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The Pama Croaker, Otolithoides pama, is an economically important fish species in Bangladesh. Intra-family similarities in morphology and typical barcode sequences of cox1 create ambiguities in its identification. Therefore, morphology and the complete mitochondrial genome of O. pama, and comparative mitogenomics within the family Sciaenidae have been studied. Extracted genomic DNA was subjected to Illumina-based short read sequencing for De-Novo mitogenome assembly. The complete mitogenome of O. pama (Accession: OQ784575.1) was 16,513 bp, with strong AC biasness and strand asymmetry. Relative synonymous codon usage (RSCU) among 13 protein-coding genes (PCGs) of O. pama was also analyzed. The studied mitogenomes including O. pama exhibited consistent sizes and gene orders, except for the genus Johnius which possessed notably longer mitogenomes with unique gene rearrangements. Different genetic distance metrics across 30 species of Sciaenidae family demonstrated 12S rRNA and the control region (CR) as the most conserved and variable regions, respectively, while most of the PCGs undergone a purifying selection. Different phylogenetic trees were congruent with one another, where O. pama was distinctly placed. This study would contribute to distinguishing closely related fish species of Sciaenidae family and can be instrumental in conserving the genetic diversity of O. pama. [ABSTRACT FROM AUTHOR]

Traditional methods for evaluating decision-making provide valuable insights yet may fall short in capturing the complexity of this cognitive capacity, often providing insufficient for the multifaceted nature of decisions. The Kalliste Decision Task (KDT) is introduced as a comprehensive, ecologically valid tool aimed at bridging this gap, offering a holistic perspective on decision-making. In our study, 81 participants completed KDT alongside established tasks and questionnaires, including the Mixed Gamble Task (MGT), Iowa Gambling Task (IGT), and Stimulating & Instrumental Risk Questionnaire (S&IRQ). They also completed the User Satisfaction Evaluation Questionnaire (USEQ). The results showed excellent usability, with high USEQ scores, highlighting the user-friendliness of KDT. Importantly, KDT outcomes showed significant correlations with classical decision-making variables, shedding light on participants' risk attitudes (S&IRQ), rule-based decision-making (MGT), and performance in ambiguous contexts (IGT). Moreover, hierarchical clustering analysis of KDT scores categorized participants into three distinct profiles, revealing significant differences between them on classical measures. The findings highlight KDT as a valuable tool for assessing decision-making, addressing limitations of traditional methods, and offering a comprehensive, ecologically valid approach that aligns with the complexity and heterogeneity of real-world decision-making, advancing research and providing insights for understanding and assessing decision-making across multiple domains. [ABSTRACT FROM AUTHOR]

In the alternative uses task (AUT), a well-established creativity assessment, participants propose alternative uses for common items (e.g., a brick) within a 2–3 min timeframe. While idea evaluation is likely involved, the emphasis is strongly on idea generation. Here, we test the value of presenting a word overlapping an image compared to a word only prompt, and we introduce a cyclic adaptation of the AUT explicitly calling on participants to choose their best idea. In Experiment 1, as compared to word only, word + image prompts increased idea fluency but reduced idea originality and variability within a group of native Polish speakers. Thus, word + image prompts improve AUT baselining. In Experiment 2, different participants produced as many ideas as possible within two minutes (List) or their single best idea at the end of each of three 30 s ideation cycles (Cycle). Although originality did not differ between List and Cycle overall, the first three ideas in List were rated as less creative than the ideas in Cycle. Overall, we conclude that using disambiguating images reduces spurious interindividual variability in the AUT while introducing idea evaluation in the task allows us to assess creativity beyond idea generation. [ABSTRACT FROM AUTHOR]

In this study, we have presented a novel probabilistic model called the neutrosophic Burr-III distribution, designed for applications in neutrosophic surface analysis. Neutrosophic analysis allows for the incorporation of vague and imprecise information, reflecting the reality that many real-world problems involve ambiguous data. This ability to handle vagueness can lead to more robust and realistic models especially in situation where classical models fall short. We have also explored the neutrosophic Burr-III distribution in order to deal with the ambiguity and vagueness in the data where the classical Burr-III distribution falls short. This distribution offers valuable insights into various reliability properties, moment expressions, order statistics, and entropy measures, making it a versatile tool for analyzing complex data. To assess the practical relevance of our proposed distribution, we applied it to real-world data sets and compared its performance against the classical Burr-III distribution. The findings revealed that the neutrosophic Burr-III distribution outperformed than the classical Burr-III distribution in capturing the underlying data characteristics, highlighting its potential as a superior modeling toolin various fields. [ABSTRACT FROM AUTHOR]

The objective of this research is to enhance the precision and efficiency of design concept assessments during the initial stages of new product creation. Design concept evaluation, which occurs at the end of the conceptual design phase, is a critical step in product development. The outcome of this evaluation significantly impacts the product's eventual success, as flawed design concepts are difficult to remedy in later stages. However, the evaluation of new product concepts is a procedure that encompasses elements of subjectivity and ambiguity. In order to deal with the problem, a novel decision-making method for choosing more logical new product concepts is introduced. Basically, the evaluation process is outlined in three main phases: the construction of evaluation index system for design concept alternatives, the calculation of weights for evaluation criteria and decision-makers, the selection of the best design concept alternatives. These stages are composed of a hybrid method based on kano model, multiplicative analytic hierarchy process (AHP) method, the entropy of IVPFS and improved grey relational projection (GRP) under interval-valued picture fuzzy set (IVPFS). The novel approach integrates the strength of interval-valued picture fuzzy number in handling vagueness, the advantage of multiplicative AHP and the merit of improved GRP method in modelling multi-criteria decision-making. In final, the effectiveness of the proposed model is validated through comparisons with other models. The potential applications of this study include but are not limited to product development, industrial design, and innovation management, providing decision-makers with a more accurate and comprehensive design concept evaluation tool. [ABSTRACT FROM AUTHOR]

Individual traits and reactions to ambiguity differ and are conceptualized in terms of an individual's attitudes toward ambiguity or ambiguity tolerance. The development of natural language processing technology has made it possible to measure mental states and reactions through open-ended questions, rather than predefined numerical rating scales, which have traditionally been the dominant method in psychological research. This study presented three ambiguity-related situations and responses collected online from 591 participants in an open-ended format. After the analysis with bidirectional encoder representations from transformers, correlations were calculated using scores from the numerical evaluation by conventional questionnaire, and a significant moderate positive correlation was found. Therefore, this study found that attitudes toward ambiguity can be measured using an open-ended response method of reporting everyday life states. It is a novel methodology that can be expanded to other scales in psychology and can potentially be used in educational and clinical situations where participants can be asked to respond with minimal burden. [ABSTRACT FROM AUTHOR]

English speakers use probabilistic phrases such as likely to communicate information about the probability or likelihood of events. Communication is successful to the extent that the listener grasps what the speaker means to convey and, if communication is successful, individuals can potentially coordinate their actions based on shared knowledge about uncertainty. We first assessed human ability to estimate the probability and the ambiguity (imprecision) of twenty-three probabilistic phrases in a coordination game in two different contexts, investment advice and medical advice. We then had GPT-4 (OpenAI), a Large Language Model, complete the same tasks as the human participants. We found that GPT-4’s estimates of probability both in the Investment and Medical Contexts were as close or closer to that of the human participants as the human participants’ estimates were to one another. However, further analyses of residuals disclosed small but significant differences between human and GPT-4 performance. Human probability estimates were compressed relative to those of GPT-4. Estimates of probability for both the human participants and GPT-4 were little affected by context. We propose that evaluation methods based on coordination games provide a systematic way to assess what GPT-4 and similar programs can and cannot do. [ABSTRACT FROM AUTHOR]

Grid theory is rather commonly-used through out the research of integer ambiguity. In order to promote the efficiency of computation, it is of great necessity to reduce the correlations of the grid basis through the reduction. The classical reduction algorithm is known as the LLL (Lenstra–Lenstra–Lovász) algorithm. So as to further enhance the reduction effect, the deep-insertion LLL algorithm can be utilized as an alternative to the basis vector exchange algorithm. In practice, the deep-insertion LLL algorithm can achieve a better reduction effect, but it requires more time for reduction. The PotLLL algorithm replaces the basis vector exchange condition of deep-insertion LLL with an improving in the basis quality, and it can run in polynomial time, but with certain limitations. Therefore, this article proposes a global deep-insertion PLLL algorithm (GS-PLLL) to address the issue of integer ambiguity. GS-PLLL adopts a global strategy for deep-insertion processing, and introduces a rotation sorting method for preconditioning the grid basis. Comparative evaluations were conducted using simulation experiments and real-world measurements on the LLL, DeepLLL, PotLLL, and GS-PLLL algorithms. The experimental results indicate that the GS-PLLL algorithm achieves a better reduction effect than the PotLLL algorithm while improving the efficiency of reduction. [ABSTRACT FROM AUTHOR]

The mismatch between supply and demand in the tourism and hospitality labor markets becomes increasingly serious in the past few years. The main reason for such a problem is that tourism and hospitality students are equipped with academic knowledge but lack VUCA skills. VUCA are the acronyms of volatility, uncertainty, complexity, and ambiguity. However, little research has explored the antecedent mechanism of tourism and hospitality students' VUCA skills. Hence, the purpose of the present study is to clarify the leading factors that would enhance tourism and hospitality students' perceived VUCA skills. This study collected data by distributing questionnaires to senior students majoring in tourism and hospitality management (THM) from five universities in China. The results show: First, students' perceived the effectiveness of outcome-based education (PEOBE) has a significant effect on their perceived VUCA skills and self-concept including cognitive self-concept (CSC) and affective self-concept (ASC). Second, THM students' CSC is positively related to their perceived VUCA skills. Finally, the relevance of ASC and students' perceived VUCA skills was not significant. The present study further justified that PEOBE is the prepositive variable of THM students' cognitive self-concept, supporting the linkage effect of "PEOBE → CSC → self-efficiency → perceived VUCA skills". From the practical implications, this study focuses on OBE as the entry point to explore the antecedent mechanism of THM students' perceived VUCA skills, supplying a basic formulation of educational reform policies for the administrative department of higher education around the world. [ABSTRACT FROM AUTHOR]

Because the traditional Cholesky decomposition algorithm still has some problems such as computational complexity and scattered structure among matrices when solving the GNSS ambiguity, it is the key problem to further improve the computational efficiency of the least squares ambiguity reduction correlation process in the carrier phase integer ambiguity solution. But the traditional matrix decomposition calculation is more complex and time-consuming, to improve the efficiency of the matrix decomposition, in this paper, the decomposition process of traditional matrix elements is divided into two steps: multiplication update and column reduction of square root calculation. The column reduction step is used to perform square root calculation and column division calculation, while the update step is used for the update task of multiplication. Based on the above ideas, the existing Cholesky decomposition algorithm is improved, and a column oriented Cholesky (C-Cholesky) algorithm is proposed to further improve the efficiency of matrix decomposition, so as to shorten the calculation time of integer ambiguity reduction correlation. The results show that this method is effective and superior, and can improve the data processing efficiency by about 12.34% on average without changing the integer ambiguity accuracy of the traditional Cholesky algorithm. [ABSTRACT FROM AUTHOR]

Data classification, the process of analyzing data and organizing it into categories or clusters, is a fundamental computing task of natural and artificial information processing systems. Both supervised classification and unsupervised clustering work best when the input vectors are distributed over the data space in a highly non-uniform way. These tasks become however challenging in weakly structured data sets, where a significant fraction of data points is located in between the regions of high point density. We derive the theoretical limit for classification accuracy that arises from this overlap of data categories. By using a surrogate data generation model with adjustable statistical properties, we show that sufficiently powerful classifiers based on completely different principles, such as perceptrons and Bayesian models, all perform at this universal accuracy limit under ideal training conditions. Remarkably, the accuracy limit is not affected by certain non-linear transformations of the data, even if these transformations are non-reversible and drastically reduce the information content of the input data. We further compare the data embeddings that emerge by supervised and unsupervised training, using the MNIST data set and human EEG recordings during sleep. We find for MNIST that categories are significantly separated not only after supervised training with back-propagation, but also after unsupervised dimensionality reduction. A qualitatively similar cluster enhancement by unsupervised compression is observed for the EEG sleep data, but with a very small overall degree of cluster separation. We conclude that the handwritten letters in MNIST can be considered as 'natural kinds', whereas EEG sleep recordings are a relatively weakly structured data set, so that unsupervised clustering will not necessarily re-cover the human-defined sleep stages. [ABSTRACT FROM AUTHOR]

Chronic stress is associated with profound behavioral and physiological alterations, including intolerance to uncertainty and reduced resting-state heart-rate-variability (HRV). Critically, uncertainty may arise in situations with known probabilities (risk) or unknown probabilities (ambiguity). Whether associations between chronic stress and decision-making under uncertainty are dependent on the specific type of uncertain decisions, and whether physiological alterations play a role in these putative associations is not yet clear. Here, ninety-two healthy adults that exhibit various levels of perceived chronic stress underwent resting-state HRV recording before completing a behavioral task that involves decision-making under either risk or ambiguity. Computational modelling quantified participants' behavioral attitudes of approach and avoidance separately for risk and ambiguity. Results indicate, as expected, that perceived chronic stress is positively associated with intolerance to uncertainty and negatively associated with resting-state HRV. Contrary to expectations, behavioral attitudes towards risk and ambiguity were not directly associated with perceived chronic stress, yet HRV fully mediated the association between chronic stress and ambiguity avoidance. Taken together and given the direction of the associations, elevated HRV despite chronic stress may foster adaptive behavior in the form of avoiding ambiguous situations, and hence contribute to reduced exposure to uncertainty and to lower levels of allostatic load. [ABSTRACT FROM AUTHOR]

Chronic stress is associated with profound behavioral and physiological alterations, including intolerance to uncertainty and reduced resting-state heart-rate-variability (HRV). Critically, uncertainty may arise in situations with known probabilities (risk) or unknown probabilities (ambiguity). Whether associations between chronic stress and decision-making under uncertainty are dependent on the specific type of uncertain decisions, and whether physiological alterations play a role in these putative associations is not yet clear. Here, ninety-two healthy adults that exhibit various levels of perceived chronic stress underwent resting-state HRV recording before completing a behavioral task that involves decision-making under either risk or ambiguity. Computational modelling quantified participants' behavioral attitudes of approach and avoidance separately for risk and ambiguity. Results indicate, as expected, that perceived chronic stress is positively associated with intolerance to uncertainty and negatively associated with resting-state HRV. Contrary to expectations, behavioral attitudes towards risk and ambiguity were not directly associated with perceived chronic stress, yet HRV fully mediated the association between chronic stress and ambiguity avoidance. Taken together and given the direction of the associations, elevated HRV despite chronic stress may foster adaptive behavior in the form of avoiding ambiguous situations, and hence contribute to reduced exposure to uncertainty and to lower levels of allostatic load. [ABSTRACT FROM AUTHOR]

Failure mode and effects analysis (FMEA) is an effective model that identifies the potential risk in the management process. In FMEA, the priority of the failure mode is determined by the risk priority number. There is enormous uncertainty and ambiguity in the traditional FMEA because of the divergence between expert assessments. To address the uncertainty of expert assessments, this work proposes an improved method based on the belief divergence measure. This method uses the belief divergence measure to calculate the average divergence of expert assessments, which is regarded as the reciprocal of the average support of assessments. Then convert the relative support among different experts into the relative weight of the experts. In this way, we will obtain a result with higher reliability. Finally, two practical cases are used to verify the feasibility and effectiveness of this method. The method can be used effectively in practical applications. [ABSTRACT FROM AUTHOR]

Brain systems dealing with multiple meanings of ambiguous stimuli are relatively well studied, while the processing of non-selected meanings is less investigated in the neurophysiological literature and provokes controversy between existing theories. It is debated whether these meanings are actively suppressed and, if yes, whether suppression characterizes any task that involves alternative solutions or only those tasks that emphasize semantic processing or the existence of alternatives. The current functional MRI event-related study used a modified version of the word fragment completion task to reveal brain mechanisms involved in implicit processing of the non-selected solutions of ambiguous fragments. The stimuli were pairs of fragmented adjectives and nouns. Noun fragments could have one or two solutions (resulting in two words with unrelated meanings). Adjective fragments had one solution and created contexts strongly suggesting one solution for ambiguous noun fragments. All fragmented nouns were presented twice during the experiment (with two different adjectives). We revealed that ambiguity resolution was associated with a reduced BOLD signal within several regions related to language processing, including the anterior hippocampi and amygdala and posterior lateral temporal cortex. Obtained findings were interpreted as resulting from brain activity inhibition, which underlies a hypothesized mechanism of suppression of non-selected solutions. [ABSTRACT FROM AUTHOR]

Traditional Chinese Medicine (TCM) treatment has been commonly used to treat Chronic Hepatitis B (CHB) in Asian countries based on TCM syndrome diagnosis, also called 'ZHENG'. The syndrome is identified through the four-diagnostic methods, with certain degree of subjectivity and ambiguity from individual doctors. Normally those CHB patients also receive series of parameters from modern clinical examination, while they are routinely believed to be unrelated with the TCM syndrome diagnosis. In this study, we investigated whether these biomedical indexes in modern medicine could be beneficial to TCM syndrome diagnostics in an integrative way. Based on 634 patient samples from health controls and three subtypes of CHB syndromes, a two-view based hierarchical classification model was tested for TCM syndromes prediction based on totally 222 parameters integrated from both TCM practice and modern clinical tests. The results indicated that the performance of syndrome classification based on a proper integration of TCM and modern clinical indexes was significantly higher than those based on one view of parameters only. Furthermore, those indexes correlated with CHB syndrome diagnosis were successfully identified for CM indexes and biochemical indexes respectively, where potential associations between them were hinted to the MAPK signaling pathway. [ABSTRACT FROM AUTHOR]