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Engineering inspection is of great significance to ensure the safe operation of the project. However, the unclear query statements of the detectors pose a challenge to the intelligent question answering task. Existing knowledge graph-based question-answering systems face issues of vocabulary limitations and reliance on fixed templates. Solely relying on Large Language Models (LLMs) for questioning introduces noise and randomness due to their extensive knowledge base. Therefore, this paper proposes a novel approach that synergistically employs both knowledge graphs and LLMs for intelligent question-answering in hydroengineering inspection. The method divides the overall task into five units, progressively clarifying query statements for accurate answers. Leveraging LLM’s vast prior knowledge, robust semantic understanding, and contextual learning mitigates issues related to vocabulary limitations and template dependence. Simultaneously, the knowledge contained in the graph is integrated into an optimal clarification path and transferred to LLM to address noise and randomness, thereby enhancing the efficiency of the clarification process. Benchmark experiments demonstrate that the proposed method achieves Mean Reciprocal Rank (MRR), Mean Average Precision (MAP), Precision, and Recall metrics all above 0.73. The results affirm the method’s effectiveness in improving the accuracy of intelligent question-answering in hydroengineering inspection, with potential implications for similar applications in other domains of hydraulic engineering.

Abstract Reservoir dispatching regulations are a crucial basis for reservoir operation, and using information extraction technology to extract entities and relationships from heterogeneous texts to form triples can provide structured knowledge support for professionals in making dispatch decisions and intelligent recommendations. Current information extraction technologies require manual data labeling, consuming a significant amount of time. As the number of dispatch rules increases, this method cannot meet the need for timely generation of dispatch plans during emergency flood control periods. Furthermore, utilizing natural language prompts to guide large language models in completing reservoir dispatch extraction tasks also presents challenges of cognitive load and instability in model output. Therefore, this paper proposes an entity and relationship extraction method for reservoir dispatch based on structured prompt language. Initially, a variety of labels are refined according to the extraction tasks, then organized and defined using the Backus–Naur Form (BNF) to create a structured format, thus better guiding large language models in the extraction work. Moreover, an AI agent based on this method has been developed to facilitate operation by dispatch professionals, allowing for the quick acquisition of structured data. Experimental verification has shown that, in the task of extracting entities and relationships for reservoir dispatch, this AI agent not only effectively reduces cognitive burden and the impact of instability in model output but also demonstrates high extraction performance (with F1 scores for extracting entities and relationships both above 80%), offering a new solution approach for knowledge extraction tasks in other water resource fields.

Abstract Background The prospective phase III multi-centre L-MOCA trial (NCT03534453) has demonstrated the encouraging efficacy and manageable safety profile of olaparib maintenance therapy in the Asian (mainly Chinese) patients with platinum-sensitive relapsed ovarian cancer (PSROC). In this study, we report the preplanned exploratory biomarker analysis of the L-MOCA trial, which investigated the effects of homologous recombination deficiency (HRD) and programmed cell death ligand 1 (PD-L1) expression on olaparib efficacy. Methods HRD status was determined using the ACTHRD assay, an enrichment-based targeted next-generation sequencing assay. PD-L1 expression was assessed by SP263 immunohistochemistry assay. PD-L1 expression positivity was defined by the PD-L1 expression on ≥ 1% of immune cells. Kaplan–Meier method was utilised to analyse progression-free survival (PFS). Results This exploratory biomarker analysis included 225 patients and tested HRD status [N = 190; positive, N = 125 (65.8%)], PD-L1 expression [N = 196; positive, N = 56 (28.6%)], and BRCA1/2 mutation status (N = 219). The HRD-positive patients displayed greater median PFS than the HRD-negative patients [17.9 months (95% CI: 14.5–22.1) versus 9.2 months (95% CI: 7.5–13.8)]. PD-L1 was predominantly expressed on immune cells. Positive PD-L1 expression on immune cells was associated with shortened median PFS in the patients with germline BRCA1/2 mutations [14.5 months (95% CI: 7.4–18.2) versus 22.2 months (95% CI: 18.3–NA)]. Conversely, positive PD-L1 expression on immune cells was associated with prolonged median PFS in the patients with wild-type BRCA1/2 [20.9 months (95% CI: 13.9–NA) versus 8.3 months (95% CI: 6.7–13.8)]. Conclusions HRD remained an effective biomarker for enhanced olaparib efficacy in the Asian patients with PSROC. Positive PD-L1 expression was associated with decreased olaparib efficacy in the patients with germline BRCA1/2 mutations but associated with improved olaparib efficacy in the patients with wild-type BRCA1/2. Trial registration NCT03534453. Registered at May 23, 2018.

Excessive cavity pressure may result in a sand casting explosion, and corresponding measures should be adopted to prevent these consequences. In this study, the pressure variations in the cavity were first investigated based upon on-site testing by taking the resin contents into consideration, and then the evolution characteristics of sand casting explosion accidents were analyzed in depth by system dynamics, chaos theory, and the bow-tie model. When the resin contents are 1.3 wt%, 1.4 wt%, and 1.5 wt%, the pressures of the gas vent increase by 27.0 Pa, 32.8 Pa, and 35.6 Pa, respectively. To reduce the pressure of the cavity, the resin content should be reduced. The evolutionary process of sand casting explosion accidents has a noticeable butterfly effect and randomness, whose occurrence is comprehensively affected by human, object, environment, management and emergency subsystems. The leading causes of sand casting explosion accidents mainly include the extensive gas evolution characteristics of foundry sand, cavity exhaust blockage, and inadequate safety monitoring. The leading consequences of sand casting explosion accidents mainly include casualties, secondary disasters, and social panic. The implications of these findings concerning sand casting explosion accidents can be regarded as the foundation for accident prevention in practice.

The pouring of sand casting is accompanied by severe heat conduction, and there is an urgent need to investigate the pyrolysis properties of foundry sand. The main purpose of this study was to investigate the pyrolysis behaviors of resin sand, including precoated sand (PCS), hot box sand (HBS), and warm box sand (WBS), at heating rates of 20 °C/min, 30 °C/min, and 40 °C/min in nitrogen and air atmospheres. The mass loss of the resin sand was monitored continuously with a simultaneous thermal analyzer, and the kinetic parameters of the resin sand were calculated based on the Coats–Redfern method and thermal data. The average mass loss of the resin sand during pyrolysis was 3.03%, which was much smaller than that of the other sands. The volatile release characteristic index of resin sand could not be calculated based on this concept. To solve this issue, the term Tstv/mloss was established, and its value was determined. With increasing heating rates from 20 °C/min to 30 °C/min and from 30 °C/min to 40 °C/min, the mass losses of the resin sand increased by 0.79% and 0.64%, respectively, and the volatile release characteristic indices of the resin sand increased by 3.8 × 10−10 and 1.06 × 10−9, respectively. In addition, the mass losses and volatile release characteristic indices of resin sand in an air atmosphere were greater than those in a nitrogen atmosphere. With increasing heating rate, the activation energy of the resin sand decreased in a nitrogen atmosphere. The findings concerning the thermal decomposition behaviors of resin sand provided a theoretical basis for the pouring step of the sand casting process.

Abstract Background Angiopoietin-like 4 (ANGPTL4) is highly expressed in a variety of neoplasms and promotes cancer progression. Nevertheless, the mechanism of ANGPTL4 in ovarian cancer (OC) metastasis remains unclear. This study aimeds to explore whether ANGPTL4 regulates OC progression and elucidate the underlying mechanism. Methods ANGPTL4 expression in clinical patient tumor samples was determined by immunohistochemistry (IHC) and high-throughput sequencing. ANGPTL4 knockdown (KD) and the addition of exogeneous cANGPTL4 protein were used to investigate its function. An in vivo xenograft tumor experiment was performed by intraperitoneal injection of SKOV3 cells transfected with short hairpin RNAs (shRNAs) targeting ANGPTL4 in nude mice. Western blotting and qRT-PCR were used to detect the levels of ANGPTL4, CDH5, p-AKT, AKT, ETV5, MMP2 and MMP9 in SKOV3 and HO8910 cells transfected with sh-ANGPTL4 or shRNAs targeting ETV5. Results Increased levels of ANGPTL4 were associated with poor prognosis and metastasis in OC and induced the angiogenesis and metastasis of OC cells both in vivo and in vitro. This tumorigenic effect was dependent on CDH5, and the expression levels of ANGPTL4 and CDH5 in human OC werepositively correlated. In addition, CDH5 activated p-AKT, and upregulated the expression of MMP2 and MMP9. We also found that the expression of ETV5 was upregulated by ANGPTL4, which could bind the promoter region of CDH5, leading to increased CDH5 expression. Conclusion Our data indicated that an increase in the ANGPTL4 level results in increased ETV5 expression in OC, leading to metastasis via activation of the CDH5/AKT/MMP9 signaling pathway.

Abstract Arranging dense donors around a single acceptor for the assembly of efficient light‐harvesting antennas is a long‐standing challenge due to the intractable aggregation‐caused quenching of dense donors. Herein, we designed a cationic aggregation‐induced emission (AIE) amphiphile to self‐assemble with natural DNA duplexes. As an efficient donor, the as‐prepared cationic AIE amphiphile could be densely attached to the phosphate groups of natural DNA duplexes by using the smaller cationic trimethylammonium. The long alkyl chain between the cationic trimethylammonium and the AIE fluorophore allowed for avoiding the insufficient binding caused by the steric hindrance of the AIE fluorophore, resulting in a remarkably high donor/acceptor ratio comparable to that of the widely developed custom DNA assemblies. The proposed self‐assembly strategy provided novel flexible avenues for the assembling of finely controlled and efficient light‐harvesting systems into natural DNA with little synthetic modifications and low cost.

ObjectiveAiming at the problems of dynamic uncertainty and unknown disturbance in the trajectory tracking control of underactuated surface ships, an adaptive neural network finite time trajectory tracking control scheme is designed. MethodThe underactuated variation is carried out using the method of kinematic virtual control law transformation and bounded constraints. Under the framework of Backstepping, neural networks are used to reconstruct unknown dynamics, and an adaptive law is designed to approach the upper bound of unknown disturbances. The Lyapunov direct method provides a rigorous theoretical analysis which proves that all the signals of the closed-loop system are bounded, and the tracking error converges to a bounded interval. ResultsThe simulation results show that this control scheme can make an underactuated ship track the desired trajectory in a limited time, the convergence speed of the system error is faster than that of the traditional control scheme, and the upper and lower bounds of the error are also smaller. It also shows good robustness in the face of unknown time-varying interference from the outside world. ConclusionThe results of this study can provide valuable references for the tracking and control of ship trajectories, giving it great practical engineering significance.

Background Circular RNA is a key regulator involved in the progression of many human diseases including diabetic nephropathy (DN). However, the role and mechanism of hsa_circ_0037128 in the occurrence and development of DN remains to be explored. Methods High glucose (HG)-induced podocytes were used to construct in vitro DN models. The expression of hsa_circ_0037128, microRNA (miR)-31-5p, and Kruppel-like factor 9 (KLF9) was determined using quantitative real-time polymerase chain reaction. The viability and apoptosis of podocytes was measured using cell counting kit 8 assay and flow cytometry. Western blot analysis was performed to examine the protein levels of apoptosis markers and KLF9 in podocytes. Inflammation factors were detected by ELISA assay, and oxidative stress markers were assessed by corresponding Assay Kits. In addition, the interaction between miR-31-5p and hsa_circ_0037128 or KLF9 was verified using dual-luciferase reporter assay and RIP assay. Results Our data suggested that hsa_circ_0037128 was highly expressed in DN patients and HG-induced podocytes. In HG-induced podocytes, hsa_circ_0037128 knockdown could alleviate HG-induced podocytes injury. In the term of mechanism, hsa_circ_0037128 could sponge miR-31-5p to upregulate KLF9. MiR-31-5p inhibitor could reverse the negative regulation of hsa_circ_0037128 silencing on HG-induced podocytes injury. Also, miR-31-5p relieved HG-induced podocytes injury, and this effect also could be reversed by KLF9 overexpression. Conclusion In summary, our data showed that hsa_circ_0037128 could promote HG-induced podocytes injury via regulating miR-31-5p/KLF9 axis, showing that hsa_circ_0037128 might be a target for DN treatment.

A deep understanding of the relationship between the knowledge acquired and the graduation requirements is essential for students to precisely meet the graduation requirements and to become human resources with specific knowledge, skills and professionalism. In this paper, we define the ontology layer of the knowledge graph by deeply analyzing the relationship between graduation requirement, course and knowledge. Based on the implementation of the concept of Outcome Based Education, we use Knowledge extraction, fusion, reasoning techniques to construct a hierarchical knowledge graph with the main line of "knowledge-course-graduation requirements. In the process of knowledge extraction, in order to alleviate the huge labor overhead brought by traditional extraction methods, this paper adopts a transfer learning method to extract triadic knowledge using the multi-task framework EERJE, Finally, knowledge reasoning was also performed with the help of LLM to further expand the knowledge scope. The comprehensiveness, correctness and relatedness of the data were evaluated through the experiment, and the F1 value of the ternary group extraction was 87.76%, the accuracy rate of entity classification was 85.42%, the data coverage was more comprehensive, and the results showed that the data quality was better, and the knowledge graph constructed in this way can fully optimize the organization and management of teaching resources, help students intuitively and comprehensively grasp the correlation and difference between graduation requirements and various knowledge points, and let the Students can carry out personalized independent learning through the navigation mode of knowledge graph, strengthen their weak links, and complete the relevant graduation requirements, which effectively improves the degree of students' graduation requirements achievement. This new paradigm of knowledge graph enabled teaching is of reference significance for engineering education majors to improve the degree of graduation requirements achievement.

BackgroundAlthough global contraceptive coverage has increased significantly, high rates of unintended pregnancy remain the current global status quo. A comparative analysis of the differences and correlations of knowledge, attitude and practice (KAP) of sexual and reproductive health (SRH) of both partners will help guide public health work according to gender characteristics and needs, and reduce the occurrence of unintended pregnancy.MethodsA questionnaire survey of people with unintended pregnancies including women and their male partners (n = 1,275 pairs) who sought help from the Shanghai General Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from October 2017 to October 2021. Data were collected on sexual and reproductive health knowledge, attitudes, and practices in both partners who had unintended pregnancies. Chi-square test and Logistic regression were used to analyze the relationship between the occurrence of unintended pregnancy and KAP and its influencing factors. Paired odds ratio and McNemar's test were used to estimate the difference and concordance of KAP between partners.ResultsThis study included 1,275 partners with a mean age of 30.0 years. The partner's overall level of KAP is good. Compared with women, men had better knowledge (χ2 = 3.93, p = 0.047) and more active contraceptive practices (χ2 = 19.44, p < 0.001). In the analysis of partner concordance, male contraceptive intention was found to be better than female [matched pairs odds ratio (ORMP) = 2.56, p < 0.001], and the concordance of positive contraceptive practice between partners increased with male education [adjusted odds ratio (aOR) = 1.556, 95% confidence interval (CI) = 1.185–2.044, p = 0.001]. In partner-paired regression analysis, compared with good contraceptive knowledge in both men and women in the partner, the risk of negative contraceptive practice was 1.7 times (aOR = 1.721, 95% CI = 1.234–2.400, p = 0.001) higher with good contraceptive knowledge in women but negative in men, while women with poor contraceptive knowledge but men with good knowledge are 1.3 times (aOR = 1.349, 95% CI = 1.000–1.819, p = 0.05) more likely to have negative contraceptive practices. In addition, compared with partners with positive contraceptive attitudes, women with positive attitudes but negative men and women with negative attitudes but positive men had 1.7 and 1.4 times the risk of negative contraceptive practices, respectively.ConclusionThe study found that unintended pregnancy occurs mainly in young people, and the younger age of first sexual intercourse, the low education background and the lack of discussion of contraception between partners are risk factors for not taking contraceptive measures. Men's better knowledge and contraceptive practices compared with female partners, and poor male contraceptive knowledge and attitudes may lead to a higher risk of negative contraceptive practices, the results suggest that male KAP plays an important role in promoting contraceptive use and reducing unintended pregnancy.

Abstract Background Though massively parallel sequencing has been widely applied to noninvasive prenatal screen for common trisomy, the clinical use of massively parallel sequencing to noninvasive prenatal diagnose monogenic disorders is limited. This study was to develop a method for directly determining paternal haplotypes for noninvasive prenatal diagnosis of monogenic disorders without requiring proband’s samples. Methods The study recruited 40 families at high risk for autosomal recessive diseases. The targeted linked-read sequencing was performed on high molecular weight (HMW) DNA of parents using customized probes designed to capture targeted genes and single-nucleotide polymorphisms (SNPs) distributed within 1Mb flanking region of targeted genes. Plasma DNA from pregnant mothers also underwent targeted sequencing using the same probes to determine fetal haplotypes according to parental haplotypes. The results were further confirmed by invasive prenatal diagnosis. Results Seventy-eight parental haplotypes of targeted gene were successfully determined by targeted linked-read sequencing. The predicted fetal inheritance of variant was correctly deduced in 38 families in which the variants had been confirmed by invasive prenatal diagnosis. Two families were determined to be no-call. Conclusions Targeted linked-read sequencing method demonstrated to be an effective means to phase personal haplotype for noninvasive prenatal diagnosis of monogenic disorders.

At present, it is still a challenge to prepare multifunctional composite nanomaterials with simple composition and favorable structure. Here, multifunctional Fe3O4@nitrogen-doped carbon (N-C) nanocomposites with hollow porous core-shell structure and significant electrochemical, adsorption and sensing performances were successfully synthesized through the hydrothermal method, polymer coating, then thermal annealing process in nitrogen (N2) and lastly etching in hydrochloric acid (HCl). The morphologies and properties of the as-obtained Fe3O4@N-C nanocomposites were markedly affected by the etching time of HCl. When the Fe3O4@N-C nanocomposites after etching for 30 min (Fe3O4@N-C-3) were applied as the anodes for lithium-ion batteries (LIBs), the invertible capacity could reach 1772 mA h g−1 after 100 cycles at the current density of 0.2 A g−1, which is much better than that of Fe3O4@N-C nanocomposites etched, respectively, for 15 min and 45 min (948 mA h g−1 and 1127 mA h g−1). Additionally, the hollow porous Fe3O4@N-C-3 nanocomposites also exhibited superior rate capacity (950 mA h g−1 at 0.6 A g−1). The excellent electrochemical properties of Fe3O4@N-C nanocomposites are attributed to their distinctive hollow porous core-shell structure and appropriate N-doped carbon coating, which could provide high-efficiency transmission channels for ions/electrons, improve the structural stability and accommodate the volume variation in the repeated Li insertion/extraction procedure. In addition, the Fe3O4@N-C nanocomposites etched by HCl for different lengths of time, especially Fe3O4@N-C-3 nanocomposites, also show good performance as adsorbents for the removal of the organic dye (methyl orange, MO) and surface-enhanced Raman scattering (SERS) substrates for the determination of a pesticide (thiram). This work provides reference for the design and preparation of multifunctional materials with peculiar pore structure and uncomplicated composition.

Abstract Background Noninvasive prenatal testing (NIPT) of recessive monogenic diseases depends heavily on knowing the correct parental haplotypes. However, the currently used family-based haplotyping method requires pedigrees, and molecular haplotyping is highly challenging due to its high cost, long turnaround time, and complexity. Here, we proposed a new two-step approach, population-based haplotyping-NIPT (PBH-NIPT), using α-thalassemia and β-thalassemia as prototypes. Methods First, we deduced parental haplotypes with Beagle 4.0 with training on a large retrospective carrier screening dataset (4356 thalassemia carrier screening-positive cases). Second, we inferred fetal haplotypes using a parental haplotype-assisted hidden Markov model (HMM) and the Viterbi algorithm. Results With this approach, we enrolled 59 couples at risk of having a fetus with thalassemia and successfully inferred 94.1% (111/118) of fetal alleles. We confirmed these alleles by invasive prenatal diagnosis, with 99.1% (110/111) accuracy (95% CI, 95.1–100%). Conclusions These results demonstrate that PBH-NIPT is a sensitive, fast, and inexpensive strategy for NIPT of thalassemia.

Aim: We aimed to demonstrate noninvasive prenatal diagnosis (NIPD) of hemophilia A (HA) using a haplotype-based approach. Methods: Two families at risk for HA were recruited for this study. First, maternal haplotypes associated with pathogenic variants were constructed using the genotypes of the mothers and probands. Then, fetal haplotypes were deduced using a maternal haplotype-assisted hidden Markov model. Finally, the NIPD results were further confirmed by invasive prenatal diagnosis. Results: Two fetal genotypes were successfully inferred, with one normal fetus and one carrier fetus. The NIPD results were confirmed by invasive prenatal diagnosis, with a 100% consistency rate. Conclusion: Our test has been shown to be accurate and reliable. With further validation in a large patient cohort, this haplotype-based approach could be feasible for the NIPD of HA and other X-linked single-gene disorders.

A new control algorithm was designed to solve the problems of actuator physical failure, remote network attack, and sudden change in trajectory curvature when a port’s artificial intelligence-based transportation robots track transportation in a freight yard. First of all, the nonlinear, redundant, saturated sliding surface was designed based on the redundant information of sliding mode control caused by the finite nature of control performance; the dynamic acceleration characteristic of super-twisted sliding mode reaching law was considered to optimize the control high frequency change caused by trajectory mutation; and an improved super-twist reaching law was designed. Then, a nonlinear factor was designed to construct a nonlinear, fault-tolerant filtering mechanism to compensate for the abnormal part of the unknown input that cannot be executed by adaptive neural network reconstruction. On this basis, the finite-time technology and parameter-event-triggered mechanism were combined to reduce the dependence on communication resources. As a result, the design underwent simulation verification to verify its effectiveness and superiority. In the comparative simulation, under a consistent probability of a network attack, the tracking accuracy of the algorithm proposed in this paper was 22.65%, 12.69% and 11.48% higher those that of the traditional algorithms.

This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1186/s13048-022-01060-7.

Due to the unknown disturbance caused by the harsh environment in deep water, the stability of Underwater Tracked Remotely Opreated Vehicle (UTROV) trajectory tracking control is affected; especially the resistance forces of random vibrations caused by non-differentiable random disturbance resistance, which has become one of the main problems in controller design. Considering engineering practice, a stochastic model and new dynamic damping-based terminal sliding mode event-triggered fault-tolerant controller were designed in this paper. Firstly, based on the random resistance pre-compensation theory for the first time, a stochastic model was designed for differential drive UTROV. Meanwhile, a new nonsingular terminal sliding mode and dynamic damping reaching law were designed to achieve global finite-time convergence and reduce chattering with better robust response speed. Furthermore, to deal with the wear and tear caused by actuator failure and fixed sampling rate transmission, a new dynamic event trigger mechanism was designed and the faults analyzed. On this basis, combined with the finite-time adaptive on-line estimation technology, it can not only better reduce the transmission frequency, but also the finite-time dynamic active fault-tolerant compensation. The control scheme has semi-globally finite-time stability in probability and is proved by theory, which is compliant with engineering requirements. Then, according to characteristics of innovation, the three groups of simulation of control methods are designed to compare the methods in this paper. Finally the advantages of the method are verified by simulation to achieve the design expectations.

It has great significance to develop a convenient and efficient method for hydrogels with adjustable electric and magnetic properties, which can be used in human activity monitoring and personal healthcare diagnosis field. However, it is a big challenge to balance the relationship between the conductive and magnetic categories so that electromagnetic hydrogels could be developed by an in-situ fabrication way. In this work, we firstly proposed a sequential in-situ route to form polypyrrole (PPy) and Fe3O4 nanoparticles (Fe3O4 NPs) in sequence within polyvinyl alcohol (PVA) matrix for the hybrid hydrogels with decent mechanical, conductive, and magnetic properties simultaneously, named as Fe3O4/PPy/PVA hydrogel. The as-prepared hybrid hydrogels exhibited continuous electrons transporting path and magnetic responsive properties. Specifically, a unique combination of high electrical conductivity (up to 1.95 ± 0.17 E−4 S cm−1), saturation magnetization (5.42 emu g−1) and greatly enhanced mechanical properties (tensile strength up to 575.03 ± 28.32 kPa, elasticity modulus up to 461.19 ± 24.75 kPa). More importantly, these hybrid hydrogels demonstrated potential applications in biomedical electronic devices, such as strain sensors and magnetic navigators.

In this paper, an overlapping coalition formation game is proposed to conduct joint interference management and resource allocation in device-to-device (D2D) communications. We aim at improving the sum rate of all D2D links in D2D communications underlying cellular network without sacrificing the quality of service of each cellular user (CU) and D2D link. First, based on the cross-tier interference level between CUs and D2D links, each D2D link selects multiple best resource blocks (RBs) to reuse. Then, by dividing the user equipments (i.e., CU and D2D links) which share the same RB into one coalition, an initial overlapping coalitional structure is formed. A cooperative game with overlapping coalitions is further proposed to maximize the system utility in terms of sum rate of all D2D links. Finally, the characteristic analysis of the proposed algorithm is provided to validate that the user equipments can cooperate to form a stable and most beneficial coalitional structure with overlapping coalitions. Simulation results show that the proposed overlapping coalition formation game achieves a better performance compared with other existing schemes.

The energy-efficient resource allocation problem was taken in an ultra-dense network(UDN) consisted of multiple femtocells.Aiming at maximizing the energy efficiency (EE) of the whole network,quality of service (QoS) constraint and interference limitation was considered.Then,the established nonconvex and nonlinear problem was relaxed relying on Cauchy inequality,and was developed into a non-cooperative game.Additionally,a distributed EE maximization algorithm was proposed satisfying the max-min fairness (MMF) criterion.Simulation results show that the proposed algorithm outperformances the existing algorithms in terms of the EE and the throughput.

To cater for the requirements of high-precision indoor localization algorithms,a hybrid indoor localization algorithm based on received signal strength identification (RSSI) and inertial navigation was proposed.This algorithm used fingerprint identification algorithm to localize the agents,based on the RSSI values of ZigBee nodes in wireless sensor network.The algorithm combined the inertial information provided by inertial measurement units (IMU),to correct the RSSI localization results.This algorithm used Kalman filter and adopted state equations to describe the dynamic change rules of agents’ positions,thus it achieved a hybrid localization algorithm which relied WSN localization first and IMU last.Simulations evaluate that the proposed algorithm can improve the localization performances of algorithms which adopt RSSI localization and inertial navigation individually,and can greatly improve localization accuracy.