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The Northern Sea Route (NSR) makes travel between Europe and Asia shorter and quicker than a southern transit via the Strait of Malacca and Suez Canal. It provides greater access to Arctic resources such as oil and gas. As global warming accelerates, melting Arctic ice caps are likely to increase traffic in the NSR and enhance its commercial viability. Due to the harsh Arctic environment imposing threats to the safety of ship navigation, it is necessary to assess Arctic navigation risk to maintain shipping safety. Currently, most studies are focused on the conventional assessment of the risk, which lacks the validation based on actual data. In this study, actual data about Arctic navigation environment and related expert judgments were used to generate a structured data set. Based on the structured data set, extreme gradient boosting (XGBoost) and alternative methods were used to establish models for the assessment of Arctic navigation risk, which were validated using cross-validation. The results show that compared with alternative models, XGBoost models have the best performance in terms of mean absolute errors and root mean squared errors. The XGBoost models can learn and reproduce expert judgments and knowledge for the assessment of Arctic navigation risk. Feature importance (FI) and shapley additive explanations (SHAP) are used to further interpret the relationship between input data and predictions. The application of XGBoost, FI, and SHAP is aimed to improve the safety of Arctic shipping using advanced artificial intelligence techniques. The validated assessment enhances the quality and robustness of assessment.
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OBJECTIVE@#To explore 3.0T MRI accurate measurement of knee cartilage thickness in healthy youth provides reliable anatomical parameters for quantitative diagnosis of osteoarthritis and accurate osteotomy of joint replacement.@*METHODS@#From January 2013 to December 2013, 30 healthy young volunteers including 14 males and 16 females with an average age of (25.8±2.4) years old ranging from 22 to 33 years were recruited in Changchun, Jilin Province, and a 3.0T MRI scan was performed on the bilateral knee joints of each volunteer. The cartilage thickness was measured on the lateral femoral condyle (LFC), medial femoral condyle (MFC), lateral tibial plateau (LTP) and medial tibial plateau (MTP).@*RESULTS@#In four regions of the knee joint:LFC, MFC, LTP and MTP, whether young men or women, there was no significant difference in cartilage thickness between the left and right knee joints (P>0.05). There were significant differences in knee cartilage thickness between healthy young men and women (P<0.05). In the same sex group, LFC cartilage thickness was thinner in the middle, thicker in front and rear;MFC cartilage thickness was the thinnest in front and gradually thickening from the front to the rear; LTP cartilage thickness was thickest in the middle, second in the rear and thinnest in the front;MTP cartilage thickness was the thinnest in the front, was relatively uniform in the middle and rear and thicker than that in the front.@*CONCLUSION@#In Northeast China, among healthy adults aged 22 to 33, gender difference may be an important factor in the difference of cartilage thickness in various regions of the knee joint. Regardless of whether male or female healthy young people, the cartilage thickness of the entire knee joint is unevenly distributed, but there is no significant difference in cartilage thickness in the same area between the left and right knee joints.
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Adulto , Adolescente , Humanos , Masculino , Femenino , Adulto Joven , Cartílago Articular/diagnóstico por imagen , Articulación de la Rodilla/cirugía , Osteoartritis , Imagen por Resonancia Magnética , FémurRESUMEN
This paper aims to examine the short-term impact of government interventions on 11 industrial sectors in the Indonesian Stock Exchange (IDX) during the COVID-19 pandemic. Whereas earlier studies have widely investigated the impact of government interventions on the financial markets during the pandemic, there is lack of research on analysing the financial impacts of various interventions in different industrial sectors, particularly in Indonesia. In this research, five key types of government interventions are selected amid the pandemic from March 2020 to July 2021, including economic stimulus packages, jobs creation law, Jakarta lockdowns, Ramadan travel restrictions, and free vaccination campaign. Based on an event study methodology, the research reveals that the first economic stimulus package was critical in reviving most sectors following the announcement of the first COVID-19 case in Indonesia. Jakarta lockdowns impacted stock returns negatively in most sectors, but the impacts were relatively insignificant in comparison to other countries in the region. The recurrence of lockdowns in Jakarta had a minor detrimental impact, showing that the market had acclimated to the new normal caused by the COVID-19 pandemic. Additionally, Ramadan travel restrictions caused minor negative impacts on the stock market. Furthermore, the second Ramadan travel restrictions generated a significant reaction from the technology sector. Finally, while free vaccination campaign and job creation law did not significantly boost the stock market, both are believed to result in a positive long-term effect on the country's economy if appropriately executed. The findings are critical for investors, private companies, and governments to build on recovery action plans for major industrial sectors, allowing the stock market to bounce back quickly and efficiently. As this study limits its analysis to the short-term impact of individual interventions, future studies can examine long-term and combined effects of interventions which could also help policy makers to form effective portfolios of interventions in the event of a pandemic. Supplementary Information: The online version contains supplementary material available at 10.1007/s43546-022-00312-4.
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A transparent digital twin (DT) is designed for output control using the belief rule base (BRB), namely, DT-BRB. The goal of the transparent DT-BRB is not only to model the complex relationships between the system inputs and output but also to conduct output control by identifying and optimizing the key parameters in the model inputs. The proposed DT-BRB approach is composed of three major steps. First, BRB is adopted to model the relationships between the inputs and output of the physical system. Second, an analytical procedure is proposed to identify only the key parameters in the system inputs with the highest contribution to the output. Being consistent with the inferencing, integration, and unification procedures of BRB, there are also three parts in the contribution calculation in this step. Finally, the data-driven optimization is performed to control the system output. A practical case study on the Wuhan Metro System is conducted for reducing the building tilt rate (BTR) in tunnel construction. By comparing the results following different standards, the 80% contribution standard is proved to have the highest marginal contribution that identifies only 43.5% parameters as the key parameters but can reduce the BTR by 73.73%. Moreover, it is also observed that the proposed DT-BRB approach is so effective that iterative optimizations are not necessarily needed.
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The high mortality of tumor is one of the most urgent problems to be solved. However, the current clinical trials provide limited quantitative descriptions on dynamic changes of drug efficacy, which restrict the selection of dosing regimens. Quantitative systems pharmacology (QSP) is a new approach for precise treatment of tumors. It quantifies the network relationship between drug action and diseases by integrating the tumor growth and molecules, cells in vivo, thereby predicting the efficacy, toxicity, and mechanism of antitumor drugs as well as identifying predictive biomarkers. In this review, we provide an overview of definition of QSP, current approaches and typical applications in research of antitumor drugs to enhance our understanding of QSP.
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With a deepening understanding of cancer treatment, immune checkpoint inhibitors are recognized widely as a novel fundamental remedy for various malignancies with effectiveness and safety. With the development of pharmacometrics, model-informed drug development (MIDD) has emerged to accelerate the process of clinical research for new drugs and improve the accuracy of decision-making in new drug research, especially for immune checkpoint inhibitors. As a typical illustration, the research development of pembrolizumab is presented in this review to highlight the application of MIDD, which may provide a reference for the development of other new antitumor drugs.
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Chest wall reconstruction is a key approach to restoring the structure and function of the defective chest wall after tumor excision. While autologous flaps have been ideal materials for soft tissue reconstruction,the optimal skeletal reconstructive material still remains controversial. Currently,besides autologous bones,non-biodegradable materials have been used widely,which offer sufficient strength and stability but with some inevitable complications. Many studies have explored the clinical applications of biodegradable materials and the improvements in their characteristics,and some of these materials may be clinically feasible. This article reviews the recent advances in the applications of reconstructive materials.
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BACKGROUND:Stem cells combined with a three-dimensional scaffold have great potential for the treatment of osteoporotic bone defects. OBJECTIVE:To introduce the application of stem cells combined with the three-dimensional scaffold in repairing osteoporotic bone defects. METHODS:A computer-based search of PubMed, Web of Science, Springerlink, Medline, WanFang and CNKI databases was performed for relevant articles published from 2007 to 2017 with "stem cells, scaffold, osteoporosis, bone defects" as key words in English and Chinese, repsectively. Initially, 142 articles were retrieved, and finally 45 articles were included in result analysis. RESULTS AND CONCLUSION:Due to the potential of self-renewal and multilineage differentiation, stem cells can be used to repair or regenerate damaged tissues, which are considered as an ideal cell source for the treatment of diseases in orthopedics. The suitable scaffold can provide a favorable microenvironment for repairing the attachment and growth of the cells related to the bone defect, which can promote the healing without additional side effects. Furthermore, stem cells combined with three-dimensional scaffolds provide a promising clinical application for the treatment of osteoporotic bone defects by regulation of bone metabolism. In addition, gene-modified stem cells with three-dimensional scaffolds bring a huge potential in the treatment of osteoporotic bone defects. In conclusion, the combination of stem cells and three-dimensional scaffolds provides a new approach for the treatment of osteoporotic bone defects, which may be one of the future therapeutic strategies.
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BACKGROUND: With the development of chemical synthesis technology, the application of anti-osteoporosis drugs incorporated into scaffolds to promote bone regeneration in osteoporotic bone defects has become a hot issue nowadays. OBJECTIVE: To introduce bone tissue engineering scaffolds, and to discuss and summarize the application of the scaffolds carrying anti-osteoporosis drugs for osteogenesis in osteoporotic bone defects. METHODS: PubMed, Web of Science, Springerlink, Medline, WanFang and CNKI databases were retrieved with "osteoporosis, bone defect, scaffold" as key words for relevant articles published from 2005 to 2017. Initially, 201 articles were retrieved, and finally 64 articles were selected for further analysis. RESULTS AND CONCLUSION: With the development of biochemical synthesis technology, various types of tissue-engineered bone scaffolds have been used for the treatment of osteoporotic bone defects. For example, the modified calcium phosphate cement, β-tricalcium phosphate, and hydroxyapatite all can promote bone regeneration. However, the ability of conventional scaffolds to promote bone regeneration is severely damaged under the state of osteoporosis. In this case, an anti-osteoporosis therapy becomes necessary. Considering severe adverse effects of systemic anti-osteoporosis drugs and limited local bone regeneration, the combination of scaffold implantation and local drug delivery can promote osteoporotic bone defect healing. Importantly, to incorporate bone regeneration inducers into scaffolds and steadily release with their biological activity is the key to success. Bisphosphonate, strontium, bone morphogenetic protein 2 and parathyroid hormone, traditional Chinese medicine and mesenchymal stem cells are the drugs commonly combined with tissue-engineered bone scaffolds. With the development of biotechnology, genetically modified stem cell-scaffold composites have gradually appealed to researchers.
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Understanding individuals' voluntary vaccinating behaviors plays essential roles in making vaccination policies for many vaccinepreventable diseases. Usually, individuals decide whether to vaccinate through evaluating the relative cost of vaccination and infection according to their own interests. Mounting evidence shows that the best vaccine coverage level for the population as a whole can hardly be achieved due to the effects of herd immunity. In this paper, taking into consideration the herd immunity threshold, we present an evolutionary N-person threshold game, where individuals can dynamically adjust their vaccinating strategies and their payoffs depend nonlinearly on whether or not the herd immunity threshold is reached. First, in well-mixed populations, we analyze the relationships at equilibrium among the fraction of vaccinated individuals, the population size, the basic reproduction number and the relative cost of vaccination and infection. Then, we carry out simulations on four types of complex networks to explore the evolutionary dynamics of the N-person threshold game in structured populations. Specifically, we investigate the effects of disease severity and population structure on the vaccine coverage for different relative costs of vaccination and infection. The results and findings can offer new insight into designing incentive-based vaccination policies for disease intervention and control.
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Conducta de Elección , Juegos Experimentales , Inmunidad Colectiva , Modelos Teóricos , Vacunación , Algoritmos , Simulación por Computador , Humanos , Densidad de Población , Vigilancia de la Población , Cobertura de VacunaciónRESUMEN
BACKGROUND: In China, a nationwide emergency system takes charge of pre-hospital emergency services, and it adopts a proximity principle to send trauma patients to the nearest hospitals. However, many severely injured patients have been sent to low level hospitals with no capability to treat severe trauma. Thus those patients with high probability of in-hospital death or intensive care unit (ICU) admission need to be identified in the emergency department (ED) for optimal utilisation of hospital resources and better patient outcomes. The purpose of the study was to develop a computerised tool to aid ED physicians' prediction of in-hospital death and ICU admission for trauma patients after arrival to hospital. METHODS: We reviewed a sample of 1,299 trauma patients who had been directly sent to the ED at Kailuan Hospital, North China. After excluding those cases with incomplete data entry, information of 1,195 patients was employed for analysis. The primary outcome was severe trauma that either resulted in death in hospital or in ICU admission. We proposed to use a complementary approach to combine the Pre-Hospital Index (PHI), the Trauma Index (TI), and the Glasgow Coma Score (GCS) in a decision support system (DSS) to assess trauma and predict in-hospital death and ICU admission. The sensitivity, specificity, over-triage rate, and under-triage rate were used as measurements to compare system performances of the DSS with the three scoring tools. RESULTS: Among the 1,195 patients, 30 (2.5%) had severe trauma. The proposed DSS showed the best sensitivity (66.7%; 95% CI: 49.8-83.6%) among all the four studied tools. The TI (sensitivity 50.0%, 95% CI: 32.2-67.8%) performed slightly better than the GCS (sensitivity 46.7%, 95% CI: 28.9-64.5%), while both the TI and GCS performed better than the PHI (sensitivity 30.0%, 95% CI: 13.5-46.5%). The performance differences between the DSS and the three extant scoring tools were statistically significant. CONCLUSIONS: The proposed DSS outperformed the extant trauma scoring systems. It has a strong potential to help ED physicians identify severe trauma, optimally utilise hospital resources, and recommend appropriate triage and treatment strategies for trauma patients that have strong possibilities for in-hospital death and ICU admission.
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Servicios Médicos de Urgencia/normas , Servicio de Urgencia en Hospital/estadística & datos numéricos , Unidades de Cuidados Intensivos/estadística & datos numéricos , Admisión del Paciente/estadística & datos numéricos , Centros Traumatológicos/organización & administración , Heridas y Lesiones/mortalidad , Adulto , China/epidemiología , Servicios Médicos de Urgencia/organización & administración , Servicio de Urgencia en Hospital/organización & administración , Escala de Coma de Glasgow , Mortalidad Hospitalaria , Humanos , Puntaje de Gravedad del Traumatismo , Unidades de Cuidados Intensivos/organización & administración , Evaluación de Resultado en la Atención de Salud , Pronóstico , Medición de Riesgo , Triaje , Heridas y Lesiones/terapiaRESUMEN
It is important to predict both observable and hidden behaviors in complex engineering systems. However, compared with observable behavior, it is often difficult to establish a forecasting model for hidden behavior. The existing methods for predicting the hidden behavior cannot effectively and simultaneously use the hybrid information with uncertainties that include qualitative knowledge and quantitative data. Although belief rule base (BRB) has been employed to predict the observable behavior using the hybrid information with uncertainties, it is still not applicable to predict the hidden behavior directly. As such, in this paper, a new BRB-based model is proposed to predict the hidden behavior. In the proposed BRB-based model, the initial values of parameters are usually given by experts, thus some of them may not be accurate, which can lead to inaccurate prediction results. In order to solve the problem, a parameter estimation algorithm for training the parameters of the forecasting model is further proposed on the basis of maximum likelihood algorithm. Using the hybrid information with uncertainties, the proposed model can combine together with the parameter estimation algorithm and improve the forecasting precision in an integrated and effective manner. A case study is conducted to demonstrate the capability and potential applications of the proposed forecasting model with the parameter estimation algorithm.
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<p><b>OBJECTIVE</b>To evaluate the feasibility and efficacy of laparoscopy-assisted D2 radical gastrectomy for elderly patients with gastric cancer.</p><p><b>METHODS</b>From October 2007 to October 2012, 233 gastric cancer patients over 65 years underwent D2 lymph node dissection. Among them, 109 patients underwent laparoscopy-assisted radical gastrectomy(LAG group), while 124 patients underwent conventional open gastrectomy(OG group).</p><p><b>RESULTS</b>Compared to the OG group, LAG group was associated with less bleeding [(102.5±34.3) ml vs. (181.7±73.8) ml, P<0.05], quicker postoperative recovery of bowel function[(2.8±0.6) d vs. (4.0±1.2) d, P<0.05], shorter postoperative length of hospital stay[(10.7±7.5) d vs.(14.2±6.5) d, P<0.05], longer operative time [(231.2±51.4) min vs. (208.5±53.6) min, P<0.05]. The postoperative complication rate of LAG group and OG group was 10.1%(11/109) and 21.0%(26/124) respectively(P<0.05). Short-term quality of life of LAG group was better than that of OG group(P<0.05). The 5-year survival rates were 54.5% and 59.2% in LAG and OG groups respectively, and there was no significant difference(P>0.05).</p><p><b>CONCLUSIONS</b>Efficacy of laparoscopy-assisted D2 radical gastrectomy is similar to open gastrectomy in elderly gastric cancer patients with less invasiveness.</p>