Expert Analysis Research Articles

The Impact of NGOs on Heritage Objects and Spaces

In the context of an increasing social interest in cultural heritage and, consequently, a wide range of increasingly diversified grassroots activities related to the protection of heritage objects and spaces, there is a growing need for identifying the dimensions of social impact on cultural resources. The analysis of this issue in this article is based on the case of a group of public benefit organizations which are engaged in protecting heritage objects and spaces. As a result, the article identifies a group of factors which represent organizations’ impact in this area, giving attention to the perspective of target heritage objects and spaces, their surroundings and social and economic environment, public authorities and institutions, indirect beneficiaries, as well as considering the criterion of the time of impact (immediate, deferred and potential effects). The analysis is based on desk research, including a literature review, expert analyses, and with regard to empirical studies – reports prepared by public benefit organizations, the content of their websites and social media.

Project-Based Learning Oriented E-Worksheets with QR Code Packaging: Validity and Practicality

The lack of use of innovative student worksheets makes the learning process less effective because it does not facilitate the student learning process properly. This study aims to describe the design, validity and practicality of electronic student worksheets oriented towards Project Based Learning with QR Code packaging on the fourth grade elementary school science content. This study uses the ADDIE model (analysis, design, development, implementation, evaluation). Data collection methods are carried out by observation, interviews, document studies, and questionnaires. Data analysis techniques use quantitative descriptive analysis and qualitative descriptive analysis. The results of this electronic student worksheet development research are: the design of electronic student worksheets oriented towards Project Based Learning with QR Code packaging on the fourth grade elementary school science content, electronic student worksheets are declared valid and feasible based on the validity index of 0.90 and the feasibility analysis of media experts obtained a validity index of 0.88, and is included in the range ≥ 0.8 meaning that the product developed is included in high validity. Based on these results, it can be concluded that the electronic student worksheet oriented towards Project Based Learning with QR Code packaging on the fourth grade elementary school science content is valid and suitable for use in the learning process.

Benign epileptiform variants in EEG: A comprehensive study of 3000 patients

BackgroundThe analysis of EEG demands expertise and keen observation to distinguish epileptiform discharges from benign epileptiform variants (BEVs), a frequent source of erroneous interpretation. The prevalence of BEVs varies based on geographical, racial, and ethnic characteristics. However, most data on BEVs originates from Western populations, and additional studies on different cohorts would enrich the existing literature. MethodsWe reviewed EEGs from our institutional database to study the prevalence of benign epileptiform variants and analyzed their frequency, topography, and other characteristics. Additionally, we investigated the co-existence of epileptiform discharges with BEVs. ResultsWe identified 296 patients with BEVs after reviewing 3000 EEGs (9.9%). The most common BEV was small sharp spikes (SSS), observed in 114 patients (3.8%). Wicket waves, 6 Hz spike and slow wave, 14 and 6 Hz positive bursts, and Rhythmic Temporal Theta of Drowsiness (RTTD) were identified in 67 (2.2%), 40 (1.3%), 39 (1.3%), and 35 (1.16%) patients, respectively and one patient with Subclinical Rhythmic EEG Discharges in Adults (SREDA). Additionally, we observed the co-existence of epileptiform discharges with BEVs, most commonly with SSS (27.8%). ConclusionsThe present study is a large study with 3000 EEGs to describe the BEV characteristics. BEVs were seen in 9.9% of patients, BSSS being the most common. There were minor differences in frequency, gender or age distribution compared to existing literature. We demonstrated the co-existence of epileptiform discharges. Morphological characteristics remain the cornerstone in recognising BEVs. EEG readers need to be aware of features of BEVs to avoid wrongly interpretation.

Improving GPR interpretation by applying image-enhancing attributes and machine learning techniques: A case study over Green Hill Cemetery in Frankfort, Kentucky

Ground-penetrating radar (GPR) enables noninvasive imaging in structural mapping applications such as unmarked grave detection. However, burial signatures can be cryptic and require expert analysis. This study investigates attribute enhancement and machine learning to automate identification of variable-signature graves at Green Hill Cemetery in Frankfort, Kentucky. Nine complementary seismic attributes were computed from the GPR envelope reflectivity volume to boost discontinuities and patterns indicative of shafts. Coherent energy, pseudofrequency, and similarity transforms showed optimal visualization enhancement. These volumes were input into unsupervised k-means and self-organizing map (SOM) machine learning models to cluster potential burial sites. Both methods accurately characterized strong anomaly reflections associated with apparent grave boundaries. However, limitations emerged in classifying subtler signatures that are likely linked to deteriorated or deeper interments. SOM clustering provided finer segmentation between noise and targets. Collectively, attributes amplified burial edges for easier recognition, while machine learning clustering expedited identification of most vault structures and unmarked sites. However, edge case discrimination remains a challenge. Results suggest that hybrid human-machine learning analysis can enhance efficiency over purely manual interpretation. With further method refinement, automated attribute and machine learning workflows show strong potential for accelerating GPR-based cemetery and archaeological mapping.

Peculiarities of identification and customs commodity examination of children’s goods

Special attention is paid to the issue of identification and safety of children's products, which is aimed at ensuring the safety and quality of this category of goods. In the scientific article, the issue of classification of goods of group 95 in accordance with the Ukrainian Commodity Nomenclature of Foreign Economic Activity was considered, and a study of the practice of appointing customs examinations was conducted. The main identifying features of the classification of scooters in the category of goods for children are: purpose; design features, their modification; type of movement; number and diameter of wheels; type of ride Attention should also be paid to the following identification features of children’s goods, which are necessary both during customs control and during the examination of toys: the size of the toy, the material of manufacture, design features, application and main functional purpose. The development and improvement of current methods of identification of toys will simplify the procedure of their inspection and increase the objectivity of the results. The work summarizes the ways to classify children’s scooters in the procedure of commodity examination. The diagnostic tasks of the forensic commodity examination to determine safety, compliance with standards, which the expert must solve during the study of a children’s scooter, are defined. State-of-the-art research methods, in particular, visual inspection, functional tests, measurement of geometric parameters, mechanical tests, chemical analysis of materials, technical expertise, safety tests, computer modeling and analysis, electrical and electronic tests, expert evaluation are used to establish indicators. quality and safety of goods and obtaining objective information. The main identification tasks of the commodity examination of children’s scooters, the most typical defects of these products and defects that indicate their low quality are indicated. The mechanism of forensic commodity examination of children's scooters is described.

Mathematical Approaches to Crime Data Analysis: Enhancing Evaluation and Prevention Strategies

Crime data analysis is crucial for assessment and prevention. This research study examines mathematical techniques to crime data analysis to find effective ways to identify crime trends and design effective preventative methods. The report opens with an overview of the situation, noting rising crime rates and the need for new analysis. Crime data analysis's historical backdrop, mathematical and statistical methods, technical advances, and theoretical frameworks are covered in a thorough literature review. The study covers data collection, preprocessing, analytical technique selection, model assessment, and validation. Crime data interpretation is tested using predictive modelling, geographical analysis, clustering, classification, and network analysis. Case studies show successful implementations and compare methods. The discussion part discusses the results, crime prevention techniques, and limits and obstacles. Future research suggestions are given. This study summarizes major themes, policy consequences, and future prospects, adding to crime data analytic expertise. This study uses mathematical methods to help law enforcement and policymakers improve crime prevention. Keywords: - Crime Data Analysis, Mathematical Approaches, Predictive Modelling, Spatial Analysis, Crime Prevention Strategies

Written vs generated text: “naturalness” as a textual and psycholinguistic category

In the context of the development of text generation technologies, the opposition “naturalness − unnaturalness of text” has been transformed into a new dichotomy: “naturalness – artificiality”. The aim of this article is to investigate the phenomenon of naturalness in this context from two perspectives: analyzing the linguistic characteristics of a natural text against a generated (artificial) text and systematizing introspective perceptions of Russian native speaker informants as to what a “natural” text should be like and how it should differ from a generated text. The material for the study was a parallel corpus of film reviews in Russian, consisting of two subcorpora: reviews written by people and those generated by a large language model based on prompts, which are the beginnings of reviews, from the first subcorpus. The following methods were applied for the comparative analysis of the two subcorpora: computer-assisted text processing for calculating the values of 130 metrics of text linguistic complexity, psycholinguistic experiment, expert text analysis, contrastive analysis. As a result, it was determined that from the point of view of their own linguistic characteristics, “natural” texts differ from generated texts mainly by greater flexibility of syntactic structure, allowing both omission or reduction of structures and redundancy, as well as by slightly greater lexical variability. Naturalness as a psycholinguistic category is related to the informants’ autostereotypical ideas about the cognitive characteristics of people as a species. The analysis of texts erroneously attributed by informants (generated, labelled as natural and vice versa) showed that a number of characteristics of this autostereotype are overestimated by informants, while others, in general, correlate with the linguistic specificity of texts from the subcorpus of written reviews. In conclusion, we formulate definitions of naturalness as a textual and psycholinguistic category.

Critical expert analysis of permanent magnet synchronous motors identification methods and state variable observers

Relevance. In recent years, the oil industry has seen a tendency to transfer low-yield oil wells to intermittent mode. Unregulated electric drive and the open-loop controlled electric drive of electric centrifugal pumping with permanent magnet synchronous motors are typically not suitable for tasks of intermittent operation of wells. Due to objective reasons, there may not be smooth starts and required quality indicators of transient processes, which leads to even more reduction in oil production. The synthesis of a closed-loop electric drive control system of submersible installations is possible only using algorithms for indirect estimation of non-measured mechanical coordinates of the electric drive – state variables identification methods, observers of the rotor angular velocity and the load torque. The installation of sensors of angular velocity and torque on the shaft of the submersible electric motor is associated with technical difficulties, therefore, there is no need for significant modernization of the hardware solutions of the existing electrical equipment system. To date, the theory of identifying non-linear dynamic systems is widely used to derive an indirect estimate of the non-measured state variables of the permanent magnet synchronous motors. The large number of methods presented in scientific sources requires comparative analysis regarding their benefits and disadvantages in order to select the best identification method that meets the requirements of the oil production and takes into account its specificity and features. In this case, identification systems that are focused on minimizing computing power or operating in real time are given priority. Aim. To determine the best in terms of computational complexity and the convenience of practical use method of identifying state variables of permanent magnet synchronous motors operating in submersible oil well pumping units based on comparative analysis of existing methods presented in Russian and foreign sources. Methods. Methods for system analysis and identification of dynamic systems, a method of critical expert analysis. Result and conclusions. The most common methods for identifying and observing the state variables of synchronous motors with permanent magnets have been described in detail, given the general performance of each group of methods, their benefits and disadvantages were reviewed. By comparative critical expert analysis, it was found that for tasks of submersible electric centrifugal pump units electric drive a Luenberger observer, characterized by relatively low computational complexity and ease of setup in engineering practice can be recommended.

К проблеме допустимости доказательств

This article addresses the issue of the admissibility of evidence in criminal proceedings, specifically focusing on the use of results from operational investigative activities, expert conclusions, and testimonies. Until now, the issues of their legalization and recognition as admissible evidence remain controversial. The relevance of this study is underscored by the need in legal theory and practice to recognize the distinct role of non-procedural information in criminal proceedings, which holds significance for the case, and to develop approaches to its legal interpretation and application, considering the sources and methods of its acquisition. The aim of this publication is to justify the necessity of fully reflecting the results of operational investigative activities and expert studies in the materials of pre-trial investigation and criminal cases for subsequent judicial review. To achieve this goal, a number of tasks are solved, including: analysis of approaches to understanding the stated problem that have emerged in the scientific legal literature, determination of legal ways to solve it within the framework of current legislation. An overview of the procedural process of judicialization is provided, with emphasis on the possibilities of interrogating personnel conducting operational support and specialists performing individual studies, the results of which are then subject to verification and evaluation in accordance with the requirements of relevance and admissibility of evidence. In conclusion, the integration of operational investigative results and expert analyses as admissible evidence in criminal proceedings requires balanced approaches that uphold procedural integrity while accommodating the complexities of modern investigative techniques. By advancing these discussions, policymakers and legal practitioners can foster a more robust framework for evidence evaluation and judicial decision-making.

Pilot educational intervention for the care of adolescents with autism spectrum disorder during puberty

ABSTRACT Puberty is a particularly vulnerable time for individuals with autism spectrum disorder (ASD) during which baseline challenges are exacerbated, functioning often deteriorates, and additional barriers emerge. Specific concerns include increased vulnerability, decreased safety, and increased mood and behavioral disturbances. Youth with ASD need guidance and explicit instruction/skill development on topics such as hygiene/self-care, appropriate sexual activity, and menstruation management. Lack of provider preparation, knowledge, and confidence, along with stigma about the needs and capabilities of individuals with ASD, are major barriers to care. Initiatives to expand the preparation of health care personnel, including nurse practitioners, to provide quality care to individuals with ASD are essential. This article describes the results of a pilot project using a brief, self-guided educational intervention for developing and practicing family nurse practitioners. Before and after viewing the educational module, participants completed author-created surveys assessing their self-perceived knowledge, attitudes, and intent to change practice. Expert analysis of survey items provided face validity. Comparison of mean presurvey and postsurvey responses showed significant increases in self-perceived knowledge, attitudes, and intent to implement practice changes. Lack of confidence was endorsed as the most common remaining barrier to change. Findings indicate that the brief module improved participants' self-reported knowledge, attitudes, and intent to implement practice recommendations. Such interventions can be easily incorporated into nursing education and professional development and are appropriate for dissemination to including nurse practitioners working within and outside primary care settings, as well as to related service providers.

Deep-Learning-Based Automatic Sinkhole Recognition: Application to the Eastern Dead Sea

Sinkholes can cause significant damage to infrastructures, agriculture, and endanger lives in active karst regions like the Dead Sea’s eastern shore at Ghor Al-Haditha. The common sinkhole mapping methods often require costly high-resolution data and manual, time-consuming expert analysis. This study introduces an efficient deep learning model designed to improve sinkhole mapping using accessible satellite imagery, which could enhance management practices related to sinkholes and other geohazards in evaporite karst regions. The developed AI system is centered around the U-Net architecture. The model was initially trained on a high-resolution drone dataset (0.1 m GSD, phase I), covering 250 sinkhole instances. Subsequently, it was additionally fine-tuned on a larger dataset from a Pleiades Neo satellite image (0.3 m GSD, phase II) with 1038 instances. The training process involved an automated image-processing workflow and strategic layer freezing and unfreezing to adapt the model to different input scales and resolutions. We show the usefulness of initial layer features learned on drone data, for the coarser, more readily-available satellite inputs. The validation revealed high detection accuracy for sinkholes, with phase I achieving a recall of 96.79% and an F1 score of 97.08%, and phase II reaching a recall of 92.06% and an F1 score of 91.23%. These results confirm the model’s accuracy and its capability to maintain high performance across varying resolutions. Our findings highlight the potential of using RGB visual bands for sinkhole detection across different karst environments. This approach provides a scalable, cost-effective solution for continuous mapping, monitoring, and risk mitigation related to sinkhole hazards. The developed system is not limited only to sinkholes however, and can be naturally extended to other geohazards as well. Moreover, since it currently uses U-Net as a backbone, the system can be extended to incorporate super-resolution techniques, leveraging U-Net based latent diffusion models to address the smaller-scale, ambiguous geo-structures that are often found in geoscientific data.

Clinical Pharmacogenetics Implementation Consortium Guideline for CYP2B6 Genotype and Methadone Therapy.

Methadone is a mu (μ) opioid receptor agonist used clinically in adults and children to manage opioid use disorder, neonatal abstinence syndrome, and acute and chronic pain. It is typically marketed as a racemic mixture of R- and S-enantiomers. R-methadone has 30-to 50-fold higher analgesic potency than S-methadone, and S-methadone has a greater adverse effect (prolongation) on the cardiac QTc interval. Methadone undergoes stereoselective metabolism. CYP2B6 is the primary enzyme responsible for catalyzing the metabolism of both enantiomers to the inactive metabolites, S- and R-2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (S- and R-EDDP). Genetic variation in the CYP2B6 gene has been investigated in the context of implications for methadone pharmacokinetics, dose, and clinical outcomes. Most CYP2B6 variants result in diminished or loss of CYP2B6 enzyme activity, which can lead to higher plasma methadone concentrations (affecting S- more than R-methadone). However, the data do not consistently indicate that CYP2B6-based metabolic variability has a clinically significant effect on methadone dose, efficacy, or QTc prolongation. Expert analysis of the published literature does not support a change from standard methadone prescribing based on CYP2B6 genotype (updates at www.cpicpgx.org).

Optimizing Components Selection in Blended Learning: Toward Sustainable Students Engagement and Success

Selecting the most appropriate components for a blended learning course is a multifaceted challenge influenced by various criteria. The impact of these influential criteria on the design process is not always obvious. The aim of this study is to assist academics in designing sustainable and engaging blended courses by investigating the impact of these criteria on the selection of blended learning components. By selecting the right mix of components, academics can foster a sustainable and meaningful involvement of students in their learning process over time, ensuring that students’ engagement is both enduring and beneficial in achieving academic success. A modified Delphi survey was utilized in this study, involving the participation of eighteen experts experienced in instructional design and online teaching. The analysis primarily relied on quantitative methods, utilizing the mean (to indicate central tendency) and standard deviation (to measure dispersion) for presenting the experts’ responses. Additionally, qualitative analysis of experts’ comments provided deeper insights into their quantitative ratings. Findings indicate that face-to-face collaborative activities should be the preferred method of delivery for academics aiming to enhance students’ engagement and foster their higher-order thinking skills, which students often find challenging. However, this approach is most effective when the group size is manageable. For larger student groups, online collaborative work can be a suitable alternative, provided there is ample online resource support. The results also indicate that online self-paced learning can be advantageous for lower-order thinking learning outcomes, particularly in situations where teaching staff is limited.

Parent attitudes towards data sharing in developmental science.

Data sharing in developmental science is increasingly encouraged, supported by funder and publisher mandates for open data access. Data sharing can accelerate discovery, link researchers with high quality analytic expertise to researchers with large datasets and democratise the research landscape to enable researchers with limited funding to access large sample sizes. However, there are also significant privacy and security concerns, in addition to conceptual and ethical considerations. These are particularly acute for developmental science, where child participants cannot consent themselves. As we move forward into a new era of data openness, it is essential that we adequately represent the views of stakeholder communities in designing data sharing efforts. We conducted a comprehensive survey of the opinions of 195 parents on data sharing in developmental science. Survey themes included how widely parents are willing to share their child's data, which type of organisations they would share the data with and the type of consent they would be comfortable providing. Results showed that parents were generally supportive of curated, but not open, data sharing. In addition to individual privacy and security concerns, more altruistic considerations around the purpose of research were important. Parents overwhelmingly supported nuanced consenting models in which preferences for particular types of data sharing could be changed over time. This model is different to that implemented in the vast majority of developmental science research and is contrary to many funder or publisher mandates. The field should look to create shared repositories that implement features such as dynamic consent and mechanisms for curated sharing that allow consideration of the scientific questions addressed. Better communication and outreach are required to build trust in data sharing, and advanced analytic methods will be required to understand the impact of selective sharing on reproducibility and representativeness of research datasets.

The Impact of the Political System of the Republic of Serbia on Shaping Foreign Policy After 2012

Abstract Since 2012, the Republic of Serbia has been governed by the Serbian Progressive Party, and since 2017 its chairman has also been the president, who has full power in his hands. In the first years after taking power, this group implemented a policy that could have been surprising to public opinion, considering the fact that it separated from the Serbian Radical Party. The negotiations on Kosovo, which brought a number of agreements, the diplomatic offensive that created Serbia as a European partner and regional hegemon, dynamic progress in the EU accession process and the promotion of Western European values were the elements that noticeably exposed the change in the image of this country in relation to the previous decades. However, the second term of government began to fit into the pattern of the global phenomenon of populism, leading to the ruling group taking over the structures of the separation of powers and limiting democracy in the country. Subsequent general elections brought the strengthening of this party in the structures of the state, whose level of democracy was rated increasingly lower in international rankings. Moreover, the political system of Serbia itself began to be presented in scientific and expert analyses as an example of stabilitocracy. The aim of this topic is to analyse the specific power of President Aleksander Vučić and his party in relation to shaping the state’s multi-vector foreign policy.

Development of a knowledge base for operational diagnostics of synchronous generators of autonomous generator complexes

A method for operational monitoring of the technical condition of synchronous generators (SG) of autonomous generating complexes based on a fuzzy inference system is considered. For diagnostics based on expert analysis, knowledge bases for the SG module and analytical expressions are developed to determine the influence of the operational indicators of the object under study on its technical condition. Keywords:synchronous generator, operational diagnostics, fuzzy modeling, neural network, knowledge base kryukov@nntu.ru, steklov84@mail.ru

Using Adaptive Potential to Counteract Crisis Situations in the Context of Ensuring Financial Security and Business Sustainability of Enterprises

Abstract The main purpose of the article is to identify key factors of adaptive potential that can have a significant impact on counteracting crisis situations and increasing the level of financial security and business resilience of enterprises. The object of the study is determination of the factors of adaptive potential that directly affect the system of financial security and business sustainability of a enterprise. The scientific task is to model the hierarchical ordering of the key factors of adaptive potential according to the level of their significance in influencing crisis situations in the context of ensuring the financial security and business sustainability of enterprises. The research methodology involves the use of expert analysis methods with the additional use of the Delphi method, the method of hierarchical analysis, and graph theory. As a result of the study, a list of the most significant factors of adaptive potential for countering crisis situations was presented. As a result, the factors of adaptive potential are hierarchically ordered from the most significant to the least significant in ensuring the financial security of the enterprise. The innovativeness of the results obtained is revealed through the proposed approach to modeling the determination and order of factors of adaptive potential to counteract crisis situations. The study is limited by not taking into account the specifics of specific enterprises. Prospects for further research are aimed at taking into account the specific type of activity of enterprises for a specific country.

Geodata Processing Methodology on GIS Platforms When Creating Spatial Development Plans of Territorial Communities: Case of Ukraine

The article offers a detailed expert analysis on handling spatial information of territorial communities amid administrative and land reforms. The authors have developed multiple methodological recommendations and justified the selection of efficient tools for contemporary GIS systems. It also delves into the essence of GIS technologies, the nuances of working with geodata, and provides a concise overview of the world's most prevalent GIS platforms. The paper outlines an algorithm for developing a land resource management strategy for communities in preparation for land reform. Through the analysis and visualization of spatial data, the paper highlights enhancements in economic valuation and the ability to pinpoint risks and infringements of property rights. The study selects the Cadastr.UA system on the Soft.Farm platform, developed by Ukrainian company Quart Soft, as a notably user-friendly and promising GIS for land accounting and auditing. Research based on the experimental practical application of most functions of GIS Cadastr.UA indicates that this system aligns well with the needs for land plot accounting and auditing within the framework of Ukraine's Public cadastral map. The paper details the practical implementation of GIS technologies, using Cadastr.UA as a case study, and illustrates how to employ selected GIS tools in various scenarios and tasks.

Expert Analysis on the User Interface of an Academic E-Supervision Application Based on Vocational Education Character

Designing information systems to accommodate the unique needs of various users receives a lot of attention in contemporary software engineering. One such distinctive requirement in the educational context is academic supervision. Academic supervision encompasses activities to assist educators in enhancing their skills for managing the learning process and achieving educational objectives. In vocational high schools, the primary educational goals are to prepare students for the job market and empower them to initiate their businesses. These goals can only be realized if teachers incorporate technical and entrepreneurial skills into learning. The main goal of this study is to assist school supervisors and principals in assessing and directing teachers as they incorporate ideas of vocational education into the teaching and learning process. The research methodology used in this study is research and development, which includes several stages: initial needs analysis and assessment of the current state of academic supervision; development, which involves the creation of a conceptual system model; system interface design; model validation and revision; and evaluation, which requires system testing, implementation, and deployment. Based on the initial investigation and analysis of academic supervision, particularly in the context of vocational education, this research presents a conceptual model and system interface design. The outcomes of this research encompass the interface, system architecture, and user guide for the academic e-supervision system. An expert analysis of the user interface design indicates that the interface received positive evaluations from experts, with an overall average rating of 88%.

Intentional Homicides and Alcohol Abuse in Lithuania

The aim of the present study is to examine the links between high intentional homicide rates and alcohol abuse in the context of social transition in Lithuania. According to the extant literature, both the increase in homicide rates and the increase in alcohol abuse have a negative impact on public health and are often associated with challenges at the macrosocial level. In recent decades, Lithuania has experienced substantial political, economic, and social transformations. Lithuanian society has transitioned from a Soviet regime to embrace the Western principles of liberal democracy. Yet, despite positive political and economic progress, Lithuania remains a country with one of the highest homicide and alcohol-related harm rates in the European Union. These characteristics have made the Lithuanian homicide situation a captivating topic for a range of international and national studies, expert analyses, and evaluations. Unfortunately, the lack of reliable and consistent data on homicide continues to obstruct researchers from delving deeper into the analysis and explanation of the homicide phenomenon in Lithuania. To mitigate this issue, in this work, we present thoroughly collected and processed historical data on intentional homicide trends from 1961 to 2022. We also examine changes in the rate of homicide suspects, including their socio-demographic characteristics and alcohol intoxication for the 2004–2022 period. Finally, we investigate changes in homicide mortality rates and homicide victims’ socio-demographic characteristics. Our analyses are based on data sourced from the Lithuanian Special Archives, as well as national and international databases of crime statistics and demographic data. We noted a continuous decline in intentional homicide rates after the steep increase in 1989–1994. Furthermore, between 2004 and 2022, more than half of intentional homicide suspects were under the influence of alcohol. These findings are discussed in the broader context of societal changes in Lithuania.