Research In Field Research Articles

Image Classification Method Based on Multi-Scale Convolutional Neural Network

Traditional convolutional neural networks (CNNs) typically use fixed scale convolutional kernels for feature extraction when processing image classification tasks, while ignoring the multi-scale information present in the image. To overcome this limitation, we propose an algorithm based on multi-scale CNNs, which capture features at different levels by introducing convolutional kernels of different scales into the convolutional layer. In this study, we first designed a multi-scale convolutional layer consisting of multiple convolutional kernels of different scales to extract multi-scale features of the image. To further enhance classification performance, we introduced a multi-scale feature fusion module that can effectively fuse features of different scales and classify them through a fully connected layer. Then we conducted extensive experiments on several commonly used image classification datasets. The experimental results show that this network can not only effectively identify and locate hyperspectral image targets in different scenarios, but also reduce missed detections and false positives during the detection process. The average accuracy of the improved model has been improved, and the recognition accuracy of some small markers affected by external factors such as occlusion and lighting has also been improved. In addition, by comparing the detection effect of a single image, the progressiveness and anti-leakage ability of the improved model are proved. The image classification method based on multi-scale CNNs has broad application prospects in image recognition and feature extraction, and can provide valuable reference and reference for research in related fields.

Emerging Perspectives on the Application of Recommender Systems in Smart Cities

Smart cities represent the convergence of information and communication technologies (ICT) with urban management to improve the quality of life of city dwellers. In this context, recommender systems, tools that offer personalised suggestions to city dwellers, have emerged as key contributors to this convergence. Their successful application in various areas of city life and their ability to process massive amounts of data generated in urban environments has expedited their status as a crucial technology in the evolution of city planning. Our methodology included reviewing the Web of Science database, resulting in 130 articles that, filtered for relevancy, were reduced to 86. The first stage consisted of carrying out a bibliometric analysis with the objective of analysing structural aspects with the SciMAT tool. Secondly, a systematic literature review was undertaken using the PRISMA 2020 statement. The results illustrated the different processes by which recommendations are filtered in areas such as tourism, health, mobility, and transport. This research is seen as a significant breakthrough that can drive the evolution and efficiency of smart cities, establishing a solid framework for future research in this dynamic field.

A figure of merit for efficiency roll-off in TADF-based organic LEDs

Organic light-emitting diodes (OLEDs) are a revolutionary light-emitting display technology that has been successfully commercialized in mobile phones and televisions1,2. The injected charges form both singlet and triplet excitons, and for high efficiency it is important to enable triplets as well as singlets to emit light. At present, materials that harvest triplets by thermally activated delayed fluorescence (TADF) are a very active field of research as an alternative to phosphorescent emitters that usually use heavy metal atoms3,4. Although excellent progress has been made, in most TADF OLEDs there is a severe decrease of efficiency as the drive current is increased, known as efficiency roll-off. So far, much of the literature suggests that efficiency roll-off should be reduced by minimizing the energy difference between singlet and triplet excited states (ΔEST) to maximize the rate of conversion of triplets to singlets by means of reverse intersystem crossing (kRISC)5–20. We analyse the efficiency roll-off in a wide range of TADF OLEDs and find that neither of these parameters fully accounts for the reported efficiency roll-off. By considering the dynamic equilibrium between singlets and triplets in TADF materials, we propose a figure of merit for materials design to reduce efficiency roll-off and discuss its correlation with reported data of TADF OLEDs. Our new figure of merit will guide the design and development of TADF materials that can reduce efficiency roll-off. It will help improve the efficiency of TADF OLEDs at realistic display operating conditions and expand the use of TADF materials to applications that require high brightness, such as lighting, augmented reality and lasing.

The characteristics and functionalities of citizen-led disaster response through social media: A case study of the #HenanFloodsRelief on Sina Weibo

Using the topic of #HenanFloodRelief on Sina Weibo during the 2021 Henan floods as a case study, this research adopts a combination of social network analysis, content analysis, and text analysis to explore the characteristics and roles of public participation in disaster response through social media. The findings show that under the #HenanFloodRelief topic, the public was mainly involved in emergency response by posting help and rescue information, updating disaster information, and providing contact details for resource coordination. They also expressed emotions to reflect post-disaster social psychology, providing an emotional basis for social mobilization. Public and organizational participation demonstrated different characteristics, exhibiting the advantages of spontaneity and firsthand information. In contrast, organizational participation reflected professionalism and played a more significant role in providing emotional comfort and mobilization. The research demonstrates the vital role of social media in enabling public participation in disaster response while pointing out the potential risks of the public utilizing information resources for online relief efforts, highlighting the need for further research into effective information verification methods. This study provides a Chinese case to examine public participation in disaster response and offers insights into this field of research.

Ten dos and don’ts of Character Strengths Research

AbstractWhile both practitioners and the public regard character strengths positively, some psychologists and philosophers harbor skepticism. In this analytical commentary on current research and literature, we trace such skepticism to a premature focus on positive outcomes, which eclipsed the theoretical groundwork outlined in the 2004 handbook. We propose solutions to ten key issues which, in our estimation, not only sustain this skepticism but also hinder meaningful advancement in the field of character strengths research: (1) Criteria evaluation, (2) Virtue functions, (3) Situational affordances, (4) Content validity, (5) Criterion validity, (6) Fulfillment conceptualization, (7) Adverse outcome modeling (8) Moral excellency, (9) Strengths conservatism, and (10) Methodological mainstream thinking. We contend that resolving these issues is necessary to uphold the standing of character strengths and positive psychology among its counterparts, and to establish a potent foundation for effective character development.

An Empirical Research on the Effectiveness of the English Communication Ability Cultivation Program for International Applied Talents in Guangzhou College of Commerce

With the acceleration of globalization, Guangdong, as one of China's emerging economic development engines, has an increasing demand for international applied talents, among which English communication ability is particularly critical. This study designed a cultivation program to enhance the English communication abilities of international applied talents in Guangzhou College of Commerce, an institute in Guangdong, which included a series of training courses. The program was implemented over a one-year period with 300 college students. Through empirical research methods, by comparing the English abilities of participants before and after the training, the effectiveness of the cultivation program was verified. The results showed that participants' English communication abilities were significantly improved after systematic training, thereby affirming the positive role of the proposed cultivation program in enhancing the English communication abilities of international applied talents in Guangzhou College of Commerce. This study not only provides useful references for the training of international applied talents in Guangzhou College of Commerce and other institutes in Guangdong, but also offers new perspectives and practical foundations for future research in related fields.

Web-based spatial decision support system for precision agriculture: A tool for delineating dynamic management unit zones (MUZs)

Precision agriculture (PA) is a farming management concept that aims to provide agronomic, economic, and environmental benefits. One of the fields of research in PA is the delineation of Management Unit Zones (MUZs). MUZs are the sub-division of fields featuring an inter-zonal variation delineated by agronomists for on-field PA operations. To develop MUZs, three factors typically need to be considered: input multi-dimensional data, procedures to process the information, and the optimal number of zones a field should be divided into. PA uses digital technologies to collect and analyze a large amount of data, outline MUZs, monitor crops, and carry out site-specific crop management. Web-based spatial decision support systems (WB-SDSS) can provide users with tools that ease the complex procedures for PA. The objective of this study is twofold: on the one hand, we developed a free and open source (FOSS) WB-SDSS to facilitate the implementation and use of such tools for delineating MUZs and monitoring crops; on the other, a MUZs outline procedure was developed based on Sentinel-2 and Planetscope time series data, and spatio-temporal dynamic clustering model using fuzzy c-means. Our study highlighted that the WB-SDSS might be a helpful solution for harmonizing data collected from different sources, easing the implementation and use of complex geospatial procedures for PA, and delineating MUZs. We tested the system on a particularly representative farm in the Emilia Romagna region (Northern Italy), with 512 hectares of durum wheat crops. Using the WB-SDSS, we quickly delineated homogeneous zones for 27 fields in the study area during the phenological cycle of durum wheat (November 2018-June 2019).

The electrochemistry of stable sulfur isotopes versus lithium

Sulfur in nature consists of two abundant stable isotopes, with two more neutrons in the heavy one (34S) than in the light one (32S). The two isotopes show similar physicochemical properties and are usually considered an integral system for chemical research in various fields. In this work, a model study based on a Li-S battery was performed to reveal the variation between the electrochemical properties of the two S isotopes. Provided with the same octatomic ring structure, the cyclo-34S8 molecules form stronger S-S bonds than cyclo-32S8 and are more prone to react with Li. The soluble Li polysulfides generated by the Li-34S conversion reaction show a stronger cation-solvent interaction yet a weaker cation-anion interaction than the 32S-based counterparts, which facilitates quick solvation of polysulfides yet hinders their migration from the cathode to the anode. Consequently, the Li-34S cell shows improved cathode reaction kinetics at the solid-liquid interface and inhibited shuttle of polysulfides through the electrolyte so that it demonstrates better cycling performance than the Li-32S cell. Based on the varied shuttle kinetics of the isotopic-S-based polysulfides, an electrochemical separation method for 34S/32S isotope is proposed, which enables a notably higher separation factor than the conventional separation methods via chemical exchange or distillation and brings opportunities to low-cost manufacture, utilization, and research of heavy chalcogen isotopes.

Age-appropriate design of smart senior care product APP interface based on deep learning

With the aging of the population, the quality of life and happiness of the elderly are increasingly becoming concerns of society. Smart senior care (SSC) products are an important tool to improve the quality of life of the elderly, and their application has been widely discussed. However, due to differences in cognitive characteristics and habits of the elderly, they may face difficulties when using smart products. Therefore, how to design a suitable SSC product APP interface for the elderly has become an urgent problem to be solved. The rapid development of deep learning (DL) provides a new way to deal with this problem. This paper aims to optimize the APP interface design of SSC products suitable for the elderly by using DL technology. Specifically, this paper designs a model based on a deep-Q-network (DQN) algorithm, which can better adapt to the usage habits and needs of the elderly through training and optimization. At the same time, the proposed model is evaluated comprehensively to verify its performance and superiority. To achieve the above goals, this paper first summarizes the existing SSC technology and the design suitable for the elderly. On this basis, a model based on the DQN algorithm is designed, and four datasets are used for training and testing. In the design of the model, this paper pays special attention to how to make the interface more friendly and easy to operate to meet the specific demands and preferences of the elderly. After a comprehensive evaluation, it is found that the proposed DQN algorithm model has achieved remarkable improvement in performance. This model has an average return of about 8.8 and 3.9 compared to other models, which have an average return of about 0.9 and 0.2, respectively. This shows that the model designed in this paper performs well in terms of accuracy and average return and performs better than other algorithms. The results of this paper reveal that optimizing the age-appropriate design of the SSC product APP interface through DL technology can notably enhance the user experience and satisfaction of the elderly. This not only helps the elderly to make better use of smart products and improve their quality of life but also provides useful inspiration and guidance for research and practice in related fields.

The role of social and environmental sustainability on sportswear’s purchasing among European consumers

PurposeWhile consumer preferences for sporting goods have been widely researched within sport management, literature is lacking on aspects of social and environmental sustainability. Accordingly, this study aims to investigate the role of social and environmental sustainability for purchase decisions of sportswear and compares them to the role of price and functionality.Design/methodology/approachBased on a conjoint analysis among 1,012 Europeans, the authors conducted a two-step cluster analysis. First, the authors investigated the number of segments via Ward’s method. Second, the authors ran a k-means analysis based on part-worth utilities from the conjoint analysis.FindingsThe authors identified four segments which differ in terms of preferred product attributes, willingness to pay, and sociodemographic, behavioral, and psychographic characteristics: undecided, sustainable, price-focused and function-oriented consumers. Based on this segmentation, the authors found that the importance of social and environmental sustainability is growing, but not among all consumers.Research limitations/implicationsThe generalizability of the study is limited since it is not built on a sample representative for the included European countries, it focuses on a single product, and participants are potentially subject to a social desirability bias.Originality/valueThe consumer analysis comprises the uptake of attributes related to social and environmental sustainability. The authors thereby address a literature gap as previous research (thematizing sporting goods) in the sport management field has often neglected sustainability elements despite their rapidly growing importance within the sport sector.

Assessment of YouTube Videos on Frozen Shoulder: A Quality Analysis Using DISCERN and JAMA Scoring Systems

Background: Frozen shoulder, characterized by synovial inflammation and joint capsule fibrosis, impacts shoulder mobility and comfort. With the rise of online health information seekers, assessing the credibility of YouTube videos on frozen shoulder is crucial. This study employs DISCERN and JAMA scoring systems to evaluate video quality and explores potential differences between physician and non-physician contributors. Methods: The study screened the first 50 YouTube videos containing "frozen shoulder" in titles, excluding short, repetitive, and non-English content. Videos were categorized by content type, uploader, and key metrics recorded. Two observers independently scored videos using DISCERN and JAMA systems. Statistical analysis, including Mann-Whitney tests and Spearman correlation, assessed differences and agreement. Results: Among 50 videos, 45 featured real images, while 5 were animated. Physical therapists contributed the most (40%), and 60% focused on general information. Mean DISCERN and JAMA scores indicated predominantly poor quality. No significant differences were found between physician and non-physician videos. Observer agreement was excellent. Conclusion: Patients accessing YouTube for frozen shoulder information face challenges in discerning reliable content. Health professionals should contribute accurate videos, guiding patients to trustworthy online resources. Further research in orthopedics and other medical fields is essential to enhance the quality of health-related video content.

Analysis of influence of deep processing of metallic mineral materials on electromagnetic wave absorption performance

In this paper, the effects of deep processing of metallic mineral materials on electromagnetic wave absorption properties were studied. Firstly, the background and significance of the research are introduced, and the importance of metallic mineral materials in the field of electromagnetic wave absorption is expounded. Then the basic principle of electromagnetic wave absorption and the characteristics and influencing factors of metal mineral materials are discussed. In the section of deep processing technology, different processing methods and their applications are listed. Through experimental design and method, the electromagnetic wave absorption properties of metal mineral materials after deep processing are tested and analyzed. The experimental results are obtained and discussed. Finally, the application prospect of metallic mineral materials in electromagnetic wave absorption field is prospected, and the technical improvement and future development direction are put forward. This study provides an important reference for deepening the understanding of electromagnetic wave absorption properties of metallic mineral materials, and provides a reference for further research in related fields.

DanceMVP: Self-Supervised Learning for Multi-Task Primitive-Based Dance Performance Assessment via Transformer Text Prompting

Dance is generally considered to be complex for most people as it requires coordination of numerous body motions and accurate responses to the musical content and rhythm. Studies on automatic dance performance assessment could help people improve their sensorimotor skills and promote research in many fields, including human motion analysis and motion generation. Recent papers on dance performance assessment usually evaluate simple dance motions with a single task - estimating final performance scores. In this paper, we propose DanceMVP: multi-task dance performance assessment via text prompting that solves three related tasks - (i) dance vocabulary recognition, (ii) dance performance scoring and (iii) dance rhythm evaluation. In the pre-training phase, we contrastively learn the primitive-based features of complex dance motion and music using the InfoNCE loss. For the downstream task, we propose a transformer-based text prompter to perform multi-task evaluations for the three proposed assessment tasks. Also, we build a multimodal dance-music dataset named ImperialDance. The novelty of our ImperialDance is that it contains dance motions for diverse expertise levels and a significant amount of repeating dance sequences for the same choreography to keep track of the dance performance progression. Qualitative results show that our pre-trained feature representation could cluster dance pieces for different dance genres, choreographies, expertise levels and primitives, which generalizes well on both ours and other dance-music datasets. The downstream experiments demonstrate the robustness and improvement of our method over several ablations and baselines across all three tasks, as well as monitoring the users' dance level progression.

Automatic identification of stone-handling behaviour in Japanese macaques using LabGym artificial intelligence.

The latest advances in artificial intelligence technology have opened doors to the video analysis of complex behaviours. In light of this, ethologists are actively exploring the potential of these innovations to streamline the time-intensive behavioural analysis process using video data. Several tools have been developed for this purpose in primatology in the past decade. Nonetheless, each tool grapples with technical constraints. To address these limitations, we have established a comprehensive protocol designed to harness the capabilities of a cutting-edge artificial intelligence-assisted software, LabGym. The primary objective of this study was to evaluate the suitability of LabGym for the analysis of primate behaviour, focusing on Japanese macaques as our model subjects. First, we developed a model that accurately detects Japanese macaques, allowing us to analyse their actions using LabGym. Our behavioural analysis model succeeded in recognising stone-handling-like behaviours on video. However, the absence of quantitative data within the specified time frame limits the ability of our study to draw definitive conclusions regarding the quality of the behavioural analysis. Nevertheless, to the best of our knowledge, this study represents the first instance of applying the LabGym tool specifically for the analysis of primate behaviours, with our model focusing on the automated recognition and categorisation of specific behaviours in Japanese macaques. It lays the groundwork for future research in this promising field to complexify our model using the latest version of LabGym and associated tools, such as multi-class detection and interactive behaviour analysis.

Abstract 124: Validation of humanized TL1A mice for advancing preclinical research

Abstract TL1A, or Tumor Necrosis Factor-Like Ligand 1A, plays a pivotal role in regulating the immune system and has garnered considerable attention in the field of cancer research. Studies have shown that TL1A can impact the tumor microenvironment via inflammatory signaling, immunosuppression, and tumor growth and survival. Targeting TL1A or its downstream effects could offer new avenues for cancer treatment and immunotherapy. To this end, we generated a human TL1A knock-in (B-hTL1A) mouse model. Human TL1A gene expression in B-hTL1A mice was confirmed by RT-PCR. TL1A protein expression was not altered following TL1A humanization in B-hTL1A mice as shown by flow cytometry. Lastly, soluble human TL1A was detected in B-hTL1A mice by ELISA. Due to the purported role of TL1A in mucosal immunity, efforts to induce inflammatory bowel disease in this humanized model are currently underway. Taken together, we established a preclinical B-hTL1A mouse model for the evaluation of TL1A-targeted immunotherapy. Citation Format: Chong Li, Shujin Zhang, Zhi Zhang, Jia Feng, James Jin, Yibo Du. Validation of humanized TL1A mice for advancing preclinical research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 124.

Optimisation Studies of Mesoporous Silica Nanoparticle as a Drug Carrier for Gemcitabine: Enhancing Therapeutic Effectiveness in Pancreatic Cancer

Pancreatic cancer, often referred to as “the silent killer”, presents with minimal or no symptoms in its early stages, leading to late detection when surgical resection is no longer the optimal treatment option. Gemcitabine (GEM), one of the leading chemotherapeutic drug for advanced stages of cancer, is a crucial treatment for pancreatic cancer. However, the low 5-year survival rate of pancreatic cancer patients highlight the limited effectiveness of current treatments. In recent years, mesoporous silica nanoparticles (MSNP) have garnered significant attention in both scholarly and pharmaceutical fields due to their unique combination of properties including stable porous structure and high loading capacities. This research aims to investigate the potential of MSNP as a carrier for anticancer drugs, specifically GEM. MSNP was successfully synthesized in the laboratory using sol-gel method with tetraethyl orthosilicate (TEOS) as silica source and cetyltrimethylammonium bromide (CTAB) as surfactant template. Comprehensive morphological and physical characterizations of the MSNP product were performed through transmission electron microscopy (TEM), field emission scanning electron microscopy (FESEM), energy dispersive X-ray (EDX) spectroscopy, element mapping, X-ray diffractometry (XRD), and accelerated surface area porosimetry (ASAP). The results demonstrate that MSNP exhibits desirable properties for drug loading, including a stable mesoporous structure with pore size of ~ 4.94 nm, a high surface area of about 278.32 m²/g, and average particle diameter of approximately 85 nm. The effects of incubation time and initial GEM concentrations were studied to determine the optimal drug loading parameters for the MSNP vehicle. The successful loading of up to 24 µg of GEM in 1 mg of MSNP achieved in an optimized incubation time of 2 hour, validates the tremendous potential of MSNP as a potential anticancer drug carrier in pancreatic cancer treatment. These findings provide a valuable reference for future research and investigations in this promising field.

Role of the media in health awareness

The media play an active role in disseminating health information and data to a wide audience. This information includes messages about disease prevention, treatment methods and the latest research and developments in the medical field. This awareness is conveyed through educational programmes, articles and awareness campaigns. In addition, the media can motivate individuals and communities to take positive steps to improve their health. This is particularly important at a time when misleading information is easily disseminated. In general, the media are a fundamental pillar in raising awareness of health issues by providing information, education, advocacy and promoting positive changes in the health behaviour of individuals and communities. However, this field faces several obstacles and factors that we will address in this article.

Adaptation of the Turkish Family of Origin Scale and the Development of Parallel Short Forms

ABSTRACT There is a growing body of research in counseling-related fields that investigates the influence of the family of origin experience as a determinant for family patterns. We examined the psychometric properties of the Family of Origin Scale (FOS) in a Turkish sample to establish its applicability as a research tool and proposed a two parallel short version of the FOS. We addressed these objectives in two different studies. The purpose of these studies was to examine the applicability, validity, and reliability of these two FOS in a Turkish samples. In the first study, because of the exploratory and confirmatory factor analyses conducted with two other sample groups of university students, it was found that the theoretically proposed factor structure of the FOS needed to be supported in the Turkish sample. A reliable and valid single-factor structure was obtained in the Turkish-adapted version. In the second study, two short forms, each with 20 items, were created and applied to two different sample groups of university students. Both forms, each measuring intimacy and autonomy, had a single-factor structure and showed a strong and significant correlation with each other and the 40-item FOS. The outcomes of the present investigation indicate a strong and statistically significant link between the shortened and comprehensive forms of the FOS contributing to the assessment in marital family therapy.

Abstract 477: Tumor treating fields (TTFields) targeted self assembling nanoparticles for pancreatic cancer treatment: In vitro and in vivo assessment

Abstract Tumor Treating Fields (TTFields) is a novel, non-invasive and safe treatment modality, which is prescribed to be used in conjunction with classical anticancer chemotherapeutic drugs. TTFields when used alone are safe, but their use in combination with classical chemotherapy continues to offer drug related adverse reactions which ultimately impacts the patient compliance. To address this challenge, we earlier reported meticulously optimized self-assembling cationic-anionic polymer nanoparticles (S-CAP NPs) with average particle size of about 200 nM, encapsulation efficiency of 55-65 % and sustained drug release over 60 h. We also reported that, TTFields were capable of destabilizing the S-CAP NPs leading to targeted drug release. The results were also corroborated with in vitro cytotoxicity and colony formation studies in presence of TTFields using multiple pancreatic cancer cell lines. After establishing the proof-of-concept, the objective was to assess the in vitro cellular uptake of S-CAP NPs. For this, fluorescent dye loaded S-CAP NPs were developed and subjected to cellular uptake analysis. The in vitro cellular uptake studies confirmed the enhanced uptake of S-Cap NPs by passive diffusion in the pancreatic cancer cell lines compared to normal pancreatic epithelial cell line. The studies corroborated preferential cellular uptake of S-Cap NPs by the pancreatic tumor. Among all the formulations, the chitosan- bovine serum albumin S-CAP NPs was most optimum and was used for in vivo safety studies. For this, in vivo acute and repeated dose 28-day toxicity of the optimum placebo S-CAP NPs was conducted in Sprague Dawley rats (Western University of Health Sciences Protocol #R20IACUC031) and OECD guidelines. The in vivo studies showed a LD50 value above 2000 mg/kg and NOAEL value of 1000 mg/kg. These high doses safety of S-CAP NPs confirmed the potential of this approach for future preclinical efficacy studies followed by clinical translation. Lastly, the in vitro stability studies were conducted as per the ICH guidelines for a period of 36 months and the formulations were concluded to be stable. The tumor targeting potential, in vivo safety and stability of S-CAP NPs, establish their translational potential for TTFields triggered targeted drug release in cancer treatment. This approach will not only reduce the adverse effect associated with combination of TTFields and chemotherapy but can also be explored as a platform technology for management of other cancers. This study is supported by AACR-Novocure tumor treating fields research fellowship. Citation Format: Preshita Prafulla Desai, Sunil Prabhu. Tumor treating fields (TTFields) targeted self assembling nanoparticles for pancreatic cancer treatment: In vitro and in vivo assessment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 477.

Research of Innovation and Digital Transformation in Justice: A Systematic Review

Objective: To develop a mapping of studies on innovation and digital transformation in the justice sector, publishes from 2001 to 2022. Five research questions were defined: 1) How to define innovation and digital transformation introduced in the justice sector? 2) What types of innovations and digital transformations are implemented in the justice sector? 3) What are the objectives of introducing innovation and digital transformation in the justice sector? 4) What are the antecedents that influence the process of innovation and digital transformation in the justice sector? 5) What are the results of the innovation and digital transformation process in the justice sector?Methods: The systematic review of sources (scientific articles, conference proceedings, monographs and institutional documents) presented in this paper was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol. Selected by “research field”, “topic”, “research design”, “year of publication” and the keywords “public administration”, “public sector”, “e-justice”, “digital transformation”, and “innovation”, the sources were analyzed and evaluated according to five main aspects: (1) definition of innovation; (2) types of innovation; (3) objectives of innovation; (4) antecedents of innovation; and (5) results of innovation.Results: The heuristic model for studying innovation in the public sector developed by Vries et al. (2015) was adapted and applied to the research field of justice. The adaptation of the heuristic model allowed forming the following areas of analysis: contextual antecedents in justice; institutional antecedents in justice; characteristics of innovation and digital transformation in justice; individual antecedents in justice; types of innovation and digital transformation in justice; results of the process of innovation and digital transformation in justice.Scientific novelty: a comprehensive review of the literature in the field of innovation and digital transformation in justice is presented by adapting the approach to conducting systematic studies of the literature in the social sciences. It helped to identify gaps and define directions for further research in the given field, including the activation of comparative legal research, expansion of the methodological base, reliance on the theories of public administration, etc.Practical significance: the obtained results allow forming a heuristic map of innovation and digital transformation in justice, create antecedents (contextual, institutional and individual) and the basis for future empirical research in the field of justice, analysis, evaluation and improvement of public policy in the field of innovation and digital transformation in this area.