Set Of Criteria Research Articles

MULTI-PARAMETER MUELLER-MATRIX TOMOGRAPHY OF HISTOLOGICAL SAMPLES OF BIOLOGICAL TISSUES AS AN ACCURATE AND EFFECTIVE METHOD FOR DETERMINING THE DEGREE OF BLOOD LOSS

Establishing the volume of blood loss is extremely important in the context of forensic practice, as it can indicate various circumstances of death and is important in solving criminal cases. Consideration of modern methods of determining this parameter in the article is relevant and aims to reveal new opportunities and perspectives in this field of forensic medical examination.
 Aim of the work. To develop a set of new forensic criteria for accurate determination of the volume of blood loss using the method of multichannel polarization Muller-matrix tomography of histological sections of parenchymal organs and human blood samples.
 Materials and methods. Samples of parenchymal organs and human blood were collected from 76 corpses of both sexes with varying degrees of blood loss from 0 mm3 to 2500 mm3. The research was carried out using the method of multichannel polarization Muller-matrix linear dichroism tomography of biological tissue samples.
 Results. For all studied biological samples, a decrease in the level of circular birefringence (CB) of formed blood elements against the background of a gradual necrotic decrease in distributions of linear birefringence (LB) of the optical anisotropy of parenchymal tissues and blood films was established for the process of blood loss. The range of sensitivity of the method of differential Mueller-matrix tomography with algorithmic reproduction of linear dichroism maps to changes in blood loss volume of the deceased, which is (0±2000) mm3, is determined.
 Conclusions. The accuracy of the method of differential Mueller matrix mapping with algorithmic reproduction of linear dichroism maps of biological preparations was determined, which is 86-92 % in the range of the level of blood loss ΔV = (0±2000) mm3.

Comprehensive assessment of technical condition of vehicles during operation based on Harrington’s desirability function

The object of research is the process of changing the technical condition of vehicles during their operation. The study solved the problem of comprehensive evaluation of change in the technical condition based on Harrington’s desirability function. The essence of the results is as follows. A scale of desirability was built and a set of criteria for assessing the technical condition of vehicles was clarified. A general desirability index is proposed as a convolution of partial Harrington desirability functions. When solving the investigated problem, the characteristics and properties of the partial and generalized Harrington’s desirability function and their graphical representation were taken into account. Using an example of the technical condition of the chassis and braking system of vehicles, a set of controlled parameters was formed. Based on the values of the controlled parameters, the regression equation of the partial Harrington desirability functions was obtained. The value of the weighting coefficients of each of the criteria was determined and the generalized desirability function was calculated. As a result of the study, it was established that if the generalized criterion of desirability is D<0.37, then individual nodes, systems, and units of the vehicle are in a pre-accident condition, if 0.37£D£0.63 – in a satisfactory condition, and if D>0.63 – in a good condition and cannot be the cause of a traffic accident. An applied aspect of the results is the implementation of the technique of comprehensive assessment of the technical condition of the vehicle. This causes an increase in the productivity of the expert (specialist), will shorten the period of the auto technical examination, and improve its quality. The results could be used by insurance companies and investigators, investigators and judges when considering traffic accidents

Justification of innovative technology for variety and phytocleaning in breeding and seed plantings of potatoes and vegetable crops

The purpose of the research is to substantiate theoretically the process of variety and phytocleaning in breeding and seed plantings of potatoes and vegetable crops using machine vision technologies and robotic elements. The article analyzes modern non-destructive methods for detecting diseases of biological objects; technological processes and machines for removing the fruits of vegetable crops from plants in a digital agricultural production system with elements of robotization in the operations of caring for plants and collecting marketable products. The relevance of developing innovative technology and technical means for removing infected potato and vegetable plants in breeding and seed production has been established. To carry out health-improving techniques for the production of vegetable and potato seeds, an innovative technology and machine have been developed for removing infected potato and vegetable crop plants in breeding and seed-growing plantings, providing movement across the field using machine vision technologies with the identification of an infected plant or a plant that does not correspond to the varietal characteristics with its subsequent removal. In the process of the research (2021-2022), a morphological matrix for selecting technical means of using functioning elements for implementing innovative technology for varietal and phytocleaning of vegetable crops and potatoes, as well as the theoretical foundations of innovative technology for removing contaminated biological objects, were developed. An indicator of the effectiveness of the implementation of innovative phytotype cleaning technology has been identified, taking into account the parameters of economic and agrotechnical indicators, as well as metal intensity, energy intensity, environmental friendliness and reliability. Analytical studies of machine technology and technical means for removing infected vegetable and potato plants are presented. A substantiation of the innovative technology for varietal and phytocleaning of vegetable crops and potatoes has been carried out, in terms of the exclusion of an unmanned aerial vehicle in the technology for detecting infected potato plants with a qualitative assessment of the feasibility of choosing technical means when using the functioning elements of the implementation of the developed technology according to the criteria of economic and agrotechnical assessment, as well as metal intensity, energy intensity and reliability . An assessment of the feasibility of choosing technical means for the functioning of elements of innovative technology showed that, according to a set of criteria, the process of varietal and phytocleaning of vegetable crops and potatoes is advisable to carry out without the use of an unmanned aerial vehicle, using an optical system for identifying infected plants in the design of the machine.

Traffic management approaches using machine learning and deep learning techniques: A survey

Traffic management is improved in cutting-edge smart cities using technologies such as machine learning and deep learning to streamline daily tasks and boost productivity. However, traffic management still suffers from challenging issues such as poor traffic congestion prediction, lack of traffic flow management, public transportation optimization, and emergency management. In this article, we provide a thorough understanding of the benefits, drawbacks, and practical implications of leveraging machine learning and deep learning in Traffic Management Systems (TMSs) by methodically reviewing and critically analysing various traffic management techniques. We also present a generic traffic management architecture that uses a set of assessment criteria to evaluate 20 recently proposed research prototypes (i.e., published since 2019). Finally, we highlight the ongoing challenges and prospective trajectories within the rapidly evolving domain of traffic management, underscoring the need to address emerging issues and directions in its dynamic development. This survey article offers insights that might help in efficiently tackling the issues posed by traffic management while maximizing the potential of machine learning and deep learning techniques. This survey can be a significant resource for researchers, policymakers, and practitioners.

Prioritizing crisis management approaches in the airline industry. Evidence from Greece

The global airline industry has faced a considerable downturn, because of the recent COVID-19 pandemic crisis. Numerous measures had to be taken from governments and the airline industry itself in order to survive the pandemic crisis. The Greek airline industry is the main case of this study. The main goal of this study is to prioritize the appropriateness of crisis management approaches in the domestic airline market. To achieve that, Fuzzy MCDM (Multi-Criteria Decision Making) is employed (consequently a set of criteria and their weighting). The criteria are extracted using the thematic analysis and synthesis method gathering data from the international literature and news. The MCDM analysis is implemented in a fuzzy setting due to the inherent uncertainty in the airline market. The results of this study demonstrate that the actions better characterizing the crisis operations of the domestic airline companies fall under the knowledge-based management approach.

Fostering student agency and motivation: co-creation of a rubric for self-evaluation in an ungraded course

No one enjoys grading, neither instructors nor students. The idea is that grades provide the required incentive to learn and act as an “objective” form of evaluation. This view is especially prevalent in STEM, where practitioners pride themselves in quantitative and objective measurements. However, the science of learning tells us that grades and ranking increase competition and stress, pushing learners to engage in tasks regardless of their effectiveness. Grades have been shown to suppress interest in learning, incentivize engagement in easier tasks, and produce shallower thinking. If wanting to learn is something students and faculty can agree on, how do we get there without grading? From psychology research, we know that feedback, separated from grades, along with opportunities to reattempt work without negative consequence, are powerful drivers of the intrinsic motivation to learn. In fact, feedback loops—trying something new, getting feedback, and making changes based on feedback - are a known developmental pathway to authentic learning. In this article, I describe an experiment with a form of ungrading that involves students in the co-creation of self-assessment criteria. The goal is to create learning feedback loops, incentivize learning for learning’s sake, and give students some agency in the process of evaluation. This was conducted in an upper division Immunology course at a small liberal arts college. This paper outlines an iterative and dialogical process between students and instructional staff to craft a holistic set of criteria for the evaluation of learning. These criteria became the foundation for regular one-on-one conversations with students and a means to track progress over the semester. End-of-semester student feedback was overwhelmingly positive, citing increased motivation to learn, lower levels of anxiety, a less competitive environment, and growth as a learner. Among the few disadvantages cited were anxieties from grade ambiguity, fears about the process, and extra time, especially for the instructor. This paper highlights the ways in which this system aligns with psychosocial theories of learning, fostering an intrinsic motivation to learn utilizing principles of critical pedagogy and students as partners. It concludes with lessons learned from both the student and instructor viewpoint.

Listeners' convergence towards an artificial agent in a joint phoneme categorization task

This study focuses on inter-individual convergence effects in the perception and categorization of speech sounds. We ask to what extent two listeners can come to establish a shared set of categorization criteria in a phoneme identification task that they accomplish together. Several hypotheses are laid out in the framework of a Bayesian model of speech perception that we have developed to account for how two listeners may each infer the parameters that govern their partner’s responses. In our experimental paradigm, participants were asked to perform a joint phoneme identification task with a partner that, unbeknownst to them, was an artificial agent, whose responses we manipulated along two dimensions, the location of the categorical boundary and the slope of the identification function. Convergence was found to arise for bias but not for slope. Numerical simulations suggested that lack of convergence in slope may stem from the listeners’ prior level of confidence in the variance in VOT for the two phonemic categories. This study sheds new light on perceptual convergence between listeners in the categorization of speech sounds, a phenomenon that has received little attention so far in spite of its central importance for speech communication.

A Systematic Literature Review of the Significance of the School of Living Tradition in the Preservation of Cultural Heritage of the Indigenous Peoples

This systematic literature review investigates the critical role of the School of Living Traditions (SLT) and its educational approaches in preserving the cultural heritage of Indigenous Peoples (IP) in the Philippines. A set of pre-defined inclusion-exclusion criteria led to the selection of six pertinent papers, which were comprehensively analyzed and synthesized. The examination of these articles revealed recurring themes, allowing for the development of thematic constructs to address the study's objectives. The findings underscore the pivotal role of SLTs in safeguarding the profound traditions of Indigenous Peoples, thereby ensuring the transmission of cultural legacies to younger generations and empowering IP communities. Notably, the significance of SLTs lies in their ability to preserve the authentic essence of cultural practices, contributing to the empowerment of Indigenous communities. In the transmission of this indigenous knowledge, systems, and practices, pedagogical approaches within SLTs are centered on culture-based education and experiential learning. These approaches aim to facilitate meaningful learning experiences that enable individuals to derive personal significance from their acquired knowledge and apply it in real-world contexts. Consequently, this research sheds light on the instrumental role of SLTs in fostering cultural preservation and empowerment within Indigenous communities through tailored educational methodologies.

Set up a supply chain observatory through the comparison of multi-criteria parsimonious methods

PurposeThis study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their positioning in terms of SC performance.Design/methodology/approachA case study is used to demonstrate the set-up of the observatory. Twelve experts on automatic equipment for the wrapping and packaging industry were asked to select a set of performance criteria taken from the literature and evaluate their importance for the chosen industry using multi-criteria decision-making (MCDM) techniques. To handle the high number of criteria without requiring a high amount of time-consuming effort from decision-makers (DMs), five subjective, parsimonious methods for criteria weighting are applied and compared.FindingsA benchmarking methodology is presented and discussed, aimed at DMs in the considered industry. Ten companies were ranked with regard to SC performance. The ranking solution of the companies was on average robust since the general structure of the ranking was very similar for all five weighting methodologies, though simplified-analytic hierarchy process (AHP) was the method with the greatest ability to discriminate between the criteria of importance and was considered faster to carry out and more quickly understood by the decision-makers.Originality/valueDeveloping an SC observatory usually requires managing a large number of alternatives and criteria. The developed methodology uses parsimonious weighting methods, providing DMs with an easy-to-use and time-saving tool. A future research step will be to complete the methodology by defining the minimum variation required for one or more criteria to reach a specific position in the ranking through the implementation of a post-fact analysis.

Absolute Illiteracy in European Union Policies. Exploring the Intersections of Gender, Migration and Education

In the context of a study focused on the absolute illiteracy of migrant women in Europe, this article assesses the extent to which European Union policy instruments on gender, migration and education incorporate an intersectional perspective. The analysis was based in the content analysis of a selected group of EU policy documents and included i) the close and iterative reading and thematic codification of the texts; ii) the word frequency counting of relevant terms; and iii) the assessment of intersectionality through a set of quality criteria. Apart from revealing the invisibility of absolute illiteracy as a policy problem, results confirm previous evidence showing that the presence of intersectional approaches in EU public policy is still marginal. Some attempts to address the intersectionality of gender, migration or education inequalities have been identified in the selected documents, but a comprehensive policy framework to understand and address those inequalities is still lacking. The article adds up to the existing scholarship claiming for more inclusive policies in contemporary European societies.

Towards a practical threat assessment methodology for crop landraces.

Crop landraces (LR), the traditional varieties of crops that have been maintained for millennia by repeated cycles of planting, harvesting, and selection, are genetically diverse compared to more modern varieties and provide one of the key components for crop improvement due to the ease of trait transfer within the crop species. However, LR diversity is increasingly threatened with genetic erosion and extinction by replacement with improved cultivars, lack of incentives for farmers to maintain traditional agricultural systems, and rising threats from climate change. Their active conservation is necessary to maintain this critical resource. However, as there are hundreds of thousands of LR and millions of LR populations for crops globally, active conservation is complex and resource-intensive. To assist in implementation, it is useful to be able to prioritise LR for conservation action and an obvious means of prioritisation is based on relative threat assessment. There have been several attempts to propose LR threat assessment methods, but none thus far has been widely accepted or applied. The aim of this paper is to present a novel, practical, standardised, and objective methodology for LR threat assessment derived from the widely applied IUCN Red Listing for wild species, involving the collation of time series information for LR population range, LR population trend, market, and farmer characteristics and LR context information. The collated information is compared to a set of threat criteria and an appropriate threat category is assigned to the LR when a threshold level is reached. The proposed methodology can be applied at national, regional, or global levels and any crop group.

Analogue Quantum Simulation with Fixed-Frequency Transmon Qubits

We experimentally assess the suitability of transmon qubits with fixed frequencies and fixed interactions for the realization of analogue quantum simulations of spin systems. We test a set of necessary criteria for this goal on a commercial quantum processor using full quantum process tomography and more efficient Hamiltonian tomography. Significant single qubit errors at low amplitudes are identified as a limiting factor preventing the realization of analogue simulations on currently available devices. We additionally find spurious dynamics in the absence of drive pulses, which we identify with coherent coupling between the qubit and a low dimensional environment. With moderate improvements, analogue simulation of a rich family of time-dependent many-body spin Hamiltonians may be possible.

ABYSS. II. Identification of Young Stars in Optical SDSS Spectra and Their Properties

We developed a tool that measures equivalent widths of various lines in low-resolution optical spectra, and it was applied to stellar spectra obtained as part of SDSS-V and LAMOST programs. These lines, such as Li i, which directly indicates stellar youth, or optical H i and Ca ii, which in emission indicate activity associated with stellar youth, are commonly seen in YSOs. We observe several notable differences in the properties of these lines between YSOs and the field stars. Using these data, we devise a set of criteria through which it is possible to confirm the youth of stars that have been observed by the ABYSS program, as well as to identify likely young stars that have serendipitously been observed by other programs. We examine the decrement of H lines seen in emission in CTTSs, and estimate the properties of the accretion stream that is responsible for the production of these lines. Finally, we examine the evolution of Li i as a function of age, and characterize the scatter in its abundance that appears to be intrinsic in young M dwarfs.

The German PCL-5: evaluating structural validity in a large-scale sample of the general German population

ABSTRACT Background: In attempts to elucidate PTSD, recent factor analytic studies resulted in complex models with a proliferating number of factors that lack psychometrical and clinical utility. Recently, suggestions have been made to optimize factor analytic practices to meet a refined set of statistical and psychometric criteria. Objective: This study aims to assess the factorial structure of the German version of the PCL-5, implementing recent methodological advancements to address the risk of overfitting models. In doing so we diverge from traditional factor analytical research on PTSD. Method: On a large-scale sample of the German general population (n = 1625), exploratory factor analyses were run to investigate the dimensionality found within the data. Subsequently, we validated and compared all model suggestions from our preliminary analyses plus all standard and common alternative PTSD factor models (including the ICD-11 model) from previous literature with confirmatory factor analyses. We not only consider model fit indices based on WLSMV estimation but also deploy criteria such as favouring less complex models with a parsimonious number of factors, sufficient items per factor, low inter-factor correlations and number of model misspecifications. Results: All tested models showed adequate to excellent fit in respect to traditional model fit indices; however, models with two or more factors increasingly failed to meet other statistical and psychometric criteria. Conclusion: Based on the results we favour a two-factor bifactor model with a strong general PTSD factor and two less dominant specific factors – one factor with trauma-related symptoms (re-experiencing and avoidance) and one factor with global psychological symptoms (describing the trauma’s higher-order impact on mood, cognition, behaviour and arousal). From the perspective of clinical utility, we recommend the cut-off scoring method for the German version of the PCL-5. Basic psychometric properties and scale characteristics are provided.

The Paratextual Functions of the Early Chinese Anecdote – with *Tang zai Chimen 湯在啻門 and *Tang chu yu Tangqiu 湯處於湯丘 as Examples

Abstract This article proposes a set of function-based criteria for identifying paratextual elements in manuscript texts. With *Tang zai Chimen and *Tang chu yu Tangqiu as examples, I show how their narrative frames perform functions akin to titles, authors’ names, and prefaces. This approach offers a new explanation for the prevalence of the anecdote genre as well as a renewed understanding of the functions of the paratext.

Mathematical programming models to assist the evaluation of shipbrokers

Shipbrokers play a key role in maritime industry by acting as intermediates between shipping companies and the market. They undertake various chartering, buying or selling operations. In this paper, we propose a mathematical programming approach for the evaluation and selection of shipbrokers. Specifically, the score of each ship broker is a composite measure that is derived by aggregating a set of performance criteria, e.g., reputation, etc. The developed mathematical programming models enable the aggregation and weighting of the criteria. We employ three optimization models to explore the effect of different weighting schemes on the scores and ranking of the shipbrokers. The models that provide a common set of weights for all the shipbrokers establish the appropriate ground for comparisons among them. Also, our models facilitate the incorporation of user priorities over the criteria in the form of weight restrictions. The proposed approach is illustrated by assessing seven shipbroker offers for selling a dry-bulk ship using four criteria, namely revenue, brokerage fee, brokerage time and terms & conditions.

Ethical Distribution and Supply Efficiency of Petroleum Products: A Systematic Literature Review

This study examined ethical distribution and supply efficiency of petroleum products. It explored the contemporary ethical distribution practices adopted by petroleum marketers in extant literature; identified the current key performance indicators (KPIs) for supply efficiency in the petroleum industry; and explored the position of scholars on the influence of ethical distribution on supply efficiency of petroleum products, among other objectives. To that end, a systematic literature review methodology was adopted. Through a thorough search process supported by a set of stringent inclusion-exclusion criteria, 91 relevant articles were included in this review. The articles were analyzed using in-depth content analysis method augmented with descriptive statistics. Consequently, the major finding of the study revealed that the majority of extant scholarly studies reviewed supported the proposition that ethical distribution practices can have significant influences on supply efficiency of petroleum products in extant literature. It was also found that the contemporary ethical distribution practices adopted by petroleum marketers in extant literature can be grouped into 11 categories, while the current key performance indicators (KPIs) for supply efficiency in the petroleum industry can be grouped into 13 categories, among other findings. On that note, the study recommended the need for a robust regulatory and implementation framework that mandates and ensures that petroleum marketers consistently integrate ethical considerations into their distribution operations in order to improve supply efficiency of petroleum products.

From Posts to Knowledge: Annotating a Pandemic-Era Reddit Dataset to Navigate Mental Health Narratives

Mental illness is increasingly recognized as a substantial public health challenge worldwide. With the advent of social media, these platforms have become pivotal for individuals to express their emotions, thoughts, and experiences, thereby serving as a rich resource for mental health research. This paper is devoted to the creation of a comprehensive dataset and an innovative data annotation methodology to explore the underlying causes of these mental health issues. Our approach included the extraction of over one million Reddit posts from five different subreddits, spanning the pre-pandemic, during-pandemic, and post-pandemic periods. These posts were methodically annotated using a set of specific criteria, aimed at identifying various root causes. This rigorous process produced a richly categorized dataset, invaluable for detailed analysis. The complete unlabelled dataset, along with a subset that has been expertly annotated, is prepared for public release, as outlined in the data availability section. This dataset is a critical resource for training and fine-tuning machine learning models to identify the foundational triggers of individual mental health issues, offering valuable insights for practical interventions and future research in this domain.

Oracy Skills Instruction: Evaluating, Adapting and Creating Listening and Speaking Activities

The objective of this paper is to evaluate, modify and formulate activities related to the development of ‘oracy’ skills in the English as a Foreign Language (EFL) classroom. In this context, ‘oracy’, as defined by Sifakis (2004/2018), specifically encompasses the skills of listening and speaking. Spoken discourse is differentiated from written in that it requires real-time interaction, presenting a notable challenge for the learners. (McDonough et. al., 2013). It is apparent that oracy skills play a crucial role in the overall development of students’ language proficiency as they emphasize their ability to engage effectively in real-life communication situations. In the course of evaluating materials, the paper will utilize relevant literature and employ sets of criteria, tailored to the communicative requirements of spoken interaction. Subsequently, adjustments to existing activities and the creation of original ones will be proposed in line with the theoretical framework. To facilitate this process, the paper will draw on materials deriving from two teaching textbooks and examine two distinct teaching contexts, each aligned with one of the aforementioned language skills; listening and speaking.

Mental health indicators for children and adolescents in OECD countries: a scoping review.

This scoping review is a further step to build up the Mental Health Surveillance System for Germany. It summarizes and analyzes indicators used or described in Organization for Economic Co-operation and Development (OECD) countries for public mental health monitoring in children and adolescents aged 0-18 years. We searched PubMed-MEDLINE, PsycINFO, Cochrane Databases, and Google Scholar from 2000 to September 2022. The search used five general keyword categories: 1) "indicators/monitoring/surveillance" at the population level, 2) "mental/psychological," 3) "health/disorders," 4) "children and adolescents," and 5) 38 OECD countries. The search was complemented with an extensive grey literature search, including OECD public health institutions and an internet search using Google. A predefined set of inclusion and exclusion criteria was applied. Over 15,500 articles and documents were screened (scientific search N = 10,539, grey literature search more than 5,000). More than 700 articles and documents have been full-text assessed, with 382 being ultimately included. Out of 7,477 indicators extracted, an initial set of 6,426 indicators met our inclusion criteria for indicators. After consolidating duplicates and similar content, this initial set was categorized into 19 topics, resulting in a final set of 210 different indicators. The analysis highlighted an increasing interest in the topic since 2008, but indicators for the younger age, particularly those aged 0 to 2 years, were less readily available. Our research provides a comprehensive understanding of the current state of mental health indicators for children and adolescents, identifying both (1) indicators of public mental health noted in a previous scoping review on adults and (2) new indicators specific to this age group. These findings contribute to the development of effective public health surveillance strategies for children and adolescents and inform future research in this field.