bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recent Progress of Nano-Cooling for Electric Vehicles Battery Thermal Management Systems: A Mini Review
Authors: Abdullah A.R. , Hongkun Lu , Noor M.M. , Harikrishnan S. 
Published: January 2025

Abstract
This paper investigates the use of nano-fluids in Battery Thermal Management Systems (BTMS) for electric vehicles (EVs), where they are essential for safety and to extend battery life. As the EV industry develops rapidly, battery thermal management is essential to ensure efficient battery performance under diverse operating conditions. In this study, the recent technology of BTMS using nanoparticles including CNT, graphene and metal oxides to enhance the efficiency of cooling systems will be evaluated. The research methodology conducted a literature review based on different cooling methods such as liquid cooling systems, phase change materials (PCM), and hybrid techniques to assess how nanoparticles are handled in terms of battery temperature regulation. According to the findings, this can make the operation of heat conduction more efficient and lower battery operating temperatures while improving battery longevity by keeping its charge. PCM with nano-fluid together is indicated can deliver more uniform and fast cooling. Overall, this find not only reinforces the nanoparticle sustainable functionalities in BTMS but also assists the effort of an eco-friendly and green BTMS technology in facilitating a technological revolution upon electric vehicles.
Nutrient transport from the Ganga–Brahmaputra–Meghna River system to the Bay of Bengal: past and future trends
Authors: Elsayed Hamdy , Beusen Arthur , Bouwman Alexander Felix 
Published: January 2025

Abstract
The Ganga–Brahmaputra–Meghna (GBM) river basin is a lifeline for the livelihoods and well-being of millions of inhabitants. It has been experiencing increasing nutrient emissions from anthropogenic activities since the 1970s. This paper describes total nitrogen (TN) and total phosphorus (TP) sources and transport in the GBM basin at a 0.5-degree resolution for the past (1970–2019) and future (2020–2050) according to Shared Socioeconomic Pathways scenarios. Our results indicate a three-fold increase in the delivery and export of TN and a two-fold increase of TP in the GBM basin between 1970 and 2019. Elevated nutrient levels are driven by agriculture mainly, with sewage discharge important particularly in the large number of densely populated urban areas. Continuing current nutrient management practices in a business as usual scenario will increase the risk of eutrophication in the GBM basin and the Bay of Bengal. Implementing nutrient reduction strategies in a sustainable scenario will reduce TN and TP loads and concentrations, but nutrient imbalances remain strong with continued risk of harmful algal blooms. These findings call for integrating nutrient stoichiometry with balanced nutrient reduction strategies to mitigate nutrient pollution in the GBM River basin.
Does urban green development attention improve energy resource misallocation?
Authors: Lai Yongjian , He Xiangmin 
Published: January 2025

Abstract
Energy resource misallocation is a vital factor inhibiting energy efficiency improvement. This study uses city panel data from China and employs a theoretical and empirical research method to examine the impact of urban green development attention on energy resource misallocation. The study finds that urban green development attention has improved energy resource misallocation in Chinese cities. Urban green development attention improves energy resource misallocation through strengthening environmental regulation, promoting green technology innovation, and driving the greening of industrial structures. The impact of urban green development attention on energy resource misallocation exhibits significant heterogeneity, with more prominent improvement effects in central-western cities, resource-based cities, cities with low economic development levels, and high green finance development cities. The development of the digital economy is conducive to enhancing the energy resource misallocation improvement effect of urban green development attention. The conclusions of this study have strong implications for alleviating energy resource misallocation in cities, thereby improving urban energy efficiency.
Multi-deep learning models based analysis for classification of thunderstorms on meteorological dataset over Ranchi region
Authors: Bala Kanchan , Choubey Dilip Kumar , Gedam Shruti , Aknan Md 
Published: January 2025

Abstract
Deep learning (DL) is now generally acknowledged as the benchmark and evolution in machine learning (ML) fields. Further more, it has steadily suited the most extensively in computational techniques for ML, delivering excellent outcomes in several challenging intellectual works that have equal or still outperformed human ability. DL has the advantage of learning from enormous amounts of data. Here, the DL approach has been applied to classify thunderstorms and non-thunderstorms with a meteorological dataset. Daily observational hourly data sets from 2016 to 2021 have been used to classify the incidence of thunderstorms and non-thunderstorms. Three DL approaches are used: Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Long Short-Term Memory (LSTM) to classify thunderstorm incidences. These DL techniques are compared with conventional ML techniques, showing that DL approaches outperformed ML. The CNN method provides the highest performance with 92.01% accuracy among all DL and ML approaches.
Efficient Monte Carlo simulation of streamer discharges with deep-learning denoising models
Authors: Bayo-Muñoz F M , Malagón-Romero A , Luque A 
Published: January 2025

Abstract
Electric breakdown in non-conducting gases is a complex process that in its first stages is characterized by filamentary discharges called streamers. Streamer dynamics are inherently nonlinear and span broad temporal and spatial scales, making numerical simulation challenging. Although Monte Carlo methods are intuitive and they model the full electron energy distribution without a priori prescriptions, they suffer from artificial sampling noise which, combined with the non-linearity of streamers, distorts their evolution. Here we investigate the use of deep-learning techniques to mitigate the noise introduced by Monte Carlo sampling. We observe that traditional techniques for noise reduction in images are not satisfactory because they do not impose strict conservation of electric charge. Then we present a charge-conserving denoising filter to improve the efficiency of Monte Carlo simulations of streamers.
Advancing privacy-aware machine learning on sensitive data via edge-based continual µ-training for personalized large models
Authors: Huang Zhaojing , Yu Leping , Fernando Herbozo Contreras Luis , Eshraghian Kamran , Duy Truong Nhan , Nikpour Armin , Kavehei Omid 
Published: January 2025

Abstract
This paper introduces an innovative method for fine-tuning a large multi-label model for abnormality detection, utilizing a smaller trainer and advanced knowledge distillation techniques. It studies the effects of fine-tuning on various abnormalities, noting different improvements based on the Original Model’s performance in specific tasks. The experimental setup, optimized for on-device inference and fine-tuning with limited computational resources, demonstrates moderate yet promising enhancements in model performance post-fine-tuning. Key insights from the study include the significance of aligning the µ-Trainer’s behavior with the Original Model and the influence of hyper-parameters like batch size on fine-tuning outcomes. The research acknowledges limitations such as the limited exploration of loss functions in multi-label models and constraints in architectural design, suggesting potential avenues for future investigation. While the proposed Naive Continual Fine-tuning Process is in its early stages, we highlight this paper’s potential model personalization on long-term data. Moreover, weight transfer in our system is exclusively for fine-tuning; hence, it improves user privacy protection by failing data reconstruction attempts from weights, like an issue with Federated learning models. Our on-device fine-tuning prevents the transferring of data or gradients from the edge of the network to their server. Despite modest performance improvements after fine-tuning, these working layers represent a small fraction (0.7%) of the total weights in the Original Model and 1.6% in the µ-Trainer. This study establishes a foundational framework for advancing personalized model adaptation, on-device inference and fine-tuning while emphasizing the importance of safeguarding data privacy in model development.
Interdependency classification: a framework for infrastructure resilience
Authors: Shamsi Negin , Helmrich Alysha 
Published: January 2025

Abstract
Critical Infrastructure Systems (CISs) provide essential services for nation-wide security, economy, and social well-being, and these systems are becoming increasingly interdependent to maintain those services. Recent and diverse disturbances worldwide have highlighted that interdependencies within CISs may increase the potential for cascading failures, amplifying the impacts of both large and small-scale disturbances into events of catastrophic proportions. The methodology involved conducting a literature search through scholarly databases and using a snowball approach to identify 12 relevant papers on infrastructure interdependencies. Thematic analysis was then applied to classify 50 interdependencies, which were synthesized into a unified classification system mapped to a foundational framework. The direct citation network visualization tool, Kumu, illustrated citation patterns and guided the analysis. Identifying and classifying various interdependencies, understanding their relationships, and assessing their role in CISs are crucial steps to prevent, mitigate, or manage unfavorable consequences and enhance system resilience. In this article, classifications of infrastructure interdependencies were compiled and identified and a unified classification was described. To support the resilience of CISs in periods of stability and instability, infrastructure managers not only need consistent terminology but a shared understanding of interdependencies to ensure said interdependencies within and across CISs are appropriately accounted for throughout the life cycle of infrastructure, from early planning stages to management—reactive or proactive—for disturbances. These are critical steps toward understanding how CISs operate in concert so infrastructure managers may sense and anticipate potential disruptions, manage the impacts and consequences, and adapt to changing future conditions.
Supercharged nanoadhesive through co-assembly of recombinant protein and tetrahedral DNA for corneal transplantation
Authors: Zhao Jing , Zhang Feng , Zhang Zhe , Li Zhenhua , Yu Yanze , Sun Bingqing , Yu Binghong , Ma Yong , Ding Xuan , Wang Liyin , Zheng Lifei , Cui Wenguo , Zhou Xingtao 
Published: January 2025

Abstract
A traumatic tissue adhesive technology is highly sought after in ophthalmic surgery; however, many polymeric adhesives face significant limitations in clinical ophthalmology, particularly in corneal transplantation. A major challenge is achieving rapid adhesion without introducing polymer barriers or chemical toxicity from cross-linking. To address this, we developed a novel cornea-specific nanoadhesive constructed through protein-DNA co-assembly and applied it to corneal transplantation. In this system, a rigid tetrahedral DNA framework was employed to guide the spatial distribution of polycationic recombinant proteins (K72) and serve as the core of the nanoadhesive, facilitating energy conversion during tissue connection. The adhesive demonstrated a strength of 2.3 kPa between corneal lenticules. After modification with RGD peptides, the adhesive system significantly enhanced corneal epithelialization, reduced inflammation and neovascularization, and ultimately promoted corneal repair. This study represents the first application of a nanoadhesive in ophthalmic surgery, providing a novel solution for developing ophthalmic-specific adhesives for clinical use.
Borderline Pattern Specifier
Authors: Simonsen Erik , Paris Joel 
Published: January 2025

Abstract
This chapter reports the origin of the borderline personality disorder (BPD) diagnosis and historical developments, and how diagnostic criteria have been changed and refined over time. It introduces the new borderline pattern specifier in ICD-11 on the basis of this construct, and argues why we should keep a Borderline pattern in the classification of personality disorders as a possible indicator of severity. The most frequent co-occurrence of BPD with other mental health disorders, including depression, bipolar disorders, PTSD, and ADHD, and the epidemiology are outlined. A brief summary of empirical research on risk factors, etiology, course, risk of suicide, and mortality is offered, as well as some of the evidence for psychotherapy and pharmacotherapy. Overall research on BPD, especially on epidemiology, phenomenology, treatment, course, and outcome have changed past levels of nihilism and paved the way for a better understanding of the depth of the impairment and sufferings in these patients and their families
Crosswalk for ICD-10 and DSM-5 Personality Disorder Types
Authors: Jacobsson L Peter , Hopwood Christopher J 
Published: January 2025

Abstract
The field of personality disorders (PDs) is transitioning from a categorical to a dimensional approach to diagnosis. This transition is complicated and slow-moving. The aim of this chapter is to facilitate this transition by providing a crosswalk between PD categories listed in the ICD-10 and DSM-5 and maladaptive traits from the ICD-11 and the DSM-5 Alternative Model of Personality Disorders (AMPD). This crosswalk can help clinicians use the ICD-11 classification to capture features of the potentially more familiar PD categories. We first place this transition in historical context, with particular attention to the clinical challenges associated with the new system. We then describe the shared features of the ICD-11 and AMPD models. Next, we describe each of the PD categories in terms of personality functioning and specific traits and dysfunctions from these dimensional systems. We conclude by emphasizing the importance of moving toward a more evidence-based dimensional model while also recognizing associated challenges.
Maladaptive Sense of Identity and Agency
Authors: Lind Majse , Goth Kirstin 
Published: January 2025

Abstract
In this chapter we consider identity: what William James (1890) labeled as “the most puzzling puzzle with which psychology has to deal.” The chapter is comprised of three parts. First, we introduce common understandings of identity and identity disturbance in the context of ICD-11 personality disorders (PD). In particular, we focus on the temporal sense of identity: the narrative identity, understood as the dynamic story people construct about their past, present, and presumed future as a promising, though less-studied aspect of identity in PD. Next, we review state-of-the-art assessments on identity (e.g., AIDA, LoPF-Q; STiP-5, AMPD) in the context of ICD-11 and discuss their clinical utility. We end the chapter by discussing the role of (narrative) identity in PD psychotherapy, with a particular eye toward agency.
Malignant Self-Regard and Characterological Depressivity
Authors: Huprich Steven K , Malone Brady C 
Published: January 2025

Abstract
In this chapter, we offer a focused discussion on the historical and modern understandings of characterological depressivity. We showcase the most recent, comprehensive, and empirically studied construct in this area: malignant self-regard (MSR). We describe the emergence of MSR and empirical evidence for its convergent, discriminant, and construct validity. We also focus on the relationship of MSR to treatment-resistant depression and its differential diagnosis from major depressive disorder and ICD-11 dysthymic disorder. MSR is then considered within the ICD-11 framework for personality disorder severity and pathological traits. It is concluded that positioning MSR at the forefront of the depressive personality literature is warranted and deserves continued attention in the research literature. We close with a call for future research, with specific attention toward understanding the neurological substrate of MSR and personality-driven depression.
Interpersonal Dependency
Authors: Bornstein Robert F 
Published: January 2025

Abstract
This chapter on “Interpersonal Dependency” explores implications of the International Classification of Diseases, 11th edition (ICD-11) personality disorder (PD) framework for clinicians’ understanding of pathological interpersonal dependency. The chapter begins by outlining the Cognitive/Interactionist (C/I) model, an evidence-based framework which illuminates the central role of the “helpless self-concept” in the etiology and dynamics of interpersonal dependency and helps account for temporal and contextual variations in dependency-related responding. The chapter describes how interpersonal dependency is manifested at different levels of PD severity (mild, moderate, or severe), and reviews research on trait specifiers that characterize this personality style (Negative Affectivity, Dissociality, and Disinhibition). Implications of the ICD-11 PD framework for assessment and treatment of problematic dependency are discussed, and suggestions for future research are offered.
Grandiose and Vulnerable Narcissism
Authors: Green Ava , Day Nicholas 
Published: January 2025

Abstract
Pathological narcissism encompasses prototypical features of grandiose and vulnerable narcissism presentations which are differently associated with personality functioning and trait domain specifiers in males and females. This chapter begins with a historical review of the concept of narcissism and its evolution: from being seen as a myth to being considered an official clinical designation in the psychiatric nomenclature. It then proceeds to review the transition from categorical to dimensional models in conceptualizing narcissistic personality disorder (NPD), followed by an illustration of how grandiose and vulnerable expressions in males and females are captured in the new ICD-11 model of personality disorders. This is achieved through the use of preliminary research data (Day et al., 2024; Green et al., 2024) and six brief case descriptions, each of which contain relevant treatment considerations for clinical practice.
Dialectical Behavior Therapy
Authors: Swales Michaela 
Published: January 2025

Abstract
Dialectical behavior therapy (DBT) draws upon strategies and techniques from cognitive and behavioral therapeutic traditions, blending them with principles and practices from Zen Buddhism and embedding them within an overarching dialectical framework. The central dialectic within the treatment is of acceptance and change. DBT is a radically behaviorist treatment, conceptualizing diagnoses (including those of personality disorder) as lists of behaviors, both overt and covert. The treatment is structured to comprehensively identify, analyze, and solve the problems that result in a personality disorder diagnostic label. As such, DBT is well placed to address the challenges and changes brought about by the new conceptualization of personality disorder within ICD-11. This chapter describes the treatment, recent evidence in its support, and how it treats the problems labeled as personality disorder, using illustrative clinical examples.
Radically Open Dialectical Behavior Therapy
Authors: Hempel Roelie J , Codd R Trent , Baudinet Julian , Simic Mima 
Published: January 2025

Abstract
This chapter introduces Radically Open Dialectical Behavior Therapy (RO DBT) in relation to the ICD-11 classification of personality disorders (PD) and related traits, and briefly summarizes its empirical support. RO DBT is presented as a psychotherapy approach that focuses on maladaptive overcontrol, a transdiagnostic factor underlying many forms of psychopathology, including PD features. Furthermore, the chapter details a treatment strategy based on the ICD-11 classification of PD severity, including subdiagnostic personality difficulty, and describes how overcontrol relates to each of the trait domains, offering several examples of how RO DBT addresses aspects of personality functioning, global severity, and trait domains.
Good Psychiatric Management
Authors: Ydrefelt Erik , Björling Peder , Freidlitz Johanna , Sundström Niki 
Published: January 2025

Abstract
Good psychiatric management (GPM) is a generalist and principle-driven treatment framework initially developed for borderline personality disorder. This chapter describes the rationale for a generalist approach to treatment of personality disorder, the principles of GPM, and how they are applied in treatment. GPM is proposed as a candidate for “good enough” treatment for personality disorder in general, with its emphasis on overall self- and interpersonal functioning, straightforward theoretical model, flexibility in treatment implementation, and utilization of clinicians’ existing knowledge and skills. The chapter specifically outlines how the ICD-11 diagnostic system can be used practically in psychoeducation and treatment planning. Examples are provided on how to address personality disorder with the patient, a safety plan, and a treatment plan, following GPM principles.
Nidotherapy
Authors: Tyrer Peter 
Published: January 2025

Abstract
Nidotherapy is the collaborative and systematic manipulation of the environment, including physical, social, and personal aspects, to make a better fit between a person and his or her setting. It does not aim to treat symptoms, only to effect environmental change so that both behavior and symptoms improve as they are no longer in conflict with the environment. It is a transdiagnostic form of care and so it does not slot easily into treatment manuals, but its most effective contribution is in the management of personality disorder, where it can treat many problems that other treatment strategies fail to touch. Examples are given of its effectiveness, including the results of two controlled trials. It can be understood further by looking at www.nidotherapy.com.
Treatment Planning and Evaluation
Authors: Gamache Dominick , Savard Claudia , Leclerc Philippe , Faucher Jonathan 
Published: January 2025

Abstract
This chapter will examine the practical applications of the World Health Organization’s International Statistical Classification of Diseases and Related Health Problems, 11th Edition (ICD-11) conceptualization of personality disorders (PD), with a specific focus on how clinicians can utilize its two main components—the global level of severity of PD and the five trait domain specifiers—to inform treatment planning and evaluation. By leveraging its two main components, clinicians can gain invaluable insights into relevant treatment targets and anticipate challenges that may arise during therapy (e.g., therapeutic alliance issues and risk of treatment dropout). A number of useful clinical tools to assist clinicians in treatment planning and monitoring are briefly reviewed. Three clinical vignettes (corresponding to mild, moderate, and severe PD) provide concrete illustrations of how assessment of global level of severity and trait domain specifiers can be translated into concrete information for treatment planning.