Comparison Of Approaches Research Articles

Characterization for the Similarity Assessment Between the Proposed Biosimilar SB17 and Ustekinumab Reference Product Using State-of-the-Art Analytical Methods.

SB17 is being developed as a biosimilar to ustekinumab reference product (RP), a human monoclonal antibody (IgG1 kappa immunoglobulin) that binds to the common p40 subunit of cytokines interleukin (IL)-23 and IL-12. Binding to this subunit prevents interaction with their receptor, resulting in modulation in the immune system responses that play a key role in inflammatory disease. The objective of this study was to demonstrate structural, physicochemical, and biological similarity between ustekinumab RP and SB17 using various state-of-the-art analytical methods. Comprehensive analytical characterization was conducted by the quality range and side-by-side comparison approach for SB17 versus the European Union (EU) and US ustekinumab RP using various analytical methods. Comparisons included purity, product-related impurity, charge heterogeneity, primary structure, posttranslational modification, higher-order structure, quantity, Fab-related biological activities (potency and binding activity), and Fc-related biological activities. On the basis of the analytical similarity assessment, the structural, physicochemical, and biological characterization results demonstrated that SB17 is comparable to the ustekinumab RP. In the structural aspects, it was confirmed that there is no clinically meaningful difference between posttranslational modification profiles and higher-order structures of SB17 compared with the ustekinumab RP. Product-related impurities in the form of aggregates were also confirmed to be similar. SB17 has lower acidic and basic variants compared with ustekinumab RP, owing to the difference in the producing cell line. Ustekinumab RP is expressed in an Sp2/0 cell line, whereas SB17 is expressed in CHO cell line. However, the difference between SB17 and ustekinumab RP in the charge variants is not considered to be clinically meaningful, since equivalent biological activity was observed. In the case of mechanism of action (MoA)-related biological activities, SB17 is highly similar to the EU and US ustekinumab RP with respect to overall critical and noncritical quality attributes analyzed. Moreover, similarity or lack of activity in Fc-related biological activities was also confirmed. On the basis of these results, SB17 is expected to have comparable safety and efficacy as compared with ustekinumab RP. In summary, the overall analytical characterization and similarity assessment results show that SB17 is comparable to the EU and US ustekinumab RP in terms of structural, physicochemical, biophysical, and biological attributes.

A Fuzzy Analytical Network Process Framework for Prioritizing Competitive Intelligence in Startups

Competitive intelligence (CI) is a critical tool for startups, enabling informed decision making through the systematic gathering and analysis of relevant information. This study aims to identify and prioritize the key factors influencing CI in startups, providing actionable insights for entrepreneurs, educators, and support organizations. Through a systematic literature review, key variables and components impacting competitive intelligence were identified. Two surveys were conducted to refine these components. The first employed a five-point Likert scale to evaluate the significance of each component, while the second used a pairwise comparison approach involving ten experts in CI and startup mentorship. Utilizing the fuzzy Analytical Network Process (ANP), this study ranked Technology Intelligence as the most critical factor, followed by market and Strategic Intelligence. Competitor Intelligence and Internet intelligence were deemed moderately important, while Organizational Intelligence ranked lowest. These findings emphasize the importance of technology-driven insights and market awareness in fostering startups’ competitive advantage and informed decision making. This study provides a structured framework to guide startups in prioritizing CI efforts, offering practical strategies for navigating dynamic market conditions and achieving long-term success.

NIRsViT: a novel deep learning model for manure identification using near-infrared-spectroscopy and imbalanced data handling

The robust and accurate identification of different forms of manure stands as a pivotal imperative within the domain of agriculture. Near-infrared (NIR) Spectroscopy has emerged as an expeditious, efficient, non-destructive, and reliable approach to addressing this challenging task. NIR spectroscopy has the potential to serve as a valuable tool for the classification and identification of manure varieties. In order to enhance fertilizer identification performance, this study proposes a novel model called NIRsViT which classifies fertilizers by employing a combination of deep learning Vision Transformer model on NIR spectral data. The introduced model’s performance outperforms existing deep learning models, with an F1-Score of 86.42% and an accuracy rate of 95.19%. Additionally, the model’s classification performance has been significantly improved by proposed imbalanced data processing approaches, Focal Loss, and Upsample, with an F1-Score up to 93.91%, the improved F1-score proved that imbalanced data was considerably solved. The proposed method is a promising approach to handling imbalanced NIR spectral data and acts as a pioneering benchmark for subsequent models in manure identification through NIR spectroscopy. Future research gears toward improving the NIRsViT model’s temporal efficiency and computational load, while also testing the introduced imbalanced data handling approach for efficiency comparison across various models and larger datasets.

Должностное лицо полиции как субъект административно-процессуальных отношений: теоретико-правовой аспект

Introduction. A wide range of tasks facing internal affairs bodies, a significant load on police officials, as well as the direct dependence of law and order on the effectiveness of their activities – all this determines the relevance of the search for ways to optimise the administrative and procedural status of a police officer. On a daily basis, police officials carry out proceedings on cases of administrative offences, regularly conduct reception of citizens (including complaints proceedings). A police official often has an official need to take part in administrative proceedings. In addition, within the framework of intra-organisational service relations, each police officer is a potential participant in disciplinary, performance appraisal and promotion proceedings. The aim of this article: on the basis of achievements of administrative-procedural theory to formulate new conclusions about the concept and content of the status of a police official as a participant of administrative-procedural relations, to classify types of administrative-procedural proceedings with the participation of police officials. Methods. General methods of cognition (comparison, analysis, synthesis, abstraction, system, structural and functional approach) were used in the work. Results. The concept of administrative-procedural relations, a participant of which is a police official, is formulated; types of administrative proceedings, a potential participant of which is a police official, are defined, and their classification by various criteria is carried out; some shortcomings of administrative-procedural legislation, enshrining the status of a police official as a participant of administrative-procedural relations, are revealed.

A Comparative Study of the User Interaction Behavior and Experience in a Home-Oriented Multi-User Interface (MUI) During Family Collaborative Cooking

This study sought to ascertain the necessity of crafting specialized multi-user interfaces for scenarios involving multiple users and to provide guidance for the design of multi-user human–computer interactions by identifying the disparities in the interaction behavior and user experience when employing a conventional one-user interface (OUI) recipe versus a multi-user interface (MUI) recipe in the context of family collaborative cooking. To address this objective, this study employed a before-and-after comparison approach. Subsequently, adult users submitted self-assessments of their experiences using the OUI and MUI. The evaluation tools included a user experience survey questionnaire and a Likert seven-point scale, including aspects such as visual confirmation, content, operation, and satisfaction. Post-experiment interviews were also conducted with family members. The MUI exhibited greater effectiveness in terms of visual confirmation, with the “layout” assuming a role analogous to that of “text” in facilitating visual confirmation. Moreover, the operation of the MUI was found to be somewhat enjoyable. Nevertheless, no significant disparities were observed between the OUI group and the MUI group concerning content readability and most operational aspects. Furthermore, the users described their satisfaction with the MUI to be superior to that of the OUI, offering fun, convenience, and a clear appearance. Findings from my research clearly demonstrate that it is both valuable and essential to design a dedicated MUI.

Framing of Differences: Visual Product Frames Reduce Consumer Choice Deferrals

Consumer choice deferral contributes to the low conversion rate in online retailing. This article investigates the impact of visual product frames on consumers’ decisions regarding choice deferral. The authors show that using visual frames to separate options in a product assortment increases consumers’ relative use of the by-alternative (vs. by-attribute) approach for option comparisons, which induces greater perception of assortment variety and subsequently decreases choice-deferral rate. Through seven preregistered studies (including an eye-tracking study and a field experiment), the authors obtain convergent empirical evidence for these proposed effects and suggest actionable guidelines for online retailers regarding how to best design their product displays to encourage sales.

MSR127 Synthetic Data Generation: A New Approach for Population-Adjusted Indirect Treatment Comparisons Tested in Diabetic Macular Edema

MSR127 Synthetic Data Generation: A New Approach for Population-Adjusted Indirect Treatment Comparisons Tested in Diabetic Macular Edema

Semi-supervised learning for skeleton behavior recognition: A multi-dimensional graph comparison approach

Semi-supervised learning for skeleton behavior recognition: A multi-dimensional graph comparison approach

Formulation and evaluation of herbal tablet of jackfruit root for the treatment of antiasthmatic activity

Abstract Jackfruit is a highly nutritious plant. The ancient fruit known as jackfruit (Artocarpus heterophyllus Lam) is commonly eaten raw. Documenting the therapeutic value of the main jackfruit parts (Artocarpus heterophyllus L.) was the primary goal of this study. It contains more protein, calcium, iron, and Thiamine. Jackfruit contains many classes of phytochemicals such as carotenoids, flavonoids, volatile acids sterols, and tannins, with varying concentrations. The excellent medicinal efficacy of Artocarpus has long been recognized. Phenolic compound test. Next, using a direct comparison approach, we developed pills for asthma. After that, check evaluations such as degradability, hardness, friability, homogeneity of content, weight change, solubility, etc. The health benefits of jackfruit are attributed to its many physicochemical applications. Jackfruit is some tropical fruit rich in 4,444 nutrients such as carbohydrates, proteins, vitamins, minerals, and digestive fiber to maintain bronchial pain relief. In the case of asthma, a person suffers from bronchospasm and this herbal tablet acts as a bronchodilator. Therefore, we examined the antiasthamatic characteristics using a herbal mixture prepared from jackfruit root. Jackfruit contains vitamin A, vitamin C, thiamin, riboflavin, calcium, potassium, iron, sodium, zinc, and niacin, among many other nutrients.

Accounting support for innovative solutions in medical institutions

Intellectual property in medicine is the most important tool for stimulating innovation and protecting scientific achievements. Patents, copyrights and other forms of intellectual property contribute to the development of medical science and technology and create incentives for investment in research and development. This article is devoted to topical issues that reveal the features of accounting for intellectual property in healthcare institutions. The following methods were used in the study: analysis and synthesis, comparison, logical and systems approaches. As a result of the study, information was obtained on the rapid development of medical technologies, pharmaceuticals and digital solutions that significantly increase the role of intellectual property in healthcare. Accounting as the most important management function, along with regulation and planning, is inextricably linked with the protection of intellectual assets and is important as a tool for increasing the competitiveness of healthcare institutions, strengthening their financial stability and stimulating innovation. It is concluded that the reflection of intellectual property in the accounting system of medical institutions plays a key role in management, and it must be constantly developed and improved, taking into account modern challenges and technological innovations. Prospects for improving intellectual property accounting in healthcare are directly related to progress in digital technologies. The results reflected in this article can be used in the educational process of higher education institutions and in the practical work of accounting departments of modern organizations (including healthcare).

A new way to address missing data in late-stage clinical trials

According to ICH E9(R1), defining the estimand comes before defining the analysis approach, and the strategies for addressing intercurrent events are key components of the estimand. With the composite strategy, the problem of missing data disappears, because it becomes part of the endpoint definition. It is this perspective that we adopt in addressing the problem of missing data. We propose comparing patients in a pairwise manner to determine which patient fared better, one patient from each group, taking into account the reason for and timing of missingness. For purposes of illustration, reasons for missingness are placed into three categories: (1) death or adverse events, (2) administration of rescue medication (treated as missing even if patient continues in the study, or a poor score is assigned), and (3) other reasons such as loss to follow-up or withdrawal of consent. Each pair of patients is compared on the endpoint of interest. The comparison outcomes are determined based on the presence of missing data, its category, and timing. For instance, if both patients in a pair have received rescue medication, the patient with the later time of rescue medication is considered to have fared better. The overall treatment effect is estimated from combining results across all pairwise comparisons. This method allows the reason and timing of missing data to contribute to the assessment of treatment effects, providing a solution to some limitations of existing methods. Thus, the pairwise comparison approach addresses the missing data problem transparently via the composite strategy.

The Impact of Digital Transformation on Service Models and Employee Skill Requirements in Taiwan's Real Estate Brokerage Industry

This paper investigates how digital transformation impacts service delivery models and employee skill requirements in Taiwan's real estate brokerage industry. Through a multiple-case comparison approach, data was collected from 200 participants across real estate firms to examine organizational adaptation to technological change. The research employed structural equation modeling and hierarchical linear modeling to analyze relationships between compensation satisfaction (β = 0.45, p < 0.001), digital competency levels, and internal case circulation patterns. Results demonstrate that digital technologies significantly reshape brokerage operations, with digitalized companies achieving 32% higher client acquisition rates and 45% reduction in transaction processing time. Analysis reveals that employee digital literacy accounts for 28% of performance variance, while organizational support systems explain 23% of technology adoption rates. The findings extend service innovation literature by establishing empirical links between compensation systems and digital transformation success, providing a practical framework for technology integration in Taiwan's real estate sector. This research offers evidence-based recommendations for firms implementing digitalization strategies and developing employee capabilities in response to industry evolution.

Linguistic landscape in russian-speaking schools of Visaginas

The article describes the sociolinguistic situation in Visaginas, while also introducing the main theoretical provisions and terms of sociolinguistics (sociolinguistic situation, language policy, linguistic landscape, enculturation, etc.). The analytical part examines specific data – cultural signs compiled in the Russian-speaking schools in Visaginas – allowing the linguistic landscape to be examined through the lens of enculturation. The linguistic landscape analysis and the comparison approach were applied within the course of work. 1,142 units ‒ symbols of Russian and Lithuanian cultures compiled in three educational institutions with the Russian language of tuition – were analyzed. The material that had been classified in accordance with the groups (visual, complex, textual signs) allowed us to establish the predominance of the Lithuanian culture in the educational institutions of Visaginas Town. It also showed the presence of the signs of culture of different types.The importance of this research stems from the understudied language landscape, particularly in educational institutions. Furthermore, it should be noted that the educational linguistic environment of Visaginas has never been studied before.

Assessing Cognitive and Perceptual Abilities in Imaginative and Mainstream Elementary Schools: A Case Comparison

This study investigates the impact of imaginative pedagogy on the cognitive and perceptual abilities of elementary school students aged 7-8, using a case comparison approach. Focusing on a Waldorf school as a case for imaginative education and a mainstream Greek school, the research examines abilities including Spatial, Linguistic, Kinesthetic, Naturalistic, Mathematical and Musical. The study utilized a mixed method consisting of playful assessment activities and classroom observations to evaluate these abilities comprehensively. The findings reveal that students in the Waldorf school demonstrate significant advantages in the Spatial, Linguistic, Kinesthetic and Naturalistic areas, attributed to the school's imaginative teaching methods. More specifically, imaginative pedagogy is shown to resonate well with competences related to physical activities, language processing, understanding of the natural world, and visual-spatial reasoning. In contrast, there are no significant differences in Math-Logic and Musical abilities between the two school types, despite the traditional emphasis on language and mathematics in mainstream Greek schools. The study highlights the potential benefits of imaginative pedagogy for holistic cognitive development, suggesting its applicability in mainstream education. Received: 15 July 2024 | Revised: 21 October 2024 | Accepted: 30 October 2024 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The data that support the findings of this study are openly available in Mendeley Data at http://doi.org/10.17632/y2hkn43sd8.1. Author Contribution Statement Emmanouil Mavrelos: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Writing - original draft, Writing - review & editing. Thanasis Daradoumis: Conceptualization, Writing - review & editing, Supervision.

A novel intelligent bearing fault diagnosis method based on image enhancement and improved convolutional neural network

Bearing fault diagnostic is crucial for ensuring the normal operation of equipment. However, the working environment of mechanical equipment is often very harsh, the collection of fault data is limited in the actual industrial process. The problem of insufficient fault samples occurs, which makes the feature extraction ability of the deep learning models drop dramatically. To solve this terrible problem, an intelligent diagnosis framework based on image enhancement and an improved convolutional neural network (IEICNN) is outlined in this article. First, a signal conversion method based on feature fusion is employed to convert multi-channel one-dimensional vibration signals into red − green − blue (RGB) images to obtain more comprehensive fault data representation. In addition, a new image enhancement method is proposed, which uses the improved Squeeze and Excitation-Residual Network (SE-ResNet) to learn and extract the advanced feature map, and uses deconvolution neural networks to reconstruct RGB image. Finally, the Softmax classifier is applied to identify the health conditions of the bearing. The superiority and robustness of IEICNN are validated using two bearing datasets. By comparing with several progressive comparison approaches, it is proven that the proposed approach has better robustness and effectiveness in the case of limited data scarcity.

Health technology assessment of nailfold capillaroscopy and digital retina imaging in diabetes screening

AimThis study aims to identify the criteria for the evaluation of medical technologies in diabetes screening and then perform health technology assessment (HTA) for two technologies: digital retina imaging (DRI) and Nailfold Capillaroscopy (NFC). MethodsA multicriteria decision-making tool measuring attractiveness using a categorical-based evaluation technique (MACBETH) was used to calculate and compare alternatives. A focus group of ten decision-makers with more than ten years of experience in health technology was used for the decision-making. The Delphi Method was used to get a consensus about comparing criteria and alternatives to these criteria. The sampling method used in the study was the nonprobability purposive sampling method. ResultsThe study concluded that clinical efficacy (0.42) is the most important criterion for evaluating medical technologies, followed by cost-effectiveness (0.27). At the same time, ethical considerations were found to be less important (0.03). The sensitivity analysis concluded that the decision is sensitive to clinical efficacy and cost-effectiveness changes. The study found that none of the alternatives dominates others as an option for early detection of diabetes through vascular changes. LimitationsThis study primarily uses systemic literature review methods to identify criteria for evaluating alternatives. There may be additional criteria for evaluation. ConclusionThis study provides an approach for a multicriteria comparison of medical devices. The study findings are useful for public health professionals and health policymakers. Plain language summaryThis study assesses nailfold capillaroscopy (NFC) as a substitute for digital retina imaging (DRI) in diabetes screening using the MACBETH multicriteria decision-making tool. The research identifies five key evaluation criteria: clinical efficacy, cost-effectiveness, patient needs, user safety, and ethical considerations. A focus group of experienced health technology decision-makers was used to compare NFC and DRI. Results indicate that clinical efficacy and cost-effectiveness are the most critical factors, with NFC showing potential but not significantly outperforming DRI. Sensitivity analyses highlight the need for further research to validate NFC as an effective diabetes screening tool.

JOINT LOW-RANK REPRESENTATION AND TRANSFER MULTI-VIEW LEARNING APPROACH FOR EEG EPILEPSY CLASSIFICATION

Classification of epileptic electroencephalograms can provide strong technical support for early warning and monitoring of epilepsy. However, Electroencephalogram (EEG) has characteristics of specificity, multi-feature, and susceptibility to noise interference. Therefore, this paper proposes a joint low-rank representation and transfer multi-view learning (LRR-TML) approach for EEG epilepsy classification. The LRR-TML approach inherits the advantages of low-rank representation, filters redundant features and noise information, and focuses on the main feature and significant feature of EEG. The LRR-TML approach introduces the ideas of transfer learning and multi-view learning on the framework of low-rank representation, mines the linear correlation between different domains in the subspace through low-rank representation, and effectively transfers the discriminative knowledge of the source domain to the target domain. According to the principles of complementarity and consistency of views, the LRR-TML approach comprehensively describes EEG by integrating various features, maximizing the consistency between different views and minimizing the divergence between views. Experimental results on the Bonn dataset show that the LRR-TML approach achieves the best classification results among all comparison approaches.

An optimized pair-wise comparison approach for automated feature weight assignment in content-based image retrieval system

An optimized pair-wise comparison approach for automated feature weight assignment in content-based image retrieval system

On the Use of Image Analysis for Hematocrit Evaluation in Dried Blood Spots

Dried blood spots (DBSs) are formed by collecting a small sample of blood on specialized filter paper and allowing it to dry naturally. Various domains of life sciences and drug research extensively use DBSs as a sampling technique. The “Hematocrit (Ht) effect” affects assay bias, and several strategies have been put forth to deal with it, including the correction of quantified concentrations using an appropriate correction factor. The approach was previously applied, following the utilization of an image processing algorithm developed in Matlab® to derive a reliable equation correlating DBS areas to Ht% values. The present work looks more closely at the application of image analysis to the evaluation of Ht in DBS samples. Utilizing image analysis software, DBS samples with known Ht values were processed. Preparation of cards has followed a previously developed protocol for the appropriate formation of uniform area DBSs, irrespective of Ht. The resulting areas showed close resemblance to the respective theoretical areas calculated by applying the correlation equation. Following that, the equation was utilized to determine the Ht values for each sample, and a comprehensive comparison of measured versus calculated Ht was carried out using various statistical approaches for method comparison. The results demonstrated a strong correlation, suggesting the method’s viability in estimating Ht for unknown DBS samples.

From Data to Decisions: Analyzing PaRIS for Health Policy Insights

Abstract To inform countries on how well they perform from the perspective of people living with chronic conditions in comparison with other countries, we propose an analytical framework for the data collected in the PaRIS survey, detailing how the data will be analysed in a multilevel approach for cross-country comparison. The data structure of the PaRIS survey represents three levels: countries/health systems, primary care practices and patients. Multilevel analysis is used because of its accuracy in estimating country-level outcomes, its flexibility in modelling relationships, and its opportunities in connecting to relevant policy questions. Country-level outcomes will be estimated to facilitate cross-country comparison and (future) within-country comparison over time. A first indication for areas for cross-country learning and policy making is the distribution of variation over patients, care providers and countries. Characteristics of patients that potentially explain variation in patient-reported outcomes and experiences can be linked to primary care practice and country/health system characteristics. The second indication for areas for cross-country learning and policy making is the variation in the slope of the association between patient and practice characteristics and patient-reported outcomes and experiences. This makes it possible to address policy-relevant questions relating, e.g., to whether some health systems or providers are better able to produce positive outcomes and experiences for (e.g.) older patients, and to the impact of chronic care management on patients with a specific chronic condition. To ensure fair cross-country comparisons, all outcomes will be estimated for an OECD (age and sex standardised) reference population, also including case-mix adjustment where necessary. Analyses will be repeated using a country-specific standard population.