Probabilistic Calculation Research Articles

Antigen-Independent, Autonomous B-Cell Receptor Signaling in Diffuse Large B-Cell Lymphoma

Gene expression profiling of diffuse large B-cell lymphoma (DLBCL) defines the Cell-of-origin (CoO) classification with two major subtypes, germinal center B-cell (GCB) and the more aggressive activated B-cell (ABC) type. Chronic activation of B-cell receptor (BCR) signaling with constitutive activation of the NF-κB pathway is an essential oncogenic mechanism in ABC DLBCL. BCR pathway activation with increased NF-κB activation can be caused by gain-of-function mutations of the BCR signaling cascade. We investigated whether antigen-independent, i.e. autonomous BCR signaling, akin to its essential pathogenetic role in chronic lymphocytic leukemia, acts as a functional driver mechanism in DLBCL without such gain-of-function mutations. DNA and RNA were extracted from ABC DLBCL cell lines TMD8 and OCI-Ly3 and from fresh-frozen biopsies of 18 histologically confirmed DLBCL cases. Functional BCR transcripts were identified by ARTISAN PCR and transduced into murine triple knock out (TKO) cells. TKO cells lack the recombination activation gene 2 (Rag2) and lambda 5 gene (λ5) and are therefore incapable of expressing an endogenous BCR. In addition, the BCR signal transduction molecule SLP65 is replaced with a tamoxifen-inducible estrogen receptor (ERT2) - SLP65 fusion gene. Upon transduction of both heavy and light BCR chains and staining with Indo-1, background calcium flux can be measured as Indo-1 signal intensity ratio (SIR) by flow cytometry. After restoring functionality of the BCR signaling cascade by tamoxifen, antigen-independent BCR signaling is measured as SIR, followed by maximum BCR stimulation with an isotype-specific crosslinking antibody. Autonomous BCR signaling strength (SSBCR) is quantified by an arithmetic product based on the relative Indo-1 SIR and the relative number of cells with SIR above background in the presence of tamoxifen and calibrated on crosslinking-induced maximum SIR. According to the primary hypothesis, the BCR of CARD11 wild-type, IgM-expressing TMD8 cells demonstrated strong autonomous BCR signaling (SSBCR=0.243), whereas the BCR of CARD11 mutated, IgG-expressing OCI-Ly3 cells completely lacked autonomous signaling (SSBCR=0.022). BCR from 13 primary DLBCL signaled autonomously (SSBCR=0.125-0.619), where 5 samples were negative (SSBCR=0.004-0.023) Autonomous BCR signaling was absolutely dependent on IgM isotype (Fisher's exact test: p=0.0016). CoO classification by digital gene expression (Nanostring) analyses or immunohistochemistry demonstrated autonomous BCR signaling in 8/9 ABC (non-GCB) DLBCL, 2/6 GCB DLBCL, and 2 unclassifiable DLBCL, and a transformed follicular lymphoma DLBCL. Independent of CoO, DLBCL can be assigned to 6-7 clusters based on their genetic aberrations (Chapuy 2018, Wright 2020). Fifteen DLBCL were suited for WES and targeted panel sequencing. Four cases were assigned by a probabilistic calculation to Chapuy cluster C5, 2 cases to C2, and one case to C1, while 8 cases remained unclassifiable. Clustering by the LymphGen tool assigned 3 cases to cluster ST2, one case each into MCD, EZB, and N1, 4 cases into various clusters, and 5 cases unclassified. DLBCL with autonomous BCR signaling fell into clusters C1/unclassified, C2/unclassified, C5/unclassified (n=3), unclassified/EZB, unclassified/ST2, unclassified/N1 and unclassified/unclassified (n=2). Cases lacking autonomous BCR signaling were assigned to unclassified/ST2 (n=2), C5/MCD, and unclassified/unclassified. Eleven of 13 cases with an autonomous signaling BCR lacked activating CARD11 mutations. In conclusion, autonomous BCR signaling is a potential immunological oncogenic driver in DLBCL that cannot be detected by sequencing studies, is independent of external antigen stimulation, and originates from a self-organizing conformation of the surface BCR (Minici 2017). Autonomous BCR signaling is present predominantly in ABC DLBCL and dependent on IgM isotype. Autonomous BCR signaling offers a convincing explanation for oncogenic NF-κB activation in DLBCL. Limited data suggest that the majority of DLBCL with autonomous BCR signaling fall into the ABC-dominated genetic clusters C1/C5, and MCD/N1, respectively. In summary, genetic aberrations, BCR function, and gene expression profile form 3 independent layers of DLBCL pathophysiology that need to be analyzed separately and offer independent targets for therapy.

A non-intrusive probabilistic multi-energy flow calculation method and its application in operation risk analysis of integrated energy systems

With the deep coupling of electricity, heat, and gas systems, the uncertainties in renewable energy sources and loads significantly impact the energy flow distribution of integrated energy systems. Probabilistic multi-energy flow calculations considering these uncertain factors have become essential for risk analysis, optimal management, and operational control. However, it is still difficult to efficiently and accurately deal with the diverse and large numbers of correlated random variables. This paper proposes a non-intrusive probabilistic multi-energy flow calculation method and explores its application in the operation risk analysis of integrated energy systems. The probabilistic multi-energy flow model is established considering the uncertainties and correlations of renewable energy sources and loads. The proposed model is solved within the sparse polynomial chaos expansion framework based on Bayesian compressive sensing. Thus, the probabilistic density functions of the risk indices of each subsystem can be obtained. On this basis, the conditional value-at-risk method is employed for the operation risk analysis. The feasibility and advantages of the proposed method are verified using a typical integrated energy system test case.

Studies on the local structure of the F ∕ OH site in topaz by magic angle spinning nuclear magnetic resonance and Raman spectroscopy

Abstract. The mutual influence of F and OH groups in neighboring sites in topaz (Al2SiO4(F,OH)2) was investigated using magic angle spinning nuclear magnetic resonance (MAS NMR) and Raman spectroscopy. The splitting of 19F and 1H NMR signals, as well as the OH Raman band, provides evidence for hydrogen bond formation within the crystal structure. Depending on whether a given OH group has another OH group or fluoride as its neighbor, two different hydrogen bond constellations may form: either OH⋯O⋯HO or F⋯H⋯O. The proton accepting oxygen was determined to be part of the SiO4 tetrahedron using 29Si MAS NMR. Comparison of the MAS NMR data between an OH-bearing and an OH-free topaz sample confirms that the 19F signal at −130 ppm stems from F− ions that take part in H⋯F bonds with a distance of ∼ 2.4 Å, whereas the main signal at −135 ppm belongs to fluoride ions with no immediate OH group neighbors. The Raman OH sub-band at 3644 cm−1 stems from OH groups neighboring other OH groups, whereas the sub-band at 3650 cm−1 stems from OH groups with fluoride neighbors, which are affected by H⋯F bridging. The integrated intensities of these two sub-bands do not conform to the expected ratios based on probabilistic calculations from the total OH concentration. This can be explained by (1) a difference in the polarizability of the OH bond between the different hydrogen bond constellations or (2) partial order or unmixing of F and OH, or a combination of both. This has implications for the quantitative interpretation of Raman data on OH bonds in general and their potential use as a probe for structural (dis-)order. No indication of tetrahedrally coordinated Al was found with 27Al MAS NMR, suggesting that the investigated samples likely have nearly ideal Al/Si ratios, making them potentially useful as high-density electron microprobe reference materials for Al and Si, as well as for F.

Stochastic Reliability-Based Design Optimization Framework for the Steel Plate Girder with Corrugated Web Subjected to Corrosion.

This paper proposes the framework for reliability-based design optimization (RBDO) of structural elements with an example based on the corrugated web I-girder. It tackles the problem of topological optimization of corroding structures with uncertainties. Engineering restrictions follow a concept of the limit states (LS) and extend it for stability and eigenfrequency assessment. The reliability constraints include all the LS; they are computed according to first- and second-order reliability methods. The RBDO example minimizes the bridge girder cross-section while satisfying the structural reliability level for the ultimate and the serviceability limit states, stability, and eigenfrequency. It takes into consideration two uncorrelated random effects, i.e., manufacturing imperfection and corrosion. They are both Gaussian; the first of them is applied at assembly time, while the second is applied according to the time series. The example confronts three independent FEM models with an increasing level of detailing, and compares RBDO results for three concurrent probabilistic methods, i.e., the iterative stochastic perturbation technique (ISPT), the semi-analytical method, and the Monte Carlo simulation. This study proves that the RBDO analysis is feasible even for computationally demanding structures, can support automation of structural design, and that the level of detailing in the FEM models influences its results. Finally, it exemplifies that reliability restrictions for LS are much more rigorous than for their deterministic counterparts, and that the fastest ISPT method is sufficiently accurate for probabilistic calculations in this RBDO.

A novel approach to touch voltage risk assessment for gas pipelines in shared transmission corridors

Touch voltages are more likely to appear on long-distance pipelines that lie in shared corridors with transmission lines. The touch voltage level varies with soil resistivity and can become hazardous while maintenance is being undertaken, necessitating risk assessment. Therefore, a novel approach is proposed that achieves better accuracy in the risk assessment of hazardous touch voltages appearing on pipelines than current approaches. The proposed approach incorporates soil resistivity measurements taken over a 1-year period, allowing for the derivation of soil models, touch voltage hazard profiles versus time and, thus, a probability reduction factor that can be integrated into a probabilistic risk calculation. Using a probability reduction factor is a key aspect to improving the accuracy of risk assessment, allowing pipeline asset operators to clearly identify whether or not, risk mitigation action is required. Further, the proposed approach allows appropriate risk mitigation actions to be identified. The efficacy and significance of the proposed approach are demonstrated through a case study on an area of land near a shared gas pipeline and transmission line corridor. The case study results show how appropriate safety levels can be achieved by adjusting the number of work day per year and temporary protection settings.

Risk assessment of photovoltaic distribution network based on adaptive kernel density estimation and cumulant method

In order to efficiently and accurately evaluate the out of limit risk of photovoltaic power distribution network, the adaptive kernel density estimation (AKDE) method is introduced to fit the actual light intensity sequence, and the probability distribution model of photovoltaic power station output characteristics is established. At the same time, the Cornish–Fisher series combined with the cumulant method (CM) is used to calculate the probabilistic power flow of photovoltaic distribution network, the accuracy of probabilistic power flow calculation (PPFC) is verified by Monte Carlo Method (MCM), the system level voltage out of limit risk index (VOLRI) and branch power flow out of limit risk index (BPFOLRI) are established. Finally, MATLAB is used to verify the accuracy and efficiency of the algorithm for photovoltaic distribution network risk assessment.

Practical concepts for the use of probabilistic methods in the structural analysis and reassessment of existing bridges - presentation of latest research and implementation

In structural engineering and bridge construction, probabilistic calculations are only performed in a few exceptional cases. The ability to directly use information from the existing structure is an important advantage of probabilistic methods. Geometric data or the position and quantity of the installed reinforcing steel and tendons can be measured. Results from monitoring of the traffic can be used to generate structure-specific load models. Many clients are still very sceptical about the results of probabilistic calculations, even though there are several examples of successful application. The use of probabilistic verification formats is explicitly permitted by the German guideline for the assessment of existing bridges (German: Nachrechnungsrichtlinie). Since a high degree of special knowledge is required for the application of probabilistic calculations, it is difficult to establish the potential of this verification method in practice. It is necessary to enable the practical engineer to utilize the advantages of probabilistic calculations and to include the actual structural conditions into the calculation model, but without the need for all the special knowledge. Structure-specific partial safety factors include measured data and can be used for the well-known and in the codes established semi-probabilistic design concept. The authors present examples for the successful application of probabilistic methods and of data measurement during the reassessment of two existing bridges in Germany. The capabilities of full-probabilistic calculations for the reassessment of existing structures are described and concepts for the calculation of structure-specific partial safety factors are shown.

Comparison of the collapse frequency and failure probability of buildings

In a previous study, the collapse frequencies and associated mortalities of buildings were compiled based on various publications. The investigation showed a considerable scattering of collapse frequencies depending on the countries. In this paper, the collapse frequencies determined for buildings are compared with the results of probabilistic calculations. Such comparisons have already been carried out for bridges, dams, tunnels and retaining walls including the consideration of central estimators and standard deviations. In order to limit the scatter, the probabilities of failure for buildings were subdivided into the different causes of failure, and collapse frequencies were subdivided into different countries and geographical regions. Overall, the comparison shows that the probabilities of failure are on overage larger than the observed collapse frequencies. Furthermore, the comparison shows are large span, which is unusual for other types of structures. Of concern are the high observed collapse frequencies in various developing countries. Human error, lack of training, etc. are often cited as the cause. Should this correspond to the facts, the basic safety concept of modern building standards, which generally excludes human error, would only be applicable in these regions to a limited extent. However, the investigation includes some limitations, such as different safety targets in different standards and different years of constructions, which are not considered. Further work is required.

Maximizing information obtained from standardized fire tests using a Bayesian framework

Current practice is mostly focused on prescriptive design approaches where the performance of the structure in case of fire is assessed based on its performance in standardized fire tests. Those tests indicate whether the structural member can withstand standardized ISO 834 fire exposure for a certain code specified time. This method however does not provide an explicit safety level. This issue is enlarged even more by the fact that the ISO 834 fire exposure does not represent a natural fire exposure, but a pseudo-worst-case exposure, making the correlation between the standardized fire test results and real-life behaviour of structural members exposed to fire questionable. However, there has been a century-old tradition of standardized fire tests with a lot of experience and infrastructure based on it. For that reason, here, a methodology is presented to obtain more information on the behaviour of structural members exposed to a natural fire from the standardized fire test results by using a Bayesian framework. As an example structure, a simply supported concrete slab is considered. Its failure during the standardized fire test is modelled and the parameters affecting the time when it fails (i.e., parameters affecting the nominal fire resistance time) are determined. The model is then used in a Markov chain Monte Carlo procedure to update parameter distributions based on the measured fire resistance time. Using these updated distributions, a full probabilistic calculation of the performance of the slab considering a natural fire exposure is then conducted to assess the failure probability.

Probabilistic Safety Factor Calculation of the Lateral Overturning Stability of a Single-Column Pier Curved Bridge under Asymmetric Eccentric Load

At present, the calculation methods for the lateral overturning stability safety factor of a single-column pier curved bridge under asymmetric eccentric load in the highway bridge code adopt deterministic calculation models. This paper presents a transverse overturning stability safety factor study of single-column pier curved bridges under asymmetric eccentric load based on inverse reliability theory. This method, which both considers the influence of uncertainty factors among the structural parameters and satisfies the prescribed reliability level, was used to obtain safety factors through a target reliability index. Transverse overturning stability factors of single-column pier curved bridges under asymmetric eccentric load were estimated using the proposed method. A new method was proposed to calculate the design parameter of the safety factor of single-pier instability, and then an application was carried out. The results show that parameter uncertainty has a major effect on transverse overturning stability safety factors of single-column pier curved bridges under asymmetric eccentric load. Ignoring parameter uncertainty will produce an overestimation of the transverse overturning stability safety factors of single-column pier bridges. The vehicle load must be strictly controlled to avoid transverse overturning due to overloading. Compared to the deterministic model, the proposed method has the advantages of calculating the safety factors considering the randomness of parameters and establishing the relationship of the safety factor with the target reliability index.

Probabilistic power flow calculation considering electro-thermo-mechanical dynamics of overhead conductor

Conductor temperature and tension are important physical states that determine the security of the overhead line. The states are sensitive to the line power flow and the meteorological conditions around the conductor that have strong uncertainty. In this paper, the electro-thermo-mechanical coupling dynamics of the power system are modeled. Then, focusing on the calculation of the distributions of the electro-thermo-mechanical dynamics (ETMDs) of critical spans under the uncertain operational environment of the power system, the implementation framework and the fast calculation methods for the probabilistic power flow considering electro-thermo-mechanical dynamics (PPF-ETMD) are proposed. The work presented in this paper provides an effective method for operators to capture distributions of the ETMDs of critical spans under the uncertain environment and detect the underlying system security risk based on the thermal and mechanical essence of the security of the overhead line. Numerical simulations based on a regional power system in China and the IEEE 300-node system are carried out to verify the effectiveness of the proposed method.

Peculiarities of Application of Mathematical Modeling Methods in Forensic Fire and Technical Expertise in the Study of the Dynamics of Fire Hazards

The paper deals with the issues of law enforcement of methods (techniques) of mathematical modeling within the framework of forensic fire technical examinations in the study of the dynamics of fire hazards. The normative documents in the field of technical regulation, containing calculation methods and techniques, and their application in modern conditions in the framework of the production of forensic fire technical examinations are analyzed. The issue of admissibility, degree of accuracy and the scope of techniques (methods), as well as the use of probabilistic calculation results in the production of forensic examinations is considered. To eliminate doubts and controversial issues regarding the use of typical initial data and the correct choice of mathematical models, it is proposed to conduct an extended comparative study on various fires, taking into account the analysis of reliable data obtained during the investigation of fire cases. The paper discusses the issues of validation of the methodology for determining the dangerous factors of a fire and calculating the probability of evacuation of people within the framework of a forensic fire-technical examination.

An Assessment Method for the Impact of Electric Vehicle Participation in V2G on the Voltage Quality of the Distribution Network

In order to further evaluate the impact of vehicle-to-grid (V2G) on the distribution network, this paper studies a method to assess the influence of electric vehicles participating in charge and discharge on the voltage quality of the distribution network. First, considering the state of charge of the EV, the participation of the owner and other factors, the charging and discharging model is built. Then, the probabilistic power flow calculation based on Latin hypercube sampling is used to obtain the probability distribution of the voltage amplitude of the charge and discharge load connected to the distribution network, and finally the evaluation index is established to quantify and calculate the voltage quality of the distribution network participating in the V2G process of electric vehicles. Simulation results show that the evaluation method has the advantage of fast calculation speed while ensuring known accuracy, introduces the probability distribution of expected value and variance quantification of voltage amplitude, more intuitively understands the degree of influence on voltage quality before and after V2G, and can effectively assess the impact of electric vehicles accessing the distribution network in V2G mode on the power quality of low-voltage residential areas and industrial and commercial areas, and this evaluation method can provide useful reference for the formulation of future V2G control strategies and the planning of future urban power grids.

Modeling the migration of chemicals from food contact materials to food: The MERLIN-expo/VERMEER toolbox

Evaluating the migration of chemicals from food contact materials (FCM) into food is a key step in the safety assessment of such materials. In this paper, a simple mechanistic model describing the migration of chemicals from FCM to food was combined with quantitative property-property relationships (QPPRs) for the prediction of diffusion coefficients and FCM-Food partition coefficients. The aim of the present study was to evaluate the performance of these operational models in the prediction of a chemical's concentration in food in contact with a plastic monolayer FCM. A comparison to experimental migration values reported in literature was conducted. Deterministic simulations showed a good match between predicted and experimental values. The tested models can be used to provide insights in the amount and the type of toxicological data that are needed for the safety evaluation of the FCM substance. Uncertainty in QPPRs used for describing the processes of both diffusion in FCM and partition at the FCM-Food interface was included in the analysis. Combining uncertainty in QPPR predictions, it was shown that the third quartile (75th percentile) derived from probabilistic calculations can be used as a conservative value in the prediction of chemical concentration in food, with reasonable safety factors.

A Probabilistic Block Economic Value Calculation Method for Use in Stope Designs under Uncertainty

Uncertainty is intrinsic to mine design and planning and introduces risk into the process. Nonetheless, most mine design and planning processes have historically been undertaken as deterministic processes, often resulting in unrealistic mine designs and plans which potentially lead to the destruction of shareholder value. This paper presents a probabilistic block economic value (BEV) calculation approach to minimise the shortcoming of using deterministic BEVs, and evaluates the impact of uncertainty on stope designs. The probabilistic BEV calculation approach was applied to a synthetic geological block model of a gold mineral deposit. The uncertainty associated with BEV input parameters was simulated using Monte Carlo simulation to create equally probable economic orebody models which were then used to create stope designs at different levels of risk. The probabilistic approach generated 20% to 53% higher net present values (NPVs) compared to the deterministic approach within 30% to 70% probability range. This indicates that, for the case study deposit, blocks with approximately 30% to 70% probability of having positive BEVs are the ones that should be used for mine design and planning. The results demonstrate that incorporating uncertainty early in underground mine design and planning potentially creates higher-value stopes.

Probabilistic Damage Stability for Passenger Ships—The p-Factor Illusion and Reality

The paper complements an earlier publication by the authors addressing the probability of survival in the IMO framework for damage stability assessment, the s-factor. The focus here is on the probability of occurrence of a certain damage scenario (breach), conditional on its dimensions and location (centre and port or starboard side), the p-factor. Pertinent assumptions and limitations are explained, following its evolution for specific application to passenger ships. Attempts to provide analytical descriptions of the damage breach distributions as tetrahedra shapes positioned along the ship length whilst accounting for changes in ship geometry, structural arrangements, and subdivision for consumption by the wider profession has led to misconceptions and misunderstandings of what exactly the p-factor is in the context of probabilistic damage stability calculations. This is evidenced by the fact that the same original damage breach distributions, derived in Project HARDER, based on largely cargo ships with the age spread over the last three decades of the previous century, are still being used today for all ship types, including modern passenger ships. Filling this gap, a new database for passenger ships developed in the EC-funded Project FLARE, is briefly presented, leading to new damage breach distributions specifically for passenger ships. It is believed that this paper will throw considerable light in enhancing understanding on the p-factor, which has been cluttered with unnecessary complexity from the outset.

Probabilistic Multi-Energy Flow Calculation of Electricity–Gas Integrated Energy Systems With Hydrogen Injection

Probabilistic multienergy flow (PMEF) analysis is the fundamental of planning and operation of integrated energy systems (IES) considering uncertainties. The injection of hydrogen will make the PMEF calculation more complex and can deeply affect the distribution of energy flows. This article studies an efficient PMEF calculation method which can obtain the probabilistic information of electricity–gas IES with hydrogen injection. First, the steady-state model of electricity–gas IES with hydrogen injection is established, in which the gas network with hydrogen injection is formulated in compact matrix form. Second, the Jacobian matrix for the steady-state model of electricity–gas IES with hydrogen injection is derived. Third, the cumulant method and Nataf transformation are applied to calculate the PMEF considering the correlations. Finally, case studies are carried out on a coupled IES, which consists of modified IEEE 33-bus electricity system and 11-node gas system. The results demonstrate that the proposed PMEF method can reduce computational time greatly while keeping high computational accuracy when compared with the Monte–Carlo simulation method.

Calculation of Probabilistic Energy Flow of Colding-heating-electricity Interconnection System Considering Wind Power

In order to effectively evaluate the impact of wind power connection on the operation of the colding-heating-electricity interconnection system, a probabilistic energy flow calculation method based on the semi-invariant method and improved K-means is proposed. First, a colding-heating-electricity joint system model was established. Secondly, based on the semi-invariant method, an improved K-means clustering technique was proposed to solve the problems caused by different input random sample types. Finally, the efficiency of the proposed method is verified by simulation.

Effect of vertical-to-horizontal acceleration ratio of earthquake components on the utilization of buckling-restrained braces in steel frames

This paper presents an approach to design the buckling-restrained braces (BRB) system based on the resisting work of the steel braced structures to mitigate the structural seismic collapse. This approach covers the influence of different structural brace variables, the vertical-to-horizontal acceleration ratio (V/H ratio), and the percentage of brace utilization on structural resistance to seismic collapse considering column loss. The determination of this column loss relies on the probabilistic calculation of the critical demand-capacity ratio of the column element that poses the highest threat to fail under large lateral displacements. The investigation uses thirty-six archetypes of steel braced structures with regard to the V/H ratios and various structural parameters related to the bracing systems. The results of the proposed BRB design expand the role of the bracing systems from the protection of the structure against the lateral loading to the prevention of the vertical structural collapse.

Statistical machine learning model for capacitor planning considering uncertainties in photovoltaic power

New energy integration and flexible demand response make smart grid operation scenarios complex and changeable, which bring challenges to network planning. If every possible scenario is considered, the solution to the planning can become extremely time-consuming and difficult. This paper introduces statistical machine learning (SML) techniques to carry out multi-scenario based probabilistic power flow calculations and describes their application to the stochastic planning of distribution networks. The proposed SML includes linear regression, probability distribution, Markov chain, isoprobabilistic transformation, maximum likelihood estimator, stochastic response surface and center point method. Based on the above SML model, capricious weather, photovoltaic power generation, thermal load, power flow and uncertainty programming are simulated. Taking a 33-bus distribution system as an example, this paper compares the stochastic planning model based on SML with the traditional models published in the literature. The results verify that the proposed model greatly improves planning performance while meeting accuracy requirements. The case study also considers a realistic power distribution system operating under stressed conditions.