Reliable Criteria Research Articles

Diffuse cortical atrophy in young males with alcohol dependence

ABSTRACT Background: One of the most common and significant issues associated with alcohol consumption is its consequences, and one of the organs most affected is the brain. Numerous chronic drinkers in their fifth and sixth decades have demonstrated cortical atrophy in radiological examinations; nevertheless, there is little study in the young age range. Aim: To assess the degree of cortical atrophy in young male adults with alcohol dependence compared to those who have no history of alcohol consumption and its correlation with the severity of alcohol dependence. Materials and Methods: This cross-sectional study included a purposive sampling of 30 patients aged 18–45 years, fulfilling the diagnostic criteria of alcohol-dependence syndrome, and having no prior history of brain damage-causing substances other than alcohol. An equal number of age- and sex-matched control subjects were taken who did not have any history of alcohol consumption. Computed tomography (CT) scans were done for both groups. Alcohol Use Disorders Identification Test C (AUDIT-C), Severity of Alcohol Dependence Questionnaire (SADQ), and Global Cortical Atrophy (GCA) scale were applied to measure alcohol dependence and its severity and the degree of cortical atrophy. Results: All 30 male patients who fulfilled the criteria of alcohol dependence showed significant cortical atrophy in CT scans as compared to control subjects. Out of the 30 alcohol-dependence patients, 4 had only frontal lobe atrophy, while 26 patients had diffuse cortical atrophy, among which 19 patients showed frontal lobe predominance. The degree of atrophy and the severity of alcohol dependency also showed a strong association. Conclusion: There is a persistent pattern of neuroradiological evidence of diffuse cortical atrophy with frontal predominance in young people having alcohol dependence with a mean total duration of alcohol consumption of around 21 ± 5.5 years as compared to those who have no history of alcohol consumption.

Immunohistochemical insights into hypothermia-related deaths: a systematic review.

Hypothermia occurs when core body temperature drops below 35°C. The purpose of this review was to identify and analyze studies on the topic of hypothermia from an immunohistochemical perspective to determine robust markers of fatal hypothermia. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines. It has been registered with Prospero (registration number: CRD42024572782). In total, 2618 publications met the search criteria. A total of 63 duplicate articles were excluded and a further 2489 publications were excluded for not meeting the inclusion criteria, leaving 29 full-text articles. Furthermore, from the bibliographies of the included articles, four more publications were selected, which also respected the established inclusion and exclusion criteria. Only six studies identified a statistically significant correlation between immunohistochemical patterns and hypothermia-related deaths. The existing literature examined appears fragmented and lacks robust statistical validation. Therefore, there is an evident need for more comprehensive and methodologically rigorous research to develop reliable diagnostic criteria.

Raising siblings is stressful: Measuring parental emotion regulation in the sibling context

Parents’ ability to manage intense emotions in the face of conflictual sibling interactions is a significant challenge that has been linked with various child and parent outcomes. With existing instruments focused on raising a single child, we lack validated instruments to assess dimensions of parental emotion regulation in the context of rearing siblings. We tested the factor structure, reliability, divergent and concurrent criterion validity of a new instrument designed to measure parental emotion regulation ( Parental Emotional Regulation in the Sibling Context Questionnaire) while raising two or more children. Participants, 359 mothers from 35 countries, with two children aged 4- to 8-years, completed the new instrument along with established measures of parental emotion regulation, sibling relationship quality, and children’s emotion regulation. A confirmatory factor analysis supported the utility of the instrument in reliably assessing dimensions of parent emotional regulation (Reactivity and Dysregulation). Evidence for divergent validity stemmed from associations with an established measure of general emotion regulation strategies and evidence for concurrent criterion validity stemmed from associations with children’s sibling relationship quality. Findings have implications for the reliable identification of mothers who are facing emotion regulation difficulties, the design of customized intervention strategies, and the evaluation of prevention and intervention programs.

Influence of Strain Rate and Temperature on the Multiaxial Failure Stress Locus of a Polyamide Syntactic Foam

This study introduces a comprehensive experimental methodology allowing for the direct measurement of the rate dependent multiaxial response of polymer syntactic foams under combined direct-shear loading. The combined tension-torsion behaviour of a syntactic foam and its rate dependence are investigated for the first time.Dynamic tension-torsion experiments were conducted using a newly developed Tension-Torsion Hopkinson Bar (TTHB) enabling the measurement of the combined tensile-shear response of engineering materials at high rates of strain.The response and multiaxial failure envelope of a polyamide syntactic foam were experimentally measured and analysed to determine the combined influences of stress state, strain rate, and temperature. The multiaxial failure stress locus was defined in both the normal versus shear stress space and the principal stress space, providing a comprehensive characterisation of the behaviour of the material under various loading and environmental conditions.The suitability of existing pressure dependent failure criteria to represent the measured experimental data was also assessed. The Drucker-Prager pressure dependent criterion proved to be effective in capturing the measured quasi-static and dynamic multi-axial stress loci at different temperatures.The effects of temperature, loading rate and stress state on the deformation and failure modes were analysed by means of SEM micrographs of the tested samples.

The Psychometric Performance of State Mindfulness Scales Around Sitting and Walking on Desert Trails: A Pilot Study

State mindfulness is a dynamic construct reflecting current mindfulness, or purposeful attention to the present moment with openness, non-judgment, non-reactivity, and acceptance. Despite its popularity and research in psychology and medicine, measuring state mindfulness remains a challenge. Validity and reliability of the State Mindfulness Scale (SMS) and State Mindfulness Scale for Physical Activity (SMS-PA) in applied settings like nature require more data to be established. This pilot study aimed to evaluate these scales and introduce a new, one-item scale, the Visual Analog Scale-Mindfulness (VAS-M), for quicker mindfulness assessment. Participants completed the SMS, SMS-PA, and VAS-M upon arrival at a desert trail, after 10 minutes of sitting, and after 10 minutes of walking. A subset repeated the intervention 24 hours later. The study found that the SMS and SMS-PA could be given before, during, and after nature immersion. The SMS-PA showed evidence of concurrent validity with the SMS (ρ = .89, p < .001). However, the VAS-M did not meet the criteria for concurrent validity with the other scales. None of the scales met the criteria for test-retest reliability. This study underscores the need to validate state mindfulness scales, especially in non-laboratory settings. While the SMS-PA shows promise, further validation and refinement of the VAS-M are needed. The findings enhance our understanding of measuring state mindfulness, particularly in natural environments. While the scales are already in use, our study helps address gaps in evidence and informs future decisions about their application.

Phenotypic characterization and principal component analyses of Bangkok chicken in Indonesia

ABSTRACT Bangkok chicken is a significant genetic resource in Indonesia, valued culturally and economically. However, limited reports on its phenotypic diversity risks genetic loss. This study aimed to assess phenotypic characterization of Bangkok chicken through qualitative and quantitative traits. Methods included qualitative classification, morphometric measurements, correlation, and principal component analysis (PCA). A T-test analyzed sex differences in body weight and morphometric traits. The research findings revealed that the male Bangkok chickens had 44.16% black-red (black dominant) feather colour and 73.20% yellow shank. Meanwhile, the females had 78% black feather colour and 34% black shank. The pea comb type was dominant in both sexes. The results indicated that the body weight and morphometric traits of male Bangkok were higher than those of females. In the total population, the PC1 accounted for 56.92% of the total variance. Morphometric features, such as breast girth and shank length were strongly correlated with body weight, highlighting their potential as reliable traits for selection and breeding Bangkok chickens. In conclusion, the study identified key phenotypic characteristics, which were body weight, breast girth, and shank length. These traits are strongly correlated and can serve as reliable criteria for selecting and improving Bangkok chicken breeds. Highlight The variation of qualitative traits of Bangkok chickens, consisting of feather colour, shank colour, and comb type, were widely varied across the population. Sexual dimorphism (male and female) affected all the parameters in quantitative traits, and the PCA identified breast girth and shank length as the key potential criteria for selecting Bangkok chicken.

Attribution of Media Texts Based on a Trained Natural Language Model and Linguistic Assessment of Identification Quality

The creation of effective systems for filtering media texts is due to the need to develop artificial intelligence systems, which is a large language model that should be trained using “correct” text samples that do not contain signs of disinformation, infodemic and unreliability. The article presents the results of automatic detection of high-quality media texts, as well as text samples with infodemic features carried out using a trained natural language model based on a manually labeled corpus. Manual marking of the corpus was carried out by experts based on the parameterization of the text content. The goal of our work is to build a model of the language of media messages, assess the quality and identify detection errors caused by the linguistic characteristics of texts. Creating a model of the language of media messages is a condition for increasing the efficiency and quality of artificial intelligence systems. It has been established that the test use of a trained natural language model allows filtering media texts with fairly high accuracy. The support vector machine method proved to be most effective. The share of incorrectly recognized informative texts that meet the criteria of reliability and novelty is low and amounts to 6.2 percent. The percentage of incorrectly recognized uninformative texts is approximately 3.9 percent, which indicates a fairly high efficiency of the developed model. The errors in the detection of informative texts are associated with the use of proper names (anthroponyms, toponyms) and numerals in the headings. Linguistic features of misclassified texts containing signs of fake and misinformation comprise text samples using statements with speech verbs that are often used in informative texts.

Occupational bronchial asthma from the perspective of molecular genetic research

Currently, occupational bronchial asthma is considered as a phenotypically and genetically heterogeneous disease. The assessment of clinical data, functional features, and immunopathogenesis opens up new opportunities in assessing the development, predicting the characteristics of the course, and working out a personalized approach to pharmacotherapy of occupational asthma, as well as in developing an individual strategy for its prevention. The purpose of the study is to determine clinical and immunological markers of the risk of developing occupational asthma under conditions of exposure to sensitizing substances in various phenotypes of this disease. Materials and methods. The study included 170 patients with various OA phenotypes and 50 participants in the control group. The pulmonary function test was carried out on the CareFusion MicroLab Desktop Spirometer (Great Britain). The levels of IL-1β, IL-4, IL-6, IL-8, IL-10, IL-17, TNF-α, vascular endothelial growth factor (VEGF), MCP-1, IFN-γ, and total IgE in blood serum were determined by solid-phase enzyme immunoassay using kits and reagents (OOO «Protein contour», «Vector-Best», «Diatex-E», «DIA-plus», «Pharmacia diagnostika»). Genotyping was performed by real-time polymerase chain reaction using primers and probes designed using PrimerQuest (Integrated DNA Technologies, Inc.). Results. For the first time, the features of clinical and immunological manifestations in allergic and non-allergic OA phenotypes, as well as phenotypes of OA combination with occupational chronic obstructive pulmonary disease and metabolic syndrome were established; the features of formation, immunopathogenesis, and prognosis in various phenotypes of occupational bronchial asthma were revealed. The study identified genetic markers of occupational asthma risk under conditions of exposure to sensitizing substances: IL5 rs2069812 and TSLP rs1837253 polymorphisms. This allows recommending the determination of these immunological parameters and genetic markers during in-depth periodic medical examinations of workers under conditions of exposure to sensitizing and irritating substances for differential diagnosis of various phenotypes of occupational bronchial asthma in a specialized inpatient examination. Limitations of the study. The study has regional (Samara Region) and professional (in terms of detailing working conditions in the studied comparison groups) limitations. Conclusion. The identified clinical, immunological, and genotypic features in various OA phenotypes and the established profiles of OA genotypes can optimize the approach to early diagnosis, prognosis, prevention, and pharmacotherapy of this disease, as well as expand the list of immunological study indicators used during preliminary and periodic medical examinations, in-depth examination of patients with occupational bronchial asthma in occupational disease clinics and occupational pathology centers, and the application of new reliable criteria for predicting the course of the disease.

Melodic Movements: The Role of Music in Shaping Sport Performance and Psychological Responses

The application of music in sport can enhance training and competition performance. This study explored the effects of different music genres on students' emotional, psychological, and athletic performance. Motivational music (e.g., blues, jazz, classical) has reflective and complex qualities, with a tempo of 60-80 beats per minute; high-tempo music (e.g., rock, heavy metal, alternative) has intense and rebellious characteristics, with a tempo of 120-140 beats per minute; upbeat music (e.g., pop music, New German Wave), film music, and popular German music have cheerful and traditional qualities, with a tempo of 100-130 beats per minute; rhythmic music (e.g., soul/R&B, rap/hip-hop, and electronic music), have strong rhythmic features, with a tempo of 80-100 beats per minute; and self-selected music is chosen by the participants based on preference. Using a structured questionnaire, data were collected from 400 students at Shandong Sport University (50.8% male, 49.3% female, ages 18-21) to assess demographics, music preferences (Short Test of Music Preferences), psychological responses (Sport Emotions Questionnaire (SEQ) and Attention Questionnaire (AQ-RARC), sport motivation (adapted from Gill et al., 1983), and physical performance (International Fitness Inventory). Results from the PLS-SEM analysis indicated a composite reliability (CR ≥0.7) and an average variance extracted (AVE ≥0.5), meeting the Fornell-Larcker criteria for the model's reliability and validity. Model fit indices (SRMR, RMSEA < 0.08; CFI > 0.90) and path coefficient (t-value > 1.96), confirmed significance, with an R² value > 0.3 and a Q² value > 0, demonstrating the model's explanatory and predictive power. Findings suggest that different music genres significantly enhance students' athletic performance and psychological well-being.

A machine learning based prediction model for the impact mechanical response of composite laminates considering microstructure sensitive transverse properties

AbstractThe accurate and efficient prediction of impact mechanical response is crucial for safety design of composite structures. In this work, high‐fidelity representative volume elements (RVEs) with fiber, matrix and fiber/matrix interface are established, in which random fiber distributions are considered. A failure envelope under transverse loads is proposed based on computational micromechanical RVEs, and it is implemented by ABAQUS VUMAT subroutines to predict the mechanical response of composite laminates under impact loads. Based on a dataset from computational macromechanical finite element simulations, an artificial neural network model is established and trained. It is found that the random fiber distribution introduced a more obvious fluctuation to tension/compression strength than shear strength. The proposed failure criteria showed a better performance than Hashin and Tsai‐Wu criteria especially in combined compression and shear loads. An ANN model with 8 hidden layers can achieve the prediction with an acceptable coefficient of determination (R2) 0.98 and loss functions of mean absolute error (MAE) 71. For certain impact loading conditions, the well trained machine learning model predicted impact contact force history within 30 min, while the FEA costs about more than 75 min on the same computer. The prediction speed is increased by over 60% for certain impact loading conditions. It is hence shown that this method provides a potential alternative for evaluation of the impact resistance of composite structures.Highlights High‐fidelity computational micromechanics analysis based on representative volume elements are performed to uncover the complex relationship between microstructure and transverse strengths of composite laminates. The microstructure dependent transverse strength criterion shows high accuracy in combined compression and shear loads compared with Hashin and Tsai‐Wu criteria. A multi‐layer artificial neural network model is established and trained for the rapid prediction of impact force history for composite laminates. The rapid prediction method is achieved with a coefficient of determination of 0.98, and the prediction speed is increased by more than 60% for certain impact loading conditions.

A Novel Methodology for Classifying Wikipedia Articles: Insights into Digital Forensics and Content Integrity

Well-written articles shape readers interaction with information, as top-ranked articles are more likely to be seen than those further down the ranks. We present a new approach to classifying Wikipedia articles across various quality dimensions, harnessing knowledge gained from expert assessments. The study also includes an attempt to develop a solid framework that meets the evaluation of the quality of an article for the sole purpose to ensure the integrity of the content in the multipoint structure of the Internet, and to have input for the applications of Digital Forensics. The suggested method: the article details is gathered using the Wikipedia API and a set of metrics is well-defined to store and analyze this information. The methodology then explores the relationship between independent variables (metrics of the articles) and the dependent variable (quality level as rated by the experts). Three machine learning algorithms (RF, J48, and NB) are then used to classify the articles. The classification is dragged along with the expert reviews to determine whether quality level of Wikipedia articles. The empirical evidence illustrates the effectiveness of the proposed approach, with average accuracies greater than 70% for the J48 algorithm. The precision, recall and F-measure values corresponding to the classification models’ accuracy exceed 0.7, representing a strong performance model. Overall, these findings indicate that the method uses reliable criteria, which classifies Wikipedia articles in accordance with experts' opinions, making it a reliable tool for quality assessment. In addition, the study underscores the significance of the combined focus on precision and recall for assessing the quality of a model, thereby demonstrating how useful this method is in ensuring that content can be trusted and as part of digital forensics.

PHOTONEUTRON REACTION CROSS SECTIONS FOR 90Zr IN DIFFERENT EXPERIMENTS

Reliability of the data on partial photoneutron reactions on 90Zr obtained in the experiment carried out on the beam of bremsstrahlung was investigated using the experimental-theoretical method for partial reaction cross section evaluation basing on objective physical criteria. It was found out that (γ, 1𝑛) and (γ, 2𝑛) reaction cross sections obtained using the corrections calculated via statistical theory to the neutron yield cross section σ(γ, 𝑥𝑛) = σ(γ, 1𝑛) + 2σ(γ, 2𝑛) satisfy physical criteria of data reliability. The integrated characteristics of the cross sections of the reactions (γ, 1𝑛) and (γ, 2𝑛) in which the distinct structural features were obtained as well as in the experimentally measured neutron yield cross section σ(γ, 𝑥𝑛) agree with those of evaluated cross sections. This shows that information on 90Zr partial reactions competition obtained using statistical theory satisfies physical criteria of data reliability. The evaluated reaction cross sections are compared in detail with analogous data obtained before using the results of experiments carried out on the beams of quasimonoenergetic annihilation photons.

Development of Character Education Assessment Instruments at Asta Learning Center Training Institution

Character education in vocational training institutions requires valid and reliable assessment instruments. At Asta Learning Center, the character assessment instrument has not been fully developed. This study aims to (1) identify the characteristics of the character education evaluation instrument at Asta Learning Center in relation to industrial needs, (2) examine the construction of character education variables based on empirical data, and (3) assess the validity and reliability of the developed character assessment instrument. This research uses the Research and Development (RnD) method, conducted from May to June 2024. The assessed character traits discipline, honesty, work ethic, independence, and social concern—are essential for developing competent employees. A Confirmatory Factor Analysis (CFA) approach, using SPSS 25.0 for Windows, was applied. The results indicate that the Likert-scale assessment instrument meets validity and reliability criteria. The small-scale trial (10 participants) showed a reliability of 0.761 and rtabel = 0.632, while the large-scale trial showed a reliability of 0.758 and rtabel = 0.367. The findings suggest that the developed instrument is valid, reliable, and suitable for use in Asta Learning Center's learning activities.

Network management: proposition and validation of a framework

Purpose This study aims to propose and validate a framework for analyzing management activities in regional strategic networks. It addresses the knowledge gap regarding network management and the lack of focus on specific activities and management modes employed by network actors. Design/methodology/approach The research methodology involves a literature review to identify essential network management functions, which academic experts and field specialists then evaluate. Based on their feedback, an instrument is refined to assess these activities’ strategic importance and frequency. Data is collected from 86 regional strategic network managers, meeting the required criteria for factor analysis. Principal component analysis with varimax rotation measures the “Network Management” construct and identifies underlying dimensions summarizing observed variables. Findings The analysis reveals two dimensions within the framework: one encompasses early-stage network development activities (ex ante activities), and the other includes activities associated with more advanced stages (ex post activities). This framework contributes methodologically to measuring and analyzing network management. Research limitations/implications This research addresses the need for robust conceptual frameworks in network governance, advancing the understanding of governance drivers and their impact on network outcomes by aligning network phenomena with performance. Practical implications The framework provides valuable insights for network managers, enhancing their understanding of management activities’ strategic importance and frequency. This knowledge can inform managerial decisions and improve network management practices. Originality/value This study introduces an original framework for analyzing network management activities in regional strategic networks, filling a significant research gap. Despite limitations like specificity to certain network types and subjective responses, the study maintains validity and reliability criteria. Future research opportunities involve applying the framework to different network contexts and conducting longitudinal studies to track network management evolution.

Validation of the Nurse Practitioner Knowledge and Attitudes of Patient Obesity Scale: A pilot study.

Obesity is a chronic, complex, relapsing disease requiring medical intervention that has reached epidemic proportions globally. Most patients are still experiencing bias and stigma related to their disease-even by health care providers. Our goal in this pilot study is twofold: to develop a scale to accurately measure nurse practitioner knowledge and attitude regarding the disease of obesity to determine whether bias exists and to potentially identify gaps in knowledge that can be targeted with future educational interventions. To determine whether nurse practitioners in the Northeast have less stigmatized knowledge and attitudes regarding obesity. A survey was created by the primary investigator as the "Nurse Practitioner Knowledge and Attitudes of Patient Obesity Scale" and distributed through email to New York State Nurse Practitioner Association members. Questions explored knowledge related to treatment of the patient living with obesity and nurse practitioner attitudes toward the disease. The sample (N = 45) was homogenous, which did not allow for generalization. Preliminary results show that a large percentage of respondents were aware of the definition of obesity as a disease and treatment guidelines. The scale met reliability and validity criteria and showed that Nurse Practitioners (NPs) with continuing education had more positive views. More research is needed to understand nurse practitioner knowledge and attitudes regarding the disease of obesity and the benefit of continuing education in reducing bias and stigma. This may serve to improve NP obesity continuing education.

Novel PROMETHEE method with dependent criteria

Novel PROMETHEE method with dependent criteria

Paroxysmal sympathetic hyperactivity in brain damage (scientific review). Part 1

Paroxysmal sympathetic hyperactivity (PSH) is a separate form of fever of central origin and is a neurological syndrome characterized by simultaneous paroxysmal occurrence of hypertension, hyperpyrexia, tachycardia, tachypnea, increased sweating and dystonic posture due to sympathetic activation in brain damage. PSH is a syndrome that can manifest itself in a wide range of clinical symptoms. Paroxysmal sympathetic hyperacti-vity is an example of a clinical correlate of central and autonomic nervous system dysfunction. Almost all cases of PSH are associated with craniocerebral trauma, hypoxia, and acute cerebrovascular accident. There is a disengagement theory and a model of the excitation-inhibition relationship of the PSH pathogenesis. In 2014, an expert consensus group proposed a PSH-assessment measure (PSH-AM), which can not only serve as a reliable diagnostic criterion but also stratify the severity of PSH. Assuming clinical evaluation as the current gold standard, PSH-AM has a sensiti-vity of 94 % when used retrospectively. In the treatment of patients with traumatic brain injury, PSH-AM can help avoid misdiagnosis, increase diagnostic efficiency, save time, and reduce economic costs. Hypodiagnosis of PSH can lead to an increase in mortality, disability, length of hospital stay and material costs, but timely diagnosis will allow optimizing treatment for PSH.

Ranking of Criteria Affecting the Implementation Readiness of Internet of Things in industries Using TISM and Fuzzy TOPSIS Analysis

The Internet of Things (IoT) technology has emerged as a vital driver across various fields, engaging businesses, platforms, and industries. IoT involves a holistic ecosystem and a value chain that necessitates the evaluation of impactful dimensions for successful implementation. This research employs the TISM method to identify driver and dependent criteria regarding IoT implementation readiness and uses the fuzzy TOPSIS method to rank these criteria. In the initial step, 15 criteria were identified through a review of previous studies. The TISM results reveal five levels reflecting the driver power and dependence of the criteria. Based on these results, “Implementation Knowledge and Expertise (C2)”, “Technical and Infrastructural Readiness (C9)” and “Financial and Investment Readiness (C12)” were placed at level 5, marking them as the most driver criteria. Additionally, “Implementation Roadmap (C8)” was identified as the most dependent criterion at level one. According to the fuzzy TOPSIS results, “Senior Management Support (C6)”, “IoT Usage Culture (C1)”, “Business Model Development Capability (C15)”, “Financial and Investment Readiness (C12)” and “Technical and Infrastructural Readiness (C9)” ranked first to fifth, respectively. The combined results provide valuable insights for decision-makers and stakeholders involved in IoT implementation. By determining driver and dependent levels and ranking the criteria, industries can effectively prepare for the successful implementation of IoT.

Вибротранспортирование твердеющих смесей при подземной разработке месторождений

Increasing volumes of consumed mineral raw materials alongside with depletion of their reserves in the regions, where their mining is convenient, and other modern phenomena explain the need to modernize the technologies for the development of mineral deposits. One of the main ways to improve the efficiency of mineral raw material extraction is to manage the mined-out space by filling it with solidifying mixtures. At the same time, the problem of transporting these solidifying mixtures to remote areas of the mine becomes more acute. Existing technologies are limited in their ability to solve this challenge, which significantly increases the costs of mining mineral raw materials. The article describes a relatively new technology for transporting a hydraulic mixture over a distance of 2000 m in the vibration-forced mode, which has been used for a number of years in the underground mining of adjacent deposits with preparation of mixtures at one of the deposits and their transportation to another deposit. The paper justifies the possibility of optimizing the processes of hydraulic mixture movement while minimizing the costs and reducing the environmental impact by constructing a pipeline not on the earth's surface, but in the underground workings. The results of justifying the parameters of hydraulic mixture transportation in the vibration-forced mode are given, obtained by modeling according to the criteria of distance and reliability of transportation and confirmed by practice.

Absence of Strikes as a Criterion of Efficiency of Staff Security Costs Management at Industrial Enterprises

The article is devoted to studying the possibility of using the absence of strikes as a reliable criterion for measuring the efficiency of staff security cost management at industrial enterprises. The authors proved that the threat of losing a job due to an industrial downturn and economic instability creates conditions under which the interest of employees in protecting enterprises and their owners is higher than the benefits of initiating a labor dispute with them. Based on the results obtained, it is established that despite a low level of social standards in most Ukrainian enterprises, including wage arrears and a low wage level, the number of strikes in Ukraine is scanty. In 2018-2020, there was not a single strike in Ukraine. In 2021, 11 strikes were recorded in the field of education, with the total number of participants accounting for 700 people. Since 2022, strikes in Ukraine have been banned due to the martial law introduction. The article introduces the concept of “employees’ forced loyalty” and elaborates on the classification of loyalty types. The authors proposed the matrix for determining the situations, in which the absence of strikes is a criterion for the efficiency of staff security costs at Ukrainian industrial enterprises. It is grounded that the relationship between employees and employers in Ukraine can be described by the term “neo-feudalism”. The authors systematized the negative consequences of neo-feudalism for labor productivity and staff security. Having considered the results of the study, the authors proposed a list of measures aimed at minimizing and eliminating those consequences.