Comparison Of Approaches Research Articles

A generative whole-brain segmentation model for positron emission tomography images

PurposeWhole-brain segmentation via positron emission tomography (PET) imaging is crucial for advancing neuroscience research and clinical medicine, providing essential insights into biological metabolism and activity within different brain regions. However, the low resolution of PET images may have limited the segmentation accuracy of multiple brain structures. Therefore, we propose a generative multi-object segmentation model for brain PET images to achieve automatic and accurate segmentation.MethodsIn this study, we propose a generative multi-object segmentation model for brain PET images with two learning protocols. First, we pretrained a latent mapping model to learn the mapping relationship between PET and MR images so that we could extract anatomical information of the brain. A 3D multi-object segmentation model was subsequently proposed to apply whole-brain segmentation to MR images generated from integrated latent mapping models. Moreover, a custom cross-attention module based on a cross-attention mechanism was constructed to effectively fuse the functional information and structural information. The proposed method was compared with various deep learning-based approaches in terms of the Dice similarity coefficient, Jaccard index, precision, and recall serving as evaluation metrics.ResultsExperiments were conducted on real brain PET/MR images from 120 patients. Both visual and quantitative results indicate that our method outperforms the other comparison approaches, achieving 75.53% ± 4.26% Dice, 66.02% ± 4.55% Jaccard, 74.64% ± 4.15% recall and 81.40% ± 2.30% precision. Furthermore, the evaluation of the SUV distribution and correlation assessment in the regions of interest demonstrated consistency with the ground truth. Additionally, clinical tolerance rates, which are determined by the tumor background ratio, have confirmed the ability of the method to distinguish highly metabolic regions accurately from normal regions, reinforcing its clinical applicability.ConclusionFor automatic and accurate whole-brain segmentation, we propose a novel 3D generative multi-object segmentation model for brain PET images, which achieves superior model performance compared with other deep learning methods. In the future, we will apply our whole-brain segmentation method to clinical practice and extend it to other multimodal tasks.

A bilateral comparison of 227Th activity standards between National Physical Laboratory and National Institute of Standards and Technology

Abstract The National Physical Laboratory (United Kingdom) and the National Institute of Standards and Technology (United States) each determined the massic activity of a common solution of 227Th. Measurements at both laboratories were performed before radioactive equilibrium. The direct comparison showed good accord between the laboratories’ activity standards with a t-test score of 0.15 based on ionization chamber measurements. Challenges associated with pre-equilibrium comparisons are addressed and multiple comparison approaches are presented. The use of a hybrid comparison methodology using a model to correct asynchronously acquired data to an intermediate timepoint mitigates major sources of uncertainty and potential bias in extreme cases.

Early Experience of Endoscopic Endonasal Approach for Craniopharyngiomas and Comparison with Supraorbital Keyhole Approach: A Case Series

Early Experience of Endoscopic Endonasal Approach for Craniopharyngiomas and Comparison with Supraorbital Keyhole Approach: A Case Series

Activity capacity-based urban shrinkage trend prediction model and response strategy comparison approach

Activity capacity-based urban shrinkage trend prediction model and response strategy comparison approach

Outcome measures in muscular dystrophy rehabilitation: an ICF content comparison approach to the most commonly used MD scales.

Functioning is the reason to be of rehabilitation as it is essential to the lives of people who suffer from a disease. The International Classification of Functioning, Disability and Health (ICF) can help in designing a functioning profile of a patient, identifying needs for rehabilitation plans and measuring the results of an intervention. To identify the outcome measurement instruments reported in clinical studies in muscular dystrophies (MDs) and provide an ICF content analysis. A systematic literature review was conducted until October 2022, using Medline, PubMed, and Scopus databases. Papers assessing outcomes related to functioning in patients with MDs were included. A total of 116 papers were included and all identified outcome measures were linked to the ICF. Inter-researcher agreement for the linking process was 0.82. The analysed instruments focused mainly on aspects of body functions, followed by activities and participation. General scales were more comprehensive than specific. The application of ICF in this research enhances the understanding of functioning of patients with MDs and the need to develop more specific but comprehensive scales tailored to the needs of MD patients, and can guide clinicians in a assessing patients through a biopsychosocial perspective.

When Personal Identity Meets Professional Identity: A Qualitative Study of Professional Identity Formation of International Medical Graduate Resident Physicians in the United States

International medical graduates (IMGs) account for 25% of the physician workforce in the United States, yet little is known about their professional identity formation (PIF). This qualitative study explores the process of PIF in IMG residents with special attention to how they integrate their intersectional marginalized personal identities. Method: Using a social constructivist approach, the researchers conducted semi-structured individual interviews with 15 IMG resident physicians in the United States. The authors analyzed the data using a constant comparison approach and identified themes by consensus. Results: Participants described their PIF journey beginning before starting residencies in the US. Their PIF was challenging due to structural barriers associated with their immigrant status. Furthermore, participants reported more difficulties with PIF if they did not look white. When their pre-existing professional and personal identities clashed with the American professional norm, the residents suppressed or compartmentalized these pre-existing identities. However, participants also reported that their diverse personal identities could be assets to the provision of care for diverse patient populations. Conclusions: This study reveals the identity tension experienced by IMGs in their PIF journey and the different strategies they employed to navigate the conflicts with American professional norms. This study suggests reimagining PIF frameworks to cultivate a more diverse physician workforce.

Mechanisms of increased pain discrimination by contingent reinforcement: a perceptual decision-making and instrumental learning account.

Recent evidence highlights that monetary rewards can increase the precision at which healthy human volunteers can detect small changes in the intensity of thermal noxious stimuli, contradicting the idea that rewards exert a broad inhibiting influence on pain perception. This effect was stronger with contingent rewards compared with noncontingent rewards, suggesting a successful learning process. In the present study, we implemented a model comparison approach that aimed to improve our understanding of the mechanisms that underlie thermal noxious discrimination in humans. In a between-subject design, 54 healthy human volunteers took part in a pain discrimination task with monetary rewards either contingent or noncontingent on successful discrimination of small changes in the intensity painful heat stimulation. We used models from 2 traditions in decision-making research, perceptual decision-making, and instrumental learning. Replicating the previous findings, only rewards contingent on behavior enhanced pain discrimination. Drift diffusion modelling revealed increased sensory signal strength and decreased response caution and nondecision times as mechanisms underlying this effect of contingent rewards on pain discrimination. In addition, reinforcement learning models indicated a temporal evolution of discriminative abilities reflected by a trial-by-trial increase of perceived signal strength only with contingent rewards but not with noncontingent rewards. Modelling of separate learning rates for positive and negative prediction errors indicated that this temporal evolution of discriminative abilities was driven by positive reward prediction errors. These results might indicate increased sensitivity towards better-than-expected outcomes in the temporal adaptation of pain discrimination abilities to a rewarding context in humans.

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.