Probability Index Research Articles

Devising of a risk map on the management of high risk alert medication in a high level university hospital

ObjectiveTo classify hospital units into three risk levels in order to define and prioritise improvement and training measures in each of them. MethodThe risk map was developed in two phases: First phase involved the setting up of a multidisciplinary team, a bibliographic search, the identification of medications and of the criteria to design the map: (1) Location: number of high-alert medications; (2) Staff turnover: the units were classified in low turnover units = 1, medium turnover units = 2 and high turnover units = 3 according to data provided by the human resource department; (3) Frequency: quotient between the number of high alert medicactions in each unit and the total of medications used, and (4) Severity: voluntary survey of professionals. An accumulated risk of severity of each unit was calculated: Σ (severity of the drug x number of its units). The Neperian logarithm was applied to this value to reduce the variability of the values. Thus a risk probability index was established = staff turnover x frecuency x Neperian logarithm of severity. In a Los artículos publicados en esta revista se distribuyen con la licencie Articles published in this journal are licensed with a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. http://creativecommons.Org/licenses/by-nc-sa/4.0/ La revista Farmacia no cobra tasas por el envío de trabajos, ni tampoco por la publicación de sus artículos. second phase, the units were classified into three groups and the risk map of high-alert medication was elaborated in the hospital. In it, the units that had a risk probability index higher than 2.9 were classified as high risk units, those that had between 1–2.9 as intermediate risk units and those that had less than 1 as low risk units. According to the risk probability index, improvement measures were defined and priorities were set for each of them. ResultsA total 447 high-risk medications corresponding to 227 active ingredients were identified during the study period. The units showing a higher risk were: Intensive Care Medicine (10.51), Reanimation (4.01), and Palliative Care (3.90). Improvement actions (informative poster, visual identification, alerts, training and double checks) were defined and prioritised in accordance with the risk probability index. ConclusionsKnowing the degree of risk of hospitalization units in the management of high-alert medications allows for the implementation of improvement plans in relation to the degree of vulnerability detected.

Using decoys and camera traps to estimate depredation rates and neonate survival.

Ungulate neonates-individuals less than four weeks old-typically experience the greatest predation rates, and variation in their survival can influence ungulate population dynamics. Typical methods to measure neonate survival involve capture and radio-tracking of adults and neonates to discover mortality events. This type of fieldwork is invasive and expensive, can bias results if it leads to neonate abandonment, and may still have high uncertainty about the predator species involved. Here we explore the potential for a non-invasive approach to estimate an index for neonate survival using camera traps paired with decoys that mimic white-tailed deer (Odocoileus virginianus) neonates in the first month of life. We monitored sites with camera traps for two weeks before and after the placement of the neonate decoy and urine scent lure. Predator response to the decoy was classified into three categories: did not approach, approached within 2.5 m but did not touch the decoy, or physically touched the decoy; when conducting survival analyses, we considered these second two categories as dead neonates. The majority (76.3%) of the predators approached the decoy, with 51.1% initiating physical contact. Decoy probability of survival was 0.31 (95% CI = 0.22, 0.35) for a 30-day period. Decoys within the geographic range of American black bear (Ursus americanus) were primarily (75%) attacked by bears. Overall, neonate survival probability decreased as predator abundance increased. The camera-decoy protocol required about ½ the effort and 1/3 the budget of traditional capture-track approaches. We conclude that the camera-decoy approach is a cost-effective method to estimate a neonate survival probability index based on depredation probability and identify which predators are most important.

Reliability Analysis of Biomass Power Plant Using Loss of Load Probability Index at PT. Tanjung Buyu Perkasa Plantation

The main function of a power generation system is to provide reliable electrical energy. This study aims to determine the reliability of Biomass Power Plants at PT. Tanjung Bayu Perkasa Plantation (PT. TBPP) in the years 2020, 2021, and 2022 using the Loss of Load Probability (LOLP) index calculation method. LOLP is a reliability index that indicates the possibility that the power plant cannot meet the demand. The LOLP of biomass power plants at PT. TBPP in 2020 amounted to 1.2769 days per year. However, the LOLP in 2020 does not comply with the standards set by the Republic of Indonesia Minister of Energy and Mineral Resources Decree in 2018. In contrast, in 2021, it was 0.53403 days per year, and in 2022, it was 0.41748 days per year, both of which meet the standards of the Republic of Indonesia Minister of Energy and Mineral Resources Decree in 2018. The LOLP is affected by the Forced Outage Rate (FOR) and demands exceeding the capacity. Based on the LOLP of biomass power plants at PT. TBPP in 2020, 2021, and 2022, it can be concluded that the reliability of biomass power plants at PT. TBPP is at a higher level of reliability compared to the micro-hydro power plant in Pantai Baru Pandasimo with a LOLP of 51.3627 days per year and the steam power plant at Pertamina EP Asset IV Field Sukowati with LOLP of 4.259535 days per year. The recommendation for future research is to explore ways better to optimize boiler operations in steam power plants at PT. TBPP.

Diagnostic Utility of Parent Ratings on the Behavior Assessment System for Children-Third Edition in Children who are Deaf and Hard of Hearing and Diagnosed with Autism Spectrum Disorder.

Between 1 to 2 of every 1,000 children are born deaf or hard of hearing (DHH) and, of those, 30-50% have additional disabilities, including Autism Spectrum Disorder (ASD). Most measures assessing ASD characteristics rely on some degree of behavioral response to sound (e.g., responding to name, listening response), and may not be appropriate for use with children who are DHH. Further, ASD specific measures do not provide information on a child's functional abilities across developmental domains. We conducted a cross-sectional analysis comparing mean T-scores on a standardized multidimensional measure, the Behavior Assessment System for Children, Third Edition, Parent Rating Scale (BASC-3 PRS), across three groups matched for age and sex: children who are DHH and diagnosed with ASD (DHH + ASD; n = 16); children who are DHH without ASD (DHH-ASD; n = 16); and children who are typically hearing with ASD (H + ASD; n = 16). Analyses revealed statistically significant differences across scales of Attention Problems, Atypicality, Withdrawal, Behavioral Symptoms Index, Social Skills, Leadership, Functional Communication, Activities of Daily Living, Adaptive Skills, Autism Probability Indices, and Developmental Social Disorders. Pairwise comparisons showed DHH + ASD and H + ASD mean T-scores were statistically similar and distinct from DHH-ASD mean T-scores on all these scales except for Withdrawal, Leadership, Functional Communication, and Activities of Daily Living, where pairwise comparisons varied. The findings add to the literature on ASD and DHH childrenand call for further exploration of the BASC-3 as a tool for both evaluation of ASD and the development of individualized treatment plans in this unique population.

Effect of scour erosion and riprap protection on horizontal bearing capacity and reliability of monopiles using FEM-BPNN-RSM coupled method

Scour erosion around monopiles of offshore wind turbines (OWTs) can significantly reduce their horizontal bearing capacity and reliability. To combat scouring, riprap protection has been identified as a simple and effective method. This study aims to analyze the impact of different scour depths and riprap protection on the horizontal bearing capacity and reliability of monopile-supported OWTs, considering the interaction between the structure and the soil. In this research, we establish three-dimensional finite element models and propose a novel coupled analysis method, integrating the finite element method (FEM), back-propagation neural network (BPNN), and response surface method (RSM), to assess the bearing capacity reliability under various scour and protection conditions. This analysis incorporates extreme value data from 30 years of marine environmental conditions and employes an 8MW wind turbine as a case study. By utilizing the established response surface, we determine the failure probability and reliability index. The results demonstrate that the rotational center of the monopile shifts either downward or upward with increased scour depth or implementation of riprap protection. Furthermore, the findings reveal that riprap protection not only effectively mitigates the negative impact of scour on the bearing capacity of monopiles but also enhances their bearing capacity and reliability directly.

Reliability-based design optimization of post-tensioned self-centering rocking steel frame structures

This paper reports the Reliability-Based Design Optimization (RBDO) of post-tensioned self-centering rocking steel frame structures with buckling-restrained bracing systems. The objective was to investigate the reliability index, optimization of self-centering structures to reach minimum weight using metaheuristic algorithms, and their application in linear and nonlinear reliability problems. For this purpose, three steel structures (10-, 15-, and 20-storey structures) were each evaluated with three steel framing systems (buckling-restrained bracing, post-tensioned self-centering multiple rocking steel frame with buckling-restrained bracing, and post-tensioned self-centering single rocking steel frame with buckling-restrained bracing), making a total of nine models. Subsequently, specific 2D frames of the structural models were numerically simulated using nonlinear dynamic analysis (NDA) in OpenSees software. Optimization was carried out in two stages: with and without considering the uncertainties. Finally, for calculating the failure probability and structural reliability index, Monte-Carlo Simulation (MCS) was employed. Results indicate that, although considering the reliability index leads to heavier structures, structural safety was increased and failure probability was reduced to even lower specified levels. Furthermore, among the incorporated algorithms, the Colliding Bodies Optimization (CBO) and Charged System Search (CSS) algorithms proved to have superior performances in terms of accuracy and converging time. On average, using these two algorithms for cases without uncertainty resulted in maximum weight reductions of 36%, 30%, and 32% for 10-, 15-, and 20-storey structures. In addition, for cases with uncertainty, these two algorithms with reliability index (β) of 2 respectively reduced the weight of 10-, 15-, and 20-storey structures by 21%. Also, it was shown that not considering the uncertainties can increase the failure probability by up to 23%.

Systemic Lupus Erythematosus Risk Probability Index: ready for routine use? Results from a Chinese cohort

ObjectivesTo evaluate the performance of Systemic Lupus Erythematosus Risk Probability Index (SLERPI) in patients with SLE using a Chinese cohort.MethodsThe Chinese cohort included 352 patients with and 385 without SLE...

Study of the Multilevel Fuzzy Comprehensive Evaluation of Rock Burst Risk

Rock burst is a multifaceted phenomenon that involves various intricate factors. A precise evaluation of its risk encounters numerous challenges. To address this issue, the present paper proposed a multilevel fuzzy comprehensive evaluation model based on the Analytic Hierarchy Process–Fuzzy Comprehensive Evaluation (AHP-FCE) method. Three primary influencing factors and twelve secondary influencing factors that impact the rock burst risk were identified. The mechanisms by which each influencing factor affects the rock burst were analyzed and the membership degree for each factor was calculated accordingly. The weight of each influencing factor was determined through the AHP. To obtain a quantitative evaluation result, the evaluation model was calculated using the second-order fuzzy mathematics calculation method. The application of the model was demonstrated on the 310 working face of the Tingnan Coal Mine, and the evaluation results were consistent with those achieved through the use of the comprehensive index method and the probability index method. All of the results exhibited consistent alignment with the actual circumstances. The verification process confirmed the scientific, effective, and practical nature of the model.

Smoothed empirical likelihood for optimal cut point analysis

In diagnostic studies, a continuous biomarker is often dichotomized for the diagnosis of binary disease status. Various criteria have been studied for the cut point selection of the continuous biomarker in receiver operating characteristic (ROC) analysis, in particular, the Youden index, the closest-to-(0,1) index, and the concordance probability index. Recently, Wang, Tian, and Zhao (2017) established a Wilks theorem for a smoothed empirical likelihood ratio statistic of Youden index. However, it is not directly useful for statistical inference compared to the cut point. In addition, the optimal cut point may vary with different criteria. In this article, we study smoothed empirical likelihood for optimal cut point selection with Youden index, closest-to-(0,1) criterion, and concordance probability. We develop confidence estimation for the optimal cut points based on the smoothed empirical likelihood ratio statistics. We examine the empirical performance by extensive simulation studies. We also illustrate the method with a real dataset.

Corporate Fraud, Earnings Management and Firm Value: Empirical Application of M-Scores

Background: Corporate fraud and earnings management have been controversial and discussed extensively in the literature, as companies consider the practices strategic and creative to keep their companies afloat and sustain a desired firm value. While this unethical practice has remained illegal, unethical and a global concern, the trajectory to higher incentives by executives to insider dealings to keep the stock price attractive by managers is unacceptable, this study provides new insight and implications of corporate fraud and earnings management on firm value. Objective: This paper investigates the effect of corporate fraud and earnings management on firm value from the perspective of the application of Beneish M-Score manipulation and probability index as indicators to detect corporate fraud and earnings management on Tobin’s Q as a surrogate of firm value The main aim is to establish the consequence of corporate fraud and earnings management on firm value and highlights the forms of corporate fraud and earnings management, stakeholders concerns and unattractiveness of fraud corporate in whatever capacity. Method: Using descriptive statistics and inferential analysis, the study provides evidence that leverage index, sales growth and sales and administrative expense exerted positive effects and channels for corporate fraud and earning management of the selected Nigerian-listed consumer goods manufacturing companies. We found that while each of the day’s sales trade receivables index, assets quality index, leverage index and sales growth quality index exerted positive effects, the gross margin index, depreciation index and total accruals to total index exhibited negative insignificant effects. However, the joint attributes of corporate fraud and earnings management had a positive significant effect on Tobin’s Q as a firm value surrogate Our Conclusion: The study contributing to knowledge, provides new empirical evidence of the application of the Beneish M-Score model as a novelty to the probability incentive for corporate fraud and earnings management in the companies examined.

Analisis Keandalan Pembangkit Listrik Tenaga Mini Hidro Orya-Genyem Berdasarkan Load of Loss Probability

Electricity is crucial for supporting development, the economy, and human well-being, thus leading to an increasing demand for electrical energy. Therefore, power plants are planned and constructed to be as economically viable as possible. In line with the principles of affordability, security of supply, and acceptability, to ensure long-term capacity demand and reliability. The reliability of the power plant is measured using the Load of Loss Probability (LOLP) index, which assesses the probability of components functioning satisfactorily to meet demand. The objective of this research is to analyze the reliability of PLTM Orya-Genyem based on the Load of Loss Probability (LOLP) index. The research methodology is qualitative, commencing with the collection of secondary data, followed by LOLP calculations to obtain reliability information. LOLP index for PLTM Orya-GGenyem is 0,4204%, equivalent to 1,5346 days per year, exceeding the PLN standard of 1 day per year. This indicates a lack of reliability in the power plant. Research findings reveal that daily power demand increases by 0,054 MW for every 1% increase in time. Assessment indicates that peak load surge factor is not the cause of the high LOLP value in PLTM Orya-Genyem. Instead, outages are the cause. The assessment shows that there were 72 disturbances of maintenance outages for PLOG-TA-01 and 145 disturbances of system adjustment outages for PLOG-TA-02. Other outages that happen include low water elevation, water storage duration, floods (accumulated debris), transmission work, blackouts, network disturbances, forced outages, planned outages, sedimentation dredging, water drainage, water filling, performance testing, and maintenance during plant operation.

Maximum Surgical Blood Ordering Schedule in Orthopedic Department at UNAIR Hospital January-June 2021

Excessive ordering of blood components causes problems such as a lack of proper distribution of blood products between centers, increased costs, and workload of blood banks. Effective use of MSBOS will reduce the cross-match of patient blood samples and reduce unnecessary testing. This is also expected as a way to improve the quality of health services at UNAIR Hospital and reduce patient treatment costs. This study aimed to find out the MSBOS profile for orthopedic surgery at UNAIR Hospital in the period January-June 2021. This study is a cross-sectional study with a sample of orthopedic patients at UNAIR Hospital. The period was 6 months (January-June 2021). Cross-match to Transfusion Ratio (CTR), transfusion probability, and transfusion index calculations were carried out so that MSBOS could be formulated. A total of 33 units of blood were cross-matched from 21 patients in this study, whereas only 5 units of blood were transfused to 4 patients. It was found that 7 out of 8 types of surgeries had a CTR value of more than 2, a total of 6 types of surgeries had a low transfusion probability (below 30), and 6 types of surgeries had a TI below 0.5. In Total Hip Replacement (THR) and ORIF plating symphysis surgery, it is recommended that 2 units of blood be MSBOS, while for others, Group, Screen, Hold (GSH) is recommended. Further research with larger samples is needed to obtain more accurate results.

Developing process-based geomorphic indicators for understanding river dynamics of a highly braided system: Implications for designing resilience based management strategies

The present paper utilizes the Google Earth Engine (GEE) cloud computing platform and hydro-morphological dataset to understand the complex process-form relationships of the highly braided Brahmaputra River, India. To identify dynamic gradients between low and high risk of geomorphic adjustment/change, an analytical approach is developed to track and quantify the spatial patterns of geomorphic adjustment. In order to address the dominant geomorphological adjustments, two processed-based novel indicators are developed- the Normalised Threshold Exceedance (NTE) considering the excess energy theory, and the Normalised Process Gradient (NPG) utilizing the gradient between hierarchical thresholds. The results show that in a highly braided river system, the sand bar adjustments prevail over other forms of morphological changes and is closely dependent on the process gradient between the hierarchical thresholds. Further, the scale of planform evolution is computed from the Location Probability Index (LPI), and the geomorphic stationarity concept is introduced for a large braided river. Finally, a multi-faceted resilience-based freedom space management approach is designed based on system state trajectory, LPI variability, proximity to thresholds, and in-channel landform configuration.

Offshore COVID-19 risk assessment based on a fishing vessel

Offshore crews often work near each other due to limited space, signifying a complex environment for the airborne transmission of the coronavirus (COVID-19). During offshore operations, a fishing vessel can be subjected to miscellaneous airflow conditions and will respond dynamically to ocean waves. To understand the risk of COVID-19 contagion, this research establishes a new computational model to analyse the airborne transmission of COVID-19 and develops effective mitigation strategies where possible. The concentration and coverage of coronavirus are scrutinised, considering typical airflows and wave-induced vessel motions. Furthermore, the COVID-19 infection risk is quantified using a probability index. The results show that the overall infection risk of a ship in tailwind is lower than in head or beam wind. Structural motions are for the first time coupled with the virus transmission, and it was found that the vessel's oscillating movement in waves can reinforce the virus concentration in close proximity to the infected person and may help diffuse the virus outside the proximal region. The presented findings can inform the airborne contagion risks and corresponding hygienic measures for maritime and offshore operations, facilitating long-term human health in seas.i

Assessment of infection probability indices for airborne diseases in confined spaces: combination of CFD and analytical modelling

The paper presents a framework for probabilistic assessment of likelihood of infection from airborne diseases in confined spaces which are continuously occupied for relatively long periods (e.g., school classrooms). The proposed approach is based on a combination of computational fluid dynamics (CFD) pre-calculations and analytical post-processing, to define relevant indices of infection probability. The practical applicability of the method is demonstrated through a case study, where different ventilation scenarios are considered for a school classroom. Corresponding infection probability indices are determined globally for the group of occupants. Furthermore, since the method does not rely on the well-mixing assumption, local probability indices are determined for each occupied location. The obtained results confirm the intuition that an increase of ventilation and/or air filtration reduces the overall likelihood of infection, though the observed positive effect is not uniform within the space. The presented methodology can also be considered as complementary to simpler approaches.

Flexibility resource planning of a power system considering a flexible supply–demand ratio

Aiming at the problems of insufficient power system regulation capacity and lack of flexible resources caused by source-load uncertainty, the flexible resource planning of power systems is studied with the goal of improving flexibility. Uncertainty and flexibility are combined in this article, and a probability index of an insufficiently flexible supply-demand ratio is proposed based on the probability characteristics of flexibility. A bi-level programming model of power system flexibility resources considering the probability of an insufficiently flexible supply demand ratio is constructed. Optimal economics is used as the objective function of the planning layer, and the proposed minimum probability index of the flexible supply-demand ratio is used as the objective function of the operations layer. Economics and flexibility are studied, taking the power system in a certain area in Northeast China as the research object. A flexible resource planning scheme that meets different flexibility expectations is obtained, and the scheme is discussed in detail from the aspects of system flexibility, economic cost, and new energy consumption capacity. The effectiveness of quantitative indicators and planning methods are verified.

Prospects for more morality-oriented normative reformed international, inter-civilisational development system

Both Adam Smith and Mencius could be arguably considered as two of the most thought-provoking philosophical intellectual thinkers within the domains of Anglo-Saxon economic and political civilisation over the course of Industrial Revolution and of classical Chinese economic and political civilisation amid the neolithic Warring-State period. In particular, the former one conceptualised moral sentiments and the potential economic secrets to wealth accumulation in a system of division of labour; the latter one critically and constructivistically inherited ideational legacies from the Confucius Doctrine, historically proposing the ideational disposition of humane government, moral priority, civil superiority over the rulers and state and the benign characteristics of an individual at birth. At first glance, both these two economic and political philosophers from two separate civilisational entities have few conceptual, intellectual, political and economic interrelations or overlapped commonality from their heterogeneous geographical characteristics and variables, grand historical circumstances of far distinctive, heterogeneous means of productions: the emergence of technological revolution from manufacturing to machinery in the embryonic stage in the Smith Era and metallurgical and agricultural advancements, metamorphism and transformation in the Mencius Era, and contrastive social structures and architectures between the Smith-inhabiting British society and Mencius-inhabiting Warring-State society in antique Chinese period. Nevertheless, the chief objective of this research analytical manuscript seeks to, with the frameworks of certain international relations theories and comparative philosophy, conduct profound, comprehensive, dialectical contrastive investigations into their implicit reciprocity and trans-sectional, trans-spatial homogeneity and interplay, especially a series of organic associations of their analytical propositions on the nature, implications and implementations of morality of different forms and fashions with the necessity for recalibrating, reconstructing and even re-modeling a more morality-oriented normative international, inter-civilisational development architecture in the contemporary volatile, unpredictable, competitive and ambiguous world between disorder and integration, between amalgamation and fragmentation, between win-win cooperation and zero-sum confrontation upon a firm theoretical roots of Thucydides Traps. Methodologically, this analytical manuscript has sought to take advantage of constructivistic representative sampling of Chinese pandemic-controlling measures, and China’s uniquely active, autonomous participation into the global economic development paradigm and trajectory, in contradiction with the unanticipated demise of Silicon Valley Bank, which may be comparable to Bears Stearns Moment chiefly owning to the withdrawal of governmental regulations, the dismal fiasco of financial and banking regulations and excessive non-performing loans, and unethical misbehaviours by the financial oligarchs within. Moreover, Russia-Ukraine geopolitical dilemma drains the global economic sluggish movement. As a result of must fairly exhaustive, quantitative and qualitative investigation into representative sampling of failed amoral, non-normative institutions and differently up-coming normative initiatives, it could be initially observed that whilst the conditions and contexts for successfully constructing a morality-oriented normative international, inter-civilisational development system and mechanism are divergent because of diverse political, economic, social, cultural and environmental circumstances, the probability index and necessity for doing so can be circumstantial and verifiable and such kinds of international normative institutions and mechanisms should be enforceable in a more civilisational, international society as it should be. Furthermore, Mencius Doctrine and Smithian Doctrine can uphold a supplementary role to play in achieving that kind of prospect of unconventional collective morality and collective norm, which is not unique to Western context alone, that certain mainstream Western-initiating international relations theoretical findings may have fallen short of quantitatively and qualitatively reconstructing, recalibrating and re-evaluating. China’s examples could be the quintessential example worthy of re-learning and abstract inheritance for others who choose to take lessons at an inter-philosophical, cross-sectional level.

T1 relaxation time analysis in predicting hepatic dysfunction and prognosis in patients with HCC undergoing transarterial chemoembolization

ObjectiveTo evaluate the value of T1 mapping in predicting hepatic dysfunction and prognosis in patients with hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE). Material and Methods100 consecutive patients with treatment-naive HCC treated with TACE were prospectively analyzed. Clinical, laboratory, and MRI parameters (liver and tumor T1 relaxation times (T1L, T1T)) before and/or following TACE were measured and calculated. Clinical parameters included the Child-Turcotte-Pugh (CTP) classification, Barcelona Clinic Liver Cancer Classification (BCLC) criteria, and albumin-bilirubin (ALBI) score. Laboratory parameters were the gold standard for hepatic dysfunction. T1L and T1T were combined by stepwise multivariate logistic regression to yield a T1-related probability index (T1com) for further analysis. Study endpoints included hepatic dysfunction and progression-free survival (PFS) rate. Results38 patients (38%) were diagnosed with hepatic dysfunction following TACE. There was no significant difference in clinical parameters between the groups with and without hepatic dysfunction. Logistic regression analysis showed that T1L and T1T were independent risk factors for assessing hepatic dysfunction. T1com showed a better AUC than T1L and T1T (0.81 vs. 0.76 and 0.69, P = 0.007 and 0.006). Patients with low T1com (≤0.42) showed a better median PFS than patients with high T1com (>0.42) (167.0 vs. 215.9 days, P = 0.010). In comparison, CTP, BCLC, and ALBI scores were not statistically significant in predicting PFS in HCC patients treated with TACE (P > 0.05). ConclusionCompared with widely used clinical parameters, T1 was more capable of predicting hepatic dysfunction after TACE. Stratification of patients with HCC undergoing TACE according to T1 may help clinicians to develop treatment strategies in preventing the occurrence of hepatic dysfunction and improving individual prognoses.

An artificial intelligence-based assessment of soil erosion probability indices and contributing factors in the Abha-Khamis watershed, Saudi Arabia

Soil erosion is a major problem in arid regions, including the Abha-Khamis watershed in Saudi Arabia. This research aimed to identify the soil erosional probability using various soil erodibility indices, including clay ratio (CR), modified clay ratio (MCR), Critical Level of Soil Organic Matter (CLOM), and principle component analysis based soil erodibility index (SEI). To achieve these objectives, the study used t-tests and an artificial neural network (ANN) model to identify the best SEI model for soil erosion management. The performance of the models were then evaluated using R2, Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and Mean Absolute Error (MAE), with CLOM identified as the best model for predicting soil erodibility. Additionally, the study used Shapley additive explanations (SHAP) values to identify influential parameters for soil erosion, including sand, clay, silt, soil organic carbon (SOC), moisture, and void ratio. This information can help to develop management strategies oriented to these parameters, which will help prevent soil erosion. The research showed notable distinctions between CR and CLOM, where the 25–27% contribution explained over 89% of the overall diversity. The MCR indicated that 70% of the study area had low erodibility, while 20% had moderate and 10% had high erodibility. CLOM showed a range from low to high erodibility, with 40% of soil showing low CLOM, 40% moderate, and 20% high. Based on the T-test results, CR is significantly different from CLOM, MCR, and principal component analysis (PCA), while CLOM is significantly different from MCR and PCA, and MCR is significantly different from PCA. The ANN implementation demonstrated that the CLOM model had the highest accuracy (R2 of 0.95 for training and 0.92 for testing) for predicting soil erodibility, with SOC, sand, moisture, and void ratio being the most important variables. The SHAP analysis confirmed the importance of these variables for each of the four ANN models. This research provides valuable information for soil erosion management in arid regions. The identification of soil erosional probability and influential parameters will help to develop effective management strategies to prevent soil erosion and promote agricultural production. This research can be used by policymakers and stakeholders to make informed decisions to manage and prevent soil erosion.

Structural damage identification of subseabed shield tunnels based on distributed fiber optic sensors and information fusion

Subseabed shield tunnels are constantly subjected to erosion induced by seepage and corrosive ions and electrochemical effects of diffuse currents from subway traction locomotives during service, resulting in damage to the outer wall of the segment. However, the outer wall cannot be directly observed, making damage identification a challenge. In this research, an approach based on distributed fiber optic sensors (DFOSs) and information fusion is proposed to solve this issue. To monitor strain, DFOSs were installed along the circumference of the segment inner wall. The strain curvature was adopted to solve the adverse influence of the spatial resolution (SR) averaging effect in DFOSs. Using the strain and strain curvature as information sources, the strain damage probability index (SDPI) and strain curvature damage probability index (SCDPI) were developed. Based on Dempster-Shafer (D-S) evidence theory, the SDPI and SCDPI were further utilized to build basic probability assignment (BPA) functions and perform information fusion for damage identification. To validate the feasibility of this approach, model experiments were conducted. The analysis of the test data indicated that information fusion can suppress the independent features of the two information sources while emphasizing their common features. The SR averaging effect, which can cause data distortion and diminish or even mask the damage anomaly feature in strain, and multiple extrema in the strain curvature that can interfere with damage localization are simultaneously eliminated. The damage identification accuracy is improved, and the damage localization error for the segment outer wall can reach 0.79 cm.