Identification Process Research Articles

Navigating the path to equitable rheumatologic care for underserved children with quality improvement.

The aim of this quality improvement project is to identify children with rheumatologic conditions to prevent delayed or missed diagnosis in underserved pediatric populations. Our focus is on prompt and accurate identification and subsequent treatment of rheumatologic symptoms in pediatric patients referred from Atrium Health safety-net primary care clinics that deliver care to families without private insurance, including those lacking insurance entirely. We collaborated with providers at one safety-net clinic to improve the processes of identification and subspecialty referral, resulting in an increase in the number of identified pediatric patients and referrals for these patients with potential rheumatologic disease. We used the Model for Improvement framework with rapid Plan-Do-Study-Act cycles and evaluated improvement with run and statistical process control charts. We achieved improvement, with zero referrals in the previous 5 years for the targeted population increasing to 15 patient referrals within 1 year of project initiation. Despite this increase in referrals, the rheumatology clinic was able to see all priority patients within 20 business days from referral. An awareness of concerning rheumatologic symptoms in safety-net primary care clinics, combined with the use of both visual and decision aids, allows care teams to efficiently recognize and accurately refer patients needing specialty care.

A hierarchical multistage holistic model for acoustic emission source monitoring in composites

Abstract This paper introduces a multistage smart structural health monitoring (SHM) model for carbon-fiber composites, with a focus on multiple types of acoustic emission (AE) source localization and classification. The SHM model uses time-frequency data from various AE events (such as tool drops, impact, and artificial debonding) across different zones of a composite structure. The SHM strategy demonstrates a robust smart monitoring of composites with high accuracy. Further, a hypothesis testing has been carried out that supports the superiority of a 2-stage identification process, revealing statistically significant higher accuracy and confidence intervals across all zones and AE source types. This research establishes a novel framework for solving a hierarchical multistage holistic damage source identification problem, offering robustness in identifying various damage scenarios and quantifying associated prediction uncertainties.

Factors Influencing Special Education Career Choices: Interplay of Personality Traits and Identity Statuses

<p style="text-align:justify">Recent research has identified factors influencing the choice of a special education career; however, it has not thoroughly examined their connection with personality traits and identity status. Thus, the present study was designed to explore how different personality traits and identity statuses correlate with the motives and perceptions associated with the choice to teach in special education. The study involved 209 pre-service special education teachers. The NEO-Five Factor Inventory was used to measure the Big 5 personality traits. The Ego Identity Process Questionnaire assessed identity commitment and exploration. The Factors Influencing Teaching Choice Scale was used to evaluate motivations and perceptions about teaching. Regarding the factors that influenced the decision to pursue a career in special education, intrinsic value, shaping children’s future, social equity, making social contributions, working with children, task demands, and job satisfaction were highly rated. Additionally, extraversion, openness to experience, conscientiousness, and identity statuses were identified as positive predictors for certain factors influencing the choice of a teaching career in special education. Finally, the study identified two distinct groups of students: "Identity Achievers" characterized by high positive personality traits, and identity commitment, and "Identity Explorers" characterized by lower positive personality traits and higher identity exploration. Differences were observed between the groups in their motives and perceptions concerning teaching in special education. In conclusion, this study highlights the relationships between personality, identity status, and career decision factors, offering insights into the factors that influence this critical career decision among future special educators. Directions for future research are discussed.</p>

ИССЛЕДОВАНИЕ СОЦИАЛЬНОГО ИНТЕЛЛЕКТА КУРСАНТОВ И АДЪЮНКТОВ САНКТ-ПЕТЕРБУРГСКОГО УНИВЕРСИТЕТА ГПС МЧС РОССИИ

The features of the manifestation of social intelligence of adjuncts and cadets during their studies at the Saint-Petersburg university of State fire service of EMERCOM of Russia are considered. The ability to understand the behavior, actions of students, their logic and adequacy, interrelationships and interdependence of social contacts was evaluated. The main means of solving the task set for the authors was the methodology of Joy P. Guilford, designed to help assess the level of social intelligence of two categories of university students – adjuncts and cadets. The authors managed to carry out a comparative analysis of the behavior of employees, their ability to recognize different meanings of phrases, understanding the logic of the emergence and development of socio-psychological contradictions and reactions to nonverbal expression. The specific features of the ways of expressing the sense of «WE» are associated with the aggravation of the processes of group identification and reference are indicated. The practical significance of the results obtained for cadets, adjuncts studying at the Faculty of training highly qualified personnel, scientific and pedagogical staff and heads of structural divisions of EMERCOM of Russia is substantiated.

Eyewitness Testimony – How Reliable is It?

This paper examines the intricacies associated with eyewitness testimony in legal settings, emphasizing its crucial role as evidence while also addressing its fundamental limitations. An eyewitness is described as an individual who witnesses an event firsthand, and their description can greatly influence the court's decisions. Nevertheless, factors such as stress, racial bias, focus on firearms, and memory lapses can compromise the accuracy of these accounts. The article analyses the legal framework established by the Bharatiya Sakshya Adhiniyam, 2023, which pertains to the competency of witnesses and the reliability of their testimonies. An analysis of the prominent wrongful conviction case of Ronald Cotton, highlights the fallibility of human memory. Furthermore, a review of pertinent psychological studies indicates that eyewitness memory is reconstructive and susceptible to inaccuracies. The necessity for corroborative evidence, expert opinions, and enhanced identification processes is highlighted as a means to improve the reliability of eyewitness testimonies and reduce wrongful convictions, thereby upholding the integrity of the trial process. In summary, this study advocates for a thorough reassessment of eyewitness testimony within a wider legal context to ensure justice.

Joint torque estimation method of industrial robot by combining error compensation model based on LSTM and iterative weighted parameter identification

It is essential for human-robot interaction to accurate joint torque value estimation of industrial robots without force/torque (F/T) sensors. The most common method to estimate the value of robot joint torque is based on dynamic model parameter identification. However, no matter how elaborate the modeling methods are used, there are always uncertainty errors when robot’s joint rotation direction changes. In this paper, an identification framework is proposed to estimate optimal model parameters, and a deep learning network is proposed to compensate for the uncertainty errors caused by the unmodeled dynamics part. At first, the dynamic parameters are estimated during the Least Squares (LS) identification process considering the noise influence and data outliers, and the nonlinear friction model is unified into the identification framework. Secondly, based on Long-Short Term Memory (LSTM) network, an error compensation model (ECM) is proposed to establish the mapping relationship between the joint motion and the identification errors. Finally, a 6-DOF robot is used for parameter identification and ECM validation. Experimental results show that the proposed identification method is better than the LS method. Compared with the torque value estimated by the identification method, the proposed ECM can compensate for the uncertainty errors and improve the torque estimation accuracy.

Adaptive Measurement and Parameter Estimation for Low-SNR PRBC-PAM Signal Based on Adjusting Zero Value and Chaotic State Ratio

Accurately estimating the modulation parameters of pseudorandom binary code–pulse amplitude modulation (PRBC–PAM) signals damaged by strong noise poses a significant challenge in emitter identification and countermeasure. Traditionally, weak signal detection methods based on chaos theory can handle situations with low signal-to-noise ratio, but most of them are developed for simple sin/cos waveform and cannot face PRBC–PAM signals commonly used in ultra-low altitude performance equipment. To address the issue, this article proposes a novel adaptive detection and estimation method utilizing the in-depth analysis of the Duffing oscillator’s behaviour and output characteristics. Firstly, the short-time Fourier transform (STFT) is used for chaotic state identification and ternary processing. Then, two novel approaches are proposed, including the adjusting zero value (AZV) method and the chaotic state ratio (CSR) method. The proposed weak signal detection system exhibits unique capability to adaptively modify its internal periodic driving force frequency, thus altering the difference frequency to estimate the signal parameters effectively. Furthermore, the accuracy of the proposed method is substantiated in carrier frequency estimation under varying SNR conditions through extensive experiments, demonstrating that the method maintains high precision in carrier frequency estimation and a low bit error rate in both the pseudorandom sequence and carrier frequency, even at an SNR of −30 dB.

Petrous bones versus tooth cementum for genetic analysis of aged skeletal remains.

A proper sampling strategy is important to obtain sufficient DNA for successful identification of aged skeletal remains. The petrous bone is the highest DNA-yielding bone in the human body. Because DNA extraction from the petrous bone is very destructive, the demand for other DNA sources is significant. When investigating aged skeletal remains, teeth are usually preserved, and recent studies have shown that DNA in teeth can be best preserved in the dental cementum that surrounds the surface of the tooth root. To extract DNA from the surface of the tooth root, a nondestructive method without grinding was used. Petrous bones and teeth from 60 archaeological adult skeletons were analyzed. The DNA yield, degree of DNA degradation, and STR typing success were compared, and the results showed higher DNA yield and higher amplification success in petrous bones, despite higher degradation of petrous bones' DNA. The greater success of petrous bones is associated with poorly preserved DNA in a quarter of the teeth analyzed. When teeth with badly preserved DNA were excluded from the statistical analysis, no differences in the success of STR loci amplification were observed even if DNA yield was higher in petrous bones, which can be explained by greater degradation of petrous bones' DNA. When teeth are well preserved, they can be used for genetically analyzing aged skeletal remains instead of petrous bones, and a rapid nondestructive extraction method can be applied to shorten the identification process and to physically preserve the biological specimen.

We Think There’s Been a Glitch

Forensic anthropology plays a pivotal role in the medicolegal system analyzing skeletal remains in forensic casework. With the increased incorporation of artificial intelligence (AI) and machine learning (ML), their continued application in the field promisesenhanced efficiency and accuracy in identification processes, trauma analyses, and decision-making. However, the integration of AI/ML also raises critical ethical concerns. The use of any technology involving human skeletal remains poses challenges related to privacy, consent, and the potential for dehumanization. Furthermore, the risk of bias within algorithms cannot be ignored—specifically, the inadvertent perpetuation of existing biases in training data, which can lead to incorrect identifications or skewed results. Addressing these concerns requires a balanced approach. Transparency in AI/ML design, clear guidelines for data collection and integration, and ongoing evaluation of algorithmic performance are essential. Additionally, interdisciplinary collaboration between anthropologists, ethicists, computer scientists, and legal experts would be a crucial step forward to ensure that the benefits of AI/ML are maximized while capturing the accountability and responsibilities within a legal and ethical context. Only through such an integrated approach can the potential of AI/ML in forensic anthropology be utilized as a tool responsibly, preserving the dignity of the deceased.

Identifying groundwater characteristics and controlling factors in Jiaozhou Bay’s northern coastal region, China: a combined approach of multivariate statistics, isotope analysis, and field empirical investigations

Explicit identification of hydrochemical processes and their controlling factors within groundwater systems is critical for the sustainable utilization of water resources in coastal urban areas. This study was undertaken in the North Coastal Region of Jiaozhou Bay (NCRJB), located in the eastern part of Shandong Province, China, an area grappling with significant issues of groundwater quality degradation and water scarcity. A total of 105 groundwater samples and 34 surface water samples, collected from 2020 to 2024, were analyzed and studied using various hydrogeological tools, multivariate statistical analyses, and water quality assessment methods. These include the Piper diagram, hydrochemical facies evolution diagram (HFE-D), Principal Components Analysis (PCA), correlation analysis, stable isotope analysis, Water Quality Index (WQI), and USSL diagrams. The results indicated that all surface water and pore groundwater samples were categorized as Na-Cl type, exhibiting high Total Dissolved Solids (TDS) and Electrical Conductivity (EC) values, characteristics that render them poor to unsuitable for drinking and irrigation purposes. The fracture groundwater is predominantly of the Ca-Na-Cl mixed type, with average suitability for irrigation and a limited proportion (22.5%) deemed suitable for drinking. Seawater intrusion, primarily through the surface water system, and the impact of human activities were identified as the predominant controlling factors con-tributing to the degradation of the local groundwater environment. Field empirical investigations further validated the results derived from hydrogeological assessments, multivariate statistical analyses, and isotopic approaches. The long-term shifts in hydrochemical properties, along with the latent threat of seawater intrusion, exhibit an upward trend during the dry season and show a certain degree of mitigation during the wet season. This study highlights that field investigations, in conjunction with hydrochemical tools, multivariate statistical analyses, and stable isotope analysis, can successfully furnish reliable insights into the predominant mechanisms governing regional groundwater evolution within the context of long-term and intricate envi-ronmental settings.

Novel Antioxidant Peptides from Fermented Whey Protein by Lactobacillus rhamnosus B2-1: Separation and Identification by in Vitro and in Silico Approaches.

Whey is a byproduct of the dairy industry and is rich in protein. To enhance the significance of such byproducts and find efficacious antioxidants for combating oxidative stress, this study reported on the preparation, purification, and identification of novel peptides with antioxidant activities from whey protein metabolites following fermentation by Lactobacillus rhamnosus B2-1. The isolation and identification processes involved macroporous adsorption resin column chromatography, gel filtration column chromatography, and liquid chromatography-tandem mass spectrometry. Therein, three novel antioxidant peptides (PKYPVEPF, LEASPEVI, and YPFPGPIHNS) were selected to be synthesized, and they demonstrated remarkable antioxidant activities in vitro chemical assays. PKYPVEPF, LEASPEVI, and YPFPGPIHNS (100 μg/mL) displayed a notable cytoprotective impact on HepG2 cells under oxidative stress induced by H2O2, increasing the cell viability from 49.02 ± 3.05% to 88.59 ± 10.49%, 82.38 ± 19.16%, and 85.15 ± 7.19%, respectively. Moreover, the peptides boosted the activities of catalase and superoxide dismutase in damaged cells and reduced reactive oxygen species levels. The molecular docking studies highlighted that these antioxidant peptides efficiently bound to key amino acids in the Kelch domain of Keap1, thereby preventing the interaction between Keap1 and Nrf2. In conclusion, PKYPVEPF, LEASPEVI, and YPFPGPIHNS demonstrated substantial antioxidant activity, suggesting their potential for widespread application as functional food additives and ingredients.

Identity development of Arab drama therapists: The role of ethnic boundary work

Previous studies have suggested that creative arts therapists who work in conservative societies must adapt their Western therapeutic ideologies to collectivist and traditional norms. Less is known about how these creative arts therapists construct and maintain their professional identity in diverse sociocultural contexts. Building on the literature that emphasizes the role of ethnic boundary work in professional identity processes, we examined how Arab drama therapists maintain, challenge, and negotiate ethnic boundaries in the process of professional identity construction.Participants were 38 Israeli-Arab drama therapists (36 female) working in Israeli-Arab schools. Data were collected through semi-structured interviews (27 participants) and playback theater groups (12 participants). Thematic analysis revealed three different forms of ethnic boundary work: "Distinguishing Arab identity from drama therapy", "Drama therapy as an act of challenging ethnic and gender boundaries", and "Negotiating ethnic boundaries within the context of drama therapy".The current study emphasizes the sociocultural context of boundary work by illustrating how Israeli-Arab drama therapists define their professional identity across ethnic, gender, and political tensions. We conclude with implications for research and practice.

A Comprehensive Framework for Machine Learning-Based Threat Intelligence in Health Information Systems

This research work provides a comprehensive architecture of Machine Learning based threat intelligence particularly for Health Information System (HIS). The number of cybersecurity threats executed by healthcare companies is even higher since healthcare organizations continue to introduce digitized data into medical data. This work employs complex machine learning techniques from the MIMIC-III Critical Care Database to develop a practical threat identification and mitigation system. In this case, the strategy of analysis involves selection of data, data processing, modeling and real time dangers identification considering both supervised and unsupervised learning. The results reveal that the proposed framework covers high performance indicators such as: accuracy that equals 97.92%, and the level of precision and recall which also equal 90% ROC AUC has reached 0.94. These results demonstrate that the framework can identify and categorise cybersecurity risks in systems of health information on a regular basis. It not only increases threat perception but also makes the system internally valuable for healthcare IT professionals since it contains real-time monitoring and anomaly detection functionality. Therefore, this study stands in support of the ongoing efforts to enhance the security of the healthcare bodies on the use of policies on cybersecurity so as to ensure the protection of individual patient’s information against new forms of threats.

Comparison of identification methods used in Forensic Anthropological services in four distinct institutes in Brazil and the United States

ABSTRACT Identifying unknown deceased individuals, especially those in advanced stages of decomposition, dismemberment, or burning, is a major medico-legal challenge. Forensic anthropologists play a crucial role in these cases due to the numerous characteristics that can be derived from bone remains. Their methods help evaluate the biological profile and individual characteristics, narrowing potential matches. This research investigates the identification methods used by forensic anthropologists in Medicolegal Institutes and Medical Examiner’s Offices in Brazil and the USA. Case reports from forensic anthropology institutes in Vitória, Rio de Janeiro, Porto Velho (Brazil), and New York City (USA) were analysed. In resolved cases, details such as the biological profile, trauma, decomposition extent, and individualization markers were documented. Statistical tests evaluated the association between these variables and identification outcomes. Conventional identification methods included dental analysis, DNA testing, and fingerprint analysis. Additionally, Bayesian methods, visual identification, prosthetics, and X-ray comparison proved useful. This study highlights that forensic anthropologists can employ a variety of methodologies beyond standard practices, enhancing the identification process in complex cases.

Exploring community resilience through Arctic residents' narratives in the Republic of Sakha (Russia).

This article uses the Resilient Community Development frame to explore how the residents from two coastal settlements in the Russian Arctic cope with the long-term effects of climate change, permafrost thaw and challenging socio-economic conditions. Semi-structured interviews were conducted in 2019 in Tiksi and Bykovsky (Republic of Sakha, Russia). These narratives were coded and qualitatively analyzed using the aforementioned framing as a guideline. This article shows that migration, mobility, culture, history, identity and extended networks play a key role in the way that these residents cope with disturbances and upheavals. Sharing past experiences and specific ways to interact with their natural environment, other neighbors and the land they live in are pivotal for the local social configuration and can underpin identity processes. This analysis demonstrates that residents' narratives regarding socio-economic challenges, climate change and permafrost thaw can inform us about short-term concerns, but also how to enhance long-term community resilience.

Athletic Identity and Sport Injury Processes and Outcomes in Young Athletes: A Supplemental Narrative Review.

Background: Identity formation, a primary developmental task of adolescence, may be particularly relevant to another commonly occurring event for young athletes-sport injury. Relationships between a subdimension of self-identity-athletic identity-and sport injury processes and outcomes have been documented in the general athlete population. The purpose of this supplemental narrative review is to explore the potential role of athletic identity in the risk of injury occurrence and responses to and consequences of injury among young athletes. Methods: Studies on athletic identity in relation to sport injury, with a focus on young athletes, were extracted from a recent scoping review and identified through an updated literature search from April 2020 through June 2024. A total of 23 studies were examined. Results: Across the studies reviewed, high levels of athletic identity were associated with a reluctance to report injury-related symptoms, a tendency to endorse attitudes and behaviors reflecting a willingness to play through pain and injury, intensified physical and psychological symptoms after injury, a disposition toward over-adhering to rehabilitation, high levels of postinjury coping skills, and better functional and return-to-sport outcomes after injury among young athletes. Conclusions: Athletic identity may, therefore, be a source of both strength and vulnerability in young athletes in terms of sport injury processes and outcomes.

Vision transformer introduces a new vitality to the classification of renal pathology

Recent advancements in computer vision within the field of artificial intelligence (AI) have made significant inroads into the medical domain. However, the application of AI for classifying renal pathology remains challenging due to the subtle variations in multiple renal pathological classifications. Vision Transformers (ViT), an adaptation of the Transformer model for image recognition, have demonstrated superior capabilities in capturing global features and providing greater explainability. In our study, we developed a ViT model using a diverse set of stained renal histopathology images to evaluate its effectiveness in classifying renal pathology. A total of 1861 whole slide images (WSI) stained with HE, MASSON, PAS, and PASM were collected from 635 patients. Renal tissue images were then extracted, tiled, and categorized into 14 classes on the basis of renal pathology. We employed the classic ViT model from the Timm library, utilizing images sized 384 × 384 pixels with 16 × 16 pixel patches, to train the classification model. A comparative analysis was conducted to evaluate the performance of the ViT model against traditional convolutional neural network (CNN) models. The results indicated that the ViT model demonstrated superior recognition ability (accuracy: 0.96–0.99). Furthermore, we visualized the identification process of the ViT models to investigate potentially significant pathological ultrastructures. Our study demonstrated that ViT models outperformed CNN models in accurately classifying renal pathology. Additionally, ViT models are able to focus on specific, significant structures within renal histopathology, which could be crucial for identifying novel and meaningful pathological features in the diagnosis and treatment of renal disease.

A systematic approach for scoping potential key biodiversity areas

AbstractThe new key biodiversity areas (KBA) standard is an important method for identifying regions of the planet‐hosting unique biodiversity. KBAs are identified through the implementation of threshold‐based criteria that can be applied to any target species and region. Current methods to rapidly assess the existence of potential KBAs in different areas of the planet still present important challenges, although they are needed to accelerate the KBA identification process for large numbers of species globally. We developed a methodology to scan geographical regions and detect potential KBAs under multiple criteria. We tested the methodology on 59 species of reptiles and amphibians in Italy through the application of selected KBA criteria. Potential KBAs were identified for multiple species under most criteria, covering 1.4%–12% of the study area, depending on analytical settings. Cell size used to identify KBAs played an important role in shaping the distribution of potential KBAs, also affecting the overlap between areas triggered by different criteria. New potential KBAs identified in this study are only partially coincident with current KBAs in Italy (previously identified for birds) and within the national protected areas.

Residents’ place attachment and tourist sexual behaviour in a European coastal tourist destination

PurposeDespite extensive research into residents’ attitudes towards tourist behaviour, little has been explored about the extent to which visitors’ practices contribute to the formation of residents’ bonds with their place of residence, which is also a tourist destination. Therefore, this research aims to determine how residents’ perception of tourist sexual behaviour affects their engagement with the urban environment and the image of the city and tourist destination in which they live. To structure and interpret the various attitudes of the residents surveyed, the authors used a conceptual framework based on identity process theory (IPT) in relation to residents’ attitudes and the impact of a particular dimension of tourist behaviour – their sexual practices – on their perceived connection to their place of residence.Design/methodology/approachA questionnaire was administered to a sample of 457 residents in Salou to collect data regarding their assessments of the sexual behaviour of tourists in their community. A cluster analysis was used to classify residents according to their attitudes and stances towards the different sexual practices of visitors and their evaluation of the importance of those practices for current and future tourism at the destination. Finally, an analysis of variance was performed to compare significant differences in attitudes towards tourist behaviour and the attachment to Salou among the different segments of residents identified.FindingsThe study identified four groups of residents classified by their attitudes towards tourist sexual behaviour: permissive bystanders, supportive expectants, ambivalent pragmatics and opposed rejectors. Two attitudinal components explain the differences between the groups: tolerance and personal interest, which are associated with how residents construct their bond with Salou in terms of place attachment (PA). These results align well with IPT, as they highlight processes of assimilation, evaluation and the contribution of symbolic significance to the place of residence, mediated by the perception of tourist sexual behaviour.Practical implicationsSome practical recommendations are offered to tourist destination administrations regarding the differences among residents’ attitudes towards tourist behaviour and PA. The findings can serve as a valuable tool for designing tourism policies aimed at selecting markets, as well as for marketing and promoting tourist destinations.Originality/valueThe originality of this study lies in that it considers the role of tourist sexual behaviour as a compositional element of the identity of the place – a tourist destination – where residents live, providing new empirical data on an under-researched academic issue. This article attempts to contribute to a critical perspective by conceptualising and introducing new elements for understanding the identity, attraction and sexuality of tourist sites. The study also connects with the urban analysis of tourist destinations, incorporating the role of sex into the social construction of the tourist city, the creation of identity and image and the attribution of symbolic meaning to destination settings.

A Digital Identity Intervention Incorporating Social Media Activities Promotes Identity Exploration and Commitment Among Emerging Adults

ABSTRACT Identity interventions that support young people by promoting adaptive identity processes have traditionally been designed for in-person group settings, making them time and resource intensive to implement. Here, we examine the feasibility and efficacy of the Bay Area Adult Development Program, a digital intervention program that combines reflection activities (adapted from past positive development programs) with social media activities (designed to leverage the affordances of social media for information access and social connection) to promote positive identity development among emerging adults. Following a pilot trial to assess the intervention procedure, a randomized controlled trial was conducted (Nenrolled = 267; Ncompleted = 141). Results showed that participants who completed both reflection and social media activities experienced increases in personal identity exploration and commitment (i.e. exploration in breadth, exploration in depth, commitment making, identification with commitment) and increases in exploration of vocational identity (i.e. in-depth career exploration), compared to those in the control condition. Moreover, the combination of reflection and social media activities was a more efficacious intervention treatment, compared to reflection alone. We provide evidence for the feasibility and efficacy of a digital intervention for emerging adults while pointing to future research directions on identity development in the digital context.