogen turbo-expanders. To estimate the performance of the expander quickly, a one-dimensional preliminary design is conducted. This paper aims to identify dependable one-dimensional design codes for hydrogen turbo-expanders by employing three mean-line design approaches. The precision of the loss models is validated through hydrogen experiments, revealing a maximum deviation of less than 10 %. This study presents a summary of the optimal design parameter ranges for achieving high-efficiency hydrogen turbo-expanders. One common factor among the three methods is the characteristic ratio, which exhibits an optimal value range of 0.67–0.71. Furthermore, the three methods are applied to design hydrogen turbo-expanders of three different sizes, and the compositions of losses are thoroughly analyzed. The PR method exhibits the highest losses related to geometry sizes, while the VC method shows the greatest losses associated with velocities. The SS-CR method with moderate parameters is recommended for hydrogen turbo-expander design due to its superior maximum efficiency design limit and convenience. The two initial design parameters (specific speed and characteristic ratio) of this method play crucial roles in determining the scalability and efficiency of the hydrogen turbo-expander design.

Abstract Background and aim The optimal management strategy for early gastric cancer (EGC) a topic of contention. This study aims to compare the prognostic outcomes of endoscopic submucosal dissection (ESD) and surgical treatment in patients diagnosed with EGC. Methods In thisretrospective cohort study, we analyzed data from539 patients diagnosed with EGC between January 2012 and December 2020 from two centers. We compared Clinicopathological features, procedure-related complications, recurrence rate, overall survival, and disease specific survival between the 262 patients who underwent ESD and the 277 patients who underwent surgical treatment. ESD procedures were conducted using a dual knife by experienced endoscopists, while surgical treatments included laparoscopic or open gastrectomy. Regular ollow-up examinations were conducted post-treatment. Results The two groups exhibited comparable baseline characteristics. Multivariable Cox regression analysis identified vascular invasion as a risk factor for worse recurrence-free survival (RFS), and overall survival (OS) in patients with early gastric cancer. The ESD group experienced fewer overall postoperative complications compared to the surgical treatment group. Kaplan-Meier curves demonstrated no significant differences in recurrence rate or overall survival between the two groups. Conclusions Both ESD and surgical treatment emerged as safe and effective approaches for managing EGC. The choice of treatment should be tailored to individual patient factors. ESD can be considered an alternative treatment option for selected patients who are not suitable candidates for surgery. Further studies are warranted to determine the long-term outcomes of ESD and surgical treatment for EGC.

The Fusarium species is an important plant pathogen that can cause plant diseases in grassland, leading to the degradation of grassland quality. However, the morphology of Fusarium is greatly affected by environmental factors, which makes it difficult to identify its species. In addition, the pathogenic ability of different Fusarium species in plants has not been fully studied. In this study, Fusarium isolates were obtained from grassland herbaceous plants via tissue separation. Through morphological means and based on ITS, RPB2, and TEF-1 gene sequences, we compared and constructed polygenic phylogenetic trees to classify and identify the Fusarium species. In addition, the pathogenicity of different Fusarium species was also analyzed. The results showed that a total of 24 Fusarium strains were successfully isolated from grassland, from which ten species were identified: F. flagelliforme, F. longifundum, F. clavum, F. scirpi, F. ipomoeae, F. oxysporum, etc. and were included in four complexes: Fusarium incarnatum-equiseti species complex (FIESC), Fusarium oxysporum species complex (FOSC), Fusarium tricinctum species complex (FTSC), and Fusarium sambucinum species complex (FSAMSC). Pathogenicity tests demonstrated that except for F. ipomoeae QJ5211, F. sambucinum QJ203, and F. acuminatum QJ1662, other Fusarium species had different degrees of pathogenic ability. This is the first study that discusses the effect of Fusarium on grassland disease control in this area. This study further provides clear pathogen information for the prevention and control of grassland diseases.

Live stump-supported slopes are an environmentally friendly form of support that utilizes the powerful anchoring and reinforcing effects of deep-rooted plants to enhance slope stability. In order to ensure the safety and stability of embankment slopes during their service life, it is necessary to carry out research on the dynamic characteristics and stability of live stump slopes under train vibration loading. In this study, a large-scale indoor dynamic loading model test with a geometry of 1:7 was carried out on the live stump slope of a ballasted passenger railroad track to explore the attenuation characteristics of additional dynamic stresses, the dynamic displacement response law of the slope surface and the stress response characteristics of the live stumps, and to further investigate the influence of the live stumps on the stability of the slope under the dynamic loading. The results are as follows. (i) Additional dynamic stresses decayed at the bed surface and bed floor at a greater rate than the embankment body, and were significantly affected by dynamic loading when the vertical depth was less than 0.89 m. (ii) The dynamic displacement of the foundation bed is larger than that of the embankment body. The displacement response of the slope near the top and about 1/4 of the elevation of slope is the largest. (iii) The taproot of the living poles has many reverse bending points, and the bending moment of the taproot between the lateral roots shows the law of being larger on the top and smaller on the bottom. (iv) The slope facing has an amplifying effect on the vibration load of the train, and the farther away from the track, the smaller the amplifying effect. The research results have reference significance for the theoretical research and engineering application of living poles.

Biodegradation was considered a promising and environmentally friendly method for treating environmental pollution caused by diuron. However, the mechanisms of biodegradation of diuron required further research. In this study, the degradation process of diuron by Achromobacter xylosoxidans SL-6 was systematically investigated. The results suggested that the antioxidant system of strain SL-6 was activated by adding diuron, thereby alleviating their oxidative stress response. In addition, degradation product analysis showed that diuron in strain SL-6 was mainly degraded by urea bridge cleavage, dehalogenation, deamination, and ring opening, and finally cis, cis-muconic acid was generated. The combined analysis of metabolomics and transcriptomics revealed the biodegradation and adaptation mechanism of strain SL-6 to diuron. Metabolomics analysis showed that after the strain SL-6 was exposed to diuron, metabolic pathways such as tricarboxylic acid cycle (cis, cis-muconic acid), glutathione metabolism (oxidized glutathione), and urea cycle (arginine) were reprogrammed in the cells. Furthermore, diuron could induce the production of membrane transport proteins in strain SL-6 cells and overexpress antioxidant enzyme genes, finally ultimately promoting the up-regulation of genes encoding amide hydrolases and dioxygenases, which was revealed by transcriptomics studies. This work enriched the biodegradation mechanism of phenylurea herbicides and provided guidance for the removal of diuron residues in the environment and promoting agriculture sustainable development.

Abstract Background Rhododendron pudingense, firstly discovered in Puding county of Guizhou province in 2020, have adapted to living in rocky fissure habitat, which has important ornamental and economic values. However, the genetic diversity and population structure of this species have been rarely described, which seriously affects the collection and protection of wild germplasm resources. Results In the present study, 13 pairs of primers for polymorphic microsatellite were used to investigate the genetic diversity of 65 R. pudingense accessions from six different geographic populations. A total of 254 alleles (Na) were obtained with an average of 19.5 alleles per locus. The average values of polymorphic information content (PIC), observed heterozygosity (Ho), and expected heterozygosity (He) were 0.8826, 0.4501, and 0.8993, respectively, These results indicate that the microsatellite primers adopted demonstrate good polymorphism, and the R. pudingense exhibits a high level of genetic diversity at the species level. The average genetic differentiation coefficient (Fst) was 0.1325, suggested that moderate divergence occurred in R. pudingense populations. The average values of genetic differentiation coefficient and gene flow among populations were 0.1165 and 3.1281, respectively. The analysis of molecular variance (AMOVA) indicated that most of the population differences (88%) were attributed to within-population variation. The PCoA results are consistent with the findings of the UPGMA clustering analysis, supporting the conclusion that the six populations of R. pudingense can be clearly grouped into two separate clusters. Based on Mantel analysis, we speculate that the PD population may have migrated from WM-1 and WM-2. Therefore, it is advised to protect the natural habitat of R. pudingense in situ as much as possible, in order to maximize the preservation of its genetic diversity. Conclusions This is the first comprehensive analysis of genetic diversity and population structure of R. pudingense in Guizhou province. The research results revealed the high genetic diversity and moderate population diferentiation in this horticulture plant. This study provide a theoretical basis for the conservation of wild resources of the R. pudingense and lay the foundation for the breeding or cultivation of this new species.

Abstract Single-atom catalysts (SACs) are particularly sensitive to external conditions, complicating the identification of catalytically active species and active sites under in situ or operando conditions. We developed a methodology for tracing the structural evolution of SACs to nanoparticles, identifying the active species and their link to the catalytic activity for the reverse water gas shift (RWGS) reaction. The new method is illustrated by studying structure-activity relationships in two materials containing Pt SACs on ceria nanodomes, supported on either ceria or titania. These materials exhibited distinctly different activities for CO production. Multimodal operando characterization attributed the enhanced activity of the titania-supported catalysts at temperatures below 320 ˚C to the formation of unique Pt sites at the ceria-titania interface capable of forming Pt nanoparticles, the active species for the RWGS reaction. Migration of Pt nanoparticles to titania support was found to be responsible for the deactivation of titania-supported catalysts at elevated temperatures. Tracking the migration of Pt atoms provides a new opportunity to investigate the activation and deactivation of Pt SACs for the RWGS reaction.

Trees play a crucial role in urban environment, offering distinct ecological and aesthetic values. Fine-grained urban tree models hold valuable potential for urban landscape planning and green space management. Consequently, in recent years, how to reconstruct detailed tree models using digital twin technology has become a focal point of interest. Point cloud data has become a major source for tree modeling because of its unique capability to represent objects’ geometry. However, current methods for tree reconstruction primarily concentrate on individual trees, and necessitate high-quality point cloud data that is arduous to acquire on a large scale within complex urban settings. Furthermore, adequately storing and managing tree models of a large scale is another vital challenge to address. In response to these challenges, we propose a novel approach for 3D modeling and parameterization of large-scale urban trees based on point clouds acquired from consumer-grade mobile laser scanning (MLS) and UAV laser scanning (ULS) platforms. Our pipeline encompasses several key techniques: tree extraction, adaptive tree modeling, and model parameterization. To validate our approach, we collected MLS and ULS data covering an area of 36,400 m2. Using the proposed pipeline, we achieved large-scale tree modeling and lightweight model representation with a success rate of 96%. Both qualitative and quantitative evaluations have proved the effectiveness of our reconstruction method in terms of visual quality and estimation of tree structure parameters. The generated tree models, amenable to lightweight representation, facilitate integration and contribute to the advancement of digital urban forest construction, management, and applications.

The sub-grains coarsening and low melting point eutectic are the internal causes of cracking of single crystal super-alloys in welding. Aiming to overcome two internal causes, in this paper, the effect of ultrasonic pulse arc welding on the grains, sub-grains and the precipitations of single crystal super-alloys (IN738) has been comprehensively studied, and the microstructure evolution of IN738 in ultrasonic pulse arc welding has been systematically revealed. The results show that (1) the combined effect of ultrasonic vibration and electromagnetic oscillation not only realizes the synchronous refinement of grains and sub-grains in WMZ (weld metal zone), and the polycrystalline transformation of single crystal super-alloys. A novel 3D schematic model of sub-grains is established to evaluate the size and orientation of sub-grains in 3D direction. (2) The ultrasonic vibration and electromagnetic field induced by ultrasonic pulse current can effectively reduce the microstructural segregation of welds. With the increase of ultrasonic pulse frequency, the size and volume fraction of harmful precipitations (η + δ eutectic, mixed eutectic and MC carbides) decrease greatly, especially the morphology and distribution characteristics of γ′ in HAZ (heat affected zone). Thanks to the above outstanding advantages, ultrasonic pulse arc welding has great application value in single crystal super-alloys.

The timely injection of gangue slurry into the mining space formed after coal mining can scale up the disposal of gangue and control surface deformation. However, the waterproof effect of gangue slurry in the mining space remains unclear, necessitating urgent investigation into the permeability characteristics of compacted backfill bodies of gangue slurry under the action of overburden. In this study, a multi-field coupled seepage test system for backfill materials was developed based on Forchheimer’s nonlinear seepage law, and a laboratory preparation method for compacted backfill body (CBB) of gangue slurry after grouting and backfilling in mining space under pseudo-triaxial conditions was proposed. Additionally, the pressure bleeding characteristics of gangue slurry under the action of overburden were studied, the variation law of permeability of the CBB with the axial pressure, a particle size range, and cement dosage was revealed, and the determination method for the permeability level of the CBB and its optimization method were put forward. The research results indicate that there are obvious staged characteristics in the pressure bleeding changes in gangue slurry. Axial pressure, particle size range, and cement dosage all have a significant impact on the permeability of the CBB. The permeability level of the CBB of gangue slurry is within the range of poor permeability and extremely poor permeability. After backfilling into the mining space, gangue slurry exhibits a significant water-blocking effect.

Extracting geoscientific dataset names from the literature is crucial for building a literature–data association network, which can help readers access the data quickly through the Internet. However, the existing named-entity extraction methods have low accuracy in extracting geoscientific dataset names from unstructured text because geoscientific dataset names are a complex combination of multiple elements, such as geospatial coverage, temporal coverage, scale or resolution, theme content, and version. This paper proposes a new method based on the hierarchical temporal memory (HTM) model, a brain-inspired neural network with superior performance in high-level cognitive tasks, to accurately extract geoscientific dataset names from unstructured text. First, a word-encoding method based on the Unicode values of characters for the HTM model was proposed. Then, over 12,000 dataset names were collected from geoscience data-sharing websites and encoded into binary vectors to train the HTM model. We conceived a new classifier scheme for the HTM model that decodes the predictive vector for the encoder of the next word so that the similarity of the encoders of the predictive next word and the real next word can be computed. If the similarity is greater than a specified threshold, the real next word can be regarded as part of the name, and a successive word set forms the full geoscientific dataset name. We used the trained HTM model to extract geoscientific dataset names from 100 papers. Our method achieved an F1-score of 0.727, outperforming the GPT-4- and Claude-3-based few-shot learning (FSL) method, with F1-scores of 0.698 and 0.72, respectively.

Enzyme stoichiometry can reflect the resource limitation of soil microbial metabolism, and research on the relationships between plants and resource limitation in Karst Microhabitats is scarcely investigated. To clarify the extracellular enzyme stoichiometry characteristics in soil across different karst microhabitats and how the Rhododendron pudingense adapts to nutrient restrictions, plot investigation experiments were set up in Zhenning County, Qinglong County, and Wangmo County of Guizhou Province which included total three karst microhabitats, i.e., soil surface (SS), rock gully (RG), and rock surface (RS), by analyzing he rhizosphere soil nutrient, extracellular enzyme activity, and nutrient content of R. pudingense. The findings indicated that all karst microenvironments experienced varying levels of nitrogen (N) limitation, with the order of N limitation being as follows: SS > RG > RS. Notably, there were significant discrepancies in N content among different plant organs (p< 0.05), with the sequence of N content as follows: leaf > stem > root. However, no significant differences were observed in nutrient content within the same organ across different microenvironments (p > 0.05). A noteworthy discovery was the significant allometric growth relationship between C-P in various organs (p< 0.05), while roots and stems exhibited a significant allometric growth relationship between N-P (p< 0.05). The study highlighted the substantial impact of Total Nitrogen (TN) and N-acquiring enzymes (NAE) on nutrient allocation within the components of R. pudingense. Overall, the research demonstrated that N was the primary limiting factor in the study area’s soil, and R. pudingense’s nutrient allocation strategy was closely associated with N limitations in the karst microenvironment. Specifically, the plant prioritized allocating its limited N resources to its leaves, ensuring its survival. This investigation provided valuable insights into how plants adapt to nutrient restrictions and offered a deeper understanding of soil-plant interactions in karst ecosystems.

Abstract Background The lack of obvious symptoms of early gastric cancer (GC) as well as the absence of sensitive and specific biomarkers results in poor clinical outcomes. Tubulin is currently emerging as important regulators of the microtubule cytoskeleton and thus have a strong potential to be implicated in a number of disorders, however, its mechanism of action in gastric cancer is still unclear. Tubulin alpha-1 C (TUBA1C) is a subtype of α-tubulin, high TUBA1C expression has been shown to be closely related to a poor prognosis in various cancers, this study, for the first time, revealed the mechanism of TUBA1C promotes malignant progression of gastric cancer in vitro and in vivo. Methods The expression of lncRNA EGFR-AS1 was detected in human GC cell lines by qRT–PCR. Mass spectrometry experiments following RNA pulldown assays found that EGFR-AS1 directly binds to TUBA1C, the CCK8, EdU, transwell, wound-healing, cell cycle assays and animal experiments were conducted to investigate the function of TUBA1C in GC. Combined with bioinformatics analyses, reveal interaction between Ki-67, E2F1, PCNA and TUBA1C by western blot. Rescue experiments furtherly demonstrated the relationship of EGFR-AS1and TUBA1C. Results TUBA1C was proved to be a direct target of EGFR-AS1, and TUBA1C promotes gastric cancer proliferation, migration and invasion by accelerating the progression of the cell cycle from the G1 phase to the S phase and activating the expression of oncogenes: Ki-67, E2F1 and PCNA. Conclusion TUBA1C is a new potential target of LncRNA EGFR-AS1 promotes gastric cancer progression and could be a novel biomarker and therapeutic target for GC.

The rate of flavor release in the mouth from traditional dry-cured pork was evaluated in this study. It was hypothesized that a slow steady release of flavor would occur on chewing and hydration. To test this, high salt dry-cured pork was chewed and held in oral cavity without swallowing for 4 different chewing stages (B, NC30, C30, EC). Saliva and food bolus from 16 healthy subjects were collected during oral processing, and analyzed for saliva flow rate, total saliva protein content, saliva pH, conductivity, saliva and sodium, and taste components. Results show that oral processing behavior and salivary release have important effects on flavor release of dry-cured pork. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis showed that oral processing has a certain effect on the protein composition and concentration in saliva. This study suggests that the interaction between food and saliva that accompanies chewing can lead to significant changes in sensory perception during oral processing.

BackgroundThe convolutional neural network (CNN) is a mainstream deep learning (DL) algorithm, and it has gained great fame in solving problems from clinical examination and diagnosis, such as Alzheimer's disease (AD). AD is a degenerative disease difficult to clinical diagnosis due to its unclear underlying pathological mechanism. Previous studies have primarily focused on investigating structural abnormalities in the brain's functional networks related to the AD or proposing different deep learning approaches for AD classification.ObjectiveThe aim of this study is to leverage the advantages of combining brain topological features extracted from functional network exploration and deep features extracted by the CNN. We establish a novel fMRI-based classification framework that utilizes Resting-state functional magnetic resonance imaging (rs-fMRI) with the phase synchronization index (PSI) and 2D-CNN to detect abnormal brain functional connectivity in AD.MethodsFirst, PSI was applied to construct the brain network by region of interest (ROI) signals obtained from data preprocessing stage, and eight topological features were extracted. Subsequently, the 2D-CNN was applied to the PSI matrix to explore the local and global patterns of the network connectivity by extracting eight deep features from the 2D-CNN convolutional layer.ResultsFinally, classification analysis was carried out on the combined PSI and 2D-CNN methods to recognize AD by using support vector machine (SVM) with 5-fold cross-validation strategy. It was found that the classification accuracy of combined method achieved 98.869%.ConclusionThese findings show that our framework can adaptively combine the best brain network features to explore network synchronization, functional connections, and characterize brain functional abnormalities, which could effectively detect AD anomalies by the extracted features that may provide new insights into exploring the underlying pathogenesis of AD.

Chrysanthemum tea, a typical health tea with the same origin as medicine and food, is famous for its unique health benefits and flavor. The taste and sensory quality of chrysanthemum (Juhua) tea are mainly determined by secondary metabolites. Therefore, the present research adopted untargeted metabolomics combined with an electronic tongue system to analyze the correlation between the metabolite profiles and taste characteristics of different varieties of chrysanthemum tea. The results of sensory evaluation showed that there were significant differences in the sensory qualities of five different varieties of chrysanthemum tea, especially bitterness and astringency. The results of principal component analysis (PCA) indicated that there were significant metabolic differences among the five chrysanthemum teas. A total of 1775 metabolites were identified by using untargeted metabolomics based on UPLC-Q-TOF/MS analysis. According to the variable importance in projection (VIP) values of the orthogonal projections to latent structures discriminant analysis (OPLS-DA), 143 VIP metabolites were found to be responsible for metabolic changes between Huangju and Jinsi Huangju tea; among them, 13 metabolites were identified as the key metabolites of the differences in sensory quality between them. Kaempferol, luteolin, genistein, and some quinic acid derivatives were correlated with the “astringency” attributes. In contrast, l-(-)-3 phenyllactic acid and L-malic acid were found to be responsible for the “bitterness” and “umami” attributes in chrysanthemum tea. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed that the flavonoid and flavonol biosynthesis pathways had important effects on the sensory quality of chrysanthemum tea. These findings provide the theoretical basis for understanding the characteristic metabolites that contribute to the distinctive sensory qualities of chrysanthemum tea.

The deployment of Li–S batteries in the commercial sector faces obstacles due to their low electrical conductivity, slow redox reactions, quick fading of capacity, and reduced coulombic efficiency. These issues stem from the “shuttle effect” associated with lithium polysulfides (LiPSs). In this work, a haystack-like CeO2 derived from a cerium-based metal-organic framework (Ce-MOF) is obtained for the modification of a polypropylene separator. The carbon framework and CeO2 coexist in this haystack-like structure and contribute to a synergistic effect on the restriction of LiPSs shuttling. The carbon network enhances electron transfer in the conversion of LiPSs, improving the rate performance of the battery. Moreover, CeO2 enhances the redox kinetics of LiPSs, effectively reducing the “shuttle effect” in Li–S batteries. The Li–S battery with the optimized CeO2 modified separator shows an initial discharge capacity of 870.7 mAh/g at 2 C, maintaining excellent capacity over 500 cycles. This research offers insights into designing functional separators to mitigate the “shuttle effect” in Li–S batteries.

Abstract A temporary road composed of traffic cones is an indispensable practical scene for the realization of automatic driving technology. However, the detection of traffic cones is a challenging issue because of their small volume and unfixed position. This work proposes a novel method that fuses colour and depth image information for traffic cone detection. Traffic cones are captured by a special machine vision system consisting of two monochrome cameras for cone distance perception and two colour cameras for cone colour acquisition. Via the YOLOv4 algorithm based on the Darknet platform and a detection result matching algorithm, the position of the traffic cone can be obtained and path planning can be performed. The results of experiments show that the proposed method can recognize red, blue, and yellow traffic cones in colour images with an average detection time of 35.46 ms and respective accuracies of 97.51%, 98.63%, and 97.29%. Compared with the previous traffic cone detection research, the proposed algorithm was found to exhibit advantages in small target sensitivity and overall detection accuracy in both static and dynamic experiments.

The vibration quality of concrete is crucial to ensure the long-term safe operation of concrete structural components. In recent years, computer vision technology based on deep learning has achieved excellent results in the field of concrete quality inspection. However, when used for assisting construction inspection, this technology relies heavily on large-scale, labeled, high-quality image data. To solve this drawback, this study proposes a vision-based method that integrates semi-supervised learning and data augmentation for detecting the concrete vibration quality. Initially, StyleGAN2 was adopted as the data augmentation strategy to improve the diversity of the dataset. Then, SE-ResNet50, a model that couples an attention mechanism module and residual network, was employed as a classifier for accurately extracting information contained in images. Subsequently, in order to reduce the workload of data annotation, a novel semi-supervised learning method (Co-MixMatch) was proposed to train the model by coupling MixMatch with co-training. Finally, the trained model was deployed on mobile devices to assist onsite construction workers in detecting the quality of concrete vibration. A real-world concrete dam dataset was employed to verify the proposed method. Based on the experimental results, the proposed method improves the accuracy of the baseline method by 3.62% on average. Additionally, the proposed method achieves an accuracy of 0.9600, which is only 0.67% lower than that of supervised learning, while only requiring 20% of the labeled data. Therefore, the proposed method has great application prospects and can further promote the intelligent development of concrete vibration inspection.

BackgroundMost patients with Alzheimer's disease (AD) have an insidious onset and frequently atypical clinical symptoms, which are considered a normal consequence of aging, making it difficult to diagnose AD medically. But then again, accurate diagnosis is critical to prevent degeneration and provide early treatment for AD patients.ObjectiveThis study aims to establish a novel EEG-based classification framework with deep learning methods for AD recognition.MethodsFirst, considering the network interactions in different frequency bands (δ, θ, α, β, and γ), multiplex networks are reconstructed by the phase synchronization index (PSI) method, and fourteen topology features are extracted subsequently, forming a high-dimensional feature vector. However, in feature combination, not all features can provide effective information for recognition. Moreover, combining features by manual selection is time-consuming and laborious. Thus, a feature selection optimization algorithm called MOPSO-GDM was proposed by combining multi-objective particle swarm optimization (MOPSO) algorithm with Gaussian differential mutation (GDM) algorithm. In addition to considering the classification error rates of support vector machine, naive bayes, and discriminant analysis classifiers, our algorithm also considers distance measure as an optimization objective.ResultsFinally, this method proposed achieves an excellent classification error rate of 0.0531 (5.31%) with the feature vector size of 8, by a ten-fold cross-validation strategy.ConclusionThese findings show that our framework can adaptively combine the best brain network features to explore network synchronization, functional interactions, and characterize brain functional abnormalities, which can improve the recognition efficiency of diseases. While improving the classification accuracy of application algorithms, we aim to expand our understanding of the brain function of patients with neurological disorders through the analysis of brain networks.

Cormorants (Phalacrocoraxe), types of aquatic birds, utilize the compliance/flexibility of the flippers and exploit hydrodynamic/biomechanic processes to accomplish diverse operations. Particularly, the flipper‐propelled locomotion exhibits traits such as super‐redundancy and large deformations, necessitating depiction of both movements of the rigid skeletons as well as local deformations of the soft tissues. However, there are few well‐established kinematic/hydrodynamic framework models and constitutive equations for such rigid–flexible intrinsically coupled biosystems. Herein, combined with a skeletal skinning algorithm to handle the deformation of a flexible body attached to a rigid body, a numerical computation framework for an in‐depth fluid–structure interaction is presented, which enables the capture of viscoelastic and anisotropic characteristics of a highly compliant 3D rigid–flexible coupled model in a low‐Reynolds‐number flow. Considering the biorobotic cormorant flipper with a nonuniformly distributed stiffness as a representative, the challenging issue of controlling a biomechanically compliant flipper to synthesize realistic locomotion sequences, including rigid skeleton movements and soft tissue deformations, is addressed. Furthermore, a numerical computational hydrodynamic analysis is performed to demonstrate that the cormorant flipper can generate 5 N fluid force and 0.45 N m fluid moment during the turning operation in 0.8 s, which is consistent with the former experimental results.

Background: As a novel non-apoptotic cell death, ferroptosis has been reported to play a crucial role in acute kidney injury (AKI), especially cisplatin-induced AKI. Valproic acid (VPA), an inhibitor of histone deacetylase (HDAC) 1 and 2, is used as an antiepileptic drug. Consistent with our data, a few studies have demonstrated that VPA protects against kidney injury in several models, but the detailed mechanism remains unclear.Results: In this study, we found that VPA prevents against cisplatin-induced renal injury via regulating glutathione peroxidase 4 (GPX4) and inhibiting ferroptosis. Our results mainly indicated that ferroptosis presented in tubular epithelial cells of AKI humans and cisplatin-induced AKI mice. VPA or ferrostatin-1 (ferroptosis inhibitor, Fer-1) reduced cisplatin-induced AKI functionally and pathologically, which was characterized by reduced serum creatinine, blood urea nitrogen, and tissue damage in mice. Meanwhile, VPA or Fer-1 treatment in both in vivo and in vitro models, decreased cell death, lipid peroxidation, and expression of acyl-CoA synthetase long-chain family member 4 (ACSL4), reversing downregulation of GPX4. In addition, our study in vitro indicated that GPX4 inhibition by siRNA significantly weakened the protective effect of VPA after cisplatin treatment.Conclusion: Ferroptosis plays an essential role in cisplatin-induced AKI and inhibiting ferroptosis through VPA to protect against renal injury is a viable treatment in cisplatin-induced AKI.

Abstract To make charging of electric vehicles (EVs) more convenient, the service providers of charging stations (CSs) establish a large number of CSs. Existing methods address the problem of reducing costs and increasing revenue for the service providers from multiple aspects, such as CS location optimisation and charging pricing strategy. This study proposes multi‐parameters‐based‐dynamic scheduling with energy management for the CSs, considering energy management and EV charging scheduling (EVCS). A fully functional battery management system is designed for energy storage. A multi‐parameters optimisation algorithm is proposed by designing the CS selection operator based on alternative set and adjusting parameters. The experiments show that our proposed algorithms got better performance in terms of optimisation effect, the number of iterations, and stability.

BackgroundThe fibrinogen-to-prealbumin ratio (FPR), a novel immune-nutritional biomarker, has been reported to be associated with prognosis in several types of cancer, but the role of FPR in the prognosis of resectable pancreatic cancer has not been elucidated.MethodsA total of 263 patients with resectable pancreatic cancer were enrolled in this study and were randomly divided into a training cohort (n = 146) and a validation cohort (n = 117). Receiver operating characteristic curve (ROC) was used to calculate the cut-off values of immune-nutritional markers. The least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression were performed in the training cohort to identify the independent risk factors, based on which the nomogram was established. The performance of the nomogram was evaluated and validation by the training and validation cohort, respectively.ResultsThe optimal cutoff value for FPR was 0.29. Multivariate analysis revealed that FPR, controlling nutritional status (CONUT), carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), and tumor node metastasis (TNM) stage were independent predictors of overall survival (OS). The nomogram was established by involving the five factors above. The C-index of the training cohort and validation cohort were 0.703 (95% CI: 0.0.646-0.761) and 0.728 (95% CI: 0.671-0.784). Decision curve analysis and time-dependent AUC showed that the nomogram had better predictive and discriminative ability than the conventional TNM stage.ConclusionFPR is a feasible biomarker for predicting prognosis in patients with resectable pancreatic cancer. The nomogram based on FPR is a useful tool for clinicians in making individualized treatment strategies and survival predictions.

In printed circuit board (PCB) defect detection, it is difficult to collect defect samples, and the detection effect is poor due to the lack of data. On the basis of the few-shot learning method, a few-shot PCB defect detection model is proposed. This model introduces feature enhancement module and multi-scale fusion module. The feature enhancement module based on the improved convolution block attention module (CBAM) can highlight the key areas of the received feature maps and suppress the interference of useless information. Aiming at the small size of PCB defects, a multi-scale feature fusion strategy is proposed. It can extract multi-scale feature maps of PCB and fuse them into a high-quality feature map containing different scale information, which can improve the detection precision of the model for small object defects. A large number of experiments on PCB dataset show that our few-shot PCB defect detection model outperforms state-of-the-art methods under different shot settings ( $\text{k}=1$ ,2,3,5,10,30). Notably, the proposed model can take into account both detection efficiency and precision, which means it has high practical application value.

Recently, the concept of low-salt and healthy diet has been widely accepted, while the market recognition of low-salt meat products is generally inferior due to their inability to satisfy the oral pleasure of consumers. Therefore, to investigate the role of saliva in saltiness during oral processing of chewing high-salt dry-cured pork, a subset of 3 male subjects with high salt-sensitivity were selected to partake this study. Cooked dry-cured pork (5% salt added) as chewed and held in the oral cavity without swallowing for four different chewing stages during oral processing. Saliva from the 3 subjects was collected and analyzed for salivary proteomics by Data Independent Acquisition (DIA) combined with food oral processing methods. According to the analysis of human proteome (H.sapiens, UP000005640), the abundance of RAC1(RAS-related C3 botulinum toxin substrate 1) and calmodulin-like 3 (CALML 3) was first found to be related to the change of saltiness sensing during oral processing. Moreover, oral chewing leads to upregulation of RAC1 protein, which leads to positive regulation of protein kinase B signaling, ultimately leading to increased serine-type endopeptidase activity and salt perception.

Ulcerative colitis (UC) is a chronic inflammatory colorectal disease characterized by excessive mucosal immune response activation and dysfunction of autophagy in intestinal epithelial cells. Traditional herbal preparations, including the Huangkui lianchang decoction (HLD), are effective in UC clinical treatment in East Asia, but the underlying mechanism is unclear. This study evaluated the therapeutic effects and associated molecular mechanisms of HLD in UC in vivo and in vitro. A C57BL/6 UC mouse model was established using 2.5% dextran sulfate sodium. The effects of HLD on the colonic structure and inflammation in mice were evaluated using mesalazine as the control. The anti-inflammatory effects of HLD were assessed using disease activity index (DAI) scores, histological scores, enzyme-linked immunosorbent assay, immunohistochemistry, immunofluorescence, and western blotting. HLD displayed a protective effect in UC mice by reducing the DAI and colonic histological scores, as well as levels of inflammatory cytokines and NF-κB p65 in colonic tissues. NCM460 lipopolysaccharide-induced cells were administered drug serum-containing HLD (HLD-DS) to evaluate the protective effect against UC and the effect on autophagy. HLD-DS exhibited anti-inflammatory effects in NCM460 cells by reducing the levels of inflammatory cytokines and increasing interleukin 10 levels. HLD-DS reduced p-NF-κB p65, LC3II/I, and Beclin 1 expression, which suggested that HLD alleviated colitis by inhibiting the NF-κB pathway and autophagy. However, there was no crosstalk between the NF-κB pathway and autophagy. These findings confirmed that HLD was an effective herbal preparation for the treatment of UC.

(1) Background: In managing ecological tea gardens, litter composed of pruned and fallen tea leaves from companion tree species is an important component of tea garden soil. The decomposition of litter plays a crucial role in regulating nutrient cycling in tea garden ecosystems. (2) Methods: This study employed the litterbag method to investigate chemical stoichiometry characteristics and enzyme activity changes during the decomposition process of pruned and fallen Camellia sinensis leaves from companion tree species in an ecological tea garden located in central Guizhou Province. (3) Results: With decomposition duration, the general trend of changes in the C/N and C/P ratios showed a decrease in the activity of UE (urease), AP (acid phosphatase), and PPO (polyphenol oxidase) followed by an increase, while CAT (catalase) and CEL (cellulase) activity decreased, then increased, and then decreased again. On the other hand, the N/P and the activity of SC (sucrase) first increased and then decreased. The C/N and the activities of UE, PPO, and AP generally reached their maximum values during the late decomposition stage (366–428 d), while the N/P and the CAT activity peaked during the mid-decomposition stage (305 d). In contrast, the activity of SC and CEL reached its maximum value during the early decomposition stage (123 d). The N/P ratios were significantly higher than those of the CS (C. sinensis) litter in the mixed treatment, while C/N and C/P ratios were significantly lower than those in the CS during decomposition for 184–366 days. The UE, CAT, AP, and SC activities of CBL (C. sinensis + B. luminifera) litter were significantly higher than those of the CS litter during decomposition. During the experiment, antagonistic effects were observed in the C/N and C/P ratios of the different litter types. Most mixed litter exhibited additive effects on enzyme activity, while a few showed nonadditive effects. For the nonadditive effects, most were antagonistic effects, mainly in the CPM (C. sinensis + C. glanduliferum) litter. A small portion, mainly observed in the CBL and CCG (C. sinensis + C. glanduliferum) litter, showed synergistic effects. (4) Conclusions: Selecting B. luminifera and C. glanduliferum to be part of the tree species composition in ecological tea gardens can produce positive mixed effects on enzyme activity during litter decomposition, increase nutrient return capacity, maintain tea garden fertility, and achieve the ecological development of tea gardens.

To improve the speed and dynamic adaptability of robotic arm trajectory planning, a collision-free optimal trajectory planning method combining non-uniform adaptive time meshing and bounding box collision detection was proposed. First, the dynamics and objective function of the asymmetric industrial robotic arm with three degrees of freedom (DOF) was formulated in the form of the dynamic optimization problem. Second, the control vector parameterization (CVP) was improved to enhance the computational performance of the problem. The discrete grid was adaptively adjusted according the trend of control variables. Then, a quick and effective collision detection strategy was used to avoid obstacles and to speed up calculation efficiency. The non-collision constraint is built by transforming the collision detection into the distance between two points, and then is combined into the dynamic optimization problem. The solution of the new optimization problem with the improved CVP leads to the higher calculation performance and the avoidance of obstacles. Lastly, the Siemens Manutec R3 robotic arm is taken as an example to verify the effectiveness of the planning method. The approach not only reduces computation time but also maintains accurate calculations, so that optimal trajectory can be selected from symmetric paths near the obstacles. When weights were set as λ1 = λ2 = 0.5, the solution efficiency was improved by 33%, and the minimum distance between the robotic arm and obstacle could be 0.08 m, which ensured that there was no collision.

In dairy herd management, it is significant and irreplaceable for veterinarians to make rapid and effective diagnosis of dairy cow diseases. Based on electronic medical records, deep learning (DL) has been widely used to support clinical decisions for humans. However, this method is rarely adopted in veterinary diagnosis. In addition, most DL models are driven by large datasets, failing to utilize the knowledge acquired by veterinarians in subjective experience, which is critical to disease diagnosis. To address these problems, this paper proposes a DL method for disease diagnosis of dairy cow: convolutional neural network (CNN) based on knowledge graph and transfer learning (KGTL_CNN). Firstly, the structural knowledge was extracted from a knowledge graph of dairy cow diseases, and treated as part of the inputs to the CNN based on knowledge graph (KG_CNN). Then, the model performance was enhanced through pre-training by transfer learning. To verify its performance, experiments were carried out on dairy cow clinical datasets. The results show that our model performed satisfactorily on disease diagnosis: the KG_CNN and KGTL_CNN achieved an F1-score of 85.87% and 86.77%, respectively, higher than that of typical CNN by 6.58% and 7.7%. The research results greatly promote the effective, fast, and automatic clinical diagnosis of dairy cow diseases.;;

A consequence of the improvement in China’s agricultural production capacity has been increased production of pesticide packaging waste, which is a major obstacle to the sustainable development of rural areas. Although the Chinese government has made great efforts to control pollution by waste pesticide packaging, a unified recycling system has not yet been established. Therefore, determining whether farmers are willing to participate in recycling of pesticide packaging is of great relevance. This study conducted a random questionnaire survey in which 459 responses were obtained in rural areas in Liaoning, Henan, Guizhou, Anhui, Gansu, and Hunan provinces. The disorderly classification logistic model was used to analyze the individual characteristics of farmers, pesticide container sizes, perception of risk, conditions of local facilities, and awareness. The result showed that the individual characteristics of farmers and awareness had no influence of their willingness to participate in recycling, whereas container size, perception of risk, and condition of local facilities did have an influence. Container specifications have the strongest correlation with farmers’ willingness to recycle, and attempts can be made to promote pesticide packaging of about 500 ml; raising farmers’ awareness of environmental safety and possible health hazards, all of which can increase farmers’ participation in the work. Using these results, this study proposed suggestions for pesticide container waste disposal. Attempts can be made to establish a suitable recycling model and management mechanism through the establishment of additional recycling points. Refine pesticide packaging waste recycling, collection and storage, disposal and other measures to purify the environment of origin, to achieve green agricultural development, and promote the construction of ecological civilization.

Epilepsy is a neurological disorder that is characterized by transient and unexpected electrical disturbance of the brain. Seizure detection by electroencephalogram (EEG) is associated with the primary interest of the evaluation and auxiliary diagnosis of epileptic patients. The aim of this study is to establish a hybrid model with improved particle swarm optimization (PSO) and a genetic algorithm (GA) to determine the optimal combination of features for epileptic seizure detection. First, the second-order difference plot (SODP) method was applied, and ten geometric features of epileptic EEG signals were derived in each frequency band (δ, θ, α and β), forming a high-dimensional feature vector. Secondly, an optimization algorithm, AsyLnCPSO-GA, combining a modified PSO with asynchronous learning factor (AsyLnCPSO) and the genetic algorithm (GA) was proposed for feature selection. Finally, the feature combinations were fed to a naïve Bayesian classifier for epileptic seizure and seizure-free identification. The method proposed in this paper achieved 95.35% classification accuracy with a tenfold cross-validation strategy when the interfrequency bands were crossed, serving as an effective method for epilepsy detection, which could help clinicians to expeditiously diagnose epilepsy based on SODP analysis and an optimization algorithm for feature selection.

Flooding is the main cause of inhibited seed germination and seedling growth during the direct seeding of rice. As a growth-regulating hormone, melatonin plays an important role in promoting seed germination and enhancing plant stress resistance. However, there are still many unknown mechanisms related to the exogenous-melatonin-mediated regulation of submergence tolerance during seed germination. To overcome these challenges, this study investigated the effects of seed-soaking with different melatonin concentrations on the germination and physiological characteristics of rice seeds over different flooding times. The results showed that the exogenous administration of 100 μM of melatonin significantly improved the germination potential, germination rate, germination index, and vigor index of seeds and increased the size of the aboveground and underground biomass. By increasing the activities of superoxide dismutase (SOD) and peroxidase (POD) in shoots and roots, and reducing the content of malondialdehyde (MDA), the 100 μM melatonin alleviated the damage of rice seeds under flooding stress. The gray relational grade between the root MDA content and the melatonin seed-soaking treatment was the highest, and this was used to evaluate the effect of melatonin in alleviating flooding stress. A two-factor analysis of variance showed that the flooding stress treatment and the melatonin treatment had more significant effects on rice seed germination than the flooding and melatonin interaction treatments (p < 0.01). The optimal number of days for rice seeds to resist flooding stress was two, and the optimal concentration for the melatonin seed-soaking treatment was 100 μM. In sum, a 100 μM melatonin seed-soaking treatment can effectively alleviate the damage of flooding stress on rice seeds and promote the growth and development of seedlings. This study provides the theoretical basis for a light and simple cultivation technique for the direct seeding of rice.

This paper presents a comprehensive framework for the reliability analysis of ship local structures. Existing reliability analysis of ship local structures relies on empirical analysis without experimental validation. The presented framework improves the probabilistic simulation process by combining finite element analysis and the Kriging surrogate model to increase the computational efficiency in uncertainty quantification. In addition, ultimate strength test data are introduced to update the prior distribution based on Bayesian data fusion. A cross-deck structure of a ship is studied in detail to present the application of this work. The framework provides a valuable reference for the reliability analysis of ship local structures and promotes the development of reliability-based design code. The novelty of this paper is that it introduces the combination of testing and probabilistic simulation into the reliability analysis of ship local structures.

The continuum manipulators, which have gradually become a research hotspot of minimally invasive surgery have the characteristics of small size, lightweight, and better environmental adaptability. In this paper, a two degrees of freedom continuum manipulator with notches is proposed. The kinematic and mechanical models of the notch continuum manipulator are coupled. The output driving force of the motor is needed to control the manipulator. Due to the drift of the current of the motor, the accuracy of the control is low. In order to solve the above problem, the constant curvature assumption is realized by changing the structural parameters of the notches. The continuum manipulator mechanics model is established through the analysis of the continuum manipulator structure. The calculation of the deformation angle of a single notch of the manipulator is carried out. The overall deformation of the manipulator is derived through iterative algorithms. The stiffness of the continuum manipulator, which can affect the deformation of the continuum manipulator is modified by changing the structural parameters. In this way, the problem of the non-constant curvature deformation under the uniform notch of the continuum manipulator is improved. And the effectiveness of the variable stiffness model is verified by simulation experiments.

The drying process is a significant step in the manufacturing process of enteric hard capsules, which affects the physical and chemical properties of the capsules. Thus, the drying characteristics of plant-based enteric hard capsules were investigated at a constant air velocity of 2 m/s in a bench scale hot-air dryer under a temperature range of 25 to 45 °C and relative humidity of 40 to 80%. Results indicate that the drying process of the capsules mainly occur in a falling-rate period, implying that moisture transfer in the capsules is governed by internal moisture diffusion rate. High temperature and low relative humidity reduce drying time but increase the drying rate of the capsules. Investigation results of the mechanical properties and storage stability of the capsules, however, reveal that a fast drying rate leads to plant-based enteric hard capsules of low quality. Scanning electron microscopy further demonstrates that more layered cracks appear in capsules produced under a faster drying rate. The Page model yielded the best fit for describing thin-layer drying of the capsules based on the coefficient of determination and reduced chi-square. Moreover, it was established that the effective moisture diffusivity of the capsules increases with an increase in drying temperature or reduction in relative humidity.

With the continuous development of modern information technology and the continuous improvement of people's living standards, electronic information technology has been widely used in people's lives. People's lives are inseparable from it. With its continuous development, its application range is getting wider and wider. This article first gives a brief overview of digital signal processing technology, analyzes the advantages and disadvantages of digital signal processing technology in the communication field, and the specific applications of speech compression coding and software radio in communication are analyzed in order to better promote the application of digital signal processing technology in the communication field.

The contention based medium access method of 802.11 standards is a fundamental cause of poor downlink goodput and high latency over wireless networks, which makes it impossible to provide QoS guarantees. The intensive channel contention leads to the performance degradation. The problem exacerbates when the traffic asymmetry between the uplink and the downlink is present. While prior research works proposed various mechanisms to alleviate the issue, little was done to specifically address the appropriate parameter setting in a real world network. This study presents a way to obtain the appropriate access parameters that improves the performance of QoS applications over wireless networks. In particular, we propose AQEDCA, a traffic-aware minimum contention window adjustment algorithm. We validate our scheme by the extensive real world network tests and the results show that our scheme improves the downlink goodput up to 199.13%, decreases the latency up to 54.77%, and can achieve tight QoS guarantees as compared to the existing schemes.

This paper considers the performance problem of VoIP over 802.11e WLANs caused by the unfairness between uplink and downlink as well as the inefficient EDCA. A novel medium access control scheme named BEDCA (Balanced EDCA) is presented, which provides service differentiation between the access point (AP) and the mobile stations (STAs) to enhance VoIP capacity. In BEDCA, the expression of AP's contention window is obtained which is a relative constant value independent of the participating STAs. The minimum contention window of the STAs is traffic-aware based on the proposed algorithm. The performance improvement of BEDCA is verified through intensive simulations and the results show the capacity improvement of 82.1% compared to EDCA.

Using sophoridine 1 and chalcone 3 as the lead compounds, a series of novel α, β-unsaturated sophoridinic derivatives were designed, synthesized, and evaluated for their in vitro cytotoxicity. Structure-activity relationship (SAR) analysis indicated that introduction of α, β-unsaturated ketone moiety and heterocyclic group might significantly enhance anticancer activity. Among the compounds, 2f and 2m exhibited potential effects against HepG-2 and CNE-2 human cancer cell lines. Furthermore, molecular docking studies were performed to understand possible docking sites of the molecules on the target proteins and the mode of binding. This work provides a theoretical basis for structural optimizations and exploring anticancer pathways of this kind of compound.