Search Results (27)

Japanese narcissism refers to a culturally embedded form of narcissistic personality that emerges within collectivist societies, particularly in Japan, where self-worth is maintained through emotional over-adaptation, perfectionism, self-sacrifice, and conformity to internalized moral obligations. Within the framework of Schema Therapy, this construct is characterized by dominant coping modes, such as Armor mode and Demanding Community mode, that suppress vulnerable emotional states and promote socially sanctioned compliance. Although narcissistic personality disorder (NPD) has been extensively studied in individualistic Western cultures, its manifestation in collectivist cultures remains underexplored. Japanese narcissism offers a culturally contextualized model that integrates psychoanalytic and Schema Therapy perspectives to explain thin-skinned narcissistic vulnerability, disguised as adaptive functioning. Clinical observations and case analyses indicate that patients often develop Armor mode (fusing Detached Protector and Perfectionistic Over-controller functions) and Demanding Community mode (internalizing collective moral expectations). These adaptive-appearing modes mask core maladaptive schemas—Emotional Deprivation, Defectiveness/Shame, Enmeshment, and Self-Sacrifice—while being mistaken for mature or healthy functioning. Historically, such patterns have been reinforced by moral-collectivist ideals, exemplified by the Imperial Rescript on Education, which valorized loyalty, endurance, and self-denial. Japanese narcissism may therefore represent a culturally specific clinical configuration, suggesting the need for contextually adapted Schema Therapy interventions that recognize both the harmony-preserving and narcissism-reinforcing functions of adaptive behavior. This framework contributes to the cross-cultural extension of Schema Therapy by theorizing how narcissistic structures manifest in collectivist societies, and highlights the need for empirical validation of culturally sensitive treatment protocols. Full article

Electronic health records (EHRs) are typically stored in relational databases, making them difficult to query for nontechnical users, especially under privacy constraints. We evaluate two practical clinical NLP workflows, natural language to SQL (NL2SQL) for EHR querying and retrieval-augmented generation for clinical question answering (RAG-QA), with a focus on privacy-preserving deployment. We benchmark nine large language models, spanning open-weight options (DeepSeek V3/V3.1, Llama-3.3-70B, Qwen2.5-32B, Mixtral-8 × 22B, BioMistral-7B, and GPT-OSS-20B) and proprietary APIs (GPT-4o and GPT-5). The models were chosen to represent a diverse cross-section spanning sparse MoE, dense general-purpose, domain-adapted, and proprietary LLMs. On MIMICSQL (27,000 generations; nine models × three runs), the best NL2SQL execution accuracy (EX) is 66.1% (GPT-4o), followed by 64.6% (GPT-5). Among open-weight models, DeepSeek V3.1 reaches 59.8% EX, while DeepSeek V3 reaches 58.8%, with Llama-3.3-70B at 54.5% and BioMistral-7B achieving only 11.8%, underscoring a persistent gap relative to general-domain benchmarks. We introduce SQL-EC, a deterministic SQL error-classification framework with adjudication, revealing string mismatches as the dominant failure (86.3%), followed by query-join misinterpretations (49.7%), while incorrect aggregation-function usage accounts for only 6.7%. This highlights lexical/ontology grounding as the key bottleneck for NL2SQL in the biomedical domain. For RAG-QA, evaluated on 100 synthetic patient records across 20 questions (54,000 reference–generation pairs; three runs), BLEU and ROUGE-L fluctuate more strongly across models, whereas BERTScore remains high on most, with DeepSeek V3.1 and GPT-4o among the top performers; pairwise t-tests confirm that significant differences were observed among the LLMs. Cost–performance analysis based on measured token usage shows per-query costs ranging from USD 0.000285 (GPT-OSS-20B) to USD 0.005918 (GPT-4o); DeepSeek V3.1 offers the best open-weight cost–accuracy trade-off, and GPT-5 provides a balanced API alternative. Overall, the privacy-conscious RAG-QA attains strong semantic fidelity, whereas the clinical NL2SQL remains brittle under lexical variation. SQL-EC pinpoints actionable failure modes, motivating ontology-aware normalization and schema-linked prompting for robust clinical querying. Full article

This paper presents a BIM-oriented methodological framework for integrating air quality monitoring systems based on IoT sensors into building and infrastructure projects. A set of low-cost environmental sensors capable of measuring PM1, PM2.5, PM10, temperature, and humidity was deployed in a real residential setting to illustrate the proposed approach. To enable semantic integration within BIM workflows, a structured classification system, AllBIMclass, was developed. It provides dedicated hierarchical codes for environmental sensors, defined by monitored parameters, installation location (indoor, outdoor, or mixed), power supply, and data handling mode. The pilot experience demonstrated how sensors can be registered, classified, and linked to BIM models, supporting data visualisation and basic management tasks. AllBIMclass is available in Revit 2026 (version 26.6.4.409, build 20250227_1515, 64-bit) (TXT) and Archicad 28 (version 28.0.0, build 3001, x86–64-bit) (XML) formats and is fully compatible with IFC schemas. Although the framework has not yet been applied to large-scale projects, its components are technically operational and ready for implementation. This research contributes to bridging the gap between environmental monitoring and digital construction workflows, paving the way for integration into digital twins, smart buildings, and sustainable infrastructure systems. Full article

Recent European policies fostering sustainable mobility target urban proximity as a core strategy for a modal shift towards low-carbon modes. Urban proximity, as a characteristic of the built environment, can be studied as a sub-thread of a broad and complex body of literature which associates urban factors such as density or land use mix with observed travel behavior, so as to address their relative influence on the latter. Building on this previous knowledge, the present work addresses the importance of a diverse set of factors on local travel modal choice between walking and other modes, according to the 2018 Household Mobility Survey of the Metropolitan Region of Madrid, and a large variety of demographic and built environment characteristics. The work proposes to address this importance through a workflow on a set of Machine Learning models, filtering different distance thresholds and purposes of the trips, going through a strict feature selection process, and executing under different schema definitions. The resulting models are inspected for accuracy, feature importance, and composition. Results suggest that even small changes in distance thresholds exert a great impact on all models; sociodemographic variables are slightly more important in most models, yet building age, along with other street layout factors, pervasively obtain fairly accurate predictions too. Full article

Culture is a central theme across various theories and disciplines, influencing behavior and self-perception through interactions within social groups, families, and legal systems. This influence extends to the general population and particularly impacts sexual and gender minorities (SGMs), resulting in minority stress that contributes to mental health issues and the development of Early Maladaptive Schemas (EMSs). Adolescents within these groups face typical developmental stressors—such as hormonal changes and societal pressures—compounded by prejudice, increasing their vulnerability to depression, anxiety, stress, substance abuse, and eating disorders. Despite these challenges, Schema Therapy (ST) lacks comprehensive studies on the sociocultural aspects influencing EMS acquisition in SGM adolescents. This theoretical review aims to fill this gap by exploring the impact of society and culture on EMS development within SGM adolescents. We recognize the broad spectrum of cultural influences and emphasize the importance of cultural sensitivity and diversity. This review specifically addresses how societal and cultural dynamics impact SGM individuals, acknowledging that while ethnic or other cultural factors are not the focus of this paper, they merit future research. This manuscript will discuss central topics and their impact on LGBTQIA+ youth, including (1) the background (definition of culture, lack of studies on ST focusing on culture, and studies on adverse psychological outcomes), (2) minority stress theory and prejudice against sexual and gender diversity (distal and proximal stressors and sociocultural aspects), (3) EMSs and unmet emotional needs, (4) ST affirmative strategies (working with schema modes, imagery rescripting, chair work, and photo techniques), and (5) final considerations (limitations and research agenda). Full article

The default mode network (DMN) is a complex network that plays a significant and active role during naturalistic stimulation. Previous studies that have used naturalistic stimuli, such as real-life stories or silent or sonorous films, have found that the information processing involved a complex hierarchical set of brain regions, including the DMN nodes. The DMN is not involved in low-level features and is only associated with high-level content-related incoming information. The human sexual experience involves a complex set of processes related to both external context and inner processes. Since the DMN plays an active role in the integration of naturalistic stimuli and aesthetic perception with beliefs, thoughts, and episodic autobiographical memories, we aimed at quantifying the involvement of the nodes of the DMN during visual sexual stimulation. After a systematic search in the principal electronic databases, we selected 83 fMRI studies, and an ALE meta-analysis was calculated. We performed conjunction analyses to assess differences in the DMN related to stimulus modalities, sex differences, and sexual orientation. The results show that sexual stimulation alters the topography of the DMN and highlights the DMN’s active role in the integration of sexual stimuli with sexual schemas and beliefs. Full article

Conventional optical fiber temperature/strain sensors often have to make compromises between the resolution and the dynamic range. Here we present a new method that meets the measurement requirements for both high resolution and large dynamic range. A high-quality optical fiber Fabry-Perot Interferometer (FPI) constructed using a pair of chirped fiber Bragg gratings is employed as the sensor and a dual-mode direct spectrum interrogation method is proposed to identify the small drift of external temperature or strain. As a proof-of-concept illustration, a temperature resolution of 0.2 °C within 30–130 °C is demonstrated. For strain sensing, the resolution can be 10 µε within 0–1000 µε. The measurement resolution can be improved further by routinely increasing the reflectivity of the CFBG and the cavity length and the sensor can also be mass-produced. This new sensing schema not only resolves the conflict between the resolution and the dynamic range of fiber-optic temperature/strain sensors but can also be extended to other sensors and measurands. Full article

Industry Foundation Classes (IFCs), as the most recognized data schema for Building Information Modeling (BIM), are increasingly combined with ontology to facilitate data interoperability across the whole lifecycle in the Architecture, Engineering, Construction, and Facility Management (AEC/FM). This paper conducts a bibliometric analysis of 122 papers from the perspective of data, model, and application to summarize the modes of IFC and ontology integration (IFCOI). This paper first analyzes the data and models of the integration from IFC data formats and ontology development models to the IfcOWL data model. Next, the application status is summed up from objective and phase dimensions, and four frequent applications with maturity are identified. Based on the aforementioned multi-dimensional analysis, three integration modes are summarized, taking into account various data interoperability requirements. Accordingly, ontology behaves as the representation of domain knowledge, an enrichment tool for IFC model semantics, and a linkage between IFC data and other heterogeneous data. Finally, this paper points out the challenges and opportunities for IFCOI in the data, domain ontology, and integration process and proposes a building lifecycle management model based on IFCOI. Full article

Image-to-image translation (I2IT) is an important visual task that aims to learn a mapping of images from one domain to another while preserving the representation of the content. The phenomenon known as mode collapse makes this task challenging. Most existing methods usually learn the relationship between the data and latent distributions to train more robust latent models. However, these methods often ignore the structural information among latent variables, leading to patterns in the data being obscured during the process. In addition, the inflexibility of data modes caused by ignoring the latent mapping of two domains is also one of the factors affecting the performance of existing methods. To make the data schema stable, this paper develops a novel binary noise guidance learning (BnGLGAN) framework for image translation to solve these problems. Specifically, to eliminate uncertainty of domain distribution, a noise prior inference learning (NPIL) module is designed to infer an estimated distribution from a certain domain. In addition, to improve the authenticity of reconstructed images, a distribution-guided noise reconstruction learning (DgNRL) module is introduced to reconstruct the noise from the source domain, which can provide source semantic information to guide the GAN’s generation. Extensive experiments fully prove the efficiency of our proposed framework and its advantages over comparable methods. Full article

(1) Background: The search for new strategies to diagnose people at risk of suicide and to help them is highly significant in view of the still high rate of suicidality. Schema therapy and its core constructs, i.e., early maladaptive schemas (EMSs) and schema modes, correspond to both directions. (2) Methods: This study compared the severity of EMSs and schema modes in a clinical group of suicide risk, a clinical non-suicidal group, and a control group. Intragroup comparisons were also conducted between times of crisis and psychological stability. The evaluation was supported by controlling for the psychopathological symptoms presented, following the dimensional concept. (3) Results: The unquestionable relevance of the disconnection/rejection domain in suicidality has been proven. The importance of EMSs from other domains, especially during psychiatric crises, was confirmed. Among the schema modes, child and Punitive Parent modes proved to be the most significant. There were changes in coping modes but of a lesser effect size. The protective importance of the Healthy Adult and Happy Child modes was also proven. (4) Conclusions: The results provide an indication for practitioners about the EMSs and schema modes most associated with suicide risk. They can also serve as a framework for deepening the issue of identifying and preventing suicidality in schema therapy. Full article

(1) Background: Schema therapy and working with schema modes is increasingly popular. Since there is no validated tool to measure schema modes in Poland, in this study, we present an assessment of the psychometric properties of the Polish version the Short Schema Mode Inventory (SMI) adaptation. (2) Methods: First, the original version of the scale was translated. Subsequently, a validity and reliability study was conducted on a sample of 240 patients and 400 non-patients. In particular, the factor structure of the inventory was checked, internal reliability and intercorrelations between subscales were tested, differences between the clinical and non-clinical groups in terms of the severity of each factor were examined, and construct validity was assessed by comparing the association of results with external variables. (3) Results: The results did not conclusively confirm the 14-factor structure postulated in the original scale. Nevertheless, the relatively best fit indices were obtained for such a model. The internal reliability for the 14 subscales ranged from 0.74 to 0.95 (McDonald’s omega). Correlations between subscales demonstrated values from 0.03 to 0.72. The existence of differences between the clinical and non-clinical groups and the construct validity were confirmed. (4) Conclusions: The psychometric evaluation performed is mostly similar to the results obtained for other adaptations, and the results justify the inventory being used for research and clinical purposes when knowledge of its limitations is included. Full article

This paper introduces a simple decentralized sliding-mode (SM) approach to control active power sharing by regulating the local frequency in inverter-based islanded microgrids (MGs). Its sliding surface arises from the frequency correction term introduced in the droop-free technique; it relates local active power to neighboring MGs’ active power by considering available communications among voltage source inverters. Then, this schema allows one to avoid hierarchical control just as the droop-free method does, and the benefits associated are twofold. First, it reduces the steady-state frequency error while providing accurate active power distribution. Second, the system stays reliable, withstands uncertainties, and provides a fast transient response. A Lyapunov analysis confirms stability, and simulations on a realistic four-inverter MG platform substantiate the control scheme’s effectiveness. Its performance regards frequency regulation while achieving active power sharing, stability, and robustness against clock drifts and load steps. Full article

The main objective of the present study was to examine, in a non-clinical population, the validity of a moderated mediation model for obsessive mental functioning. The research was conducted on a sample of 205 participants. Data were collected using the Psychiatric Screening and Diagnostic Questionnaire, Young’s Modes Questionnaire-form SMI-2, Padua Inventory of Obsessive-Compulsive Symptoms, Fear of Guilt Scale in OCD, Disgust Propensity and Sensitivity Scale-Revised, and Not Just Right Experiences Questionnaire-Revised. The results revealed that there is a significant positive, indirect effect of the Demanding Parent mode on OCD-like tendencies, which is completely mediated by fear of guilt, tendency and sensitivity to disgust, and Not Just Right Experiences severity. The Punitive Parent mode moderates only the indirect effect of the Demanding Parent mode mediated by fear of guilt, not the indirect effect mediated by disgust tendency and sensitivity and Not Just Right Experiences severity. Also, the indirect effect of the Demanding Parent mode on obsessive tendencies mediated by fear of guilt is significant only at medium and high values of the Punitive Parent mode, not at low values of the moderator. Our results provide a novel direction targeting the direct therapeutic intervention on demanding and punitive internal dialogue, complementing the classical CBT intervention protocol. Full article

Background: The identification of variables affecting suicidality and the search for interventions to reduce suicide risk are priorities among mental health researchers. A promising direction for such research is schema therapy and its two main constructs, i.e., early maladaptive schemas (EMSs) and schema modes. Methods: This systematic review was designed in accordance with the PRISMA guidelines. It summarizes the studies conducted to date that describe the relationship between EMSs and schema modes and measures of suicidality in individuals over the age of 16. Results: The review confirmed that there are many significant associations between EMSs (especially from the Disconnection/Rejection domain) and suicide risk. Although only one study was found that explores the association between schema modes and suicidality, the correlations it identified are also confirmed here. Discussion: The results show the unquestionable importance of EMSs and schema modes in assessing suicide risk. The co-occurrence of these variables represents the first step in further assessing causality and introducing schema therapy techniques into work with patients who are at risk of suicide. This issue requires more extensive experimental research. Full article

Metabolomics is emerging as a promising tool to understand the effect of immunometabolism for the development of novel host-directed alternative therapies. Immunometabolism can modulate both innate and adaptive immunity in response to pathogens and vaccinations. For instance, infections can affect lipid and amino acid metabolism while vaccines can trigger bile acid and carbohydrate pathways. Metabolomics as a vaccinomics tool, can provide a broader picture of vaccine-induced biochemical changes and pave a path to potentiate the vaccine efficacy. Its integration with other systems biology tools or treatment modes can enhance the cure, response rate, and control over the emergence of drug-resistant strains. Mycobacterium tuberculosis (Mtb) infection can remodel the host metabolism for its survival, while there are many biochemical pathways that the host adjusts to combat the infection. Similarly, the anti-TB vaccine, Bacillus Calmette-Guerin (BCG), was also found to affect the host metabolic pathways thus modulating immune responses. In this review, we highlight the metabolomic schema of the anti-TB vaccine and its therapeutic applications. Rewiring of immune metabolism upon BCG vaccination induces different signaling pathways which lead to epigenetic modifications underlying trained immunity. Metabolic pathways such as glycolysis, central carbon metabolism, and cholesterol synthesis play an important role in these aspects of immunity. Trained immunity and its applications are increasing day by day and it can be used to develop the next generation of vaccines to treat various other infections and orphan diseases. Our goal is to provide fresh insight into this direction and connect various dots to develop a conceptual framework. Full article