Quantitative Reliability Research Articles

Probabilistic approach of state transition elements of truss structures at corrosion

The purpose of the presented study is to determine and mathematically model the reliability of a steel truss with different variants of local failures of rod elements due to corrosion processes. In order to achieve a quantitative reliability assessment, the truss structure is considered as a combination of subsystems containing relatively small groups of rod components. Numerical calculations of truss structures taking into account the influence of corrosion have been carried out. It is shown that the components of the truss system can change their state by different schemes. The transition from one state to another depends on the level of stress state, which is caused by corrosion effects. It is easier to visualize this in a binary system. The probability of failure-free performance of rod components over the operating time can be written in vector form. By the matrix analysis method, failure states and functional states can be determined. As an example, a 5-bar structural system of a metal staircase type truss is considered.

Prediction and reliability analysis of reservoir lithology spatial distribution

Reliable lithology spatial distribution directly reflects the geological situation of the reservoir, which is the basis of stratigraphic correlation, sedimentary modeling, and other geological research. Under the condition of limited reservoir data, it is a challenging task to accurately depict the lithology spatial distribution and provide a quantitative reliability analysis of the results. In this study, we propose a flexible spatial distribution prediction and model reliability analysis method. Firstly, the method develops a spatially dependent deep Kriging technology to fit the heterogeneous characteristics of the reservoir lithology, and adopts the extracted spatial key information and related reservoir attributes to invert lithology spatial distribution intelligently. Then, it focuses on the real-time assimilation of non-Gaussian data in the reliability modeling and quantitatively analyzes the reliability of the prediction system under the non-Gaussian hypothesis. Finally, the method is applied to the actual heterogeneous reservoir, good results are achieved in the prediction accuracy, model fitting degree, model reliability, and time performance compared with other methods. The method is conducive to finding future mineral deposits locations and reducing exploration costs.

THE PROBLEM OF RELIABILITY OF GEODESIC NETWORKS

Nowadays, the theory of reliability is widely used in the construction industry, and it is also used in the field of geodesy. By abstracting its position, it can be successfully transferred to systems that, it would seem, are not in a dynamic state. Let's take, for example, the points of the polygonal (leveling) network in the city. It would seem that such a network is in a static state, but over time it undergoes changes, that is, it is in imperceptible dynamics and its reliability gradually decreases.
 Reliability in the broadest sense of the word means the ability of a technical device (system, network) to operate without interruption (failure) for a given period of time under certain conditions. Such a period of time is usually determined by the time of execution of some task, which is carried out by the device or system and is part of the general operational task.
 Currently, the problem of reliability is becoming one of the central problems of engineering and management organization. Ensuring the reliable operation of all system elements is of primary importance.
 The modern interpretation of the term "reliability" in geodesy is associated with Baard's reliability theory, according to which reliability is defined as "the ability of the network to self-monitor against gross errors [1]. One of the indicators of reliability is the minimum amount of gross error that can be detected after statistical analysis of the corrections obtained after equalization. On this path, many difficulties arise, most of which remain unsolved, namely the impossibility of localizing a gross error, quantitative assessment of reliability, methods of designing reliable geodetic networks. The unsatisfactory state of reliability theory limits its practical application, but at the same time, the problem of product reliability is the main one in modern production and its importance is growing all the time. In this regard, there is an acute problem in highlighting new views on solutions to this problem in the field of designing and creating geodetic networks.
 A new scheme for constructing the theory of reliability of geodetic measurements is proposed. Its basis is a probabilistic determination of reliability, a system of tolerances, and methods of localizing gross errors. Reliability is defined as a probabilistic measure of the homogeneity of measurements that have passed control. Quantitative reliability is estimated by three indicators: differential, integral and the minimum gross error. The Neumann-Pearson criterion is recommended for establishing tolerance. This theory makes it possible to design geodetic networks with a given reliability.

An Exploratory Factor Analysis for Developing and Validating a Scale of Long-Term Care Competencies among Care Managers in Long-Term Care System

Background: Care managers (CMs) play a crucial role in delivering long-term care (LTC) services for dependent older adults in the district health system (DHS). However, there are limitations of the instrument for assessing LTC competency of CMs in the DHS. Objective: To develop and validate an LTC competency instrument for CMs in the DHS in Thailand. Materials and Methods: An exploratory mixed methods study was conducted. In the qualitative phase, eight participants took part in in-depth interviews and 26 participants took part in focus group discussions, all of them were stakeholders in LTC. The participants included policymakers, practitioners, and academics covering the national, regional, provincial, and district levels. They were invited to determine the LTC competency of CMs. Data were analyzed by content analysis. Trustworthiness was confirmed by triangulation. From the qualitative data, an item pool of 109 items was developed. In the quantitative phase, the validity and reliability of the instrument were assessed with exploratory factor analysis and internal consistency. The content validity index was examined. A pilot test of 30 CMs confirmed the reliability. The exploratory factor analysis was conducted with 378 CMs, and the internal consistency of Cronbach’s alpha and corrected item-to-total correlation was investigated. Results: The LTC competency instrument comprised of four dimensions with 24 items. The four dimensions included 1) management, 2) caring for dependent older persons, 3) intersectoral collaboration, and 4) resilience. They explained 34.217%, 16.803%, 13.229%, and 9.035% of the total variance, respectively. Therefore, these four dimensions together explained 73.284% of the total variance. All subscales showed a Cronbach’s alpha ranging from 0.912 to 0.944, with an overall value of 0.917. Conclusion: The developed LTC competencies scale for CMs in providing LTC services in the DHS is a valid and reliable instrument and can be applicable as a tool to tailor a training program to promote the LTC competency of CMs. Keywords: Long-term care competencies; Care manager; Older adult; Long-term Care System; Exploratory mixed methods

A Three-State Space Modeling Method for Aircraft System Reliability Design

Reliability is an inherent attribute of a system through optimal system design. However, during the aircraft system development process, the reliability evaluation and system function design efforts are often disconnected, leading to a divide between reliability experts and system designers in their work schedule. This disconnect results in an inefficient aircraft system reliability optimization process, known as the “two-skin” phenomenon. To address this issue, a three-state space model is proposed. Firstly, an analysis was conducted on the relationship between the system function architecture developed by the system designers and the reliability evaluation performed by the reliability experts. Secondly, based on the principle of function flow, the state of failure was categorized into “physical failure” and “non-physical failure”. Additionally, a new state of “function loss” was introduced as the third state for the system, in addition to the traditional states of “normal” and “faulty”. Thirdly, through the state of “Function loss”, an effective integration of system fault modes and function modes was achieved, leading to an optimized system reliability model. A three-state space modeling method was then developed by transforming the system function architecture into a system reliability model. Finally, this new model was applied to an aircraft’s rudder and fly-by-wire control system. The results demonstrate that the function architecture at the design stage of the system can be accurately transformed into the new three-state space model. The structure aligns closely with the function architecture and can be effectively utilized in quantitative system reliability calculations. In this way, the process of ensuring system reliability can be seamlessly integrated into the system optimization design process. This integration alleviates the issue of disjointed work between reliability experts and system designers, leading to a more streamlined and efficient aircraft system optimization process.

Quantitative reliability measures determination of a steel-reinforced concrete beam taking into account fatigue damage accumulation in flexible pin stops

Reliability is one of the most important properties of road bridges due to their degree of responsibility and strategic importance for the transport system. For steel-reinforced concrete bridges, which are widespread nowadays, the question of their overall structure reliability dependence on the element’s condition of steel beam and reinforced concrete slab connection remains not fully studied. The authors have performed fatigue damage accumulation numerical modelling in the conjunction elements of steel-reinforced concrete beam from the cyclic temporary loads influence and analysed this process influence on the overall structure reliability. Based on the previous studies data, a relationship model between the conjunction element shear rigidity and the amount of damage accumulated by it is proposed. The nonlinear finite element calculation algorithm with regard to the conjunction element’s rigidity reduction is proposed and tested on the model of the steel-reinforced concrete superstructure. The selection method of the equivalent time load for modelling the accumulation of fatigue damage process from traffic flow is proposed. In order to optimise the computational resources used it is proposed to use loading process clusterization into enlarged cycles groups and the rational group size is determined. A numerical experiment on the simply supported steel reinforced concrete beam model with different loading cycles number (from 1 loading to 100 million loading cycles) to determine the reliability index β under the assumption of variability of two parameters — design steel resistance and the value of temporary load. FORM (First Order Reliability Method) was used for probabilistic analysis. The study results have shown that the accumulation of fatigue damage in the elements of steel-reinforced concrete superstructures has a significant effect both on the load-bearing capacity of the superstructure beams and on the quantitative indicators of structural reliability (increase in the probability of structural failure, decrease in the reliability index β).

GENERAL PRINCIPLES OF FORECASTING THE RELIABILITY OF COMPLEX TECHNICAL SYSTEMS IN THE OIL AND GAS INDUSTRY

In the oil and gas industry, various high-risk facilities operate, among which pipeline systems occupy a leading position due to their specific characteristics (structural, technological, operational conditions, etc.).
 Pipeline systems, distributed over a large area, are characterized by a high level of risk of emergencies. Therefore, the risk analysis of accidents and failures, the main essence of which is to identify hazards and assess the possibility of their occurrence, is a crucial part of the industrial safety management system of technical systems (TS) [1]. One of the main tasks of this system is to prevent the possibility of accidents and failures, i.e., to ensure reliability. The authors emphasize the importance of assessing the reliability of high-risk objects, both when put into operation and during their operation. It is noted that reliability management during the operation stage can be carried out by determining the optimal allowable deviations of structural parameters of the technical condition and other measures. The paper provides an overview of key quantitative reliability indicators, such as the reliability function and the "unreliability function," and discusses their significance in determining failure probabilities and life-to-failure. Changes in failure intensity according to the Weibull distribution and the exponential distribution law are examined in detail. Reliability indicators for non-repairable systems include the probability of non-failure operation, failure intensity, and mean time to failure, while maintainability indicators for repairable systems are the probability of recovery and mean recovery time. The comprehensive indicator of the reliability of repairable systems is determined through the coefficient of operational readiness. The conclusions of the paper highlight the importance of using statistical data and reliability indicators to assess systems and components, in particular the oil and gas pipeline systems in Europe, which have significant importance for industrial safety and the reliability of technical facilities.

Risk-informed design of advanced nuclear reactor: A target unavailability approach

Incorporating specified safety and production targets during the design phase of an engineered facility can effectively support reductions in construction and operation costs of nuclear power plants. In addition, this supports efforts toward making nuclear power technology more competitive and profitable than other electric power production forms by incorporating operational and design features into the design phase that directly support the increased likelihood of meeting such originating targets. Unavailability is the key parameter to establish plant-level capabilities that cascade down to function, system, and component levels to ensure that all sources of unavailability are addressed in the facility's design phases. In this article, two methods are presented to propose unavailability targets for nuclear reactor systems to risk-inform and optimize the design features, from an availability perspective: the first method is a simple method, and the second is a non-dominated sorting genetic algorithm III (NSGA-III) multi-objective optimization. These iterative methods are demonstrated in this paper for a hypothetical facility with a design maturity such that there is knowing the main components to comply with the engineering and security functions of the systems. With an assumed mature design, it is implied that generic data to execute quantitative reliability, and availability analyses are available at the systems levels that are sufficient to support a design-specific probabilistic risk assessment (PRA). The proposed methods modify the probabilities of basic events within the fault tree structures that model system and component unavailability sources that will be required for the facility’s operating license. The methods provided are applied to visualize the characteristics of the problem and the quantitative results. This work forms the basis for future work in which design alternatives affecting unavailabilities can be estimated and compared to their associated unavailability targets at different levels of granularity.

A dynamic Bayesian network based reliability assessment method for short-term multi-round situation awareness considering round dependencies

During abnormal situations, the perception, comprehension, and projection of elements related to abnormality, i.e., situation awareness (SA), is one of the critical factors to guarantee system safety, and dynamically achieved in short-term multi-round interactions. The short-term multi-round SA (STMR-SA) experiences round dependencies due to anchoring effect (AE) and confirmation bias (CB). For SA in current round, AE biases judgement of system states towards previous cognition, and CB leads to neglect of information disproving previous opinion. Therefore, AE and CB mutually promote and impede the correction of STMR-SA errors. The effects of AE and CB on STMR-SA have been verified in qualitative research but disregarded in quantitative STMR-SA reliability assessments. This paper aims to propose a novel STMR-SA reliability assessment method considering AE-caused and CB-caused round dependencies. First, a round dependency model (RDM) is developed to quantify above-mentioned round dependencies. Subsequently, STMR-SA evolution is modeled with dynamic Bayesian network, where round dependencies are represented by connections between adjacent time slices and quantified by RDM. Case study on Boeing 737-8 (MAX) accident demonstrates the effectiveness of this method. Results indicates that improvement measures including adding angle of attack (AOA) disagree warning and training enhancement, could improve the STMR-SA reliability and system safety.

Reliability Analysis of PAUT Based on the Round-Robin Test for Pipe Welds with Thermal Fatigue Cracks.

Thermal fatigue cracks occurring in pipes in nuclear power plants pose a high degree of risk. Thermal fatigue cracks are generated when the thermal fatigue load caused by local temperature gradients is repeatedly applied. The flaws are mainly found in welds, owing to the effects of stress concentration caused by the material properties and geometric shapes of welds. Thermal fatigue pipes are classified as targets of risk-informed in-service inspection, for which ultrasonic testing, a volumetric non-destructive testing method, is applied. With the advancement of ultrasonic testing techniques, various studies have been conducted recently to apply the phased array ultrasonic testing (PAUT) method to the inspection of thermal fatigue cracks occurring on pipes. A quantitative reliability analysis of the PAUT method must be performed to apply the PAUT method to on-site thermal fatigue crack inspection. In this study, to evaluate the quantitative reliability of the PAUT method for thermal fatigue cracks, we fabricated crack specimens with the thermal fatigue mechanism applied to the pipe welds. We performed a round-robin test to collect PAUT data and determine the validity of the detection performance (probability of detection; POD) and the error in the sizing accuracy (root-mean-square error; RMSE) evaluation. The analysis results of the POD and sizing performance of the length and depth of thermal fatigue cracks were comparatively evaluated with the acceptance criteria of the American Society of Mechanical Engineers Code to confirm the effectiveness of applying the PAUT method.

Quantitative Electroencephalography Objectivity and Reliability in the Diagnosis and Management of Traumatic Brain Injury: A Systematic Review.

Background. Persons with a history of traumatic brain injury (TBI) may exhibit short- and long-term cognitive deficits as well as psychiatric symptoms. These symptoms often reflect functional anomalies in the brain that are not detected by standard neuroimaging. In this context, quantitative electroencephalography (qEEG) is more suitable to evaluate non-normative activity in a wide range of clinical settings. Method. We searched the literature using the "Medline" and "Web of Science" online databases. The search was concluded on February 23, 2023, and revised on July 12, 2023. It returned 134 results from Medline and 4 from Web of Science. We then applied the PRISMA method, which led to the selection of 31 articles, the most recent one published in March 2023. Results. The qEEG method can detect functional anomalies in the brain occurring immediately after and even years after injury, revealing in most cases abnormal power variability and increases in slow (delta and theta) versus decreases in fast (alpha, beta, and gamma) frequency activity. Moreover, other findings show that reduced beta coherence between frontoparietal regions is associated with slower processing speed in patients with recent mild TBI (mTBI). More recently, machine learning (ML) research has developed highly reliable models and algorithms for the detection of TBI, some of which are already integrated into commercial qEEG equipment. Conclusion. Accumulating evidence indicates that the qEEG method may improve the diagnosis and management of TBI, in many cases revealing long-term functional anomalies in the brain or even neuroanatomical insults that are not revealed by standard neuroimaging. While FDA clearance has been obtained only for some of the commercially available equipment, the qEEG method allows for systematic, cost-effective, non-invasive, and reliable investigations at emergency departments. Importantly, the automated implementation of intelligent algorithms based on multimodally acquired, clinically relevant measures may play a key role in increasing diagnosis reliability.

Dual Hardware-In-the-Loop (DHIL) platform for testing and validation of WEC subsystems

This paper presents the design process and application of a dual hardware hardware-in-the-loop (DHIL) testing platform targeting components and subsystems of wave energy conversion devices. The DHIL testing methodology combines two HIL-equipped test rigs allowing to simultaneously test components mounted on each rig and connected to the same simulation loop. The platform was therefore developed combining a HIL test rig for drivetrains with a HIL test rig for structural components.The DHIL testing platform has the capability to address multiple types of tests on critical subsystems and components within a WEC: characterization tests, for defining key performances of the equipment under test; accelerated tests, to assess qualitative and quantitative reliability features; and ultimate load testing, for survivability purposes. The overall aim of these tests is to identify weaknesses in an early design phase of device design or as a qualification activity prior the deployment of an ocean prototype. Additionally, HIL and DHIL tests can be used to assess the influence of a design update on the overall WEC model and to track failure interdependencies at a relevant scale. Finally, all of the above-mentioned activities can inform the development of a more accurate global numerical model, potentially at sub-system / critical component level, to be validated based on the test results.The definition of the test rig mechanical and electrical input specifications is dependent on the understanding of the load envelope each subsystem / component will be subject to during its lifetime. To define such envelope, a research activity modelling three different device types, three deployment sites and multiple design situations (e.g. power production, parked, shut-down etc.) led to the creation of a load database that was combined with information from WEC developers.After defining the input specifications, the rigs were designed by identifying the optimal layout, the key components and the setup of the overall test area. Analyses on mechanical, electrical and hydraulic parameters were completed to ensure the required performance of each rig could be achieved, while guaranteeing the safety during their operation.The signal processing of each rig was also analysed, with the aim of defining the minimum rig latency to allow HIL and DHIL tests to be performed. This analysis took into account the possible interface characteristics of the simulator, the sensors and the main features of the models used for real-time tests.An overview of the testing activities to be conducted within the IMPACT project will be presented in this paper. Such activities aim to de-risking the technologies at early stages and increasing their maturity through a structured process. The proposed approach has the final goal of demonstrating that the DHIL testing platform is capable to reduce capital-intensive activities, often associated with the development of large-scale prototypes, which is a critical factor for the successful development and time-to-market of a WEC.

Water Supply Reliability Analysis of Multi-Purpose Dams in Preparation for Water Disasters

Purpose: In this study, in order to find a way to minimize water supply shortage, reliability analysis of water supply was conducted by operating the Andong and the Imha Dam. The purpose is to find a way to minimize water shortage by the allocation distribution model from the reliability analysis results.
 Method: In this study, in order to analyze the water supply reliability of Andong and Imha Dam, using the Allocation rule presented by Park et al(2007), based on the planned water supply of Andong and Imha Dam for a total of 360 months from 1993 to 2022, analyzed. From the analysis results, the reliability of stable water supply was evaluated.
 Results: In the case of supplying the planned water supply of Andong and Imha Dam, the analysis result of Rule(B), which considers the ratio of the storage and inflow of the dam in the reservoir operation analysis result, showed that the shortage of Andong Dam occurred the most at 23 months, Regarding the number of shortages of control points, Rule(A), which considers only the storage capacity of the dam, was found to be short at 39 months, which is the largest number of shortages. As for the frequency standard reliability, Rule(B) showed the highest reliability of 90%, but in the case of quantitative reliability, the reliability was similar in all cases.
 Conclusion: In the water supply reliability, the reliability of stable water supply by supplying only the planned water supply amount is 94%, 93%, and 90% in Rule(B) of the allocation distribution model. 5% at the Andong dam, 7% at the Imha dam, and 10% at the control point. When water supply is evaluated with frequency reliability, it is judged that countermeasures for the shortfall are necessary. Next, in the case of quantitative reliability, when only the planned water supply was supplied, it was analyzed to be 95%, 94%, and 95% in all methods, so that the quantitative reliability was higher than the frequency reliability.

A hybrid HFACS model using DEMATEL-ORESTE method with linguistic Z-number for risk analysis of human error factors in the healthcare system

The human error factor is one of the leading causes of medical errors. Among risk analysis techniques for human error factors, HFACS (Human Factor Analysis and Classification System) method has been regarded as one of the most valuable approaches due to its advantage in potential failure classification. However, the conventional HFACS method is insufficient to handle the risk analysis problem for human error factors considering the interactive relationship among these factors. Moreover, the current fuzzy HFACS frameworks cannot address quantitative risk analysis issues, including imprecision and reliability of information. Thus, this paper constructs an integrated linguistic Z-number-based HFACS framework for analyzing the risk of human error factors. This framework can capture the uncertainty and reliability of the risk evaluation information and the interactive relationships among factors. First, the linguistic Z-number-DEMATEL (Decision Making Trial and Evaluation Laboratory) method is used to generate the comprehensive risk matrix of human error factors identified by the HFACS method. Then, an extended linguistic Z-number-ORESTE method based on the score function is presented to prioritize the risk of human error factors, which can show the preference, indifference, and incomparability relationship among human error factors. Finally, a case study of a healthcare system is conducted to illustrate the reliability of the proposed method. The result of this case indicates that inadequate resources are the most severe risk. Sensitivity analysis and comparative analysis indicate the necessity of considering the effect of the semantics of language terms and the interrelationships between human error factors on risk analysis results. These results show that the proposed hybrid framework is a reliable means to analyze the risk of human error factors within the HFACS method.

Honeycomb-like AgNPs@TiO2 array SERS sensor for the quantification of micro/nanoplastics in the environmental water samples

There has been a growing concern over the micro/nanoplastics pollution and treatment. The fast qualitative and quantitative analysis of these small plastic particles is the crucial issues. Herein, a novel honeycomb-like AgNPs@TiO2 array-based surface-enhanced Raman scattering (SERS) sensor was developed for efficient identification and analysis of the micro/nanoplastics in the environmental water samples. The plasmonic AgNPs were uniformly anchored within the periodic TiO2 nanocage arrays to form a AgNPs@TiO2 array. The dual enhancement mechanisms in the AgNPs@TiO2 hybrid structure endow the SERS sensor high sensitivity to detect trace amount of micro/nanoplastics down to 50 μg/mL with a hand-held Raman spectrometer. Further, this SERS sensor successfully discerns two-component mixtures of the micro/nanoplastics due to the fingerprint feature. In addition, the superior reproducibility (RSD of 9.69%) of the SERS sensor assures the quantitative detection reliability, realizing quantitative analysis of Polystyrene (PS) microplastics in tap water, lake water, soil water and seawater with detection limits of 100 μg/mL, 100 μg/mL, 100 μg/mL, 100 μg/mL and 250 μg/mL, respectively. The recovery rates of PS microspheres in four water environments ranged from 97.6% to 109.7%, with the RSD ranging from 0.49% to 10.23%. This honeycomb AgNPs@TiO2 array sensor provides a promising application prospect in the detection of micro/nanoplastics contaminants from the environmental water.

Effect of moderate prenatal ethanol exposure on the differential expression of two histamine H3 receptor isoforms in different brain regions of adult rat offspring.

We have reported that prenatal alcohol exposure (PAE) elevates histamine H3 receptor (H3R) agonist-mediated inhibition of glutamatergic neurotransmission in the dentate gyrus. Here, we hypothesized that PAE alters the expression of two prominent H3R isoforms namely, the rH3A and rH3C isoforms, which have differing intrinsic activities for H3R agonists, in a manner that may contribute to heightened H3R function in PAE rats. In contrast to our predictions, we found different effects of sex and PAE in various brain regions with significant interactions between sex and PAE in dentate gyrus and entorhinal cortex for both isoforms. Subsequently, to confirm the PAE-and sex-induced differences on H3R isoform mRNA expression, we developed a polyclonal antibody selective for the rH3A inform. Western blots of rH3A mRNA-transfected HEK-293 cells identified a ~ 48 kDa band of binding consistent with the molecular weight of rH3A, thus confirming antibody sensitivity for rH3A protein. In parallel, we also established a pan-H3R knockout mice line to confirm antibody specificity in rodent brain membranes. Both qRT-PCR and H3R agonist-stimulated [35S]-GTPγS binding confirmed the absence of mH3A mRNA and H3 receptor-effector coupling in H3R knockout (KO) mice. Subsequent western blotting studies in both rat and mouse brain membranes were unable to detect rH3A antibody binding at ~48 kDa. Rather, the H3RA antibody bound to a ~ 55 kDa band in both rat and mouse membranes, including H3R KO mice, suggesting H3RA binding was not specific for H3Rs in rodent membranes. Subsequent LC/MS analysis of the ~55 kDa band in frontal cortical membranes identified the highly abundant beta subunit of ATPase in both WT and KO mice. Finally, LC/MS analysis of the ~48 kDa band from rH3A mRNA-transfected HEK-293 cell membranes was able to detect rH3A protein, but its presence was below the limits of quantitative reliability. We conclude that PAE alters rH3A and rH3C mRNA expression in some of the same brain regions where we have previously reported PAE-induced alterations in H3R-effector coupling. However, interpreting the functional consequences of altered H3R isoform expression was limited given the technical challenges of measuring the relatively low abundance of rH3A protein in native membrane preparations.

Towards quantitative digital subtraction perfusion angiography: An animal study.

X-ray digital subtraction angiography (DSA) is the imaging modality for peri-procedural guidance and treatment evaluation in (neuro-) vascular interventions. Perfusion image construction from DSA, as a means of quantitatively depicting cerebral hemodynamics, has been shown feasible. However, the quantitative property of perfusion DSA has not been well studied. To comparatively study the independence of deconvolution-based perfusion DSA with respect to varying injection protocols, as well as its sensitivity to alterations in brainconditions. We developed a deconvolution-based algorithm to compute perfusion parametric images from DSA, including cerebral blood volume (CBV ), cerebral blood flow (CBF ), time to maximum (Tmax), and mean transit time (MTT ) and applied it to DSA sequences obtained from two swine models. We also extracted the time intensity curve (TIC)-derived parameters, that is, area under the curve (AUC), peak concentration of the curve, and the time to peak (TTP) from these sequences. Deconvolution-based parameters were quantitatively compared to TIC-derived parameters in terms of consistency upon variations in injection profile and time resolution of DSA, as well as sensitivity to alterations of cerebralcondition. Comparing to TIC-derived parameters, the standard deviation (SD) of deconvolution-based parameters (normalized with respect to the mean) are two to five times smaller, indicating that they are more consistent across different injection protocols and time resolutions. Upon ischemic stroke induced in a swine model, the sensitivities of deconvolution-based parameters are equal to, if not higher than, those of TIC-derivedparameters. In comparison to TIC-derived parameters, deconvolution-based perfusion imaging in DSA shows significantly higher quantitative reliability against variations in injection protocols across different time resolutions, and is sensitive to alterations in cerebral hemodynamics. The quantitative nature of perfusion angiography may allow for objective treatment assessment in neurovascularinterventions.

Untargeted screening of plant metabolites based on data-independent and data-dependent acquisition modes using LC-ESI-QTOF-MS: Tribulus terrestris L. as a case study

Metabolomics has been used as a powerful tool for the analysis, and drug-lead identification in medicinal plants and herbal medicines. For the coverage of a broader range of plant-based metabolites using LC-MS, one of the important parameters is the selection of analysis mode and data processing for identification. This paper describes the utility of two distinctive acquisition modes in combination, a classic data-dependent acquisition (DDA) mode and a data-independent acquisition (DIA) mode for obtaining the mass spectrometry data of plant extracts using LC-ESI-QTOF/MS. Tribulus terrestris plant was used as a case study. We have applied three-step data analysis pipeline 1-annotation and putative identification of metabolites, 2-validation, and relative quantification, and 3-multivariate analysis using open-access MS-DIAL, Skyline, and Perseus software. A total of four samples of T. terrestris (aqueous extracts), two fruits, and two whole plant samples, from two different regions, were used. By combining data analysis results of plant fruit samples from two different regions, a total of 95 and 77 metabolites were identified in positive and negative ionization modes, respectively. Similarly, in the analysis of the whole plant from two different regions, 75 and 76 metabolites were identified in positive and negative ionization modes, respectively. We suggested the use of DDA mode for annotation, identification of metabolites, and generation of transition lists in MS-DIAL, furthermore, the use of DIA acquisition mode for enhancing metabolites sensitivity in complex samples, deconvolute MS1/MS2 spectra in Skyline for the quantitative performance and analytical reliability. The developed protocol can be used for the broader coverage of plant-based metabolites.

Peningkatan Daya Saing UMKM melalui Financial Technology dan Digital Marketing

The research purpose is to produce a model for increasing the competitiveness of micro, small and medium enterprises (MSMEs) through financial technology and digital marketing in Pangkalpinang City. 60 SMEs were selected as a sample using accidental sampling. Data was collected through observation and interview methods. Data analysis used a mixed method which is a combination of qualitative and quantitative methods, including validity and reliability tests, descriptive analysis, qualitative data analysis, and important performance analysis (IPA). The results show that the performance of MSMEs in implementing financial technology and digital marketing has met expectations, so that MSMEs can improve their service quality dimensions. This research is expected to contribute ideas to Pangkalpinang City government regulations in increasing the competitiveness of MSMEs in the current and future Covid-19 pandemic era.

Internal Validation of a Real-Time qPCR Kit following the UNE/EN ISO/IEC 17025:2005 for Detection of the Re-Emerging Monkeypox virus.

Human mpox is caused by the Monkeypox virus, a microorganism closely related to the Variola virus, both belonging to the Orthopoxvirus genus. Mpox had been considered a rare disease until a global outbreak occurred in 2022. People infected with the virus present similar symptoms to patients suffering smallpox and other rash illnesses, hindering diagnosis. The WHO indicated that no commercial PCR or serology kits are currently widely available. In the present study, the MPXV MONODOSE dtec-qPCR kit was validated following guidelines of the UNE/EN ISO/IEC 17025:2005. The parameters evaluated for the acceptance of the assay were in silico and in vitro specificity, quantitative phase analysis, reliability, and sensitivity. The assay passed validation criteria and yielded an efficiency of 95.8%, high repeatability, reproducibility, and a Limit of Detection and Quantification of at least 10 copies. Results from the validation of the MPXV dtec-qPCR kit were satisfactory. The use of the MONODOSE format (dehydrated single PCR-tubes, ready to use) provided considerable advantages allowing the detection of the Monkeypox virus to be accurately achieved. This detection kit may be considered a reliable, fast, simple, and universally available option.