How to implement a knowledge graph completeness assessment with the guidance of user requirements

In the context of big data, many large-scale knowledge graphs have emerged to effectively organize the explosive growth of web data on the Internet. To select suitable knowledge graphs for use from many knowledge graphs, quality assessment is particularly important. As an important thing of quality assessment, completeness assessment generally refers to the ratio of the current data volume to the total data volume.When evaluating the completeness of a knowledge graph, it is often necessary to refine the completeness dimension by setting different completeness metrics to produce more complete and understandable evaluation results for the knowledge graph.However, lack of awareness of requirements is the most problematic quality issue. In the actual evaluation process, the existing completeness metrics need to consider the actual application. Therefore, to accurately recommend suitable knowledge graphs to many users, it is particularly important to develop relevant measurement metrics and formulate measurement schemes for completeness. In this paper, we will first clarify the concept of completeness, establish each metric of completeness, and finally design a measurement proposal for the completeness of knowledge graphs.

Classification of knowledge graph completeness measurement techniques

At present,although knowledge graphs have been widely used in various fields such as recommendation systems,question and answer systems,and intelligent search,there are always quality problems such as knowledge omissions and errors.Quality assessment and control,as an important means to ensure the quality of knowledge,can make the applications based on knowledge graphs more complete and more accurate by reasonably assessing the knowledge graphs and fixing and improving the quality problems at the same time.Therefore,as an indispensable part of the knowledge graph construction process,the results of quality assessment and control determine the usefulness of the knowledge graph.Among them,the assessment and enhancement of completeness,as an important part of the assessment and control phase,determine whether the knowledge graph can fully reflect objective phenomena and reveal potential connections among entities.In this paper,we review specific techniques of completeness assessment and classify completeness assessment techniques in terms of closed world assumptions,open world assumptions,and partial completeness assumptions.The purpose of this paper is to further promote the development of knowledge graph quality control and to lay the foundation for subsequent research on the completeness assessment of knowledge graphs by reviewing and classifying completeness assessment techniques.

Fourth-order phase-field modeling for brittle fracture in piezoelectric materials

Failure analyses of piezoelectric structures and devices are of engineering and scientific significance.In this paper,a fourth-order phase-field fracture model for piezoelectric solids is developed based on the Hamilton principle.Three typical electric boundary conditions are involved in the present model to characterize the fracture behaviors in various physical situations.A staggered algorithm is used to simulate the crack propagation.The polynomial splines over hierarchical T-meshes(PHT-splines)are adopted as the basis function,which owns the C1continuity.Systematic numerical simulations are performed to study the influence of the electric boundary conditions and the applied electric field on the fracture behaviors of piezoelectric materials.The electric boundary conditions may influence crack paths and fracture loads significantly.The present research may be helpful for the reliability evaluation of the piezoelectric structure in the future applications.

Existence of Monotone Positive Solution for a Fourth-Order Three-Point BVP with Sign-Changing Green’s Function

This paper is concerned with the following fourth-order three-point boundary value problem , where , we discuss the existence of positive solutions to the above problem by applying to the fixed point theory in cones and iterative technique.

On the completeness of eigen and root vector systems for fourth-order operator matrices and their applications

In this paper, we consider the eigenvalue problem of a class of fourth-order operator matrices appearing in mechan- ics, including the geometric multiplicity, algebraic index, and algebraic multiplicity of the eigenvalue, the symplectic orthogonality, and completeness of eigen and root vector systems. The obtained results are applied to the plate bending problem.

ALMOST SURE GLOBAL WELL-POSEDNESS FOR THE FOURTH-ORDER NONLINEAR SCHR?DINGER EQUATION WITH LARGE INITIAL DATA

We consider the fourth-order nonlinear Schr?dinger equation(4NLS)(i?t+εΔ+Δ2)u=c1um+c2(?u)um-1+c3(?u)2um-2,and establish the conditional almost sure global well-posedness for random initial data in Hs(Rd)for s∈(sc-1/2,sc],when d≥3 and m≥5,where sc:=d/2-2/(m-1)is the scaling critical regularity of 4NLS with the second order derivative nonlinearities.Our proof relies on the nonlinear estimates in a new M-norm and the stability theory in the probabilistic setting.Similar supercritical global well-posedness results also hold for d=2,m≥4 and d≥3,3≤m<5.

COMPLETE KAHLER METRICS WITH POSITIVE HOLOMORPHIC SECTIONAL CURVATURES ON CERTAIN LINE BUNDLES(RELATED TO A COHOMOGENEITY ONE POINT OF VIEW ON A YAU CONJECTURE)

In this article,we study Kahler metrics on a certain line bundle over some compact Kahler manifolds to find complete Kahler metrics with positive holomorphic sectional(or bisectional)curvatures.Thus,we apply a strategy to a famous Yau conjecture with a co-homogeneity one geometry.

Fourth-Order Predictive Modelling: II. 4th-BERRU-PM Methodology for Combining Measurements with Computations to Obtain Best-Estimate Results with Reduced Uncertainties

This work presents a comprehensive fourth-order predictive modeling (PM) methodology that uses the MaxEnt principle to incorporate fourth-order moments (means, covariances, skewness, kurtosis) of model parameters, computed and measured model responses, as well as fourth (and higher) order sensitivities of computed model responses to model parameters. This new methodology is designated by the acronym 4th-BERRU-PM, which stands for “fourth-order best-estimate results with reduced uncertainties.” The results predicted by the 4th-BERRU-PM incorporates, as particular cases, the results previously predicted by the second-order predictive modeling methodology 2nd-BERRU-PM, and vastly generalizes the results produced by extant data assimilation and data adjustment procedures.

Regenerative medicine strategies for chronic complete spinal cord injury

Spinal cord injury is a condition in which the parenchyma of the spinal cord is damaged by trauma or various diseases.While rapid progress has been made in regenerative medicine for spinal cord injury that was previously untreatable,most research in this field has focused on the early phase of incomplete injury.However,the majority of patients have chronic severe injuries;therefore,treatments for these situations are of fundamental importance.The reason why the treatment of complete spinal cord injury has not been studied is that,unlike in the early stage of incomplete spinal cord injury,there are various inhibitors of neural regeneration.Thus,we assumed that it is difficult to address all conditions with a single treatment in chronic complete spinal cord injury and that a combination of several treatments is essential to target severe pathologies.First,we established a combination therapy of cell transplantation and drug-releasing scaffolds,which contributes to functional recovery after chronic complete transection spinal cord injury,but we found that functional recovery was limited and still needs further investigation.Here,for the further development of the treatment of chronic complete spinal cord injury,we review the necessary approaches to the different pathologies based on our findings and the many studies that have been accumulated to date and discuss,with reference to the literature,which combination of treatments is most effective in achieving functional recovery.

Complete Hydatidiform Mole at Menopause: A Case Report from Panzi Hospital, Bukavu, Democratic Republic of Congo

Gestational trophoblastic disease is an abnormal proliferation of trophoblastic tissue during pregnancy. It occurs in women of childbearing age, although a few cases have also been observed in post-menopausal women, although it is extremely rare in the latter. Here we describe a rare case of complete hydatidiform mole in a 56-year-old female patient who presented with genital bleeding combined with nausea and vomiting and a gravid uterus 16 cm in height. The ultrasound findings and the increase in serum β-HCG to 182566.00 mIU/ml suggested a diagnosis of complete hydatidiform mole. Given the post-menopausal state and the future risk of post-molar gestational trophoblastic neoplasia, we opted for total hysterectomy without preservation of the adnexa via a transabdominal approach, followed by antimitotic treatment with methotrexate. The uterus measured 18.45 cm × 11.18 cm with intra cavitary vesicles. Microscopic examination showed chorionic villi of variable size and shape, most of which were dilated and oedematous, associated with trophoblastic cell proliferation and haemorrhage suggestive of complete benign hydatidiform mole. Follow-up showed a consistent decrease in serum β-HCG levels and no evidence of residual disease. A suspicion of gestational trophoblastic disease should be borne in mind when evaluating a patient with peri- or post-menopausal bleeding to avoid delay in diagnosis and treatment.

Evaluation of Laboratory Request Forms Completion in a Tertiary Medical Laboratory of the Democratic Republic of Congo

Background: The inadequacy in the completeness of the Laboratory Request Form (LRF) has been reported as one of the major sources of errors during the pre-analytical step of laboratory analysis. To prevent the occurrence of such errors, this study aimed at assessing the level of completeness of LRFs. Methods: A retrospective analysis of laboratory request forms was conducted at the Clinical Biology Laboratory of the Kinshasa University Clinic, DR Congo, between November 2021 to May 2022. The LRFs were evaluated according to the completeness of all sections including administrative data of the patient, data of physician who ordered the test, relevant patient’s clinical data and data of the biological sample. Results: From a total of 2842 LRFs evaluated, none was fully completed with all required information. Particularly, patient’s clinical data including the medical history, provisional diagnosis and current treatment, were the most absent in 99% LRFs. However, two sections related to patient’s ID and prescribed test were informed in 100% LRFs. Conclusion: The results of this preanalytical audit can serve as an improvement opportunity focused on strengthening awareness about complete filling of LRF.

Fourth-Order Predictive Modelling: I. General-Purpose Closed-Form Fourth-Order Moments-Constrained MaxEnt Distribution

This work (in two parts) will present a novel predictive modeling methodology aimed at obtaining “best-estimate results with reduced uncertainties” for the first four moments (mean values, covariance, skewness and kurtosis) of the optimally predicted distribution of model results and calibrated model parameters, by combining fourth-order experimental and computational information, including fourth (and higher) order sensitivities of computed model responses to model parameters. Underlying the construction of this fourth-order predictive modeling methodology is the “maximum entropy principle” which is initially used to obtain a novel closed-form expression of the (moments-constrained) fourth-order Maximum Entropy (MaxEnt) probability distribution constructed from the first four moments (means, covariances, skewness, kurtosis), which are assumed to be known, of an otherwise unknown distribution of a high-dimensional multivariate uncertain quantity of interest. This fourth-order MaxEnt distribution provides optimal compatibility of the available information while simultaneously ensuring minimal spurious information content, yielding an estimate of a probability density with the highest uncertainty among all densities satisfying the known moment constraints. Since this novel generic fourth-order MaxEnt distribution is of interest in its own right for applications in addition to predictive modeling, its construction is presented separately, in this first part of a two-part work. The fourth-order predictive modeling methodology that will be constructed by particularizing this generic fourth-order MaxEnt distribution will be presented in the accompanying work (Part-2).

Distributed collaborative complete coverage path planning based on hybrid strategy

Collaborative coverage path planning(CCPP) refers to obtaining the shortest paths passing over all places except obstacles in a certain area or space. A multi-unmanned aerial vehicle(UAV) collaborative CCPP algorithm is proposed for the urban rescue search or military search in outdoor environment.Due to flexible control of small UAVs, it can be considered that all UAVs fly at the same altitude, that is, they perform search tasks on a two-dimensional plane. Based on the agents’ motion characteristics and environmental information, a mathematical model of CCPP problem is established. The minimum time for UAVs to complete the CCPP is the objective function, and complete coverage constraint, no-fly constraint, collision avoidance constraint, and communication constraint are considered. Four motion strategies and two communication strategies are designed. Then a distributed CCPP algorithm is designed based on hybrid strategies. Simulation results compared with patternbased genetic algorithm(PBGA) and random search method show that the proposed method has stronger real-time performance and better scalability and can complete the complete CCPP task more efficiently and stably.

Diagnostic significance of complete blood cell count and hemogramderived markers for neonatal sepsis at Southwest Public Hospitals,Ethiopia

BACKGROUND Neonatal sepsis is defined as an infection-related condition characterized by signs and symptoms of bacteremia within the first month of life.It is the leading cause of mortality and morbidity among newborns.While several studies have been conducted in other parts of world to assess the usefulness of complete blood count parameters and hemogram-derived markers as early screening tools for neonatal sepsis,the associations between sepsis and its complications with these blood parameters are still being investigated in our setting and are not yet part of routine practice.AIM To evaluate the diagnostic significance of complete blood cell count hemogramderived novel markers for neonatal sepsis among neonates attending public hospitals in the southwest region of Oromia,Ethiopia,through a case control study.METHODS A case control study was conducted from October 2021 to October 2023 Sociodemographic,clinical history,and laboratory test results data were collected using structured questionnaires.The collected data were entered into Epi-data 3.1 version and exported to SPSS-25 for analysis.Chi-square,independent sample ttest,and receiver operator characteristics curve of curve were used for analysis.A P-value of less than 0.05 was considered statistically significant.RESULTS In this study,significant increases were observed in the following values in the case group compared to the control group:In white blood cell(WBC)count,neutrophils,monocyte,mean platelet volume(MPV),neutrophils to lymphocyte ratio,monocyte to lymphocyte ratio(MLR),red blood cell width to platelet count ratio(RPR),red blood width coefficient variation,MPV to RPR,and platelet to lymphocyte ratio.Regarding MLR,a cut-off value of≥0.26 was found,with a sensitivity of 68%,a specificity of 95%,a positive predictive value(PPV)of 93.2%,and a negative predictive value(NPV)of 74.8%.The area under the curve(AUC)was 0.828(P<0.001).For WBC,a cutoff value of≥11.42 was identified,with a sensitivity of 55%,a specificity of 89%,a PPV of 83.3%,and a NPV of 66.4%.The AUC was 0.81(P<0.001).Neutrophils had a sensitivity of 67%,a specificity of 81%,a PPV of 77.9%,and a NPV of 71.1%.The AUC was 0.801,with a cut-off value of≥6.76(P=0.001).These results indicate that they were excellent predictors of neonatal sepsis diagnosis.CONCLUSION The findings of our study suggest that certain hematological parameters and hemogram-derived markers may have a potential role in the diagnosis of neonatal sepsis.

Prediction of pathological complete response and prognosis in locally advanced rectal cancer

BACKGROUND Colorectal cancer is currently the third most common malignant tumor and the second leading cause of cancer-related death worldwide.Neoadjuvant chemoradiotherapy(nCRT)is standard for locally advanced rectal cancer(LARC).Except for pathological examination after resection,it is not known exactly whether LARC patients have achieved pathological complete response(pCR)before surgery.To date,there are no clear clinical indicators that can predict the efficacy of nCRT and patient outcomes.AIM To investigate the indicators that can predict pCR and long-term outcomes following nCRT in patients with LARC.METHODS Clinical data of 128 LARC patients admitted to our hospital between September 2013 and November 2022 were retrospectively analyzed.Patients were categorized into pCR and non-pCR groups.Univariate analysis(using the χ^(2) test or Fisher’s exact test)and logistic multivariate regression analysis were used to study clinical predictors affecting pCR.The 5-year disease-free survival(DFS)and overall survival(OS)rates were calculated using Kaplan-Meier analysis,and differences in survival curves were assessed with the log-rank test.RESULTS Univariate analysis showed that pretreatment carcinoembryonic antigen(CEA)level,lymphocyte-monocyte ratio(LMR),time interval between neoadjuvant therapy completion and total mesorectal excision,and tumor size were correlated with pCR.Multivariate results showed that CEA≤5 ng/mL(P=0.039),LMR>2.73(P=0.023),and time interval>10 wk(P=0.039)were independent predictors for pCR.Survival analysis demonstrated that patients in the pCR group had significantly higher 5-year DFS rates(94.7%vs 59.7%,P=0.002)and 5-year OS rates(95.8%vs 80.1%,P=0.019)compared to the non-pCR group.Tumor deposits(TDs)were significantly correlated with shorter DFS(P=0.002)and OS(P<0.001).CONCLUSION Pretreatment CEA,LMR,and time interval contribute to predicting nCRT efficacy in LARC patients.Achieving pCR demonstrates longer DFS and OS.TDs correlate with poor prognosis.

Unconfined compressive strength and failure behaviour of completely weathered granite from a fault zone

Understanding the strength characteristics and deformation behaviour of the tunnel surrounding rock in a fault zone is significant for tunnel stability evaluation.In this study,a series of unconfined compression tests were conducted to investigate the mechanical characteristics and failure behaviour of completely weathered granite(CWG)from a fault zone,considering with height-diameter(h/d)ratio,dry densities(ρd)and moisture contents(ω).Based on the experimental results,a regression mathematical model of unconfined compressive strength(UCS)for CWG was developed using the Multiple Nonlinear Regression method(MNLR).The research results indicated that the UCS of the specimen with a h/d ratio of 0.6 decreased with the increase ofω.When the h/d ratio increased to 1.0,the UCS increasedωwith up to 10.5%and then decreased.Increasingρd is conducive to the improvement of the UCS at anyω.The deformation and rupture process as well as final failure modes of the specimen are controlled by h/d ratio,ρd andω,and the h/d ratio is the dominant factor affecting the final failure mode,followed byωandρd.The specimens with different h/d ratio exhibited completely different fracture mode,i.e.,typical splitting failure(h/d=0.6)and shear failure(h/d=1.0).By comparing the experimental results,this regression model for predicting UCS is accurate and reliable,and the h/d ratio is the dominant factor affecting the UCS of CWG,followed byρd and thenω.These findings provide important references for maintenance of the tunnel crossing other fault fractured zones,especially at low confining pressure or unconfined condition.

Non-Linear Matrix Completion

Current methods for predicting missing values in datasets often rely on simplistic approaches such as taking median value of attributes, limiting their applicability. Real-world observations can be diverse, taking stock price as example, ranging from prices post-IPO to values before a company’s collapse, or instances where certain data points are missing due to stock suspension. In this paper, we propose a novel approach using Nonlinear Matrix Completion (NIMC) and Deep Matrix Completion (DIMC) to predict associations, and conduct experiment on financial data between dates and stocks. Our method leverages various types of stock observations to capture latent factors explaining the observed date-stock associations. Notably, our approach is nonlinear, making it suitable for datasets with nonlinear structures, such as the Russell 3000. Unlike traditional methods that may suffer from information loss, NIMC and DIMC maintain nearly complete information, especially in high-dimensional parameters. We compared our approach with state-of-the-art linear methods, including Inductive Matrix Completion, Nonlinear Inductive Matrix Completion, and Deep Inductive Matrix Completion. Our findings show that the nonlinear matrix completion method is particularly effective for handling nonlinear structured data, as exemplified by the Russell 3000. Additionally, we validate the information loss of the three methods across different dimensionalities.

Advanced cervix cancer patient with chemotherapy-induced grade IV myelosuppression achieved complete remission with cadonilimab:A case report

BACKGROUND The prognosis for patients with advanced metastatic cervix cancer(MCC)is poor,and this disease continues to pose a considerable therapeutic challenge.Despite the administration of first-line regimens consisting of cisplatin,paclitaxel,and bevacizumab,survival rates for patients with metastasis remain poor.The emergence of bispecific antibodies(BsAbs)offers a novel treatment option for patients diagnosed with MCC.CASE SUMMARY In this report,we present a patient with MCC who was treated with cadonilimab monotherapy at a dose of 6 mg/kg every two weeks after chemotherapy was proven to be intolerable.The patient exhibited a sustained complete response for a duration of 6 months,demonstrating an optimistic outlook.CONCLUSION This case illustrates the considerable efficacy of cadonilimab for treating advanced MCC.Therefore,BsAb therapy is a promising strategy for effectively treating patients with advanced MCC and should be considered as an option when patients are intolerant to standard chemotherapy.

Clinical Outcomes of Complete Mesocolic Excision for Right-Sided Colon Cancer Using 3D Laparoscopy versus 2D Laparoscopy

Objective:To study the clinical outcomes of complete mesocolic excision(CME)for right-sided colon cancer using 3D(three-dimensional)laparoscopy compared to 2D(two-dimensional)laparoscopy.Methods:From January 2022 to December 2023,58 patients with right-sided colon cancer treated at the Affiliated Hospital of Hebei Engineering University were randomly divided into a 3D laparoscopy group(observation group)and a 2D laparoscopy group(control group),with 29 patients in each group.Intraoperative blood loss,postoperative time to first flatulence,length of hospital stay,and incidence of complications in both groups were recorded.Results:There was a statistically significant difference in intraoperative blood loss between the two groups(P<0.05).There was no statistically significant difference in the time to first flatulence between the groups(P>0.05).However,there was a statistically significant difference in the length of hospital stay(P<0.05)and the incidence of complications(P<0.05)between the two groups.Conclusion:3D laparoscopy for CME can reduce intraoperative blood loss,shorten hospital stay,and decrease postoperative complications,showing significant clinical advantages over traditional 2D laparoscopy.

Existence of solutions and positive solutions to a fourth-order two-point BVP with second derivative

Several existence theorems were established for a nonlinear fourth-order two-point boundary value problem with second derivative by using Leray-Schauder fixed point theorem, equivalent norm and technique on system of integral equations. The main conditions of our results are local. In other words, the existence of the solution can be determined by considering the height of the nonlinear term on a bounded set. This class of problems usually describes the equilibrium state of an elastic beam which is simply supported at both ends.