Cut Sets Research Articles

Social cultural factors influencing health seeking practices among men suffering from lower urinary tract symptoms attending surgical outpatient clinic at a county referral hospital in Kenya

Health seeking practices is critical towards early screening, detection and control of Lower Urinary Tract Symptoms (LUTS) whereby human prostate gland is the major cause of benign prostate hyperplasia (BPH) and prostate cancer (PCA), which mostly accounts for LUTS. Social cultural factors such as cultural beliefs, educational level, income level and religion among many others have a direct influence on health seeking practices both positively and negatively in as far as LUTS are concerned. The researcher explored social cultural factors influencing health seeking practices among men with LUTS attending surgical outpatient clinic at Meru level five hospital (Kenya). De-scriptive cross-sectional study design was used to collect data from 120 men with LUTS, and 4 health workers. Census method was used to select the study participants with questionnaires, interview guide and focused group discussion used as instruments of data collection. Quantitative data was analyzed using Statistical Package for Social Sciences (SPSS) software version 22, whereas the qualitative data was analyzed using qualitative techniques. Descriptive statistics were computed to generate percentages and frequencies, which were then presented in tables and charts. Logistic regression was used whereby P-values were employed to determine the statistical significance of results with cut off set at (p ≤0.05). Majority (67.0%) of the patients with LUTS were aged between 61-70 years. Also, majority (68.8%) of the respondents had primary level of education, with majority (72.0%) of them being farmers with an income level of below Ksh. 20,000. The study results showed that social cultural factors had statistical significant influence on health seeking practices among men with LUTS.   Â

System failure probability evaluation using fault tree analysis and expert opinions in intuitionistic fuzzy environment

In quantitative fault tree analysis of a system, exact failure probability values of components are utilized to calculate the failure probability of the system. However, in many real world problems, it is problematic to get precise and sufficient failure data of system components due to insufficient or imprecise information about components, changing environment or new components. A methodology has already been developed by employing fuzzy set theory for the system reliability evaluation by utilizing qualitative failure data of system components when quantitative failure data of components are inaccessible or insufficient. This paper extends the concept of fuzzy set to intuitionistic fuzzy set and proposes a novel approach to evaluate system failure probability using intuitionistic fuzzy fault tree analysis with qualitative failure data of system components. The qualitative failure data such as expert opinions are collected as linguistic terms. These linguistic terms are then quantified by triangular intuitionistic fuzzy numbers in form of membership function and non-membership function. Additionally, a method is developed for combining the different opinions of experts. To illustrate the applicability of proposed approach, a case study of the crude oil tank fire and explosion accident is performed. The obtained results are very close to the results from pre-existing approaches which confirm that the proposed approach is a more realistic alternative for the study of system reliability in intuitionistic fuzzy environment when quantitative failure data of system components are not known. To help decision makers for improving the security execution of the crude oil tank system, importance measures including Fussell-Vesely importance and cut sets importance are also executed.

Z plus jets production via double parton scattering in pA collisions at the LHC

We present results on Zjj production via double parton scattering in pA collisions at the LHC. We perform the analysis at leading and next-leading order accuracy with different sets of cuts on jet transverse momenta and accounting for the single parton scattering background. By exploiting the experimental capability to measure the centrality dependence of the cross section, we discuss the feasibility of DPS observation in already collected data at the LHC and in future runs.

Predicting Recurrent Instability of the Shoulder (PRIS): A Valid Tool to Predict Which Patients Will Not Have Repeat Shoulder Instability After First-Time Traumatic Anterior Dislocation.

To assess the sensitivity, specificity, and validity of the Predicting Recurrent Instability of the Shoulder (PRIS) tool in people with a first-time traumatic anterior shoulder dislocation. Prospective cohort study. People with first-time traumatic anterior shoulder dislocation (n = 85), aged 16 to 40 years, were recruited within 12 weeks of their shoulder dislocation and followed prospectively for 1 year post injury. We calculated the sensitivity, specificity, negative predictive value, and positive predictive value of the PRIS tool. Of the 75 participants available for 1-year follow-up, 57 (76%) did not have recurrent shoulder instability. With the PRIS tool cut point set at 0.895, the tool's sensitivity was 39% (95% confidence interval [CI]: 17.3%, 64.3%) and its specificity was 95% (95% CI: 85.4%, 98.9%). The area under the curve was 0.69 (95% CI: 0.55, 0.84; P = .01). The PRIS tool correctly identified 54 of the 57 (95%) who did not have recurrent instability (accuracy, 81%; 95% CI: 70.7%, 89.4%). Negative and positive predictive values were 83% (95% CI: 77.2%, 87.7%) and 70% (95% CI: 40.2%, 89.0%), respectively. The PRIS tool can predict those who will not have further shoulder instability in the year following first-time traumatic anterior shoulder dislocation. The PRIS tool cannot accurately predict those who will have recurrent shoulder instability. J Orthop Sports Phys Ther 2020;50(8):431-437. doi:10.2519/jospt.2020.9284.

Study of Pioneer Sea Transportation’s Safety with Formal Safety Assessment Method

Particularly the safety of sea transportation must meet at least 2 decent criterias, namely seaworthiness and cargoworthiness. During the period 2009 - 2019 there were more than 90 accident cases have been recorded (NTSC, 2020). The types of accidents that occur are sinking (31%), aground (5%), collisions (30%), on fires (32%) and other types of accidents (5%). Ship accidents that occurred in Indonesia shows that the application of regulations relating to the security and safety of sea transportation still need to be given a greater portion in terms of their application and supervision. This research is focused on the study of the safety of pioneer ship with cargo-passanger ship types. Formal safety assessment (FSA) according to the International Maritime Organization standard is used as a method for this study, FSA was developed as a safety planning guide in the maritime field which aims to reduce risks in operations, while enhancing shipping safety, includes protection of life, health, the marine environment, and property. Research using expert judgment techniques with questionnaires. Risk analysis using Fault Tree Analysis method. Ship on fire and sinking are used as a top event. Calculation of minimum cut set on FTA is done using FTA software. In this study identified several risk control options that will be used in an effort to reduce the risk of ship on fire and sinking, by looking at the risk reduction index (ΔR), after which the cost of each Risk Control Option (RCO) is calculated to get the Gross of cost averting effectiveness index fatality (GCAF) and Net of cost averting fatality (NCAF) in order to know whether the RCO option has provided benefits in terms of benefits and costs incurred. Recommendations are submitted by looking at the most optimal cost and benefit options.

An extended and generalized framework for the calculation of metabolic intervention strategies based on minimal cut sets.

The concept of minimal cut sets (MCS) provides a flexible framework for analyzing properties of metabolic networks and for computing metabolic intervention strategies. In particular, it has been used to support the targeted design of microbial strains for bio-based production processes. Herein we present a number of major extensions that generalize the existing MCS approach and broaden its scope for applications in metabolic engineering. We first introduce a modified approach to integrate gene-protein-reaction associations (GPR) in the metabolic network structure for the computation of gene-based intervention strategies. In particular, we present a set of novel compression rules for GPR associations, which effectively speedup the computation of gene-based MCS by a factor of up to one order of magnitude. These rules are not specific for MCS and as well applicable to other computational strain design methods. Second, we enhance the MCS framework by allowing the definition of multiple target (undesired) and multiple protected (desired) regions. This enables precise tailoring of the metabolic solution space of the designed strain with unlimited flexibility. Together with further generalizations such as individual cost factors for each intervention, direct combinations of reaction/gene deletions and additions as well as the possibility to search for substrate co-feeding strategies, the scope of the MCS framework could be broadly extended. We demonstrate the applicability and performance benefits of the described developments by computing (gene-based) Escherichia coli strain designs for the bio-based production of 2,3-butanediol, a chemical, that has recently received much attention in the field of metabolic engineering. With our extended framework, we could identify promising strain designs that were formerly unpredictable, including those based on substrate co-feeding.

Reliability block diagram (RBD) and fault tree analysis (FTA) approaches for estimation of system reliability and availability – a case study

PurposeIn the present worldwide situation, the survival of a business is a major crucial aspect. The business cannot be succeeded unless it produces the anticipated production levels. Achievement of this can be possible only by maintaining the equipment into an adequate level. Load-Haul-Dumpers (LHDs), as the main workhorse and massive transporting machines, are highly utilized in underground mining operations. Despite the usage of LHDs, these are prone to the uneven and unexpected occurrence of potential failures. These are causes to minimize the production and productivity of capital intensive equipment. To get a good profitability index, it is very necessary to have the required levels of equipment reliability and availability. Estimation of reliabilities and availabilities play a critical role in the performance evaluation of equipment.Design/methodology/approachBy keeping the significance of the present research work in view in this research paper one of the well appropriate techniques such as fault tree analysis (FTA) was utilized to assess the reliability of the LHD system based on the function flow diagram. Best fit distribution of data sets were made by the utilization of Kolmogorov–Smirnov (K-S) test. Parametric estimation of theoretical probability distributions was done by utilizing the maximum likelihood estimation (MLE). Failure rate of each LHD system has computed based on the best fit results from “Isograph Reliability Workbench 13.0”. Reliability configuration of each LHD system has modeled using reliability block diagram (RBD), as well as the FTA.FindingsIndependent and identical distribution (IID) assumption of data sets was validated through statistic U-test (Chi Squared test). On the basis of test results, the data sets are in accordance with IID assumption. Therefore renewal process approach has been utilized for further investigation. Allocations of best fit distribution of data sets were made by the utilization ofK-S test. Parametric estimation of theoretical probability distributions was made by utilizing maximum likelihood estimation (MLE) method. Reliability of each individual subsystem has been computed according to the best fit distribution. The deductive method called RBD was utilized to investigate the given system reliability by analyzing with graphical representations of logic system and observed highest percentage of reliability as 69.44% (LH29). FTA has been utilized to investigate the availability percentage of a system and observed highest percentage value as 79.51% (LH29). This technique also helps to identify the most critical parts/cut sets by using Fussell-Vesely (F-V) importance measure.Research limitations/implicationsAs the reliability analysis is one of the complex techniques, it requires strategic decision-making knowledge for the selection of methodology to be used. As the present case study was from a public sector company, operating under financial constraints the conclusions/findings may not be universally applicable.Originality/valueThe present study throws light on this equipment that need a tailored maintenance schedules, partly due to the peculiar mining conditions, under which they operate. This analysis provides the information on several aspects such as present working condition of the machines, occurrence of various potential failure modes, influence of failure modes on its performance and reliable life aspects etc. Also, these investigations asses the forecasting of necessary managerial practices or control measures like possible design modifications and replacement actions of components to ensure the required levels of availability and utilization of the equipment. Both qualitative and quantitative analysis of FTA has been performed to determine the minimal/most influencing cut sets of the system and to estimate overall system availability within the work environment. Based on the computed results reasons for performance drop of each machine was identified and suitable recommendations were suggested to improve the performance of capital intensive systems.

Single top partner production in the tZ channel at eγ collision in the littlest Higgs model with T-parity

Introducing the top partner is a common way to cancel the largest quadratically divergent contribution to the Higgs mass induced by the top quark. In this work, we study single top partner production in the tZ channel at eγ collision in the littlest Higgs model with T-parity (LHT). Since it is well known that polarized beams can enhance the cross section, we analyze the signal via polarized electron beams, and photon beams. we have selected two decay modes for comparison, based on the leptonic or the hadronic decays of the W and Z from the top partner. We then construct a detailed detector simulation, and choose a set of cuts to enhance signal significance. For mode A(B), the capacity for exclusion in this process at = 3 TeV is comparable to the current experimental limits with L = 1000 (500) fb−1. If the integrated luminosity can be increased to 3000 fb−1, the top partner mass can be excluded up to 1350 (1440) GeV at 2σ level. We also considered the initial state radiation effect, and find that this effect reduces the excluding ability of the eγ collision on the the top partner mass by approximately 10 GeV. Moreover, the ability to exclude the LHT parameter space at eγ collision complements the existing research.

CFD modeling of heat transfer and flow field in spin flash drying process

Spin flash drying equipment is widely used in chemical, food and other fields. Drying process consumes large amounts of energy and reduction in operating cost will be extremely beneficial for the industry. Therefore, in order to improve the efficiency of spin flash dryer. A three-dimensional CFD model of the drying process was established by computational fluid dynamics, and the flow field characteristics and heat transfer mechanism of the drying process were obtained. We studied the specific effects of different parameters on the drying process, and verified the results with calcium carbonate as raw material. The experimental results are basically consistent with the simulation results. The velocity, temperature and pressure in the drying chamber near the wall are greater than those in the central region, which generally decrease with height. The speed of the cutter set has a large effect on the tangential and radial velocity, but the influence on the pressure drop is not significant. Meanwhile the temperature and velocity of inlet air have a greater impact on distribution of flow field and material drying, the variable structure improves the stability of the drying process.

Safety risk analysis and control of tower crane

Tower crane is one of the vertical transport machinery widely used in the construction at present. Due to its own structure and safety management defects, accidents often occur and have serious consequences [1]. Therefore, it is of great significance to study the safety accidents of tower crane. In this paper, through a large number of accident statistical analysis and expert interviews, from the analysis of the entire process of tower crane installation, use and disassembly stage, the accident tree with the tower crane safety incident as the top event is established. Through the qualitative analysis of the accident tree, the minimum cut (diameter) set is obtained, on this basis, the structural importance of all basic events is sorted, the main factors affecting the safety accident of the tower crane are determined, and the corresponding management and control are proposed, and provide a basis for preventing tower crane accidents and controlling tower crane risks.

Probability of Uncontrolled External Leakage During the Production Phase of a Subsea Well

Abstract This work presents a methodology for evaluating the uncontrolled external leakage probability of a subsea well during the production phase. Based on a barrier diagram, an algorithm for possible leak path identification is proposed, considering different operation modes: gas lift operation, free-flowing, or well closed at the subsea Christmas tree. Considering the equivalency between these paths and the minimum cut sets from a fault tree modeling, the uncontrolled external leakage probability is calculated using the upper bound approximation. The effect of common cause failures is considered for the failure mode fail-to-close-valve. The instantaneous availability function of each component is considered. Non-repairable, repairable, and periodically tested items are used. Probability distribution parameters are estimated in order to make a case study. The failure rate functions determined are used as input for the proposed model, regarding the following failure modes: fail-to-close, external-leakage, and internal-leakage at the closed position. Finally, failure probability results and sensitivity analysis are demonstrated for a base case study. Parameters like time between tests, inspections, and component reliability are varied in order to identify the impact on the uncontrolled external leakage probability. The main objective of the proposed methodology is to support decision-making on the well integrity management system during the production phase of a subsea well. To this end, actual and reliable input data should be considered.

Analysis of minimal path and cut vectors in multistate monotone systems and use it for detection of binary type multistate monotone systems

Theorem specifying how all minimal cut (path) vectors to level j can be obtained from all minimal path (cut) vectors to level j in any multistate monotone system is proven. Characterizations of binary type multistate monotone systems and binary type multistate strongly coherent systems by minimal cut and path vectors and corresponding to them, binary type cut and path sets are also demonstrated.

Dynamic study of critical factors of explosion accident in laboratory based on FTA

Laboratory safety has been widely concerned, but fire, explosion, poisoning and other accidents occur from time to time. Among them, the proportion of safety accidents, casualties and economic losses caused by explosion are relatively high. In particular, the safety, reliability and maintainability of laboratories in colleges and universities and scientific research institutes should be evaluated and optimized. Therefore, it is necessary to use efficient, reliable and economical methods to identify and monitor the key factors that will cause explosion accidents in the laboratory. In this paper, through the combination of fault tree analysis (FTA) and binary decision diagram (BDD), the three main sources of explosion accidents in laboratory (gas cylinder, pressure device and hazardous chemicals) are analyzed quantitatively. When using BDD to simplify FT operation, a variety of event sorting methods are compared. Finally, it is found that “Level” and “AND” methods can provide a more convenient and reasonable number of cut sets. Considering different methods to measure the importance of basic events, it is found that similar results can be obtained. The importance of Critical is used to identify the importance of events, combined with its change with time, the change of importance is analyzed dynamically. The key factors from four aspects of “human”, “machine”, “environment” and “management” in laboratory explosion accident are determined. It provides a new idea for the dynamic safety management and maintenance of the laboratory, and puts forward some ideas for the new research content at the end of this paper.

A rapid modeling method and accuracy criteria for common-cause failures in Risk Monitor PSA model

In the development of a Risk Monitor probabilistic safety assessment (PSA) model from the basic PSA model of a nuclear power plant, the modeling of common-cause failure (CCF) is very important. At present, some approximate modeling methods are widely used, but there lacks criterion of modeling accuracy and error analysis. In this paper, aiming at ensuring the accuracy of risk assessment and minimizing the Risk Monitor PSA models size, we present three basic issues of CCF model resulted from the changes of a nuclear power plant configuration, put forward corresponding modeling methods, and derive accuracy criteria of CCF modeling based on minimum cut sets and risk indicators according to the requirements of risk monitoring. Finally, a nuclear power plant Risk Monitor PSA model is taken as an example to demonstrate the effectiveness of the proposed modeling method and accuracy criteria, and the application scope of the idea of this paper is also discussed.

Coordinated appointment scheduling with multiple providers and patient-and-physician matching cost in specialty care

To achieve effective care, it is critical to match patients with capable physicians in specialty care. Motivated by the rising popularity of patient-and-physician matching applications in specialty care, this study optimizes the matching and appointment scheduling problems simultaneously in a stochastic environment, in which a decision-maker determines the patient-and-physician pair assignment and the starting times of services. We develop a stochastic optimization model to minimize the matching and operational costs (i.e., patients’ waiting time costs, service providers’ idle time and overtime costs). This paper is the first study that incorporates matching and appointment scheduling problems together. The benefits of combining these two problems are enormous. The experimental results show that the operational costs gap is as large as 51% between the ill-matched and the well-matched patient-and-physician scenarios. We first reformulate this problem as a two-stage optimization problem. With the analysis for the optimal solution of the second stage problem, a Benders decomposition algorithm is developed. To improve the efficiency of the proposed algorithm, we also prove a low bound of our problem and use it to construct a set of feasibility cuts. Then, we extend our method to incorporate no-shows. Our algorithm can solve problems efficiently, and it can obtain optimal solutions for medium-size problems within 2 or 3 min. In contrast, traditional optimal methods require nearly 2 h. For large-size problems, our algorithm can obtain optimal solutions within 5 or 6 min, whereas traditional optimal methods cannot generate a result within 5 h. Finally, numerical experiments are conducted to evaluate the performance of our proposed algorithm and to investigate the variation of the optimal solutions in different scenarios. To provide quality care as well as minimize the total cost of appointment scheduling in specialty care, we suggest that physicians should develop or train their specialties based on the local patients’ disease pattern. We also disclose that the no-show has less influence on the service system when the weight of the matching cost is substantial.

A Systems-Based Approach for Cyanide Overproduction by Bacillus megaterium for Gold Bioleaching Enhancement.

With the constant accumulation of electronic waste, extracting precious metals contained therein is becoming a major challenge for sustainable development. Bacillus megaterium is currently one of the microbes used for the production of cyanide, which is the main leaching agent for gold recovery. The present study aimed to propose a strategy for metabolic engineering of B. megaterium to overproduce cyanide, and thus ameliorate the bioleaching process. For this, we employed constraint-based modeling, running in silico simulations on iJA1121, the genome-scale metabolic model of B. megaterium DSM319. Flux balance analysis (FBA) was initially used to identify amino acids to be added to the culture medium. Considering cyanide as the desired product, we used growth-coupled methods, constrained minimal cut sets (cMCSs) and OptKnock to identify gene inactivation targets. To identify gene overexpression targets, flux scanning based on enforced objective flux (FSEOF) was performed. Further analysis was carried out on the identified targets to determine compounds with beneficial regulatory effects. We have proposed a chemical-defined medium for accelerating cyanide production on the basis of microplate assays to evaluate the components with the greatest improving effects. Accordingly, the cultivation of B. megaterium DSM319 in a chemically-defined medium with 5.56 mM glucose as the carbon source, and supplemented with 413 μM cysteine, led to the production of considerably increased amounts of cyanide. Bioleaching experiments were successfully performed in this medium to recover gold and copper from telecommunication printed circuit boards. The results of inductively coupled plasma (ICP) analysis confirmed that gold recovery peaked out at around 55% after 4 days, whereas copper recovery continued to increase for several more days, peaking out at around 85%. To further validate the bioleaching results, FESEM, XRD, FTIR, and EDAX mapping analyses were performed. We concluded that the proposed strategy represents a viable route for improving the performance of the bioleaching processes.

Enumeration of the minimal node cutsets based on necessary minimal paths

<p>Reliability evaluation is an important research field for a complex network. The most popular methods for such evaluation often use Minimal Cuts (MC) or Minimal paths (MP). Nonetheless, few algorithms address the issue of the enumeration of all minimal cut sets from the source node s to the terminal node t when only the nodes of the network are subject to random failures. This paper presents an effective algorithm which enumerates all minimal node cuts sets of a network. The proposed algorithm runs in two steps: The first one is used to generate a subset of paths, called necessary minimal paths, instead of all minimal paths. Whereas, the second step stands to build all minimal cutsets from the necessary minimal paths.</p>

Czech analytic agreement and the characteristics of littlepro

AbstractThis study deals with subject predicate agreement in Czech and the structure of a null subject. First, it introduces the concept of Null Subject Languages as it has been used in a generative framework. Then it shows the complex feature content of the Czech subject-predicate agreement morphology, arguing that the data repeatedly signal a division of the agreement features into two clear cut feature sets and two distinct agreement domains: (a) the lower, lexical domain insidevP containing the nominal n[±φ]feature set (Gender and N-Number), and (b) the higher, functional domain on the T head, which contains the functional D[±φ]feature set (Person and D-Number). The study relates the analysis to the present day microparametric concept of a Null Subject Parameter as in, e. g., the studies in Biberauer (2010), accepting the hypothesis of the checking of the subject-predicate agreement with two levels of predicate (separate headsvand T). It proposes that with pronominal subjects, the φ feature values can be re-set with respect to the speech act information located in the Aboutness Topic. Given the several levels of agreement, each of which can be licensed by a zero morpheme, the study proposes thatprois a complex entity consisting of two separate parts, each endowed with a distinct set of φ features.

Gas pipeline failure evaluation method based on a Noisy-OR gate bayesian network

We propose a method based on the Noisy-OR gate Bayesian network to address cases of insufficient sample data. First, a fault tree model of gas pipelines was established. Mapping this model to the Bayesian network (BN), the failure probability was 0.074 according to a traditional BN and fault tree analysis (FTA). By applying the Noisy-OR gate to determine the conditional probability of related nodes, the failure probability of the system was 0.058. Compared with FTA and the BN, this approach could more precisely determine minimum cut sets and diagnose risky factors. The combination of the BN and a Noisy-OR gate is an alternative method for evaluating the reliability of gas pipelines, and this approach can provide a relatively realistic analysis in other evaluation fields because it considers other influencing factors. The findings of this study can aid decision-making and prevent accidents from occurring.

RETRACTED ARTICLE: Regression Neural Network segmentation approach with LIDC-IDRI for lung lesion

Segmenting precisely affected parts of the lungs from the output of CT (Computed Tomography) is critical in making inquiries on lung malignancy and can offer significant data for clinical conclusions. It plays a major and effective role in researches on lung diseases. The crux of the problem is developing automatic detection of lesion and segments them with perfect accuracy. Heterogeneity of lesion part makes segmentation a very difficult task. In TBGA (Toboggan Based Growing Automatic Segmentation Approach), the lack of degree of recognition results in difficulty in the boundary detection process during segmentation. To overcome the drawbacks, a Regression Neural Networks (RNN) Segmentation approach has been proposed in this paper. The degree of recognition is less in tissues which are associated to the neighboring lesion with pixels having same intensity. RNN provides a greater accuracy of recognition of the adjacent lesions with similar intensity when compared to other methods like Skeleton graph cut and Level set method. Segmentation is done based on the degree of recognition. So the RNN method proposed in this paper concentrates mainly on the precise detection of boundary for juxtapleural and juxtavascular lesions. The accuracy of segmenting lung parenchyma is a challenge in lesion segmentation. In RNN segmentation process, the result of parenchyma forms the basis of extracting lesion. RNN is a Learning Algorithm so the complexity of automatic lesion detection is avoided. RNN uses a trained set of data, so the resulting outcome is accurate.