bluuebunny/crossref_metadata_2025 huggingface dataset:
Resonant x-ray emission across the L3 edge of uranium compounds
Authors: Wang Xubo , Doumy Gilles , Marie March Anne , Otolski Christopher J , Wilson Richard E , Walko Donald A , Cheng Lan , Southworth Stephen H
Published: January 2025

A narrow bandwidth x-ray beamline and a multi-crystal von Hamos spectrometer were used to record x-ray absorption and x-ray emission (XES) across the uranium L
3 edge of UO2, UO3, Cs2UO2Cl4, and Cs2UCl6. Measurements were made over 17150–17250 eV with an instrumental resolution of ∼2 eV. This resolution allowed the use of Lorentzian peak fits to the

L
3

N
4

and

L
3

N
5

characteristic x-ray fluorescence lines that have ∼12–13 eV lifetime widths. The fluorescence yields of the four compounds display strong white lines near threshold and multiple scattering features at higher energies. The XES spectra were fit with three Lorentzians, two for the

L
3

N
4

and

L
3

N
5

lines and one for inelastic scattering by 2p–6d excitations and 4d–6d final states. The intensities of the white lines were largely due to the inelastic scattering component. To support the measurements, relativistic equation-of-motion coupled-cluster and restricted active space configuration interaction calculations were performed for uranium core-excitation energies in Cs2UO2Cl4 and Cs2UCl6. These calculations with rigorous treatments of relativistic effects are shown to provide accurate uranium L
3-edge binding energies,

L
3

N
5

emission energies, as well as the energy losses in the inelastic scattering process. The measured and calculated results show variations between compounds with U(IV) oxidation states that contain 6d05f2 electrons in their ground configurations (UO2 and Cs2UCl6) compared with U(VI) compounds (UO3 and Cs2UO2Cl4) with empty 5f and 6d configurations.
Spin assignment, hyperfine structure, and isotope shift measurements of optical transitions in dysprosium I
Authors: White B , Bulstrode N C M , Forest D H , Honeyball C , Evans B , Butt L
Published: January 2025

High resolution crossed beam laser spectroscopy has been performed on dysprosium I to measure the hyperfine structure and isotope shifts in six optical transitions. Excited states accessed by transitions at: 296.4600, 299.6833, and 301.4279 nm have been found to have different J values to those given in the literature. Field and mass factors for each transition have been extracted using the King plot method and Seltzer moments have been iterated upon to produce an order of magnitude improvement in precision.
Detection of reactor neutrinos using gadolinium-doped plastic scintillators enhanced by machine learning techniques
Authors: Altınlı Murat , Gamsızkan Halil
Published: January 2025

In this study, we present a detailed approach for detecting reactor neutrinos by employing gadolinium-doped plastic scintillators combined with machine learning techniques. The proposed detector design was simulated using the Geant4 framework, featuring segmented modules of plastic scintillators doped with gadolinium to enhance neutron capture efficiency. Inverse beta decay (IBD) events generated by ERNIE and background events produced by cosmic ray simulations were used to train and test an Extreme Gradient Boosting (XGBoost) model for signal-background discrimination. The model demonstrated high discrimination accuracy for prompt IBD events but encountered challenges with delayed neutron background discrimination due to similarities in neutron capture. Performance comparisons with traditional cut-based analyses highlighted the improved accuracy achieved through machine learning, particularly when utilizing additional event features. This work establishes the potential of gadolinium-doped plastic scintillators and machine learning in enhancing neutrino detection and lays the groundwork for future experimental validation and detector optimization.
Optimizing energy threshold selection for low-concentration contrast agent quantification in small animal photon-counting CT
Authors: Hu Xiaoyu , Zhong Yuncheng , Jia Xun , Yang Kai
Published: January 2025

Objective. Gold nanoparticles (GNPs) are widely used for biological research and applications. The in-vivo concentration of GNPs is usually low due to biological safety concerns, thus posing a challenge for imaging. This work investigates on optimal energy threshold selection in photon-counting detector(PCD)-based CT (PCCT) for the quantification of low-concentration GNPs. Approach. We derived the mathematical expression of the upper bound of the material decomposition error in the gold image. Comprehensive simulations were implemented for cylindrical phantom with inserts of different GNP concentrations. CT scans of this phantom were simulated with a 140 kVp x-ray beam under a realistic pre-clinical CT dose range. The PCD energy thresholds from 30 to 110 keV were enumerated for 2,3-channel PCCT and the optimal energy thresholds were determined by searching for the lowest decomposition error. Main results. The optimal energy threshold(s) to minimize the decomposition error in gold image was 44 keV for the 2-channel PCCT and

{
34
,
40
}

keV for the 3-channel case. Numerical results also validated the derived upper bounds of the decomposition error. Significance. This work addressed the need for selecting appropriate energy thresholds for accurate quantification of contrast agent distributions in pre-clinical PCCT. Both the analytical expression of the upper bound of material decomposition error and simulation results showed that the balanced consideration on photon counting noise levels and the numerical properties of the decomposition matrix is required in selecting the appropriate energy thresholds to achieve the most accurate material decomposition.
Preparation of high mechanical performance magnetorheological elastomer for engine mount
Authors: Wang Qiyu , Shen Yurui , Peng Lai , Liu Hao , Hua Dezheng , Liu Xinhua
Published: January 2025

Magnetorheological elastomer (MRE) has been widely applied in vibration control systems, such as engine mounts, due to its excellent magnetorheological (MR) properties. To improve the MR effect, an optimization method for the MRE preparation process is proposed in this paper. Initially, a silicone rubber-based MRE is experimentally prepared, and the effects of four key preparation parameters-mass fraction of carbonyl iron powder, ratio of mass fractions for silicone oil and silicone rubber, pre-structure magnetic field and pre-structure time on the MR effect are analyzed. Subsequently, an orthogonal experimental design and range analysis are employed to optimize the combination of these parameters, determining the optimal preparation process for significantly enhancing the MR effect. Finally, the optimized parameter combination is validated through experiments, which demonstrates that the improved MRE exhibited superior performance. In addition, case simulations confirmed that the optimized MRE mount better meets the vibration reduction requirements of the engine mount system compared to traditional rubber mounts.
Stability of emergent time periodicity in a few-body interacting system
Authors: Campbell Steve , Eisert Jens , Guarnieri Giacomo
Published: January 2025

We examine the onset and resilience of emergent time periodicity in a few-body all-to-all interacting Lipkin–Meshkov–Glick model, where one of the constituents is locally in contact with a thermal bath. Employing both a collision model framework and a suitable time-continuous description, we show that stable time-periodic behavior can only be exhibited when the bath acts as a purely dissipative channel. We assess the role that the microscopic interactions within the system play, establishing that for the all-to-all model the introduction of temperature leads to a melting of the emergent time periodicity, in contrast to stable long-time behavior which can be maintained for nearest neighbor XXZ type interactions.
Star Formation Efficiency of Blue Compact Galaxies Through (O ii), (Hα), (IR), and 1.4 GHz Radio Continuum
Authors: Kumssa Gemechu Muleta
Published: January 2025

This paper investigates the star formation efficiency (SFE) of blue compact galaxies (BCGs) by analyzing various indicators, including (O ii), (H
α
), infrared emissions, and the 1.4 GHz radio continuum. The assessment of SFE was conducted using publicly accessible data that concentrated on star formation rates (SFRs) and depletion timescales. By employing the fundamental equation, I determined the SFE in relation to its freefall time, which highlighted variations in efficiencies associated with SFR masses derived from different spectra. The results demonstrated that the highest efficiency value was observed in the analysis of the 1.4 GHz radio continuum, emphasizing the importance of studying star-forming clouds across a range of electromagnetic wavelengths to achieve a comprehensive understanding of star formation mechanisms. The study's findings indicated a peak efficiency of star formation value of approximately 0.9%, while the relative minimum obtained from (O ii) was around 0.42%, aligning with the range of SFEs documented in the existing literature. Additionally, investigating the factors that influence the variability in efficiency when examining clouds in BCGs across different wave bands is crucial for deepening our comprehension of the underlying processes of star formation.
Exploring the Barrier Function of Nickel in Lead-Free Solder Joints: Thickness and Aging Effects on IMC Formation
Authors: Idris S.R.A. , Tamar Jaya N.
Published: January 2025

The elimination of lead from electronics manufacturing has led to the widespread adoption of tin-silver-copper solders. However, the formation and growth of intermetallic compounds at the solder-substrate interface can significantly impact the reliability of these lead-free solder joints. This study investigates the effectiveness of nickel as a barrier layer in mitigating IMC formation and the influence of Ni layer thickness and aging on this process. The research provides insights into optimizing solder joint reliability by evaluating how these factors influence IMC growth at the interface between Sn-4Ag-0.5Cu (SAC405) solder and electroless nickel/immersion gold (ENIG) finishes. Three different nickel thicknesses (2µm and 5µm) were deposited on copper substrates prior to soldering. Accelerated aging tests were conducted at 150°C for durations of 250, 500, and 1000 hours. Microstructural characterization techniques were employed to analyse the composition and morphology of IMCs formed at the joint interface using an image analyser, scanning electron microscopy and xray analysis (SEM-EDX), and optical microscopy. Results demonstrate that 5µm Ni layers effectively suppress the formation of Cu-Sn IMCs with 0.11µm thickness after reflow soldering, but can lead to the growth of Ni-Sn IMCs. Meanwhile 2µm Ni layers gave 0.41µm IMC thickness. Aging significantly influences IMC growth kinetics and phase evolution, with prolonged exposure leading to increased IMC thickness and potential changes in morphology. The 5µm Ni layers gave an increment in IMC thickness from 0.22µm until 0.8µm, and the 2µm Ni layers gave an increment from 0.6µm until 1.18µm after aging. The findings underscore the importance of optimizing Ni barrier layer thickness to control IMC formation and ensure the long-term reliability of lead-free solder joints in electronic assemblies. As for future recommendations, research on different Ni thicknesses as a barrier layer would be advantageous and might help clarify their limitations.
Analysis and Prediction of Surface Crack Growth Under Fatigue Loading
Authors: Akramin M.R.M. , Husnain M.N.M. , Hasif M. , Shaari M.S. , Takahashi Akiyuki
Published: January 2025

This research uses several fatigue crack growth models to examine the cyclic evolution of fatigue cracks in a shaft. Three fatigue crack growth models are used to forecast crack growth: Walker, Paris Law, and others. Experimental data support these models. The main problem is accurately estimating the propagation of fractures in shafts under cyclic loads because the existing models frequently exhibit variations in real-world applications that could lead to failures. This study compares the experimental results with model predictions to assess the accuracy of several models and improve our understanding of fatigue crack behaviour in practical settings. The experimental approach for 4 point-bending is compared with the simulation result, including boundary conditions and material properties. Paris’s and Walker’s fatigue crack growth models are employed in the S-version Finite Element Model (S-FEM) to simulate the 4 point-bending models’ analysis. The surface fatigue crack growth prediction is simulated and compared with the experimental results. The prediction beach marks of crack depth are slightly similar to the experimental results. Moreover, the prediction beach marks of crack length differ from the experimental results. The crack closure effect influences the difference between the experimental results. In summary, no single model is perfect in general; the selection is based on the particular circumstances and characteristics of the material. This work seeks to help engineers select the best model by improving prediction tools for maintaining mechanical components and increasing safety and performance in engineering applications.
The Application CRITIC-TOPSIS Method Integrated with PDCA Cycle in Solving Material Selection of Polymer Matrix material for Natural Fibre Composites in Cap Toe Shoes
Authors: Rahman Mohd Hidayat Ab , Mahmud Jamaluddin , Rahman Siti Mariam Abdul , Jumaidin Ridhwan
Published: January 2025

Polymer matrix material are polymer materials that exhibit the property of being flexible or moldability when heated to a certain temperature, and then solidify again when cooled. These material offer various benefits, including reusability, durability, moisture resistance, and rapid processing. Therefore, material selection is a critical aspect for engineers due to the wide variety of material that have comparable attributes that meet the requirements of the product design specification. This study integrates Criteria Importance Through Inter criteria Correlation (CRITIC) - Technique Order Preference by Similarity to Ideal Solution (TOPSIS) with the PDCA cycle to select polymer matrix for use in natural fibre reinforced polymer composites in cap toe shoes. The results indicate that polyamide (PA), when assessed using CRITIC-TOPSIS method and PDCA cycle, emerges as a potential material for polymer matrix composite material in cap toe shoes, achieving the highest rating among the alternatives. The decision was based on criteria such as performance, lightweight properties, and most environmental friendliness. By providing specific tools for each phase, the integration of CRITIC-TOPSIS and the PDCA cycle significantly influenced the material selection process. Incorporating additional variables in future studies could further enhance the comprehensive of the selection process
Influence of Surface Modification and MDP-based Primer Treatment on the Shear Bond Strength of Novel Zirconia-Dentine Interfaces
Authors: Aminuddin Nurul Shayhiera , Jamadon Nashrah Hani , Hadi Nurul Hannani Abdul , Amril Muhammad Sufiyan , Yew Hsu Zenn
Published: January 2025

This study investigates the impact of surface modification of zirconia and the application of MDP-based primer on the shear bond strength (SBS) between novel zirconia and dentine. The novel zirconia blocks were produced using a colloidal processing and slip casting method, developed at UKM. The sintered zirconia blocks were divided into three groups based on surface modification: air abrasion, diamond grinding, and a control group with no surface treatment. Surface roughness measurements and morphological observation was conducted. The samples were further subdivided into groups depending on whether an MDP-based primer was applied prior to cementation to the dentine. Bonding was achieved using resin cement light curing. The SBS testing was performed and analysed using two-way ANOVA. Results showed that the control group exhibited the highest surface roughness, followed by the air abrasion and diamond grinding groups. However, no significant difference was found between the control and air abrasion groups. The application of MDP-based primer significantly increased the SBS compared to non-primer-treated subgroups. The highest SBS was observed in the air abrasion group (37.57 ± 1.88 MPa), followed by the diamond grinding group (30.34 ± 1.52 MPa), and the control group (22.65 ± 1.13 MPa). Overall, surface modification altered the zirconia surface, and the application of MDP-based primer significantly improved the SBS between novel zirconia and dentine.
A Preliminary Study on Muscle Activation During Simulated Walk & Carry Task in Palm Oil Plantation
Authors: Saedin Meor Syukri Affendi Meor , Saad Wan Aliff Abdul , Samsuri Saiful Farhan Mohd , Sulaiman Maisarah , Azaman Aizreena , Hasan Muhammad Danial Abu , Ahmad Zair Asrar , Mustapa Amirah
Published: January 2025

This paper presents an electromyography (EMG) analysis of EXOROBO, a newly developed exoskeleton designed specifically for palm oil harvesting tasks to reduce Musculoskeletal Disorders (MSDs) among palm oil harvesters. The study evaluates the muscular activity patterns of individuals operating EXOROBO & CANTAS™ compared to the harvesting method by using CANTAS™. This research seeks to provide valuable insights into the ergonomic benefits and biomechanical implications of employing EXOROBO in palm oil harvesting operations through EMG measurements. Results indicate a significant reduction in muscle activity in four key muscle groups; left Biceps Brachii (L_BB) by 51.30%, left Rectus femoris (L_RF) by 44.61%, right Biceps Brachii (R_BB) by 23.98% and right Rectus Femoris (R_RF) by 7.17%. The findings of this study contribute to the ongoing discourse on the development of ergonomic solutions for agricultural labour, particularly in addressing the prevalent issue of MSDs in the palm oil industry.
Biodegradable and Green Degreaser for Industrial Application: An Overview
Authors: Cholis Nur , Razali Mohd Najib , Ramli Najmuddin Mohd , Sahran Mohd Syahmi Iskandar
Published: January 2025

This paper provides a comprehensive overview of biodegradable and green degreasers for industrial applications. Traditional degreasers, although effective in removing oils, grease, and residues, often pose significant environmental and health concerns due to the use of hazardous chemicals like volatile organic compounds (VOCs) and nonylphenol ethoxylates (NPEs). In response to increasing regulatory pressures and sustainability goals, biodegradable alternatives are gaining attention. These green degreasers utilize renewable materials, aligning with key Sustainable Development Goals (SDGs) related to environmental protection, climate action, and sustainable industrial practices. While these eco-friendly solutions offer promising performance and environmental benefits, challenges such as cost, awareness, and certification hinder widespread adoption. The review emphasizes the importance of continuous research, the need for standardization in biodegradability assessment, and innovations in biosurfactants and nanotechnology to improve the effectiveness of these products. Ultimately, biodegradable degreasers present a sustainable path forward for industries aiming to reduce their environmental impact and comply with evolving regulatory frameworks.
Evaluation of Work-Related Musculoskeletal Disorders (WMSDs) among Manual Assembly Workers in the Medical Device Manufacturing Industry
Authors: Wan Harun W. N. , Che Ghani S. A. , Md Noh M. S.
Published: January 2025

The COVID-19 pandemic has driven an unprecedented surge in demand for medical devices, reshaping the medical device manufacturing industry. Despite advances in automation, workers in this sector remain exposed to ergonomic hazards, including manual and repetitive heavy lifting, awkward postures, and repetitive motions, leading to work-related musculoskeletal disorders (WMSDs). While WMSDs prevalence has been widely studied, research specifically focused on workers in medical device manufacturing remains limited. This study assesses the prevalence of WMSDs among manual assembly workers in a multinational medical device manufacturing plant in Penang, Malaysia. The research focuses on three critical process areas: sub-pump, sub-flow, and final assembly. We collected data through three structured questionnaires, including the Cornell Musculoskeletal Discomfort Questionnaire (CMDQ), distributed to 153 workers in the infusion systems department. The results reveal that the most affected body regions are the neck, lower back, and right shoulder, which account for almost 82 % of the prevalence of WMSDs. This study provides essential insights into the incidence and root causes of WMSDs among workers in the medical device manufacturing sector, highlighting the need for ergonomic interventions. The findings underscore the importance of developing effective strategies, particularly from mechanical and production engineering points of view, such as introducing human-robot collaborative workspaces to mitigate ergonomic risks and enhance worker well-being in the medical device manufacturing industry.
Design and Performance Analysis of a Solar-Powered Aquaponics Irrigation System for Home Gardening
Authors: Zulkifli Muhammad Badrul Amin , Thong Roy Cheong Shen , Mokhtar Nadzirah Mohd , Ramli Roshahliza M.
Published: January 2025

Aquaponics is a farming method that combines fish and plant cultivation in a closed system where fish waste fertilizes the plants, and the plants help clean the water for the fish. With the growing trend towards solar energy, integrating solar technology into irrigation systems is becoming more widespread. The aim of this study is to develop a solar-powered irrigation system based on aquaponics principles. The system was designed using AutoCAD and divided into three components: the main structure, the solar system, and the electrical parts. It was programmed to operate twice daily, using solar energy to pressurize the pump. To ensure a stable power supply, battery voltage was monitored over a 14-day period. The system’s performance was evaluated by analyzing plant growth and the pH level in the aquarium tank. The battery voltage fluctuated between 12.43 V and 14.26 V at 8:00 AM, and between 12.93 V and 14.36 V at 6:00 PM. The solar energy system reliably powered the pump daily, maintaining a voltage of 11.9 V even on Day 4 when it rained. Performance results showed a gradual decrease in plant height from the “lower level” to the “middle level” and “higher level,” with growth measurements of 4.1 cm, 3 cm, and 2.7 cm, respectively. This is due to the highest water flow at the “lower level,” where the plant roots are fully submerged, promoting better growth. The aquarium’s pH remained within the optimal range of 6.5 to 9.0, ensuring the health of the fish.
Investigation of the Automatic Sorting Machine Based on PLC - Pneumatic System
Authors: Rashid AN , Yahya NM , Senawi A
Published: January 2025

Automatic systems have been extensively significant in the Malaysian industry, especially in manufacturing, electrical, and electronic sectors, as Malaysia is a major contributor to the country’s manufacturing exports. This is due to the high demand for the product, and Malaysia is a resourceful country that excels in producing high-quality products. Sorting is one of the manufacturing processes that involve arranging items based on a set of criteria to classify and group the items that will further be stored in the correct place. The manual labour hired in this process causes inefficiency in work, significant delays, and leads the worker to fatigue, which tends to result in visual errors, overlooking the product, and consequently may affect the customer. This study aims to comprehensively assess the sorting machine’s capabilities by evaluating its sorting speed, accuracy, and adaptability to diverse materials through a prototype of an automatic sorting machine based on a PLC-Pneumatic system that may enhance work efficiency in the industrial sector. The pneumatic cylinder will be used to sort the items with respect to the sensor that gives the signal upon the detection of the type of material. The programming of the PLC is done using Siemens Step7 MicroWIN software. Through this method, the automatic sorting machine surpasses the manual sorting method in terms of power and efficiency.
Drying model of stingless bee pot-pollen using a swirling fluidised bed dryer
Authors: Halim Luqman Abdul , Basrawi Firdaus , Yudin Ahmmad Shukrie Md , Azman Nurul Aini Mohd , Ramli Ahmad Syazwan
Published: January 2025

Stingless Bees Pot-Pollen (SBPP), a mixture of pollen, nectar and bee enzyme made by stingless bees has high moisture content, making it susceptible to microbes and fungi growth. This can cause spoilage and become toxic to be. Thus, SBPP require suitable preservation method for storage. Current methods available such as sun drying, and oven drying can be unhygienic, inefficient, and hard to control the temperature which leads to nutrient loss. Hence, a swirling fluidized bed dryer (SFBD), a modified fluidised bed dryer with swirling airflow is proposed as it has rapid drying performance at relatively low temperature. Currently, drying models for various materials in a fluidised bed dryer has been previously studied. However, research on drying model of SBPP using a SFBD is still lacking. Therefore, the objective of this paper is to determine the most suitable drying model for drying of SBPP in a SFBD. A lab scale SFBD with a 67° swirling distributor is used to dry 25 g of SBPP at superficial air velocities of 4, 5, and 6 m/s. In this study, 7 drying models obtained from literatures are compared to determine the most suitable model for drying of SBPP in SFBD. It was found that, the Midilli-Kucuk model was the most suitable drying model compared to other drying models tested with highest average R
2 (0.999307), lowest X
2 (7.2 × 10-5), and lowest RMSE (2.16 × 10-2). The Midilli-Kucuk model closely predict the experimental values for all superficial air velocities tested. The experimental results also shown that increasing the superficial air velocities will lead to increase in drying rate. Thus, it can be concluded that Midilli-Kucuk model is suitable to describe the drying of stingless bee pot-pollen in SFBD.
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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.