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.

Effects of pooling,specialization,and discretionary task completion on queueing performance

Pooling,unpooling/specialization,and discretionary task completion are typical operational strategies in queueing systems that arise in healthcare,call centers,and online sales.These strategies may have advantages and disadvantages in different operational environments.This paper uses the M/M/1 and M/M/2 queues to study the impact of pooling,specialization,and discretionary task completion on the average queue length.Closed-form solutions for the average M/M/2 queue length are derived.Computational examples illustrate how the average queue length changes with the strength of pooling,specialization,and discretionary task completion.Finally,several conjectures are made in the paper.

Integrated design and control technology of liner completion and drilling for horizontal wells

Aiming at the problems of large load of rotation drive system,low efficiency of torque transmission and high cost for operation and maintenance of liner steering drilling system for the horizontal well,a new method of liner differential rotary drilling with double tubular strings in the horizontal well is proposed.The technical principle of this method is revealed,supporting tools such as the differential rotation transducer,composite rotary steering system and the hanger are designed,and technological process is optimized.A tool face control technique of steering drilling assembly is proposed and the calculation model of extension limit of liner differential rotary drilling with double tubular strings in horizontal well is established.These results show that the liner differential rotary drilling with double tubular strings is equipped with measurement while drilling(MWD)and positive displacement motor(PDM),and directional drilling of horizontal well is realized by adjusting rotary speed of drill pipe to control the tool face of PDM.Based on the engineering case of deep coalbed methane horizontal well in the eastern margin of Ordos Basin,the extension limit of horizontal drilling with double tubular strings is calculated.Compared with the conventional liner drilling method,the liner differential rotary drilling with double tubular strings increases the extension limit value of horizontal well significantly.The research findings provide useful reference for the integrated design and control of liner completion and drilling of horizontal wells.

Hyperbolic hierarchical graph attention network for knowledge graph completion

Utilizing graph neural networks for knowledge embedding to accomplish the task of knowledge graph completion(KGC)has become an important research area in knowledge graph completion.However,the number of nodes in the knowledge graph increases exponentially with the depth of the tree,whereas the distances of nodes in Euclidean space are second-order polynomial distances,whereby knowledge embedding using graph neural networks in Euclidean space will not represent the distances between nodes well.This paper introduces a novel approach called hyperbolic hierarchical graph attention network(H2GAT)to rectify this limitation.Firstly,the paper conducts knowledge representation in the hyperbolic space,effectively mitigating the issue of exponential growth of nodes with tree depth and consequent information loss.Secondly,it introduces a hierarchical graph atten-tion mechanism specifically designed for the hyperbolic space,allowing for enhanced capture of the network structure inherent in the knowledge graph.Finally,the efficacy of the proposed H2GAT model is evaluated on benchmark datasets,namely WN18RR and FB15K-237,thereby validating its effectiveness.The H2GAT model achieved 0.445,0.515,and 0.586 in the Hits@1,Hits@3 and Hits@10 metrics respectively on the WN18RR dataset and 0.243,0.367 and 0.518 on the FB15K-237 dataset.By incorporating hyperbolic space embedding and hierarchical graph attention,the H2GAT model successfully addresses the limitations of existing hyperbolic knowledge embedding models,exhibiting its competence in knowledge graph completion tasks.

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.

5G Ultra-Dense Network Fingerprint Positioning Method Based on Matrix Completion

The problem of high-precision indoor positioning in the 5G era has attracted more and more attention.A fingerprint location method based on matrix completion(MC-FPL)is proposed for 5G ultradense networks to overcome the high costs of traditional fingerprint database construction and matching algorithms.First,a partial fingerprint database constructed and the accelerated proximal gradient algorithm is used to fill the partial fingerprint database to construct a full fingerprint database.Second,a fingerprint database division method based on the strongest received signal strength indicator is proposed,which divides the original fingerprint database into several sub-fingerprint databases.Finally,a classification weighted K-nearest neighbor fingerprint matching algorithm is proposed.The estimated coordinates of the point to be located can be obtained by fingerprint matching in a sub-fingerprint database.The simulation results show that the MC-FPL algorithm can reduce the complexity of database construction and fingerprint matching and has higher positioning accuracy compared with the traditional fingerprint algorithm.

Next Words Prediction and Sentence Completion in Bangla Language Using GRU-Based RNN on N-Gram Language Model

We use a lot of devices in our daily life to communicate with others. In this modern world, people use email, Facebook, Twitter, and many other social network sites for exchanging information. People lose their valuable time misspelling and retyping, and some people are not happy to type large sentences because they face unnecessary words or grammatical issues. So, for this reason, word predictive systems help to exchange textual information more quickly, easier, and comfortably for all people. These systems predict the next most probable words and give users to choose of the needed word from these suggested words. Word prediction can help the writer by predicting the next word and helping complete the sentence correctly. This research aims to forecast the most suitable next word to complete a sentence for any given context. In this research, we have worked on the Bangla language. We have presented a process that can expect the next maximum probable and proper words and suggest a complete sentence using predicted words. In this research, GRU-based RNN has been used on the N-gram dataset to develop the proposed model. We collected a large dataset using multiple sources in the Bangla language and also compared it to the other approaches that have been used such as LSTM, and Naive Bayes. But this suggested approach provides excellent exactness than others. Here, the Unigram model provides 88.22%, Bi-gram model is 99.24%, Tri-gram model is 97.69%, and 4-gram and 5-gram models provide 99.43% and 99.78% on average accurateness. We think that our proposed method profound impression on Bangla search engines.

Completion of 6-mo isoniazid preventive treatment among eligible under six children:A cross-sectional study,Lagos,Nigeria

BACKGROUND Nigeria is one of the thirty high burden countries with significant contribution to the global childhood tuberculosis epidemic.Tuberculosis annual risk for children could be as high as 4%particularly in high tuberculosis(TB)prevalent communities.Isoniazid(INH)Preventive Therapy has been shown to prevent TB incidence but data on its implementation among children are scarce.AIM To determine the completion of INH among under six children that were exposed to adults with smear positive pulmonary TB in Lagos,Nigeria.METHODS This was a hospital-based retrospective cross-sectional review of 265 medical records of eligible children<6 years old enrolled for INH across 32 private hospitals in Lagos,Nigeria.The study took place between July and September 2020.Data was collected on independent variables(age,gender,type of facility,TB screening,dose and weight)and outcome variables(INH outcome and proportion lost to follow up across months 1-6 of INH treatment).RESULTS About 53.8%of the participants were female,95.4%were screened for TB and none was diagnosed of having TB.The participants’age ranged from 1 to 72 mo with a mean of 36.01±19.67 mo,and 40.2%were between the ages of 1-24 mo.Only 155(59.2%)of the 262 participants initiated on INH completed the six-month treatment.Cumulatively,107(41.0%)children were lost to follow-up at the end of the sixth month.Of the cumulative 107 loss to follow-up while on INH,largest drop-offs were reported at the end of month 2,52(49%)followed by 20(19%),17(16%),11(10.2%)and 7(6.5%)at months 3,4,5 and 6 respectively.The analysis showed that there was no significant association between age,gender,type of facility and completion of INH treatment(P>0.005).CONCLUSION This study demonstrated suboptimal INH completion rate among children with only 6 out of 10 children initiated on INH who completed a 6-mo treatment in Lagos,Nigeria.The huge drop-offs in the first 2 mo of INH calls for innovative strategies such as the use of 60-d INH calendar that would facilitate reminder and early engagement of children on INH and their caregivers in care and across the entire period of treatment.

High-temperature corrosion of phosphate completion fluid and corrosion inhibition method by membrane transformation

By analyzing the corrosion of phosphate completion fluid on the P110 steel at 170 °C, the high-temperature corrosion mechanism of phosphate completion fluid was revealed, and a corrosion inhibition method by membrane transformation was proposed and an efficient membrane-forming agent was selected. Scanning electron microscope (SEM) images, X-ray energy spectrum and X-ray diffraction results were used to characterize the microscopic morphology, elemental composition and phase composition of the precipitation membrane on the surface of the test piece. The effect and mechanism of corrosion inhibition by membrane transformation were clarified. The phosphate completion fluid eroded the test piece by high-temperature water vapor and its hydrolyzed products to form a membrane of iron phosphate corrosion product. By changing the corrosion reaction path, the Zn2+ membrane-forming agent could generate KZnPO4 precipitation membrane with high temperature resistance, uniform thickness and tight crystal packing on the surface of the test piece, which could inhibit the corrosion of the test piece, with efficiency up to 69.63%. The Cu2+ membrane-forming agent electrochemically reacted with Fe to precipitate trace elemental Cu on the surface of the test piece, thus forming a protective membrane, which could inhibit metal corrosion, with efficiency up to 96.64%, but the wear resistance was poor. After combining 0.05% Cu2+ and 0.25% Zn2+, a composite protective membrane of KZnPO4 crystal and elemental Cu was formed on the surface of the test piece. The corrosion inhibition efficiency reached 93.03%, which ensured the high corrosion inhibition efficiency and generated a precipitation membrane resistant to temperature and wear.

Aquatic Medicine Knowledge Graph Completion Based on Hybrid Convolution

Aquatic medicine knowledge graph is an effective means to realize intelligent aquaculture.Graph completion technology is key to improving the quality of knowledge graph construction.However,the difficulty of semantic discrimination among similar entities and inconspicuous semantic features result in low accuracy when completing aquatic medicine knowledge graph with complex relationships.In this study,an aquatic medicine knowledge graph completion method(TransH+HConvAM)is proposed.Firstly,TransH is applied to split the vector plane between entities and relations,ameliorating the poor completion effect caused by low semantic resolution of entities.Then,hybrid convolution is introduced to obtain the global interaction of triples based on the complete interaction between head/tail entities and relations,which improves the semantic features of triples and enhances the completion effect of complex relationships in the graph.Experiments are conducted to verify the performance of the proposed method.The MR,MRR and Hit@10 of the TransH+HConvAM are found to be 674,0.339,and 0.361,respectively.This study shows that the model effectively overcomes the poor completion effect of complex relationships and improves the construction quality of the aquatic medicine knowledge graph,providing technical support for intelligent aquaculture.

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.

Design and feasibility analysis of a new completion monitoring technical scheme for natural gas hydrate production tests

As a prerequisite and a guarantee for safe and efficient natural gas hydrates(NGHs)exploitation,it is imperative to effectively determine the mechanical properties of NGHs reservoirs and clarify the law of the change in the mechanical properties with the dissociation of NGHs during NGHs production tests by depressurization.Based on the development of Japan’s two offshore NGHs production tests in vertical wells,this study innovatively proposed a new subsea communication technology-accurate directional connection using a wet-mate connector.This helps to overcome the technical barrier to the communication between the upper and lower completion of offshore wells.Using this new communication technology,this study explored and designed a mechanical monitoring scheme for lower completion(sand screens).This scheme can be used to monitor the tensile stress and radial compressive stress of sand screens caused by NGHs reservoirs in real time,thus promoting the technical development for the rapid assessment and real-time feedback of the in-situ mechanical response of NGHs reservoirs during offshore NGHs production tests by depressurization.

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.

Complete Convergenceand Complete Moment Convergence for Weighted Sums of ANA Random Variables

In this paper,we investigate the complete convergence and complete moment conver-gence for weighted sums of arrays of rowwise asymptotically negatively associated(ANA)random variables,without assuming identical distribution.The obtained results not only extend those of An and Yuan[1]and Shen et al.[2]to the case of ANA random variables,but also partially improve them.

Passability test and simulation of sand control string with natural gas hydrates completion in large curvature hole

To meet the requirements of marine natural gas hydrate exploitation,it is necessary to improve the penetration of completion sand control string in the large curvature borehole.In this study,large curvature test wells were selected to carry out the running test of sand control string with pre-packed screen.Meanwhile,the running simulation was performed by using the Landmark software.The results show that the sand control packer and screen can be run smoothly in the wellbore with a dogleg angle of more than 20°/30 m and keep the structure stable.Additionally,the comprehensive friction coefficient is 0.4,under which and the simulation shows that the sand control string for hydrate exploitation can be run smoothly.These findings have important guiding significance for running the completion sand control string in natural gas hydrate exploitation.

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.

Correlation and predictive value of pathological complete response and ultrasound characteristic parameters in neoadjuvant chemotherapy for breast

BACKGROUND Breast cancer ranks as one of the most prevalent malignant tumors among women,significantly endangering their health and lives.While radical surgery has been a pivotal method for halting disease progression,it alone is insufficient for enhancing the quality of life for patients.AIM To investigate the correlation between ultrasound characteristic parameters of breast cancer lesions and clinical efficacy in patients undergoing neoadjuvant chemotherapy(NAC).METHODS Employing a case-control study design,this research involved 178 breast cancer patients treated with NAC at our hospital from July 2019 to June 2022.According to the Miller-Payne grading system,the pathological response,i.e.efficacy,of the NAC in the initial breast lesion after NAC was evaluated.Of these,59 patients achieved a pathological complete response(PCR),while 119 did not(non-PCR group).Ultrasound characteristics prior to NAC were compared between these groups,and the association of various factors with NAC efficacy was analyzed using univariate and multivariate approaches.RESULTS In the PCR group,the incidence of posterior echo attenuation,lesion diameter≥2.0 cm,and Alder blood flow grade≥II were significantly lower compared to the non-PCR group(P<0.05).The area under the curve values for predicting NAC efficacy using posterior echo attenuation,lesion diameter,and Alder grade were 0.604,0.603,and 0.583,respectively.Also,rates of pathological stage II,lymph node metastasis,vascular invasion,and positive Ki-67 expression were significantly lower in the PCR group(P<0.05).Logistic regression analysis identified posterior echo attenuation,lesion diameter≥2.0 cm,Alder blood flow grade≥II,pathological stage III,vascular invasion,and positive Ki-67 expression as independent predictors of poor response to NAC in breast cancer patients(P<0.05).CONCLUSION While ultrasound characteristics such as posterior echo attenuation,lesion diameter≥2.0 cm,and Alder blood flow grade≥II exhibit limited predictive value for NAC efficacy,they are significantly associated with poor response to NAC in breast cancer patients.

Robotic complete mesocolic excision for right colon cancer:Learning curve,training,techniques,approach,platforms,and future perspectives

Colon cancer has the fifth highest incidence worldwide and has the sixth highest mortality.Compared with rectal cancer,colon cancer currently has the worst 5-year overall survival for patients with stage Ⅱ and Ⅲ disease.Complete mesocolic excision has been developed as a standardized and optimized surgical technique for the excision of colon cancers.This technique has traditionally been performed through an open approach since laparoscopy is generally considered technically challenging.The robotic approach has been slowly implemented for colon cancer,but the newest robotic platforms allow for a safer and optimized approach for right colon cancer.Several robotic approaches have been developed and explored.The expansion of the current robotic platform ecosystem is gradually providing new outputs in the application of the robotic approach to complete mesocolic excision.This review gains an oversight of existing literature on robotic complete mesocolic excision for right colon cancer(learning curve,training,techniques,approach,platforms,and future perspectives).