Identical Functions Research Articles

Понимание идентичности в контексте культурно-исторической психологии

In the context of cultural historical psychology, it is proposed to view identity as an explication of a life project. A synergetic methodology is used, within which development is considered not only as a process determined by heredity and environment (internal and external), but also as a process of self-organization, leading to selfconstruction of the subject. In a constantly changing world, understanding identity as a stable structure of the subject’s representations, reflecting one’s actual state, is replaced by understanding the fundamental incompleteness of the “auto-project” text narrated by the subject of life, which implies the analysis of the (re)constructed author of this project. As it turned out, the growth of the complicated subject’s thinking leads to the organizational complication of the “auto-project” text. Three types of identity texts have been distinguished (personal, social, predictive), which differ by the methods of identity description. Personal identity is a collection of the descriptive characteristics of a subject. Social identity means the (re)construction of social space and the choice of social roles. The predictive identity as a representation of future vital roles provides an opportunity for the subject to plan the achievement of potential life goals. The expanded understanding of identity functions is revealed: starting as the knowledge about the self and the regulator of behavior in a social context, it becomes the instrument of self-organization, which allows making some adjustments into the life project of the subject. The depth of social identity (autonomous personality, representative of a group, citizen of society) will determine the scale of life tasks available to the subject. It is shown that as a result of the processes of circular causality, the increase in the complexity of thinking leads to the complication of the organization of any identity, which, being a tool for a self-development, provides some opportunities for the deployment of the existing human potential.

An Intrusion Detection Method based on Fusion Neural Network

Aiming at the problems of class imbalance, insufficient feature learning, weak generalization ability, and representation capability in existing intrusion detection models, we propose a multi-scale feature fusion Intrusion Detection Model (MSFF). This model combines multi-scale one-dimensional convolution and bidirectional long short-term memory (LSTM) networks, and incorporates residual connections with identity mappings to address the problem of network degradation. The multi-scale convolution captures feature representations at different levels, thereby improving the expressive power of the model. The WGAN-GP algorithm is employed to augment the minority samples and balance the dataset. By performing convolution operations and extracting local window features and global features using bidirectional LSTM units, the model effectively captures temporal information and long-term dependencies. Experimental results demonstrate significant performance improvement compared to a single model. The MSFF model achieves an accuracy of 99.50% and 94.73% in binary classification experiments on the NSL-KDD and UNSW-NB15 datasets, respectively, and an accuracy of 99.50% and 83.78% in multi-class classification experiments.

A qualitative examination of social identity and stigma among adolescents recovering from alcohol or drug use

IntroductionAlcohol and other drug (AOD) use disorders are stigmatized conditions, but little is known about youth’s experience of this stigma, which may threaten their developing social identity and recovery process. This study investigates youth’s perceptions of AOD use-related stigma in the context of their social identity. MethodsThis study uses data from 12 youth (ages 17–19) who were in recovery from problematic AOD use. Participants completed a Social Identity Mapping in Addiction Recovery (SIM-AR) exercise, in which they created a visual map of their social groups, and semi-structured interview, in which participants were asked about their experience creating their SIM-AR and reflections on their social network. SIM-AR data were descriptively analyzed, and interviews were thematically analyzed for instances of stigma. ResultsUsing stigmatizing terminology, participants expressed some stigmatizing attitudes towards themselves and others in their network who used substances and perceived both positive and negative reactions from those who knew about their disorder. Findings suggest that youth may experience some internalized stigma and perceive stigma from others in their social networks, which may be a barrier to the development of a healthy social identity and engagement in recovery supports. ConclusionsThese findings should be considered when seeking to engage youth in treatment and recovery programming. Despite the small sample, the findings suggest the importance of considering how stigma may influence adolescents’ treatment and recovery experience in the context of their social environment.

Personal identity, somatic symptoms, and symptom-related thoughts, feelings, and behaviors in adolescence: Examining between- and within-person associations and the role of depressive symptoms.

Recent literature highlights the complex relationship between personal identity and body-related pathology, yet there is a lack of integrative longitudinal research on the relationship between identity and somatic symptoms. The present study investigated the longitudinal associations between identity functioning and (psychological characteristics of) somatic symptoms, and examined the role of depressive symptoms in this relationship. A total of 599 community adolescents (Time 1: 41.3% female; Mage = 14.93, SD = 1.77, range = 12-18 years) participated in three annual assessments. Using cross-lagged panel models, a bidirectional relationship between identity and (psychological characteristics of) somatic symptoms, mediated by depressive symptoms, emerged at the between-person level; whereas only a unidirectional relationship from psychological characteristics of somatic symptoms to identity functioning, mediated by depressive symptoms, emerged at the within-person level. Identity and depressive symptoms were bidirectionally related at both levels. The present study suggests that adolescent identity development is closely related to somatic and emotional distress.

Edge convolutional networks: Decomposing graph convolutional networks for stochastic training with independent edges

After the success of Graph Convolutional Networks (GCN), many stochastic training methods have been proposed to resolve the scalability and efficiency issues of GCN by sampling. In mini-batch training, a common phase of these methods is to form a small-scale subgraph rooting in the given batch. The subgraph formation leads to heavy time consumption, additional space occupation, and complex implementation. To rectify these issues, we eliminate the subgraph formation phase and propose Edge Convolutional Network (ECN), which is trained with independently sampled edges. It has constant time complexity for sampling, reducing the sampling time by orders of magnitude without compromising convergence speed. Specifically, when there are two convolutional layers, as in the most common situation, GCN can also be trained with the techniques behind ECN, gaining substantial sampling time reduction without trade-offs. We prove that the expressiveness difference between ECN and GCN is theoretically bounded and examine the inference performance of ECN through excessive experiments on real-world, large-scale graphs. Furthermore, we improve ECN with advanced mechanisms of GCN, including skip connection, identity mapping, embedding, and attention. With proper mechanisms integrated, ECN rivals state-of-the-art (SotA) baselines in inductive node classification and produces new SotA accuracy on the dataset of Flickr. The code is available athttps://github.com/cf020031308/ECN.

Believing in science: Linking religious beliefs and identity with vaccination intentions and trust in science during the COVID-19 pandemic.

Despite evidence supporting numerous scientific issues (e.g. climate change, vaccinations) many people still doubt the legitimacy of science. Moreover, individuals may be prone to scepticism about scientific findings that misalign with their ideological beliefs and identities. This research investigated whether trust in science (as well as government and media) and COVID-19 vaccination intentions varied as a function of (non)religious group identity, religiosity, religion-science compatibility beliefs, and/or political orientation in two online studies (N = 565) with university students and a Canadian community sample between January and June 2021. In both studies, vaccination intentions and trust in science varied as a function of (non)religious group identity and beliefs. Vaccine hesitancy was further linked to religiosity through a lack of trust in science. Given the ideological divides that the pandemic has exacerbated, this research has implications for informing public health strategies for relaying scientific findings to the public and encouraging vaccine uptake in culturally appropriate ways.

National identity as a cultural filter: External perceptions of the EU in Israel

ABSTRACT This article proposes that national identity is regarded as a key cultural filter for understanding external perceptions of the EU among the public. It examines the relationship between national identity and attitudes toward the EU in Israel while considering the distinction between national identification and national chauvinism via two survey studies. Study 1 (N = 1050) used Israel’s hosting of the Eurovision Song Contest 2019 to explore the relations between national identification/chauvinism and general sympathy for the EU. Study 2 (N = 657) inspected the extent to which national identification and national chauvinism are related to perceptions of the EU as a normative power. The findings indicate that national identification and chauvinism relate dissimilarly to attitudes toward the EU and that exposure to the Eurovision Song Contest also interacted with these relations. These findings emphasize the function of national identity as a cultural filter.

0619 Comparative analysis of different methods of assessing worker fatigue

Abstract Introduction Fatigue at work causes reduced functional capacity that is experienced during the workday, is associated with sleep deprivation and impairs decision making. Fatigue can be estimated in a self-reported way, through the Psychomotor Vigilance Test (PVT), postural balance and core body temperature (CBT) that correlate with performance. Interest in fatigue assessment should focus on identifying risk conditions. Thus, the objective of the study is to present comparative results of 4 different methods used to estimate fatigue. Methods This study was approved by Research Ethics Committee (protocol CAAE nº 97394818.6.0000.5149). The sample consisted of 47 volunteers, who worked as truck operators, in a fast reverse rotational shift (4x1) with a workload for each shift of 6 hours, including a 12-hour break between shifts. All workers were submitted to fatigue assessment by postural sway using the Sonômetro for 15 days, in addition to assessments for 5 days such as CBT monitoring, 5 minutes of PVT and karolinska sleepiness scale (KSS). The gamma distribution with the identity function was considered for data analysis through the method of generalized linear models. Results CBT measurements were compared from the first to the sixth hour between shifts, no significant differences were observed . Of the variables evaluated by PVT, only the 10% faster presented worse results in the night shift (00:00 to 06:00). The KSS showed no differences between the evaluated times. The result of the pairwise comparisons indicated that there are differences in postural sway by SONOMETRO, being greater at the beginning of the shift 00:00 to 06:00, in relation to the shift 12:00 to 18:00. In the middle and at the end of the shift, a difference was found between the shift 00:00 to 06:00 and all others. Conclusion Among the presented methods, the SONOMETER and a single variable of PVT (10% faster), identified differences in the levels of fatigue. It is up to managers to identify the method that best suits the objective of the assessment, as well as the local culture and conditions. Thus, the combined use of different risk and fatigue assessment and management methods may favor the identification and management of worker fatigue. Support (if any)

Artificial intelligence tools and vegetation indices combined to estimate aboveground biomass in tropical forests

Measurement of forest biomass is a time-, money-, and labor-consuming activity. Developing methodological approaches for quantifying biomass in natural ecosystems has motivated countless investigations in several vegetation types worldwide. In this study, we developed a model to estimate the above-ground biomass (AGB) in a study site spatially located in Western Pará state, Brazilian Amazon. We applied artificial neural networks and remotely sensed data for adjusting our model based on forest inventory data. We tested four vegetation indices retrieved from a Landsat-5 thematic mapper scene and assessed their correlations with the field measured AGB. We trained 286 artificial neural networks using the vegetation stratus (two phytophysiognomies: dense lowland ombrophilous forest and dense submontane ombrophilous forest) and the normalized difference vegetation index (NDVI) and aerosol-free vegetation index as predictors variables of the AGB. We selected the artificial neural network model showing higher correlation coefficient and concentration of residuals in the center classes, which indicates higher predictive capabilities of biomass estimation. The generated model architecture (4-13-1) was composed by 4 predictor neurons in the input layer, 13 neurons in the hidden layer, activated by logistic functions, and a single neuron (the AGB in ton · ha − 1) in the output layer, activated by an identity function. We observed that the NDVI and aerosol free vegetation index showed the best performance to estimate the AGB in the study area. Using artificial neural network and a Landsat-5 image combined, we were able to accurately predict (estimation error of ∼20 % ) AGB in tropical forest. This is a promising methodological approach that can be applied to assess ecosystem services related to carbon stock in tropical regions.

Structure‐guided Capacitance Relationships in Oxidized Graphene Porous Materials Based Supercapacitors

Supercapacitors formed from porous carbon and graphene‐oxide (GO) materials are usually dominated by either electric double‐layer capacitance, pseudo‐capacitance, or both. Due to these combined features, reduced GO materials have been shown to offer superior capacitance over typical nanoporous carbon materials; however, there is a significant variation in reported values, ranging between 25 and 350 F g−1. This undermines the structure (e.g., oxygen functionality and/or surface area)‐performance relationships for optimization of cost and scalable factors. This work demonstrates important structure‐controlled charge storage relationships. For this, a series of exfoliated graphene (EG) derivatives are produced via thermal‐shock exfoliation of GO precursors and following controlled graphitization of EG (GEG) generates materials with varied amounts of porosity, redox‐active oxygen groups and graphitic components. Experimental results show significantly varied capacitance values between 30 and 250 F g−1 at 1.0 A g−1 in GEG structures; this suggests that for a given specific surface area the redox‐active and hydrophilic oxygen content can boost the capacitance to 250–300% higher compared to typical mesoporous carbon materials. GEGs with identical oxygen functionality show a surface area governed capacitance. This allows to establish direct structure‐performance relationships between 1) redox‐active oxygen functional concentration and capacitance and 2) surface area and capacitance.

Unique Measurements of Intranasal Trigeminal Function: A Pilot Study.

To investigate novel methods of measuring intranasal trigeminal function and correlate to validated measures of trigeminal function. Prospective cohort study. Tertiary medical center. Forty-one subjects without nasal congestion were assessed. The trigeminal temperature function of the cool/warmth detection threshold and cold/heat pain threshold was measured with the Thermal Sensory Analyzer (TSA) device, as previously validated at buccal mucosa and infraorbital skin. Identical temperature sensory function was assessed at the anterior septum and inferior turbinate. Lateralization of trigeminal odorants eucalyptol, isothiocyanate, and acetic acid was conducted. Visual analog scales (VAS) of trigeminal function were collected. Extraoral cheek site and oral site thermal measures were moderately correlated, suggesting consistent assessment of trigeminal function. Nearly all intranasal thermal measures correlated between the septum and turbinate (significant correlations [ρ] ranged from .3 to .8). Oral and extraoral cheek sites had modest correlations to intranasal cold and heat pain (ρ = .4-.5). The oral site had modest correlations of cold and heat detection to intranasal sites, with turbinate appearing to have the most correlations. Isothiocyanate lateralization was the most closely correlated to intranasal thermal scores for cold and heat pain. Turbinate thermal measures had weak correlations with trigeminal VAS scores (ρ = .3-.4). Intranasal trigeminal measures of thermal function correlate to validated extraoral and intraoral thermal measures. The turbinate appears to have stronger correlations to the septum than found in the mouth and face. TSA testing might provide a rapid, novel method of intranasal trigeminal function assessment.

Rhodium-Catalyzed Alkenylation of Arenes with Multi-Substituted Olefins: Comparison of Selectivity and Reaction Rate as a Function of Olefin Identity

Rhodium-catalyzed arene alkenylation using Cu(II) carboxylates as the in situ oxidant and mono-substituted olefins has been previously reported (e.g., J. Am. Chem. Soc. 2019, 139, 5474; J. Am. Chem. Soc. 2018, 140, 17007; Organometallics 2019, 38, 3860; J. Am. Chem. Soc. 2020, 142, 10534). Herein, studies are extended to multi-substituted olefins with the goal of evaluating the effect of olefin substitution pattern and substituent identity on selectivity and turnover frequency. The influence of olefin substitution is probed by comparing the conversion of benzene to alkenyl arenes with ethylene, propylene, 1-butene, cis-2-butene, trans-2-butene, isobutene, 2-methyl-2-butene, and tetramethylethylene as well as the phenyl-substituted olefins and isomers of propenylbenzene. The rate of oxidative hydrophenylation for multi-substituted olefins follows the trend monosubstituted > disubstituted > trisubstituted, and tetrasubstituted olefins are unreactive. To probe the effect of substituent size on Markovnikov/anti-Markovnikov regioselectivity, cyclohexyl, tert-butyl, isopropyl, ethyl, and methyl substituted α-olefins are compared. Selectivity for anti-Markovnikov products generally increases as substituent steric bulk is increased. Tolerance for some functionalized olefins is demonstrated. The ortho/meta/para regioselectivity with mono-substituted arenes reveals that arene and olefin identity influences selectivity. Further mechanistic studies provide evidence for Curtin–Hammet control of ortho/meta/para regioselectivity with monosubstituted arenes.

Elizabeth Usher memorial lecture: Beyond our practice borders—using a biopsychosocial framework to improve long-term outcomes for people living with aphasia

Purpose: Over 140 000 Australians live with aphasia after stroke, with this number of people living with aphasia increasing significantly when aphasia arising from traumatic brain injury, neoplasm, and infectious and progressive neurological diseases is also included. The resulting communication disability frequently compromises every aspect of daily life, significantly impacting everyday activity, employment, social participation, mental health, identity, and family functioning. Rehabilitation services rarely meet the needs of this group who have, for example, poorer healthcare outcomes than stroke peers without aphasia, nor address long-term recovery and support needs. Method: In this discussion paper, I argue that given the broad impacts of aphasia, a biopsychosocial approach to aphasia rehabilitation is required. Rehabilitation must include: interventions to improve the communication environment; programs that directly target identity, wellbeing, and mental health; and therapies focusing on functional activity, communication participation, and long-term self-management. Result: The evidence for these approaches is mounting and includes strongly stated consumer needs. I discuss the need for multidisciplinary involvement and argue that for speech-language pathologists to achieve such comprehensive service provision, an expanded scope of practice is required. Conclusion: There is a need to rethink standard therapy approaches, timeframes, and funding mechanisms. It is time to reflect on our practice borders to ask what must change and define how change can be achieved.

Partitions of Finite Nonnegative Integer Sets with Identical Representation Functions

Let $${\mathbb {N}}$$ be the set of all nonnegative integers. For $$S\subseteq {\mathbb {N}}$$ and $$n\in {\mathbb {N}}$$ , let the representation function $$R_{S}(n)$$ denote the number of solutions of the equation $$n=s+s'$$ with $$s, s'\in S$$ and $$s<s'$$ . In this paper, we determine the structure of $$C, D\subseteq {\mathbb {N}}$$ with $$C\cup D=[0, m]$$ , $$C\cap D=\{r_{1}, r_{2}\}$$ , $$r_{1}<r_{2}$$ and $$2\mid r_{1}$$ such that $$R_{C}(n)=R_{D}(n)$$ for any nonnegative integer n.

An Efficient Detection and Classification of Acute Leukemia Using Transfer Learning and Orthogonal Softmax Layer-Based Model.

For the early diagnosis of hematological disorders like blood cancer, microscopic analysis of blood cells is very important. Traditional deep CNNs lead to overfitting when it receives small medical image datasets such as ALLIDB1, ALLIDB2, and ASH. This paper proposes a new and effective model for classifying and detecting Acute Lymphoblastic Leukemia (ALL) or Acute Myelogenous Leukemia (AML) that delivers excellent performance in small medical datasets. Here, we have proposed a novel Orthogonal SoftMax Layer (OSL)-based Acute Leukemia detection model that consists of ResNet 18-based deep feature extraction followed by efficient OSL-based classification. Here, OSL is integrated with the ResNet18 to improve the classification performance by making the weight vectors orthogonal to each other. Hence, it integrates ResNet benefits (residual learning and identity mapping) with the benefits of OSL-based classification (improvement of feature discrimination capability and computational efficiency). Furthermore, we have introduced extra dropout and ReLu layers in the architecture to achieve a faster network with enhanced performance. The performance verification is performed on standard ALLIDB1, ALLIDB2, and C_NMC_2019 datasets for efficient ALL detection and ASH dataset for effective AML detection. The experimental performance demonstrates the superiority of the proposed model over other compairing models.

GraphPLBR: Protein-ligand Binding Residue Prediction with Deep Graph Convolution Network.

The intermolecular interactions between proteins and ligands occur through site-specific amino acid residues in the proteins, and the identification of these key residues plays a critical role in both interpreting protein function and facilitating drug design based on virtual screening. In general, the information about the ligands-binding residues on proteins is unknown, and the detection of the binding residues by the biological wet experiments is time consuming. Therefore, many computational methods have been developed to identify the protein-ligand binding residues in recent years. We propose GraphPLBR, a framework based on Graph Convolutional Neural (GCN) networks, to predict protein-ligand binding residues (PLBR). The proteins are represented as a graph with residues as nodes through 3D protein structure data, such that the PLBR prediction task is transformed into a graph node classification task. A deep graph convolutional network is applied to extract information from higher-order neighbors, and initial residue connection with identity mapping is applied to cope with the over-smoothing problem caused by increasing the number of graph convolutional layers. To the best of our knowledge, this is a more unique and innovative perspective that utilizes the idea of graph node classification for protein-ligand binding residues prediction. By comparing with some state-of-the-art methods, our method performs better on several metrics.

Investigating gender-based differential item functioning on the McLean Screening Instrument for Borderline Personality Disorder (MSI-BPD): An item response theory analysis.

The McLean Screening Instrument for Borderline Personality Disorder (MSI-BPD) is a popular screening tool for identifying people who may have borderline personality disorder (BPD). However, because women are more frequently diagnosed with the disorder than men, it is possible that the MSI-BPD differs in its ability to identify BPD as a function of gender identity. Using item response theory (IRT), we sought to determine if components of the MSI-BPD would demonstrate differential item functioning (DIF), such that one gender identity would be more likely to endorse certain items. Twenty-two thousand thirty-five college undergraduates (14,305 women) aged 18-55 years (M = 18.77, SD = 1.75) were assessed using the MSI-BPD as part of a subject pool screening between 2008 and 2019. The MSI-BPD contains 10 items that are measured dichotomously, and the authors recommend a cut-off of 7 of 10 items endorsed to maximize sensitivity and specificity to BPD. Results suggested that a two-parameter model was the best fit to the data and that unidimensionality and local independence assumptions were met. The following items demonstrated DIF: self-harm/suicidality, affective lability, abandonment, impulsivity, and anger. At equal levels of the latent construct of BPD, women were more likely to endorse self-harm/suicidality, affective lability, and abandonment. Women were more likely to endorse impulsivity at higher levels of BPD, and men were more likely to endorse anger at lower levels of BPD. Ultimately, the effect sizes of these differences were small, however, and likely do not impact the individual's overall outcome on the measure. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A rapid and high-throughput T cell immunophenotyping assay for cellular therapy bioprocess using the Cellaca PLX image cytometer

Abstract Cellular therapies such as chimeric antigen receptor (CAR) T or NK cells undergo phenotypic characterization during discovery and development of novel therapies, biomanufacturing, and upstream patient cell processing for clinical use. Samples are routinely analyzed via flow cytometry for T cell, NK cell, B cell, and monocyte surface marker expression. Image cytometry systems perform cell-based assays that can be used as a convenient alternative to flow cytometry. Recently, a new high-throughput image cytometer, the Cellaca PLX system (Nexcelom, Lawrence, MA) was developed for immunophenotyping, transfection/transduction efficiency, and cell health assays. This new instrument can assess several critical quality attributes (CQAs) such as cell identity, viability, and other relevant biological functions recommended by the International Organization for Standardization using the ISO Cell Characterization that focuses on cellular therapeutic products. Here we demonstrate a rapid and high-throughput immunophenotyping and viability detection in peripheral blood mononuclear cells (PBMCs) using the Cellaca PLX. PBMCs underwent red blood cell (RBC) lysis and CD3 enrichment, were stained with Hoechst/CD3/CD4/CD8 or Hoechst/CD3/CD8/RubyDead surface marker kits and measured on the Cellaca PLX and three different flow cytometers for comparison. Results showed highly comparable cell populations between the flow cytometers and the Cellaca PLX suggesting that the image cytometer may provide a rapid and convenient alternative method for immunophenotyping. The proposed method can streamline workflows from sample staining to data analysis, quickly moving precious patient samples into downstream processes.

Looking within: Elevating Black scholarly contributions to empirical approaches in developmental science.

Over the past century, Black American scholars have designed, applied, and promoted conceptual frameworks and research models that propose nuanced understandings of psychological development. This article highlights examples of their contributions to understanding the differential impact of diverse contextual and situational factors. Through examinations of the psychological effects of Blackness on the development of cognition, competence, identity, and social functioning, Black psychologists outline pathways and provide tools for ecological culturally rooted methodologies. These multidisciplinary approaches run in contrast to dominant trends in the field and thus broaden developmental science's reach and influence. In the 1950s, developmental research by Black psychologists was instrumental to the fight for civil rights. Today, it continues to provide a basis for advancing diversity, equity, inclusion, and justice. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Generalizations of Hardy-Type Inequalities by Montgomery Identity and New Green Functions

In this paper we extend general Hardy’s inequality by appropriately combining Montgomery’s identity and Green functions. Related Grüss and Ostrowski-type inequalities are also derived.