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The backfill is the safety barrier of the backfilling stopes, and the uniaxial compressive strength (UCS) of the backfill is the key indicator to keep the stability of the backfill. To investigate the actual distribution of the UCS of the backfill in the stopes, a large-scale nickel mine in Northwest China is taken as the research object, and field experiments are carried out to investigate the actual distribution characteristics of the UCS of the backfill at different locations in the underhand drift stopes with different curing times. Further, the machine learning algorithm is used to construct a spatial-temporal distribution prediction model of the backfill UCS with different locations and different curing times as variables, and with the UCS of the backfill as the prediction target, to identify the weak parts and corresponding strengths of the backfill. The results show that the UCS of backfill has the distribution characteristics of increasing and then decreasing in the horizontal direction, and gradually decreasing in the vertical direction. When the curing time of the backfill in the stopes exceeds 80 days, its UCS growth tendency slows down. Compared with the back propagation neural network (BPNN), radial basis function neural network (RBFNN), and general regression neural network (GRNN), the prediction accuracy of extreme learning machine (ELM) is improved by 4.4 %, 3.4 %, and 13.9 %, respectively. Compared with the grey wolf algorithm (GWO) and particle swarm algorithm (PSO), the prediction accuracy of ELM optimized by the sparrow search algorithm (SSA) is improved by 7.2 % and 8.4 %, respectively. The SSA-ELM spatial-temporal distribution prediction model constructed in this study achieves fast and high-precision prediction of backfill UCS, which can provide guidance for stability analysis and quality control of underhand drift stopes.

Solid waste filling is an important development direction for filling mining. This research proposes the preparation of solid waste-based cemented paste backfill (SWCPB) to fill the underground mined area by using waste rock and copper slag as the mixed aggregate and granulated blast furnace slag, steel slag, and desulfurization gypsum as raw materials of solid waste binder to reduce the environmental hazards caused by the industrial solid wastes. Based on the response surface method, experiments are designed to analyze the effect patterns of different factors on the mechanical properties of SWCPB. The formation mechanism of SWCPB mechanical properties is explored based on various microscopic analysis techniques. The mix proportions of SWCPB are designed based on machine learning. The results show that the strength of SWCPB increases and then decreases with the increase of the proportion of copper slag, and gradually increases with the increase of the steel slag dosage and binder-aggregate ratio. The alkaline environment provided by the steel slag causes the glass body in granulated blast furnace slag to depolymerize and react with desulfurization gypsum to produce hydration products, which are the main source of mechanical properties formation in SWCPB. The machine learning model constructed in this research paper has high prediction accuracy for the strength of backfill, which can achieve high-precision optimization of backfill mix proportion. The research results could guide the recycling of solid waste and the efficient use of filling mining technology.

Severe fever with thrombocytopenia syndrome (SFTS) is a newly emerged tick-borne viral zoonosis and widely prevalent in China, Japan and South Korea. Most reported SFTS cases have been identified in mountainous and hilly areas, with a few in island areas. In this study, we conducted a systematic investigation about natural infection of SFTS virus (SFTSV) among humans, animals and ticks in a coastal endemic prefecture, containing island, plains and mountain settings, in Zhejiang Province, Southeastern China. From July 2020 to June 2021, 1117 participants completed a survey with questionnaire interview and serum testing. Meanwhile, 862 serum samples of domestic animals, 275 spleen tissue samples of wild animals and 829 ticks representing five species (predominantly Haemaphysalis longicornis and Rhipicephalus sanguineus sensu lato) were collected. The seroprevalence of anti-SFTSV total antibody and IgM antibody among the participants was 4.8 % (54/1117) and 0.6 % (7/1117), respectively. Multivariate logistic regression analysis indicated that living in the island area (OR=2.66; 95 %CI: 1.04–6.80; P = 0.041) was significantly associated with seropositivity of total antibody to SFTSV. Furthermore, a higher seroprevalence was observed in domestic animals (36.1 %), while the SFTSV-RNA infection rate was 0.4 % in wild animals and the minimum infection rate (MIR) was 0.8 % for all tick species combined. The only tick species infected with SFTSV was H. longicornis. The prevalence of SFTSV infection in the island area, manifested by anti-SFTSV total antibody (P = 0.012) and IgM antibody (P = 0.004) among humans, anti-SFTSV total antibody (P

Compared with coring data, well logging data contain much lithologic information with the advantages of strong continuity and low cost. The machine learning method is applied to explore the correlation between the log curves and the lithology of the actual coring samples, realize the automatic identification of the lithology of the reservoirs, reduce the lithologic identification cost, improve the identification efficiency and accuracy and provides an effective tool for the evaluation of the reservoirs. Based on the lithology classification standard, the sample classification scheme is approximately selected and a machine learning lithologic identification method combined with the vertical reservoir information is proposed to design an experimental scheme. The depth window is used to carry out the sequence sampling of the conventional logging data and the known lithologic data to generate training samples. Logistic regression, support vector machine, random forest, convolutional neural networks and stacking ensemble learning are used to build machine learning models to identify the lithology of original samples of strongly heterogeneous rock formations in an oilfield in Xinjiang. The results show that when the width of the depth window matches the thickness of the rock layer well, the accuracy of lithologic identification obtained by each machine learning method is greatly improved after preprocessing the original strong non-equilibrium sample with the method in this paper. The width of the depth window determines the identification accuracy of the rock layer thickness. A thinner depth window can identify a thinner rock layer, while a thicker depth window contains more vertical information, which can obtain higher identification accuracy at the corresponding rock thickness. The machine learning lithologic identification method combined with vertical reservoir information is proposed, which provides an economical and effective reference solution for the automatic and effective identification of heterogeneous thin rock layers.

Abstract Background It has been proven that tumor necrosis is associated with poor prognoses in various solid malignant tumors. However, the prognostic effect of tumor necrosis in hepato‐biliary‐pancreatic cancers is still unclear. Therefore, this study was performed to evaluate the associations of tumor necrosis with survival outcomes and clinicopathological features in patients with hepato‐biliary‐pancreatic cancers. Methods Based on the PRISMA statement, eligible studies were identified from PubMed, Embase, Cochrane Library, and Web of Science from inception until January 2023. The pooled hazard ratios (HRs) and 95% confidence intervals (95%CIs) were calculated to assess the connection between tumor necrosis and hepato‐biliary‐pancreatic cancers. We then choose which effects model to use to generate pooled HRs and 95% CIs, depending on data heterogeneity. Results In total, 6497 articles were identified, 10 of which were included in this meta‐analysis. Our results suggested that the presence of tumor necrosis predicted a poorer outcome for overall survival (HR = 1.54, 95% CI = 1.35–1.77, p

Filling mining with solid waste resources as aggregates is an important development direction for cleaner production in mines. The hydration products have an important effect on the mechanical properties of superfine tailings cemented paste backfill (SCPB). This paper investigates the mechanism of hydration product formation and thermal decomposition properties of SCPB by a series of experiments combined with thermal decomposition kinetics. Also, to optimize the mechanical properties of SCPB, the effect of Nano SiO2 (NS) on the related properties of SCPB is investigated. The results show that there are two main stages of the thermal decomposition of SCPB, and the kinetic models of these two stages are both reaction order models. After adding NS, the kinetic model of the second stage of thermal decomposition of SCPB is changed to random nucleation and growth model. The substances that undergo thermal decomposition reactions in the first stage are mainly hydration products such as ettringite and C-S-H, while the substances that undergo thermal decomposition reactions in the second stage are carbonates. The activation energy E and pre-exponential factor A of the first stage of thermal decomposition of SCPB with NS added are significantly improved, which indicates a more stable structure of its hydration products. The microscopic test results show that NS can promote the hydrolysis of C3S and gypsum and increase the production of hydration products, which in turn improves the strength of SCPB. In addition, the addition of NS to SCPB decreases the Ca/Si and increases the average silica chain length of C-S-H gels, while the H2O/Si decreases and the silica group increases, resulting in the enhancement of the structure of C-S-H gels.

Abstract Organoids are three‐dimensional (3D) miniaturized versions of organs or tissues that are derived from cells with stem potential and can self‐organize and differentiate into 3D cell masses, recapitulating the morphology and functions of their in vivo counterparts. Organoid culture is an emerging 3D culture technology, and organoids derived from various organs and tissues, such as the brain, lung, heart, liver, and kidney, have been generated. Compared with traditional bidimensional culture, organoid culture systems have the unique advantage of conserving parental gene expression and mutation characteristics, as well as long‐term maintenance of the function and biological characteristics of the parental cells in vitro. All these features of organoids open up new opportunities for drug discovery, large‐scale drug screening, and precision medicine. Another major application of organoids is disease modeling, and especially various hereditary diseases that are difficult to model in vitro have been modeled with organoids by combining genome editing technologies. Herein, we introduce the development and current advances in the organoid technology field. We focus on the applications of organoids in basic biology and clinical research, and also highlight their limitations and future perspectives. We hope that this review can provide a valuable reference for the developments and applications of organoids.

Polymer gels suffer from a serious syneresis issue when exposed to high-temperature and high-salinity (HTHS) conditions, which limits their use as water-treatment agents in this type of reservoir. In this paper, the effects of the polymer type/concentration, deoxidizers, and stabilizers on the long-term stability of polymer gels were systematically studied; thus, the methods to develop stable polymer gels for two typical levels of salinity were optimized. The results show the following: (1) For a medium-salinity condition (TDS: 33,645.0 mg/L) at 125 °C, conventional HPAM gels completely dehydrate within only 1 day, and the addition of a deoxidizer hardly improved their stability. Some special polymers, e.g., AP-P5, MKY, and CPAM, are able to form stable gels if a high concentration of 0.8% is used; the syneresis rate of these gels is about 10% after 30 days. However, the addition of the complexant sodium oxalate significantly improves the stability of gels formed by all five of these different polymers, which behave with a 0% syneresis rate after 30 days pass. Complexants are the most economical and feasible agents to develop stable gels in medium-salinity water. (2) Gels enhanced using the methods above all become unstable in a more challenging ultra-high-saline condition (TDS: 225,068.0 mg/L). In this case, special calcium- and magnesium-resistant polymers are required to prepare stable gels, which show 0% syneresis rates after 30 days, have relatively low strengths, but do produce a good plugging effect in high-permeability cores.

Backcrossing is a powerful tool for plant breeding. The improved marker-assisted backcrossing intends to transfer targeted genes or quantitative trait loci (QTLs) of interest from a donor parent into a recurrent parent. In this study, a tobacco BC4F3 population was generated using Y3 and K326 as hybrid parents and YF1-1 as F1 parents. High-throughput sequencing data of 381 pedigree populations were used to construct high-density genetic maps containing 24 142 high-quality single nucleotide polymorphism (SNP) markers with an average genetic distance of 0.59 cM. A genome module analysis was then performed for all the offspring. A total of forty-three candidate QTLs for six agronomics traits were identified. This study provides original biomarkers for tobacco breeding and offers clues for prospective backcrossing applications in other plants.

Triticum urartu is the progenitor of the A subgenome in tetraploid and hexaploid wheat. Uncovering the landscape of genetic variations in T. urartu will help us understand the evolutionary and polyploid characteristics of wheat. Here, we investigated the population genomics of T. urartu by genome-wide sequencing of 59 representative accessions collected around the world. A total of 42.2 million high-quality single-nucleotide polymorphisms and 3 million insertions and deletions were obtained by mapping reads to the reference genome. The ancient T. urartu population experienced a significant reduction in effective population size (Ne) from ∼3 000 000 to ∼140 000 and subsequently split into eastern Mediterranean coastal and Mesopotamian-Transcaucasian populations during the Younger Dryas period. A map of allelic drift paths displayed splits and mixtures between different geographic groups, and a strong genetic drift towards hexaploid wheat was also observed, indicating that the direct donor of the A subgenome originated from northwestern Syria. Genetic changes were revealed between the eastern Mediterranean coastal and Mesopotamian-Transcaucasian populations in genes orthologous to those regulating plant development and stress responses. A genome-wide association study identified two single-nucleotide polymorphisms in the exonic regions of the SEMI-DWARF 37 ortholog that corresponded to the different T. urartu ecotype groups. Our study provides novel insights into the origin and genetic legacy of the A subgenome in polyploid wheat and contributes a gene repertoire for genomics-enabled improvements in wheat breeding.

Cemented paste backfill (CPB) is wildly used in mines production practices around the world. The strength of CPB is the core of research which is affected by factors such as slurry concentration and cement content. In this paper, a research on the UCS is conducted by means of a combination of laboratory experiments and machine learning. BPNN, RBFNN, GRNN and LSTM are trained and used for UCS prediction based on 180 sets of experimental UCS data. The simulation results show that LSTM is the neural network with the optimal prediction performance (The total rank is 11). The trial-and-error, PSO, GWO and SSA are used to optimize the learning rate and the hidden layer nodes for LSTM. The comparison results show that GWO-LSTM is the optimal model which can effectively express the non-linear relationship between underflow productivity, slurry concentration, cement content and UCS in experiments (R=0.9915, RMSE = 0.0204, VAF = 98.2847 and T = 16.37 s). The correction coefficient (k) is defined to adjust the error between predicted UCS in laboratory (UCSM) and predicted UCS in actual engineering (UCSA) based on extensive engineering and experimental experience. Using GWO-LSTM combined with k, the strength of the filling body is successfully predicted for 153 different filled stopes with different stowing gradient at different curing times. This study provides both effective guidance and a new intelligent method for the support of safety mining.

Abstract Background Despite their regional economic importance and being increasingly reared globally, the origins and evolution of the llama and alpaca remain poorly understood. Here we report reference genomes for the llama, and for the guanaco and vicuña (their putative wild progenitors), compare these with the published alpaca genome, and resequence seven individuals of all four species to better understand domestication and introgression between the llama and alpaca. Results Phylogenomic analysis confirms that the llama was domesticated from the guanaco and the alpaca from the vicuña. Introgression was much higher in the alpaca genome (36%) than the llama (5%) and could be dated close to the time of the Spanish conquest, approximately 500 years ago. Introgression patterns are at their most variable on the X-chromosome of the alpaca, featuring 53 genes known to have deleterious X-linked phenotypes in humans. Strong genome-wide introgression signatures include olfactory receptor complexes into both species, hypertension resistance into alpaca, and fleece/fiber traits into llama. Genomic signatures of domestication in the llama include male reproductive traits, while in alpaca feature fleece characteristics, olfaction-related and hypoxia adaptation traits. Expression analysis of the introgressed region that is syntenic to human HSA4q21, a gene cluster previously associated with hypertension in humans under hypoxic conditions, shows a previously undocumented role for PRDM8 downregulation as a potential transcriptional regulation mechanism, analogous to that previously reported at high altitude for hypoxia-inducible factor 1α. Conclusions The unprecedented introgression signatures within both domestic camelid genomes may reflect post-conquest changes in agriculture and the breakdown of traditional management practices.

The stability of the cemented paste backfill roof (CPB roof) is critical to safe production in mines using the underhand drift cut-and-fill stopping. To investigate the scientific and reasonable design method of key parameters (size and strength) of the CPB roof and the stress state of the CPB roof during the mining process, field measurements were carried out with Jinchuan Group’s third mining area as the engineering background. Based on the measurement results, a mechanics model was constructed based on the thick plate theory. The field measurement results show that the overlying load on the CPB roof tends to increase first and then decrease with the gradual mining of the stope, and the maximum overlying load values of the two CPB roofs measured are 0.240 MPa and 0.244 MPa, respectively. With the gradual mining of the stope, the deformation of the CPB roof shows a trend of increasing first and then stabilizing. Based on the thick plate theory, the stress model of the CPB roof is constructed, and the error between the calculation results of the model and the field measurement results does not exceed 5%. Applying the research results to the three mines of Jinchuan Group, the span of the stope can be expanded from 5 m to 6 m under the existing strength standard of the filling body, which can increase its mining capacity by 20%. This study is the first to measure the overlying load and the tensile stress value on the CPB roof, which is an important guideline for related theoretical research.

To explore the methodology for improving ultralow permeability reservoir recovery, cores of ultralow permeability reservoirs in China’s Ordos Basin were selected to study the dynamic imbibition micromechanism of crude oil in nanopore throat through core-flooding laboratory experiment and nuclear magnetic resonance (NMR) observation. In the meantime, the microimbibition characteristics and dynamic discharge of oil between matrix and fracture in partially closed boundary reservoirs were simulated to utmostly reflect the actual reservoir conditions. Our findings suggest that dynamic imbibition between fracture and matrix serves the core technology for improving the recovery of ultralow permeability reservoirs, while the main factors affecting dynamic imbibition efficiency include wettability, permeability, injection rate, fracture, water huff and puff cycles, and soaking time. Wettability, in particular, weighs the most, and imbibition can take place either on water-wet rocks or transformed oil-wet rocks with an imbibition agent added in during the waterflooding process. Meanwhile, the higher the permeability is in place, the greater the dynamic imbibition recovery might achieve. The experiments indicate that the dynamic imbibition recovery of a fractured core is 16.26% higher than that of a nonfractured core. Additionally, fractures can not only enhance imbibition recovery but also accelerate the occurrence of dynamic imbibition. The optimal water injection rate of dynamic imbibition is 0.1 mL/min; the reasonable huff and puff cycle of the ultralow permeability reservoirs tends to be two to three cycles; the optimal soaking time of ultralow permeability reservoir is speculated to be 30 days. Finally, the field practice shows that after Stimulated Reservoir Volume (SRV) and dynamic imbibition in 5 horizontal wells in An83 oilfield, there is a remarkable drop in water cut and a noticeable rise in oil production. This research underpins the significance of a dynamic imbibition effect in the development of ultralow permeability oilfield.

In this study, the analysis and control of stability of surrounding rock in deep fractured soft rock roadway located in the underground mine of Jinfeng gold mine in Guizhou Province, China, has been investigated. The surrounding rock of roadway has been analyzed to characterize its deformation and failure mechanism through field survey, testing of rock physical and mechanical properties, in situ stress measure, analysis of mineral components of rock, and investigation of rock fragmentation degree. Based on the numerical simulation technology, the influence of different factors on the stability of roadway is studied. The physical and mechanical properties of surrounding rock and the bearing capacity of surrounding rock layer are to be improved to maintain the stability of broken soft rock roadway as high ground stress, rock fragmentation, and poor lithology leading to tunnel instability. Hence, a high-strength “cable bolt + fiber-reinforced shotcrete + steel mesh + split sets + resin bolt + cement grouting” combined support system has been proposed to improve the effective bearing structure significantly with high integrity and bearing capacity.

Current hydraulic fracture models are mainly based on elastic theories, which fail to give accurate prediction of fracture parameters in plasticity formation. This paper proposes a fluid–solid coupling model for fracture propagation in elastoplastic formations. The rock plastic deformation in the model satisfies the Mohr-Coulomb yield criterion and plastic strain increment theory. The extended finite-element method (XFEM) combined with the cohesive zone method (CZM) is used to solve the coupled model. The accuracy of the model is validated against existing models. The effects of stress difference, friction angle, and dilation angle on fracture shape (length, width), injection pressure, plastic deformation, induced stress, and pore pressure are investigated through the model. The results indicate that compared with elastic formation, fracture propagation in elastoplastic formation is more difficult, the breakdown pressure and extending pressure are greater, and fracture shape is wider and shorter. The plastic deformation causes the fracture tip to become blunt. Under the condition of high stress difference or low friction angle formation, it is prone to occur large plastic deformation zones and form wide and short fracture. Compared with friction angle, dilation angle is less sensitive to plastic deformation, fracture parameters, and fracture geometry. For the formation with high stress difference and friction angle, the effect of plasticity deformation on fracture propagation should not be ignored.

The CRISPR/Cas9 system is an efficient genome editing tool that possesses the outstanding advantages of simplicity and high efficiency. Genome-wide identification and specificity analysis of editing sites is an effective approach for mitigating the risk of off-target effects of CRISPR/Cas9 and has been applied in several plant species but has not yet been reported in pepper. In present study, we first identified genome-wide CRISPR/Cas9 editing sites based on the 'Zunla-1' reference genome and then evaluated the specificity of CRISPR/Cas9 editing sites through whole-genome alignment. Results showed that a total of 603,202,314 CRISPR/Cas9 editing sites, including 229,909,837 (~38.11%) NGG-PAM sites and 373,292,477 (~61.89%) NAG-PAM sites, were detectable in the pepper genome, and the systematic characterization of their composition and distribution was performed. Furthermore, 29,623,855 highly specific NGG-PAM sites were identified through whole-genome alignment analysis. There were 26,699,38 (~90.13%) highly specific NGG-PAM sites located in intergenic regions, which was 9.13 times of the number in genic regions, but the average density in genic regions was higher than that in intergenic regions. More importantly, 34,251 (~96.93%) out of 35,336 annotated genes exhibited at least one highly specific NGG-PAM site in their exons, and 90.50% of the annotated genes exhibited at least 4 highly specific NGG- PAM sites, indicating that the set of highly specific CRISPR/Cas9 editing sites identified in this study was widely applicable and conducive to the minimization of the off-target effects of CRISPR/Cas9 in pepper.

As an important topographical factor, slope aspect has an essential influence on plant community structure and leaf traits. Leaf nitrogen (N) and phosphorus (P) stoichiometry is an important leaf trait indicating plant growth. However, it has rarely been studied how leaf N:P stoichiometry correlates with plant community structure along the slope aspect gradient. To understand the variation of leaf N:P stoichiometry and community structure, as well as their correlation with each other, the species composition and leaf N and P in Tibetan meadows were investigated across three slope aspects: the south-, west-, and north-facing slope aspects (i.e., SFS, WFS, and NFS). In our results, leaf N:P ratio was significantly lower on the NFS than on the SFS, indicating N and P limitation on the NFS and SFS, respectively. Richness of forb species and all species was higher on the NFS than on the SFS and was negatively correlated with leaf N concentration, whereas graminoid richness was not statistically different among the slope aspects and showed a negative correlation with leaf P concentration. Thus, our results provide evidence for the functional significance of leaf N:P stoichiometry for species composition along a natural environmental gradient. Our findings could provide applicable guidance in the refinement of grassland management and biodiversity conservation based on topography.

Abstract MADS-box genes encode transcription factors that are involved in plant development control (particularly in floral organogenesis) and signal transduction pathways, though a comprehensive analysis of MADS-box family proteins in Chinese jujube (Ziziphus jujuba Mill.) is still missing. Here, we report a genome-wide analysis of the MADS-box gene family in Chinese jujube. Based on phylogenetic analyses, 52 jujube MADS-box genes were classified into 25 MIKCC-type, 3 MIKC*-type, 16 Mα, 5 Mβ and 3 Mγ genes. 37 genes were randomly distributed across all 12 putative chromosomes. We found that the type II genes are more complex than the type I genes and that tandem duplications have occurred in three groups of MADS-box genes. Meanwhile, some gene pairs in the same clade displayed similar or distinct expression profiles, suggesting possible functional redundancy or divergence. MIKCC-type genes exhibited typical temporal and spatial expression patterns in the four whorls of floral tissues. The expressions of B, C/D and E-type genes were significantly suppressed in phyllody as compared to flower, providing valuable evidence for their involvement in flower development. This study is the first comprehensive analysis of the MADS-box family in jujube, and provides valuable information for elucidating molecular regulation mechanism of jujube flower development.

Bitter gourd (Momordica charantia) is widely cultivated as a vegetable and medicinal herb in many Asian and African countries. After the sequencing of the cucumber (Cucumis sativus), watermelon (Citrullus lanatus), and melon (Cucumis melo) genomes, bitter gourd became the fourth cucurbit species whose whole genome was sequenced. However, a comprehensive analysis of simple sequence repeats (SSRs) in bitter gourd, including a comparison with the three aforementioned cucurbit species has not yet been published. Here, we identified a total of 188,091 and 167,160 SSR motifs in the genomes of the bitter gourd lines ‘Dali-11’ and ‘OHB3-1,’ respectively. Subsequently, the SSR content, motif lengths, and classified motif types were characterized for the bitter gourd genomes and compared among all the cucurbit genomes. Lastly, a large set of 138,727 unique in silico SSR primer pairs were designed for bitter gourd. Among these, 71 primers were selected, all of which successfully amplified SSRs from the two bitter gourd lines ‘Dali-11’ and ‘K44’. To further examine the utilization of unique SSR primers, 21 SSR markers were used to genotype a collection of 211 bitter gourd lines from all over the world. A model-based clustering method and phylogenetic analysis indicated a clear separation among the geographic groups. The genomic SSR markers developed in this study have considerable potential value in advancing bitter gourd research.

Scheduling EV user’s charging behavior based on charging price and applying renewable energy resources are the effective methods to release the load pressure of power grids brought about by the large-scale popularity of electric vehicles (EVs). This paper presents a novel approach for EV charging scheduling based on price negotiation. Firstly, the EV charging system framework based on price negotiation and renewable energy resources is discussed. Secondly, the price negotiation model is presented, including the initial price models and the conditions of transactions. Finally, an EV charging scheduling mechanism based on price negotiation (CSM-PN), including the price adjustment strategies of both the operator and EV users is proposed to seek a final transaction during multi-round price negotiation. Simulation results show that this novel approach can effectively improve the charging station operator’s income, reduce the EV users’ costs, and balance the load of the power grid while improving the efficiency of the EV charging system.

The elderly comprises over one-third of hepatocellular carcinoma (HCC) patients, however, they are not adequately represented in prognostic studies. The study aims to determine the prognostic significance of the preoperative prognostic nutritional index (PNI) and develop nomograms for predicting their recurrence-free and overall survival (RFS and OS). The study consisted of 282 elderly patients (aged ≥ 65 years) with early-stage HCC (China Liver Cancer Staging System: I-IIA) after curative resection (R0). They were randomly divided into a training (n = 197) and a test cohort (n = 85). The patients were stratified into two groups: PNI-low (PNI ≤ 49.05) and PNI-high (PNI > 49.05) based on a cut-off value. Most patients' demographics and perioperative outcomes were comparable, while patients in the PNI-high group were younger (P = 0.002), heavier (P < 0.001), and had lower comorbidity rates (P = 0.003). Although the tumor stages were earlier in the PNIlow group (P < 0.001), patients' OS (5-year OS: 48.9% vs. 93.1%) and RFS (5-year RFS: 27.3% vs. 75.7%) were significantly worse compared to the PNI-high group (both P < 0.0001). Patients' OS and RFS nomograms were developed by incorporating independent survival predictors including chronic obstructive pulmonary disease (COPD), age ≥ 75 years, PNI-low, tumor presence of satellite nodules, capsule, and microvascular invasion. The nomograms showed good calibration and discrimination, with all C-indexes ≥ 0.75 and calibration plots essentially coinciding with the diagonal. In conclusion, for elderly HCC patients, COPD, age ≥ 75 years, PNI-low, and tumor presence of satellite nodules, capsule, and microvascular invasion were independent prognostic factors. The nomogram could accurately predict the prognosis of these patients. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a symmetric all-dielectric two-dimensional grating with high transmittance and high figure of merit based on cylindrical nanoarrays as a liquid sensing structure with small volume and high sensitivity. The device is optimized using the finite element method to calculate the transmissivity under TE/TM polarization. When the incident angle is 4 degrees, the transmissivity of the grating is nearly 1 with a full width at half maximum of 0.016 nm and a sensitivity of 256.2 nm/RIU. The high figure of merit is 16214.936, and the corresponding quality factor can reach 56572.438. The sensor characteristics of the incident angle on the device are analyzed, and the normalized electric field distribution indicates that the change of the incident angle has a significant modulation ability for the resonance energy distribution. The proposed sensor is independent of polarization state, easy to control and integrate, and has broad application prospects in fields such as liquid solution detection, ocean surveys, and position sensing.