Source Items Research Articles

Questioning the use in a Muslim society of an IPIP measure of the Big Five Factors: a problem with reverse-coded items?

ABSTRACT This paper examines within a Muslim society the inte­rnal consistency reliability of an established IPIP measure of the Five Factor Model of personality drawing on the International Personality Item Pool. The specific hypothesis under investigation concerned the performance of the negatively-voiced items included within the measure, testing whether these items (that may imply disrespect for self) detract from the unidimensionality of the five factors. Data provided by 370 young adults between the ages of 18 and 26 years who were born in Punjab and who had lived there since their birth supported this hypothesis. The recommendation is that further work is now required to revisit the IPIP to source items to construct and test a new IPIP measure of the Five Factor Model of personality specifically designed for use in Muslim societies.

Three-dimensional lattice Boltzmann flux solver for three-phase/component flow

In this article, an immiscible three-phase/three-component lattice Boltzmann flux solver (TPLBFS) based on diffusion interface method is proposed, which can achieve three-phase flow simulation with high density ratio (1:1000). This model quickly solved (1) the flux at the grid interface using the lattice Boltzmann method (LBM) solution format and (2) the Navier–Stokes (NS) equation and Cahn–Hilliard (CH) equation using a unified format. Compared to LBM, TPLBFS can be applied to unstructured networks. Moreover, TPLBFS can independently add or remove source items and has high secondary development features. Its outstanding computing power has been demonstrated by multiple two-dimensional/three-dimensional (2D/3D) examples, including 2D liquid lens as well as 3D bubble absorption and bubble rising in a three-phase system.

The "good is up" metaphoric effects on recognition: True for source guessing but false for item memory.

The "good is up" metaphor, which links valence and verticality was found to influence affective judgement and to direct attention, but its effects on memory remain unclear with contradictory research findings. To provide a more accurate assessment of memory components involved in recognition, such as item memory and source-guessing biases, a standard source monitoring paradigm was applied in this research. A series of three experiments provided a conceptual replication and extension of Experiment 2 by Crawford et al., (2014) and yielded a consistent result pattern suggesting that the "good is up" metaphor biases participants' guessing of source location. That is, when source memory failed, participants were more inclined to guess the "up" location versus "down" location for positive items (and vice versa for negative items). It did, however, not affect source memory or item memory for valenced stimuli learned from metaphor-congruent versus incongruent locations (i.e., no metaphor-(in)congruent effects in memory). We suggest that the "good is up" metaphor may affect cognitive processes in a more subtle way than originally suggested.

Positive Solutions and Their Existence of a Nonlinear Hadamard Fractional-Order Differential Equation with a Singular Source Item Using Spectral Analysis

Based on the spectral analysis method, Gelfand’s formula, and the cones fixed point theorem, some positive solutions with their existence of a nonlinear infinite-point Hadamard fractional-order differential equation is achieved on the interval [a, b] under some conditions, and particularly the nonlinear term allows singularities for time and spatial parameters in the present study. Finally, an analysis case is carried out to reveal the principal results.

Dietary intake of plant polyphenols: Exploring trend in the Czech population.

This study aimed to determine trend in polyphenol consumption in the Czech Republic during the last three decades. Additionally, it provides a brief overview of the beneficial effects of polyphenols in several body systems. Data from the Phenol-Explorer 3.6, a specialized database of polyphenolic substances, were assigned to the resources of the Czech Statistical Office on the consumption of food and beverages in the Czech Republic for the years 1989-2022. The average daily intake of polyphenols was determined by multiplying the average annual consumption of each type of food by the polyphenol content obtained from the database; results were given in milligrams of polyphenols per inhabitant and day. Since the food items in the data sources are not identical, it was necessary to create an extensive model of food categories. The current value of polyphenol intake is 1,673 mg per day per inhabitant; however, this level most likely reflects methodological underestimation. The favourable increase in dietary polyphenol intake in the Czech population - doubling, to be precise - which we observed from 1989 to 2007, has been replaced by the opposite trend in the last 15 years. The current intake of polyphenols corresponds to the level that was already achieved in 2004. Hydroxycinnamic acids (from the group of phenolic acids) are the most prevalent dietary polyphenols, followed by flavanols (from the group of flavonoids). The most frequent source of polyphenols in the Czech population are non-alcoholic beverages such as coffee, tea and juices, followed by fruits, cereals, and vegetables, respectively. Current trend of dietary polyphenol intake in the Czech population is slightly decreasing. This tendency, lasting since 2008, is indisputably negative. Plant polyphenols offer opportunities for inexpensive interventions in health promotion.

Design and analysis of shadow detection and removal scheme in real-time still images

This research’s main objective is to study and evaluate the detection and removal of undesired shadows from still images since these shadows might mask important information caused by light sources and other obstructions. A variety of methods for detecting and eliminating shadows as well as object tracking approaches based on movement estimation and identification are investigated. This includes shadow removal methods like background subtraction, which are intended to improve obstacle recognition of the source item and increase the accuracy of shadow removal from objects. When new items enter the frame, they are first distinguished from the background using a reference frame. The tracking procedure is made more difficult by the merging of the shadow with the foreground object. The approach highlights the difficulties in object detection owing to frequent occurrences of obstacles by using morphological procedures for shadow identification and removal. The proposed approach uses feature extraction is also discussed, highlighting its importance in image processing research and the use of suggested methods to get over obstacles in image sequences. The proposed method for shadow identification and removal offers a novel approach to improve image processing when dealing with still images. The purpose of this technique is to better detect and remove shadows from images, which will increase the precision of object tracking and detection. Depending on the type of images being processed, the process begins with initializing a background model, which is based on a static image background.

Inverse modelling and classification of magnetic responses to improve marine unexploded ordnance rationalization

SUMMARY Unexploded ordnance (UXO), often deployed in WWI and WWII, are still present on the seabed posing a risk to seabed construction. UXO surveys identify potential UXO targets which are then investigated and removed where necessary; however, approximately 96 per cent of targets investigated on projects included in this study were non-UXO (false positives). Here we investigate methods of improving statistical confidence in targets picked through the improved classification of magnetic response, utilizing simulation methods and historic data. A simulation of the induced magnetism of UXO was developed to model the most likely dimensions and orientation of a given source item. Modelling results and measured variables were combined in an optimization algorithm, hereon referred to as ‘the classifier’. We document the results of integrating the magnetic responses of 3027 targets from 18 offshore wind projects into the classifier. Five of these projects were performed as tests in which the target results were unknown during classification. Finally, the classifier was deployed on a live project, Hollandse Kust Zuid 3 and 4 Offshore Wind Farm, in which it enabled the removal of 67 targets from the from the 1200-target investigation list. The classifier proved to be a valuable additional tool to assist the target rationalization process, reliably and repeatably distinguishing UXO from other items, thereby reducing false positives and repeatably demonstrating no threshold UXO false negatives. Assumptions and limitations of this methodology were highlighted, which must be understood and considered when integrating this approach on future projects.

A novel approach to understanding and assessing the emotional side of type 1 diabetes: The Type 1-Diabetes Distress Assessment System.

To describe the development of a novel, conceptually sound instrument with contemporary content for assessing diabetes distress (DD) among adults with type 1 diabetes. Qualitative interviews with 15 adults and 7 clinicians were used to develop Core (intensity of DD emotional burden) and primary Source (key DD contributors) items. These were administered to a national sample recruited from the TCOYD Research Registry, T1D Exchange and our previous studies. Exploratory and confirmatory factor analyses were undertaken, along with reliability and construct validity studies, and cut-point analyses to determine elevated DD. Analyses based on 650 respondents yielded an 8-item Core DD scale (α = 0.95) and 10 2- or 3-item DD Source Scales (α range = 0.53-0.88): Financial Worries, Interpersonal Challenges, Management Difficulties, Shame, Hypoglycemia Concerns, Healthcare Quality, Lack of Diabetes Resources, Technology Challenges, Burden to Others and Worries about Complications. Core and Source scores were significantly associated with criterion variables: Higher DD scores were significantly linked with higher HbA1C , more frequent episodes of severe hypoglycaemia, missed boluses, and poorer quality of life (p > 0.001). A ≥2.0 scale cut-point to define elevated DD is suggested. The new T1-Diabetes Distress Assessment System demonstrated good reliability and validity, and with measures of both Core emotional burden and Sources of DD, it provides a contemporary, flexible and practical approach to assessing DD that can be used seamlessly to inform intervention for clinicians and researchers.

Important role of turbulence on the distribution of particle radioactivity in the nuclear explosions

The distribution of particle radioactivity is one of the most important source items of radioactive fallout prediction model for nuclear explosion. For radioactive particles with the diameter larger than 0.5 μm, the influence of turbulent coagulation cannot be ignored. However, few scholars have considered the role of turbulence in the study of the distribution of particle radioactivity. The General Dynamic Equation (GDE), which is solved using the Multi-Monte Carlo method, is used in this study to establish a new model of the distribution of particle radioactivity that takes the impact of turbulent coagulation into account. The results present that the surface and volume distributions of particle radioactivity are closer to those of the Defense Land Fallout Interpretative Code (DELFIC) model, and the relative error of the surface (volume) distribution reduces from 1.243 (0.687) to 0.945 (0.284) when compared to the previous model that simply takes Brownian coagulation into account. The geometric median diameter of total particle radioactivity increases as the solidification temperature increases and as the particle size range increases when considering the influence of various geological conditions. When considering the effects of turbulent coagulation, the differences in the particle radioactivity produced under different geological conditions are smaller than those only considering the Brownian coagulation. This study highlights the importance of turbulent coagulation on the distribution of particle radioactivity in the nuclear explosions.

The Nexus between Carbon Emissions and Per Capita Income of Households: Evidence from Japanese Prefectures

Household consumption is significantly influenced by various factors. Despite this, the intricate nature of consumption behaviors and the lack of comprehensive data from the supply chain have led to an incomplete recognition of the attributes contributing to home emissions at the city level. Through the analysis of city-level household consumption in relation to energy demand, utilizing a city-scale input-output model and urban residential consumption inventories, this study considers the environmental responsibility inherent in residential consumption for Japanese’s Prefectures, this study reveals that variations in this responsibility based on household type and season. The study period is 2013-2022. Various factors are taken into account when examining emissions by age and month, including emission type, source, fuel variety, and consumption items. These assertions stem from emissions data computed using the system boundary method. Our hypothesis is supported by a range of statistical findings, encompassing summary statistics and regression analysis. The connection between residential emissions and GDP is also explored through regression analysis. We uncover evidence indicating that carbon emissions in Japan fluctuate with the seasons and across diverse categories. These statistics illustrate a notable discrepancy in the regional distribution of carbon emissions, owing to evident variations in consumption rates and patterns.

Ship Model as a Museum Object

Ship models are the part of a significant number of collections of domestic and foreign museums. Such objects are the primary sources of knowledge and emotions, true monuments of history and culture, but often belong to the group of reproductions of museum objects, that is, reduced copies of original objects. The article analyzes the questions of the definition of ship models, correlates the definitions of these items in different sources. The author considers the model of the ship from the point of view of the functions and properties of a museum object, asserts their value as originals of significant historical and cultural significance, monuments of science and technology, objects of arts and crafts, ethnographic sources. The novelty of the research lies in the study by the author of the ship model from the point of view of the theory of the museum object. This allows us to consider ship models from other, not generally accepted positions, and consider them full-fledged museum objects, which, along with originals, have the same set of properties, qualities and features. The main conclusions of the study are, firstly, that the models of ships and vessels in the collections of museums are not secondary in relation to other material sources, and secondly, that such objects fully correspond to the concept of "cultural values", are source of knowledge and emotion.

THE ROAD LESS TRAVELED: NURTURING A MEDICAL JOURNAL'S QUEST FOR INTERNATIONAL INDEXATION AND IMPACT FACTOR

Journal Impact Factor (JIF), proposed by Eugene Garfield in early 1960s, is considered as the one of the most widely recognized and influential metrics for scholarly journal ranking in the world. It provided a standardized measure based on the citation data for evaluation of journals. In 1975, the Institute for Scientific Information introduced the initial version of the Journal Citation Reports (JCR) as an essential part of the Science Citation Index, spearheaded by Eugene Garfield. First JCR was based on 4,248,065 citations of around 400,OOO source items published during 1974 in 2400 journals.1 Since then, JCR & JIF have undergone significant developments and transformations. They became widely adopted tools for evaluating research impact and journal prestige. Over the years, the IF and JCR expanded their coverage, incorporating more journals and disciplines. Recently released JCR 2023 comprised of 21,522 journals (including 13,668 science journals) from 112 countries across 254 research disciplines.2

Expert opinions on informational and supportive needs and sources of obtaining information in patients with inflammatory bowel disease: a Delphi consensus study.

The present study introduces informational and supportive needs and sources of obtaining information in patients with inflammatory bowel disease (IBD) through a three-round Expert Delphi Consensus Opinions method. According to our previous scoping review, important items in the area of informational and supportive needs and sources of obtaining information were elucidated. After omitting duplicates, 56 items in informational needs, 36 items in supportive needs, and 36 items in sources of obtaining information were retrieved. Both open- and close-ended questions were designed for each category in the form of three questionnaires. The questionnaires were sent to selected experts from different specialties. Experts responded to the questions in the first round. Based on the feedback, questions were modified and sent back to the experts in the second round. This procedure was repeated up to the third round. In the first round, five items from informational needs, one item from supportive needs, and seven items from sources of obtaining information were identified as unimportant and omitted. Moreover, two extra items were proposed by the experts, which were added to the informational needs category. In the second round, seven, three, and seven items from informational needs, supportive needs, and sources of obtaining information were omitted due to the items being unimportant. In the third round, all the included items gained scores equal to or greater than the average and were identified as important. Kendall coordination coefficient W was calculated to be 0.344 for information needs, 0.330 for supportive needs, and 0.325 for sources of obtaining information, indicating a fair level of agreement between experts. Out of 128 items in the first round, the omission of 30 items and the addition of two items generated a 100-item questionnaire for three sections of informational needs, supportive needs, and sources of obtaining information with a high level of convergence between experts' viewpoints.

Linguistic features of self-repair strategies of Arab Speakers of English language

Self-repair occurring in the same turn of speaking has been subjected to analysis in studies involving first language and second language users. However, in the context of English spoken as a foreign language, the information might still need further attention. This study is conducted to first report on the self-repair strategies employed by the Arab speakers of English in the same turn of speaking and second, to describe the linguistic features of self-repair produced by the speakers. Adopting the quantitative and qualitative approaches, data for this study come from a number of videos capturing conversations in English involving Arab speakers. The conversations in the videos were later transcribed orthographically and following this, instances of self-repair were identified. Framework of self-repair strategies provided by Emrani and Hooshmand was adopted to guide the data coding while the linguistic features of self-repair in the same turn of speaking were described by looking into its context of occurrences. The first finding has shown that repetition is the most frequent type of self-repair strategy to be employed by the Arab speakers of English. This is followed by replacement, insertion, abandonment and deletion. On the other hand, the self-repair that takes place in the same turn of speaking (where trouble source can be found as well) can be marked through a number of linguistic features namely prosodic features, the presence of fillers and the repair item that comes immediately after the trouble source item. The findings have provided insight into the speakers’ ability to monitor troubles in their speech, repair the troubles and features of their self-repair which can benefit the theoretical understanding and language classroom practices.

Modeling the challenges of technology adoption in dairy farming

Purpose The global research evidences indicate that the technology adoption in case of agribusiness has a potential to enhance the performance and bring operational efficiency. India is the world’s largest producer as well as consumer of milk but struggles with yield per cattle, overall productivity, low rate of technology acceptance and adoption, health detection of milching units, animal data recording and presence of dairy products in the global market. The purpose of this study is to focus on identifying the challenges of technology adoption in dairy farms and constructing a hierarchical model using soft systems methodology. Design/methodology/approach This study uses nominal group technique-based discussion with domain experts and personal interviews with dairy farm owners/managers for the identification of challenges, fuzzy interpretative structural modeling as well as FMICMAC to develop a hierarchical model of challenging elements and to divide the identified elements into four categories based on the dominance of driving-dependence power. Findings This research has developed a list of 12 challenges affecting the technology adoption in a dairy farm business unit, identified through the personal interviews with 60 dairy farms across three highest milk-producing states of India in terms of annual milk output – Haryana, Punjab and Uttar Pradesh. Lack of government support followed by lack of educational opportunities in dairy-based education were found as the most crucial and high driving challenges, whereas high cost, huge investment and low acceptance of decision-maker were found as the most dependent challenges of technology adoption. Research limitations/implications This research is one step ahead of interpretive structural modeling that considers the fuzzy-based dominance in the model to showcase the degree of relationship along with its existence, but it lacks to statistically validate the findings using techniques like SEM. Practical implications This paper has developed a list of challenges in adoption of technology along with their inter-relationships to highlight the required focus challenge that drives or is dependent on the other challenges. The goal is to bring performance improvement and assist Indian dairy farm business stakeholders or decision-makers in formulating strategic and action plans and help policy planners to make favorable policies based on the understanding of contextual relationship between challenges. Social implications In Indian context, dairy is an important part of agriculture sector, and milk is an essential item that facilitates income generation to small and rural households and a source item for several other businesses and activities. The results of this research suggested the policy planners and government to ensure subsidized and insured technologies, training support and facilities, educational opportunities and efforts for promotion of technology adoption among dairy farmers. The suggestions are purely on the basis of the relevance of challenges in the hierarchy and can play a significant role in improving the level of technology adoption and can ultimately uplift the social and economic well-being from micro-level of farmers to macro-stage concerning economic development of India. Originality/value To the best of the authors’ knowledge, this study is purely original and outcome of the research conducted by authors.

Recovery of latent fingerprints on different substrates submerged under fresh water: A review

Fingerprint proof is the maximum dependable and popular evidence inside the legal court in the judicial system. Though fingerprints are identical to all kind of conditions of atmosphere like rain, fire etc., and a huge range with different types of physical and chemical methodologies are needed for the fingerprints development. Criminal offenders always have an essential intention is they plan not to leave any traces at the crime scene. Criminals may have thought that evidences which are recovered under water will have not a single value in the field of forensics, so they consequently try to spoil the strains by throwing items in water sources like ponds or lakes. These constitute a task for the forensic experts to investigate the fingerprints. Under water evidences which are recovered from the scenes where crime occurred, have usually been a venture for the forensic scientists, as water puts different environmental effect at the prints. There are various technical processes which available for the purpose of fingerprint development from various types of substrates like glass, metal, aluminum, plastic, wood etc. on different time intervals like two days, ten days etc. There are strategies for improvement of fingerprints discovered under fresh water. The present examine offers different techniques like SPR, PTC, Black Powder, Cyanoacrylate, zinc carbonate etc. for the development of fingerprints determined under fresh water.

The cutting path planning of main components in China initiative accelerator driven subcritical system based on the quantum evolutionary algorithm

The CiADS is a promising nuclear demonstration facility for the purpose of transmuting long-life fission products and minor actinides to the short-life isotopes. The main components in CiADS are the large volume equipment with complex structure and high radioactivity, which are also the important source items for the decommissioning plan design that should be cut into smaller blocks for the proper management and the safety storage. However, it has been believed as the extremely difficult and challenging task to construct the cutting paths on the main components in order to obtain the optimized blocks with acceptable range of radioactivity, since the cutting paths are hard to describe with explicit expressions in the complex model structures, and the manual selection of cutting blocks with suitable radioactivity is the error prone and labor intensity task. Considering this situation, the cutting path planning method has been developed in this study. During the decommissioning process, the complex models of main components have been converted to the simplified geometries with voxelized description, and then the quantum evolutionary algorithm has been used to automatically find the appropriate cutting blocks by means of the voxelized description for the purpose of meeting the decommissioned requirements. Moreover, the reconstruction procedure has been used to record the topological information of cutting paths on the main components with the visualization function in the graphical user interface. Finally, the verification and validation of the cutting path planning method have been tested in the decommissioning scenario, and all the numerical results show that the optimized method can effectively fulfill the cutting path planning tasks of the CiADS facility.

Automatic identification of self-admitted technical debt from four different sources

Technical debt refers to taking shortcuts to achieve short-term goals while sacrificing the long-term maintainability and evolvability of software systems. A large part of technical debt is explicitly reported by the developers themselves; this is commonly referred to as Self-Admitted Technical Debt or SATD. Previous work has focused on identifying SATD from source code comments and issue trackers. However, there are no approaches available for automatically identifying SATD from other sources such as commit messages and pull requests, or by combining multiple sources. Therefore, we propose and evaluate an approach for automated SATD identification that integrates four sources: source code comments, commit messages, pull requests, and issue tracking systems. Our findings show that our approach outperforms baseline approaches and achieves an average F1-score of 0.611 when detecting four types of SATD (i.e., code/design debt, requirement debt, documentation debt, and test debt) from the four aforementioned sources. Thereafter, we analyze 23.6M code comments, 1.3M commit messages, 3.7M issue sections, and 1.7M pull request sections to characterize SATD in 103 open-source projects. Furthermore, we investigate the SATD keywords and relations between SATD in different sources. The findings indicate, among others, that: 1) SATD is evenly spread among all sources; 2) issues and pull requests are the two most similar sources regarding the number of shared SATD keywords, followed by commit messages, and then followed by code comments; 3) there are four kinds of relations between SATD items in the different sources.

Analysing the relationship between altmetric attention score (AAS) and citation: a correlational study

PurposeThe purpose of this study is to assess the value of altmetrics or other indicators, showcasing the impact of academic output, which is seen too often correlated with the citation count.Design/methodology/approachThis study considered three reputed journals of Library and Information Science (LIS) published by Elsevier. A total of 1,164 articles were found in these journals from 2016 to 2020 and the relationships between altmetric attention scores (AAS) and citations were examined. The analysis was extended to compare the grouped data set based on percentile ranks of AAS like top 50%, top 25%, top 10% and top 1%.FindingsUsing Spearman correlation analysis, the findings reveal a positive correlation between AAS and citations with different significant levels for all articles, and articles with AAS, as well as for normalized AAS in the top 50%, top 25%, top 10% and top 1% data set. For the three journals International Journal of Information Management (IJIM), Journal of Informetrics (JIF) and Library and Information Science Research (LISR), a significant positive correlation is observed across all data sets. But an unexpected result was observed: in the case of the top 50% of articles for the IJIM and JIF showed no significant correlation but the LISR journal showed a positive correlation for the whole data set. This journal though has fewer articles in comparison to the other two.Research limitations/implicationsA source item that is highly cited may not be having high social media attention as reflected in the findings. This demarcates AAS with citations implying various factors on which these measurements are dependent. The study distinguishes these metrics lucidly. There is not a single guideline or uniformity in assessing the correlation found. But the problem is that the interpretation of the correlation strength affects the conclusion of the study. Moreover, this study will be a role model as a draft for librarians to select relevant journals for their libraries and will facilitate authors in the choice of the publication outlets for their papers, particularly concerning the journals that have both visibility and research impact.Originality/valueThe study reported devising a comprehensive tool to validate AAS as a measure of scholarly impact to include appropriate social media sources and verify its relationship with other metrics. To the best of the authors’ knowledge, this paper is the first attempt to discover the correlation between AAS and citations for the highly impactful LIS journal published by Elsevier. The empirical evidence lies in the citation and altmetric data extracted from the dimension database.

Investigating the concentration distribution characteristics of methane in large storage facility using desorption-concentration gradient method and CFD simulation

The continuous methane emission from the coal piles is associated with many environmental problems and safety risks, in large storage facility. The methane emission parameters of coal piles and the concentration distribution characteristics of methane, which are the basis of ventilation design, are rarely reported in large storage facilities. In this study, based on the mass-transfer diffusion theory, desorption-concentration gradient method for determining methane emission parameters of coal piles in large facilities is proposed. In this method, firstly, the coal pile methane diffusion coefficient was deduced by conducting the coal particles absorption-desorption experiments and the particle-size distribution. Then, combing the diffusion coefficient and methane concentration-gradient on the coal pile surface, the coal pile methane diffusion flux was calculated. Further, when methane diffusion flux was utilized as the source item for CFD calculations, the results were consistent with the onsite measured values, which demonstrated the accuracy of this method. The CFD simulation results show that methane has diffusion characteristics that adhere upward along the slope of the coal pile and converge on the coal ridge. The methane flow reaches the dome upwards, where a higher concentration is formed. Both the coal pile volume and the methane diffusion flux will affect the concentration distribution of methane in large storage facility. For a larger diffusion flux, the explosion limit will be exceeded, and measures need to be taken to eliminate the safety risk. These findings provide principal data and analysis guide for optimized design of ventilation performance in closed industrial building.