Different Levels Of Confidence Research Articles

Application of Multi-criteria Decision-making Methods for Forensic Analysis of Mechanical Parts in Vehicle Accidents using q-Rung Orthopair Fuzzy Numbers

This study explores the application of a Multi-Criteria Decision-Making (MCDM) approach based on q-rung orthopair fuzzy numbers to identify the origin of mechanical parts found at vehicle accident scenes. The primary objective is to determine the most likely vehicle to which these parts belong by evaluating key criteria such as compatibility, damage level, serial number matching, and color compatibility. Q-rung orthopair fuzzy numbers offer an advanced method to handle the inherent uncertainty and vagueness associated with forensic evaluations, particularly in scenarios where data is incomplete or imprecise. The proposed methodology involves defining the criteria, assigning membership and non-membership degrees using q-rung orthopair fuzzy sets, and applying an aggregation process to effectively rank alternatives. This approach facilitates flexible decision-making by accommodating different levels of confidence and uncertainty, making it particularly suitable for forensic applications where evidence is often ambiguous. The findings demonstrate that integrating q-rung orthopair fuzzy numbers into the MCDM framework significantly enhances the accuracy and reliability of identifying vehicle components involved in accidents. The proposed methodology provides a systematic tool to support forensic investigations, aiding in the determination of liability and contributing to more robust outcomes in mechanical evidence analysis.

Resolving sustainable development conflicts caused by vinyl leakage accidents in the USA: From the perspective of graph model under fuzzy preferences with self-confidence

On February 3, 2023, a railroad accident led to the release and combustion of 115,580 gallons of vinyl chloride monomer in East Palestine, Ohio, USA. The large leakage and long-time combustion of vinyl chloride monomer harmed the stability of local sustainable ecosystems and the health of residents, as the burning produced deadly toxins, triggering dissatisfaction from residents and environmental protection organizations. With the COVID-19 pandemic still unfolding globally, decision makers (DMs) in vinyl chloride leakage accidents must consider the existing environmental health uncertainty, potentially leading to uncertainty in their preference cognitive. Thus, this paper proposes a novel fuzzy preference with a self-confidence structure of the graph model for conflict resolution (GMCR) to resolve the sustainable development conflicts caused by the vinyl chloride leakage accident in Ohio. Fully considering the uncertainty of option choice by DMs and the different levels of confidence in DMs’ preference selection, four different fuzzy stability definitions of self-confidence are defined in GMCR. The analysis results suggest the following: (1) During conflicts, the US Norfolk Southern Corp should assume corporate responsibility by setting up a health monitoring system for residents in Ohio; the company should pay for the medical examinations and related care expenses for residents within the scope of the vinyl chloride leakage accident. (2) The negotiation of all stakeholders in conflicts can promote reconciliation. Finally, the analysis process and results of this study can provide guidance to government departments for properly handling major accidents and appeasing affected residents.

3D scanning a crime scene to enhance juror understanding of Bloodstain Pattern Analysis evidence

There are numerous crime scene investigation applications of 3D scanning that have been previously documented. This paper documents the application of a 3D point cloud in the presentation of Bloodstain Pattern Analysis evidence to mock jurors. 150 mock jurors viewed a presentation of Bloodstain Pattern Analysis evidence from a murder trial in the UK. After viewing the evidence, the participants were tested on their knowledge of the evidence and repeated the test again 2 weeks later; to simulate criminal trial conditions; whereby there is a time lapse between the initial viewing of evidential material and deliberation. This paper found that the mock jurors who additionally viewed a 3D flythrough of a point cloud of the crime scene, better retained knowledge of the evidence over time, reported a greater ability to visualise the crime scene and had higher levels of interest in the evidence. Crucially, the 3D flythrough group did not report different levels of confidence in the accuracy of their memories of the evidence, nor different levels of emotional arousal to the group that viewed the evidence without the 3D presentation. Together, these findings suggest that 3D scanning of crime scenes, and the resultant point cloud’s presentation to jurors, could add further value to the justice system when spatial information, such as Bloodstain Pattern Analysis evidence, is presented.

2004 How confident are we in decision making? The quantitative analysis of ambulance response to older adult fallers: A pilot survey

Abstract Introduction The number one reason for older people to be taken to hospital emergency departments is a fall1. An “Ambulance Improvement Programme Pillar”2 is trying to reduce conveyance to hospital for falls, however it is not understood how the attending clinician’s confidence impacts decision-making. The objectives were to assess recruitment rate and feasibility of online survey delivery, and determine the experiences and confidence of frontline emergency clinicians in attending older adults who have fallen. Method Online cross-sectional survey, undertaken in one English ambulance service in May 2023. Items included participant demographics and 5-point Likert scales of confidence. Data were summarised using descriptive statistics and Chi-square analyses to compare confidence between localities and years’ experience. Results 81 responses were received from across the regional ambulance service’s 16 localities, supporting online survey delivery to be feasible in this population. 76% of respondents were paramedics, and 53% were aged 25-34. 60% of respondents rated being ‘Somewhat confident’ in assessing older adults who have fallen, with responses ranging between ‘Neither confident nor unconfident’ to ‘Completely confident’. No significant difference was found between the locality and confidence levels for assessing this patient population. However, there appeared to be significant variation between confidence levels relating to utilisation of hospital pathways and localities (p-value=.0045). Length of experience in both frontline ambulance and overall healthcare provision was not significantly associated with different levels of confidence. Conclusion Online survey delivery is an effective method in this population. Locality of work had a relationship with confidence in utilising hospital avoidance pathways, however, it did not relate to assessing this population. Confidence levels were not found to be related to the number of years providing care.

Plasma Neurofilament Light Chain predicts neuroimaging alterations and functional decline in frontotemporal dementia

AbstractBackgroundPlasma Neurofilament light chain (pNfL) is a promising biomarker to discriminate Frontotemporal dementia (FTD) from other diagnoses such as Alzheimer’s disease (AD) or psychiatric disorders. Currently, the diagnostic criteria for FTD syndromes are structured hierarchically into “Possible”, “Probable” and “Definite” levels depending on the degree of confidence set by biomarkers. We aim to study the diagnostic and prognostic values of pNfL in the different confidence levels of FTD diagnosis.MethodPatients fulfilling criteria for FTD were classified as “Possible”, “Probable” or “Definite” FTD based on the current diagnostic criteria. pNfL levels were determined with SiMoA, and then compared to Control and AD groups, as well as within the different levels of confidence in the FTD diagnosis.Result187 subjects were included: 37 controls, 79 AD and 71 FTD (11 Possible, 49 Probable and 11 Definite). The FTD group showed higher concentrations of pNfL than the Control (p < 0.001, AUC: 0.817) and the AD groups (p < 0.001, AUC: 0.677) (Figure 1A and 1B).Within the FTD group, pNfL levels differed across the different diagnostic confidence levels (Figure 1C). Subjects with Probable and Definite FTD showed higher levels of pNfL than subjects with Possible FTD (p < 0.001 and p < 0.01 respectively). By contrast, the Possible FTD group did not show differences in pNfL concentrations with the control group. In that sense, the diagnostic value of pNfL varied according to the different grades of diagnostic confidence (Figure 1D), with cases with probable or definite FTD exhibiting an excellent AUC to distinguish from controls (AUC 0.860 and 0.908 respectively), but with no discrimination between possible FTD and controls (AUC 0.583).pNfL presented an excellent performance in the differentiation of structural or functional impairment in the neuroimage (AUC 0.94, and AUC 0.86 respectively) (Figure 2). Finally, higher baseline pNfL levels were associated with worse clinical progression in FTD cases (Figure 3).ConclusionpNfL were higher in FTD patients compared to controls or AD patients. However, we found significant variation across the different confidence levels of FTD diagnosis. Finally, pNfL predicted neuroimage alterations and a worse clinical progression in FTD patients.

Metacognitive judgements in the learning of cellular theory in elementary school students

ABSTRACT Understanding the role of metacognitive judgements in science learning can significantly contribute to the qualification of both teaching and learning processes. We present some of the existing relationships between two important theoretical categories in education: metacognitive judgements and cellular theory learning. The research was conducted with sixth graders from a public school in the city of Pereira, Colombia through a mixed research design. The results show that as the didactic unit was developed, students qualified their explanatory models about the cell and cellular theory. Their arguments were stronger and more coherent, while their metacognitive judgements displayed different levels of confidence, which improved over the course of time.

Transformation products of contaminants of emerging concern in water by UV-based processes

Abstract Contaminants of emerging concern (CECs) and their respective transformation products (TPs) formed following photodegradation pose considerable threats to the environment and our health. The formation of TPs during UV-LED-based degradation of three target pollutants in the EU Watch List of CECs was accessed by LC-MS-Orbitrap, and their reaction pathways were elucidated. The influence of different matrices and treatments of choice on TP formation was investigated. Results showed that matrix changes did not produce different reaction pathways during UV-A photocatalysis, although plots of TP peak areas vs. time were different for each case. A new TP was found for the antidepressant venlafaxine, (1-[2-(dimethylnitroryl)-1-(4-methoxyphenyl)ethyl]cyclohexanol. When comparing UV-A photocatalysis with UV-C photolysis, dissimilar pathways were observed due to the distinct reaction mechanisms of each process, since photocatalysis, unlike photolysis, relies on radical-based reaction routes. Different levels of confidence were obtained for each TP depending on the availability of MS2 data in the literature and of standards for comparison. All the found TPs had similar molecular masses in comparison to their respective parent compounds. Most of the TPs remained in the effluent after 6 hours of photodegradation, which highlights the importance of their control, close-monitoring, and further toxicity assessments.

Police trainees versus laypeople: Identification performance and confidence–accuracy relationship for facial and body lineups

AbstractCourt instructions and public perception endorse that eyewitness evidence provided by police should weight more heavily than laypeople's in court. Evidence is inconsistent. The current experiment provides a nuanced analysis of identification performance of police and laypeople at different levels of confidence. Laypeople and advanced police trainees (N = 192) viewed portrait, profile, and body‐only lineups for central and peripheral targets. Police trainees displayed higher hit and correct rejection rates than laypeople for portrait lineups, and higher correct rejection rates in profile lineups for central targets. Calibration was similar for both groups, although police trainees had an advantage at low target presence base rates. Calibration was best for central targets' portrait and profile lineups. Participants displayed poor calibration and strong overconfidence for body‐only lineups and peripheral target lineups. We conclude that experience and specialization of police might be important when investigating a possible superiority of police who serve as eyewitness.

Bromination of Quorum Sensing Molecules: Vanadium Bromoperoxidase and Cerium Dioxide Nanocrystals via Free Active Bromine Transform Bacterial Communication.

The halogenation of quorum sensing molecules (QSMs) is known to be catalyzed by enzymes such as haloperoxidase (HPO) as well as cerium dioxide nanocrystals (NC), which mimic enzymes. Those enzymes and mimics can influence biological processes such as biofilm formation, where bacteria use QSMs for the "chemical" communication between each other and the coordination of surface colonization. However, not much is known about the degradation behavior of a broad spectrum of QSMs, especially for HPO and its mimics. Therefore, in this study, the degradation of three QSMs with different molecule moieties was elucidated. For this purpose, different batch experiments were carried out with HPOs, NCs and free active bromine (FAB). For N-β-ketocaproyl-homoserine lactone (3-Oxo-C6-AHL), N-cis-tetradec-9Z-enoyl-homoserine lactone (C14:1-AHL) and 2-heptyl-4-quinolone (HHQ) a fast degradation and moiety-specific transformations were observed. The HPO vanadium bromoperoxidase as well as cerium dioxide NCs catalyzed the formation of the same brominated transformation products (TPs). Since the same TPs are formed in batch experiments with FAB it is very likely that FAB is playing a major role in the catalytical reaction mechanism leading to the transformation of QSMs. In this study in total 17 TPs could be identified in different levels of confidence and the catalytic degradation processes for two QS groups (unsaturated AHLs and alkyl quinolones) with cerium dioxide NCs and vanadium bromoperoxidase were expanded.

Probabilistic Decline Curve Analysis: State-of-the-Art Review

The decline curve analysis (DCA) technique is the simplest, fastest, least computationally demanding, and least data-required reservoir forecasting method. Assuming that the decline rate of the initial production data will continue in the future, the estimated ultimate recovery (EUR) can be determined at the end of the well/reservoir lifetime based on the declining mode. Many empirical DCA models have been developed to match different types of reservoirs as the decline rate varies from one well/reservoir to another. In addition to the uncertainties related to each DCA model’s performance, structure, and reliability, any of them can be used to estimate one deterministic value of the EUR, which, therefore, might be misleading with a bias of over- and/or under-estimation. To reduce the uncertainties related to the DCA, the EUR could be assumed to be within a certain range, with different levels of confidence. Probabilistic decline curve analysis (pDCA) is the method used to generate these confidence intervals (CIs), and many pDCA approaches have been introduced to reduce the uncertainties that come with the deterministic DCA. The selected probabilistic type of analysis (i.e., frequentist or Bayesian), the used DCA model(s), the type and the number of wells, the sampling technique of the data or the model’s parameters, and the parameters themselves undergo a probability distribution, and these are the main differences among all of these approaches and the factors that determine how each approach can quantify the uncertainties and mitigate them. In this work, the Bayesian and frequentist approaches are deeply discussed. In addition, the uncertainties of DCA are briefly discussed. Further, the bases of the different probabilistic analyses are explained. After that, 15 pDCA approaches are reviewed and summarized, and the differences among them are stated. The study concludes that Bayesian analysis is generally more effective than frequentist analysis, though with narrower CIs. However, the choice of DCA model and sampling algorithm can also affect the bounds of the CIs and the calculation of the EUR. Moreover, the pDCA approach is recommended for quantifying uncertainties in DCA, with narrower CIs that indicate greater effectiveness. However, the computational time and the number of iterations in sampling are also considered critical factors. That is why various assumptions and modifications have been made in the pDCA approaches, including the assumption of a certain probability distribution for the sampled parameters to improve their reliability of reserve estimation. The motivation behind this research was to present a full state-of-the-art review of the pDCA and the latest developments in this area of research.

Residue-wise local quality estimation for protein models from cryo-EM maps.

An increasing number of protein structures are being determined by cryogenic electron microscopy (cryo-EM). Although the resolution of determined cryo-EM density maps is improving in general, there are still many cases where amino acids of a protein are assigned with different levels of confidence. Here we developed a method that identifies potential misassignment of residues in the map, including residue shifts along an otherwise correct main-chain trace. The score, named DAQ, computes the likelihood that the local density corresponds to different amino acids, atoms, and secondary structures, estimated via deep learning, and assesses the consistency of the amino acid assignment in the protein structure model with that likelihood. When DAQ was applied to different versions of model structures in the Protein Data Bank that were derived from the same density maps, a clear improvement in the DAQ score was observed in the newer versions of the models. DAQ also found potential misassignment errors in a substantial number of deposited protein structure models built into cryo-EM maps.

Analysis of Students' Mathematical Communication Skills In Terms of Self-Confidence

Mathematical communication skills are the ability to convey mathematical ideas or ideas orally or in writing, and to understand and accept other people's ideas or ideas carefully, analytically, critically, and evaluative to sharpen the understanding. The purpose of this study is to analyze students ' mathematical communication skills in terms of self-confidence. The study was conducted in SMP Negeri 3 Soe with the subject of research being VIII grade students as many as 22 students. This study uses the qualitative descriptive method. Data collection techniques in the form of tests, questionnaires, and interviews. The data analysis follows the miles and Huberman model. The results showed that students ' mathematical communication skills are seen from different levels of confidence. Students who have a high level of confidence can meet 4 indicators of mathematical communication skills, namely connecting real objects, images, and diagrams into mathematical ideas; able to present ideas in the form of images; able to use terms, mathematical symbols, and structures to present ideas, describe relationships and model making; able to understand, interpret and evaluate mathematical ideas. Students who have a moderate level of confidence can meet three indicators, namely connecting real objects, images, and diagrams into mathematical ideas; being able to present ideas in the form of images; able to use terms, mathematical symbols, and structures to present ideas, describe relationships and model making. Students with a low level of confidence are only able to meet one indicator, namely in using terms, mathematical symbols, and structures to present ideas, describe relationships, and model making.

The Effect of Using Everyone's Strategy to Become a Teacher for Students' Confidence in Learning Mathematics in Grade 5 Elementary School Students

Based on the interviews and data that the researchers conducted it can be seen that many students have difficulty understanding the mathematics material presented by the teacher, besides that student lack self-confidence in learning mathematics. Therefore this research was conducted aiming to increase students confidence in learning mathematics by using the everyone is a teacher here strategy. This research uses the Pre-Experimental Design (nondesign) research method. With the design of Intact-Group Comparison reseachers. In this study, researchers used a questionnaire post to determine students confidence in learning mathematics using the everyone is a teacher here strategy. The questionnaire used amounted to 12 statements. The sample used was 2 classes, namely class IV-C as a control class with 30 students and class IV-D as an experimental class with 30 students. Data analysis using the independent sample Test t test and Eta Square test. t arithmetic (12.976)>t table (58;0.05) is 2.002, then Ho is rejected and Ha is accepted. So, the two classes have different levels of confidence. In other words, there is an influence in learning strategy everyone is a teacher here on students confidence in learning fourth grade mathematics at Pagerwojo Elementary School. And in the eta square test the researchers conclude this research has a very big effect because it shows 1,000 result, if the dependent strategy shows results less than 0.06 then the research shows there is little effect whereas if the results show 0.06-0.14 then the level of influence is moderate, and if it shows results more than 0.14, it has a big effect. So with this research the Effect of the Everyone is a Teacher Here Strategy on Students Confidence in Learning Math Grade IV at Pagerwojo Elementary School, has great influence.

A flexible method for the initial prediction of tugs escort capability

Preliminary prediction of escort tug capability aims to identify the maximum steering and braking forces the tug could deliver during operations at sea. To this end, the adoption of a steady-state equilibrium approximation ensures attaining a quick and enough accurate results for the initial design stage. Diverse techniques are suitable to resolve the equilibrium, with different simplification levels and related limitations. In this study, a method based on a nonlinear thrust allocation algorithm is improved, including propulsors interactions. Moreover, the addition of the transversal equilibrium modelling of the tug allows evaluating the compliancy with stability and safety Regulations for escort class. The coupling between enhanced equilibrium resolution and a simplified approach to estimate the hydrodynamic forces results in a flexible prediction method for tug escort capability, which is requiring few inputs, without excluding the possibility to use higher fidelity hydrodynamic loads. The calculation framework, implemented with different levels of confidence for hydrodynamic loads, is tested on different tug types, highlighting its flexibility compared to more traditional and widely accepted approaches for the initial design stage.

Experience with the evidence map in oral ozone therapy - importance for integrative and complementary health practices

medical and dental treatment in the form of ozonized water and oxygen / ozone gas mixture and associated with photobiomodulation therapy. The evidence map was based on the 3iE evidence searched in the databases: LILACS, PubMed, EMBASE and Cochrane Library, seeking systematic and narrative reviews, analyzed in an excel characterization spreadsheet. Three independent literature reviewers screened the systematic review search output blinded at the software Rayyan. The full-text publications were screened against the specified inclusion criteria by thre independent reviewers; disagreements were resolved through discussion. Forty-two studies were found, 16 of which were systematic reviews and 26 narrative reviews, published between 2006 and 2021, with different levels of confidence. The intervention that most appeared in the literature was oral ozone therapy as a bacterial colony reduction and decontamination agent, with emphasis on topical oxygen-ozone gas mixtures, topical ozonized water. Oral ozone therapy can bring benefits to clinical practice and patients. The evidence map provides an easy visualization of valuable information for patients, health practitioners and managers, in order to promote evidence-based complementary therapies.

Structure preservation adversarial network for visual domain adaptation

Domain adaptation has attracted attention by leveraging knowledge from well-labeled source data to facilitate unlabeled target learning tasks. Numerous research efforts have been devoted to extracting effective features by incorporating the pseudolabels of target data. However, the transferable knowledge reflected by intradomain structure, interdomain correlation and label supervision has scarcely been considered simultaneously. In this paper, we propose a novel structure preservation adversarial network with target reweighting (SPTR) for unsupervised domain adaptation, in which local structure consistencies and category-level semantic alignment are simultaneously considered in the adversarial learning framework. Based on the labeled and pseudolabeled samples, we attempt to align both global and category-level domain statistics from different domains and simultaneously enforce structural consistency from feature space to label space in the source and target domains. Furthermore, to suppress the influence of falsely labeled target samples, a novel and generalized sample reweighting strategy is developed to assign target samples with different levels of confidence, which fully explores the knowledge of the target distribution to benefit the semantic transfer process. The experimental results in three transfer learning scenarios demonstrate the superiority of our proposed method over other state-of-the-art domain adaptation algorithms.

StrongestPath: a Cytoscape application for protein\u2013protein interaction analysis

BackgroundStrongestPath is a Cytoscape 3 application that enables the analysis of interactions between two proteins or groups of proteins in a collection of protein–protein interaction (PPI) network or signaling network databases. When there are different levels of confidence over the interactions, the application is able to process them and identify the cascade of interactions with the highest total confidence score. Given a set of proteins, StrongestPath can extract a set of possible interactions between the input proteins, and expand the network by adding new proteins that have the most interactions with highest total confidence to the current network of proteins. The application can also identify any activating or inhibitory regulatory paths between two distinct sets of transcription factors and target genes. This application can be used on the built-in human and mouse PPI or signaling databases, or any user-provided database for some organism.ResultsOur results on 12 signaling pathways from the NetPath database demonstrate that the application can be used for indicating proteins which may play significant roles in a pathway by finding the strongest path(s) in the PPI or signaling network.ConclusionEasy access to multiple public large databases, generating output in a short time, addressing some key challenges in one platform, and providing a user-friendly graphical interface make StrongestPath an extremely useful application.

Coastal residents’ attitudes toward offshore oil and gas drilling in China

This paper reports findings from research which surveyed coastal residents’ attitudes toward offshore oil and gas drilling in China. An online survey was carried out in 22 coastal Chinese cities using a questionnaire aimed at collecting demographic information and measuring offshore drilling support, risk, and trust. The data reveal that coastal residents hold a low support, high risk-perception, and moderate trust over offshore oil and gas drilling. NIMBY (Not-In-My-Back-Yard) mentality shows up in citizens’ support towards offshore drilling. Coastal residents hold different levels of confidence in offshore drilling claims, based on source and contents. People tend to trust scientific statements more from environmental groups than from the oil industry and have more trust in information according to which offshore drilling is riskier instead of safer than previously anticipated. In addition, demographic differences were captured on support for and trust in offshore oil and gas drilling. Gender, occupation, religious attitude, and dietary habits are uncovered to be predictors of offshore drilling support.

Low-Dose vs Standard-Dose Alteplase in Acute Lacunar Ischemic Stroke: The ENCHANTED Trial.

In the article “Low-Dose vs Standard-Dose Alteplase in Acute Lacunar Ischemic Stroke: The ENCHANTED Trial” by Zhou et al.,1 the first sentence under Methods in the Abstract should read “In a cohort of 3,297 ENCHANTED participants, we identified those with lacunar or non-lacunar AIS with different levels of confidence (definite/probable/possible) according to prespecified definitions based on clinical and adjudicated imaging findings.” The publisher regrets the error.

Whole Genome Interpretation for a Family of Five.

Although best practices have emerged on how to analyse and interpret personal genomes, the utility of whole genome screening remains underdeveloped. A large amount of information can be gathered from various types of analyses via whole genome sequencing including pathogenicity screening, genetic risk scoring, fitness, nutrition, and pharmacogenomic analysis. We recognize different levels of confidence when assessing the validity of genetic markers and apply rigorous standards for evaluation of phenotype associations. We illustrate the application of this approach on a family of five. By applying analyses of whole genomes from different methodological perspectives, we are able to build a more comprehensive picture to assist decision making in preventative healthcare and well-being management. Our interpretation and reporting outputs provide input for a clinician to develop a healthcare plan for the individual, based on genetic and other healthcare data.