bluuebunny/crossref_metadata_2025_split huggingface dataset:
Review and Measure Winter Thermal Performance in CLT Building: A Case Study on Meldia Research Institute for Advanced Wood
Authors: Saputra M R , Sekartaji D , Khidmat R P , Ardiyansah W S , Husna S K , Rizkika S , Kamaruddin M 
Published: October 2024

Abstract
CLT (Cross Laminated Timber) as a building material could help lower the carbon footprint of construction projects. Thermal performance and comfort in CLT buildings as a place to work are very important for optimizing comfort and work quality using CLT buildings. In winter conditions, measure and review is very necessary to optimize the desired building according to the standard level of comfort when working. The aims of this research is to measure and review indoor thermal comfort of CLT building during winter, with the case study Meldia Research Institute for Advanced Wood, Fukuoka, Kitakyushu. This research method involves measuring indoor temperature intensity in winter to understand how CLT buildings can achieve an optimal balance of thermal comfort. The results of measurements using PMV analysis of both rooms with the HVAC on at a temperature of 22 degrees Celsius are that the PMV value tends from a Slightly warm condition (+1) to a Neutral (0) at each measurement time and at all points. Room 1 has the highest PMV value between slightly cool (-0.5) to Slightly warm (+1), while room 2 has the lowest value between Cool (-2) to Slightly warm (+1). These findings can guide building designers in developing architectural solutions that are sustainable and focus on occupant well-being.
Awareness of Campus Building Users to Achieve Energy Efficiency in Facing the Implementation of Green Buildings (Case Study: Politeknik Negeri Pontianak Integrated Lecture Building)
Authors: Yudhiarma  , Prabowo Herry , Hilmy Mochamad 
Published: October 2024

Abstract
Building users’ awareness is a very crucial factor in efforts to achieve efficient energy use in buildings, especially in the green building concept. However, research that examines the awareness of building users specifically in the campus environment is still very rarely conducted, especially in Indonesia. This research, which uses a case study at Politeknik Negeri Pontianak integrated lecture building, investigates the criteria for awareness of building users and their behavior in using energy in the building. This research tries to identify social parameters in achieving building energy efficiency using a quantitative approach. The series of statistical tools used includes ranking of average values. The results of this research show that the focus of improvement can be done by increasing awareness of several things, namely recognizing the problem of decreasing electrical resources, dividing resource use in order to reduce electricity consumption, and understanding efforts and making preparations in the face of reduced electrical energy sources.
Urban Community Perception of The Importance of Sustainable Housing in Greater Tangerang, Indonesia
Authors: Ardiyansah W S , Rizkika S , Tamariska S R , Sekartaji D , Khidmat R P 
Published: October 2024

Abstract
This study explores the perceptions of urban communities regarding the significance of sustainable housing within the Greater Tangerang region. Investigating how residents perceive the importance of sustainable features in their housing environments, the research examines the awareness and attitudes of urban inhabitants toward sustainable housing practices. Employing a survey data quantitative assessment with questionnaire, the study aims to shed light on the urban community’s perspectives on sustainable housing and its potential impact on the overall urban environment. Urban communities in Greater Tangerang show moderate understanding of sustainable housing, requiring improved education and outreach efforts. Despite already exhibiting great caring interest, there’s a need for a large-scale initiative involving all stakeholders to further promote sustainable housing concepts and enhance overall awareness and implementation. The findings contribute valuable insights for policymakers, urban planners, and developers seeking to enhance sustainable housing initiatives in the Greater Tangerang area.
Changeability, adaptability, and resiliency of Indonesian historic area: a case of Kesawan, Medan
Authors: Ginting S W , Fitri Isnen 
Published: October 2024

Abstract
This paper aims to analyse changes in buildings and plots in a historical area in Medan, Indonesia, in 1875, 1945, and 2023. Change is discussed from the aspect of physical and functional change. The ability of an environment to change and adapt is in line with the concepts of resilience and sustainability. This paper shows that buildings change functionally from hotels and clubhouses to banks. Plots became smaller as previous plots were divided into smaller parts separated by new streets or alleys. This pattern was more pronounced in large, square-shaped plots. Factors that drove these changes were influenced by political factors (lack of government regulation and social movement against Dutch colonialism) and economic factors (Kesawan’s role as a business center).
Universal production of anisotropic bilayer WSe2 nanoscrolls for high-performance photodetector
Authors: Lan Xiang , Zhang Fen , Huang Ziwei , Zhang Xuyang , Chen Zhaolong , Zhong Mianzeng , Cheng Yingliang , Zhang Zhengwei 
Published: October 2024

Abstract
Transition metal dichalcogenide nanoscrolls (NSs) exhibit unique optoelectronic properties due to their spiral tubular structures. In this study, we successfully fabricated WSe2 NSs with various morphologies, illustrating the evolution from planar to NS via an internal strain-driven rolling process. The anisotropic optical properties of the NSs were systematically analyzed by angle-resolve polarized Raman spectroscopy. For NSs with different rollup angles, the strain distribution is manifested by the variation of Raman intensity on the linear axis. In addition, the on/off ratio and detectivity of device based on bilayer NS reach 5.3 × 104 and 2.63 × 109 Jones, caused by the ultralow dark photocurrent. In summary, our study demonstrates a universal method for producing polymorphic products, demonstrating that bilayer WSe2 NSs hold significant potential as a platform for fundamental research and technological applications.
Sintering of copper nanoparticles using intense pulsed light for screen-printed films on flexible substrate
Authors: Manoranjan  , Gupta Ashish , Mohapatra Y N 
Published: October 2024

Abstract
Rapid growth in applications involving large area flexible electronics has led to wide adoption of the technique of sintering printed films using intense pulsed light due to its pulse mode operation and ability to reach high sintering temperatures without affecting the underlying substrate significantly. We study the sintering mechanisms of screen-printed thin films of copper nanoparticles on polyethylene terephthalate plastic substrates by varying the irradiance energy over a wide range to monitor conductivity and associated microstructure changes. We obtain optimized parameters which indicate the existence of a sharp threshold irradiance energy to kickstart sintering, and two distinct regimes beyond that. The low temperature regime has a high energy barrier while the high temperature regime has a substantially reduced energy barrier with a change of phase due to local melting.
Navigating carbon neutrality pathway beyond energy and economic agents: the influence of media liberty across the OECD countries
Authors: Uzar Umut , Eyuboglu Kemal , Alola Andrew Adewale 
Published: October 2024

Abstract
Press freedom is a fundamental aspect of democratic societies, playing a critical role in shaping public discourse, fostering transparency, and holding institutions accountable. Furthermore, its impact extends beyond political and social realms to encompass environmental sustainability, particularly in Organisation for Economic Co-operation and Development (OECD) countries. While extensive research has been conducted on the economic, social, and institutional factors that influence environmental outcomes, the role of press freedom in shaping ecological footprint remains underexplored. However, this study aims to address this gap by examining the relationship between press freedom and ecological footprint across 36 OECD countries from 2013 to 2022. Utilizing a system generalized method of moments (GMM) analysis and controlling for economic growth, trade openness, and energy consumption, this research reveals significant findings. Specifically, it demonstrates that press freedom serves as a catalyst for reducing ecological footprint, presenting OECD countries with a unique opportunity for environmental gains and potentially achieving carbon neutrality. In contrast, we find indicators such as economic growth, energy consumption, and trade openness have negative impact on environmental quality. Overall, this study underscores the importance of promoting press freedom as a key strategy for advancing environmental sustainability and calls for concerted efforts to harness its potential for mitigating ecological footprint in OECD countries and beyond.
Green finance, sustainable infrastructure, and green technology innovation: pathways to achieving sustainable development goals in the belt and road initiative
Authors: Mahmood Shahid , Sun Huaping , Iqbal Asifa , Alhussan Amel Ali , El-kenawy El-Sayed M 
Published: October 2024

Abstract
Achieving the Sustainable Development Goals (SDGs) remains a significant challenge for many countries, particularly in the face of increasing environmental pollution. Balancing social, economic, and environmental sustainability under these conditions is especially complex. This study explores the role of green finance in promoting sustainable infrastructure, innovation in green technology, corporate social responsibility, economic stability, and environmental conservation within the framework of Belt and Road initiative (BRI), with a specific focus on the China-Pakistan Economic Corridor (CPEC) initiatives. Furthermore, the study examines the role of government support in facilitating the issuance of GF, emphasizing its significance in large-scale international development projects like CPEC. Data were collected through a structured questionnaire targeting a diverse group of respondents, including businessmen, CPEC officials, and representatives from the Ministry of Finance, Pakistan Environmental Protection Agency, and Ministry of Planning and Development. Partial Least Squares analysis was employed to test the proposed relationships and hypotheses. The results indicate a significant positive impact of green finance on the development of sustainable infrastructure and the innovation of green technology. Additionally, the results underscore the pivotal role of environmentally friendly technologies and sustainable infrastructure in driving the achievement of SDGs, especially in the social, economic, and environmental dimensions. The study findings offer actionable insights for policymakers, highlighting the critical need to integrate green finance with sustainable practices to foster economic growth and environmental protection. These findings provide a strategic roadmap for nations aiming to align their development goals with global sustainability standards.
Implementation of time-dependent Hartree–Fock in real space
Authors: Panta Uday , Strubbe David A 
Published: October 2024

Abstract
Time-dependent Hartree–Fock (TDHF) is one of the fundamental post-Hartree–Fock (HF) methods to describe excited states. In its Tamm-Dancoff form, equivalent to Configuration Interaction Singles, it is still widely used and particularly applicable to big molecules where more accurate methods may be unfeasibly expensive. However, it is rarely implemented in real space, mostly because of the expensive nature of the exact-exchange potential in real space. Compared to widely used Gaussian-type orbitals (GTO) basis sets, real space often offers easier implementation of equations and more systematic convergence of Rydberg states, as well as favorable scaling, effective domain parallelization, flexible boundary conditions, and ability to treat model systems. We implemented TDHF in the Octopus real-space code as a step toward linear-response hybrid time-dependent density-functional theory (TDDFT), other post-HF methods, and ensemble density-functional theory methods involving exact exchange. Calculation of HF’s non-local exact exchange is very expensive in real space. We overcome this limitation with Octopus’ implementation of Adaptively Compressed Exchange, and find the appropriate mixing scheme and starting point to complete the ground-state calculation in a practical amount of time, and thus enable TDHF. We compared our results to those from GTOs on a set of small molecules and confirmed close agreement of results, though with larger deviations than in the case of semi-local TDDFT. We find that convergence of TDHF demands a finer real-space grid than semi-local TDDFT. We also present the subtleties in benchmarking a real-space calculation against GTOs, relating to Rydberg and vacuum states.
HyPELS: enhancing li-ion battery remaining useful life prediction with hybrid perspective ensemble learning strategy
Authors: Han Xuewei , Yuan Huimei , Wu Lifeng 
Published: October 2024

Abstract
Remaining useful life (RUL) prediction for Li-ion batteries typically relies on a single perspective, which leads to limited applicability and reduced prediction accuracy. To address the limitations of traditional methods, a hybrid perspective ensemble learning strategy (HyPELS) that integrates HIs and capacity degradation data is proposed. First, for the perspective of battery health indicators (HIs), the block-shuffled OS-ELM (BSOS-ELM) is proposed, which mitigates the issue of early data characteristics being overlooked when applying OS-ELM. Second, for the perspective of capacity degradation data, after decomposition using complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the obtained high-frequency signals are reconstructed using two reconstruction rules, which accounts for both local and global signal characteristics. Subsequently, during the training of the autoregressive integrated moving average model (ARIMA), we feed early capacity degradation data in reverse order, maximizing the utility of data while deepening the models understanding of the overall capacity degradation process. Finally, the predicted capacity obtained from both perspectives is constructed into a meta-dataset, utilizing BSOS-ELM as the meta-model for ensemble learning. HyPELS not only captures local variations but also learns the overall trend, fully leveraging the strengths of both perspectives to capture the multi-dimensional characteristics of battery aging comprehensively. Experimental results demonstrate that across multiple datasets, HyPELS outperforms other algorithms in various assessment criteria, fully illustrating the effectiveness of HyPELS and validating its advantages in enhancing prediction accuracy and robustness.
Multi-pronged strategies for enhancing building envelopes toward nearly-zero energy in hot climatic regions
Authors: M Ibrahim Mohanad , William Micheal A , A Hanafy Ahmed , F Moussa Mona , Suarez-Lopez María Jose 
Published: October 2024

Abstract
Growing concerns about climate change and rising energy demands necessitate advancements in building energy efficiency. This study investigates the effectiveness of radiative coatings and thermal insulation, both individually and combined, in reducing energy consumption and carbon footprint for buildings in hot and humid climates. This research contributes to a growing body of knowledge by comprehensively evaluating the combined effects of these strategies. A comparative analysis was conducted using data on energy usage and carbon emissions. The research highlights the effectiveness of envelope-enhancing techniques in reducing energy consumption and carbon emissions. The application of radiative coating led to a significant 13.1% decrease in energy usage, totaling 681.95 MWh, and corresponding emissions of 482.14 tons of CO2. Radiative coating offers the most cost-effective solution with an LCOS of $0.045 kWh−1. When integrating thermal insulation with radiative coating, there was a substantial 12.0% reduction in energy consumption, amounting to 690.39 MWh, and emissions of 488.11 tons of CO2. The integrated model provides significant energy savings at a slightly higher LCOS of $0.052 kWh−1, making it a balanced choice between efficiency and cost-effectiveness compared to using thermal insulation alone. Moreover, the study emphasizes that the combination of Glazing Integrated Photovoltaic (GIPV) with radiative coating can lead to the creation of nearly zero-energy buildings, resulting in a significant energy savings of 34.9%. These results underscore the efficacy of these technologies in achieving significant energy savings and environmental benefits. This study demonstrates that radiative coatings significantly reduce energy consumption and carbon footprints. The combined method with thermal insulation reduces energy, suggesting further optimization strategies in hot and humid conditions. The results of this investigation recommend utilizing Glazing Integrated Photovoltaic (GIPV) to achieve nearly zero-energy buildings. Such integrated solutions not only improve energy efficiency but also make a substantial contribution to environmental sustainability in the building sector.
Observation impact explanation in atmospheric state estimation using hierarchical message-passing graph neural networks*
Authors: Jeon Hyeon-Ju , Kang Jeon-ho , Kwon In-Hyuk , Lee O-Joun 
Published: October 2024

Abstract
The impact of meteorological observations on weather forecasting varies with the sensor type, location, time, and other environmental factors. Thus, the quantitative analysis of observation impacts is crucial for the effective and efficient development of weather forecasting systems. However, existing impact analysis methods are dependent on specific forecast systems, because system-specific adjoint models are used and the sensitivity of the observation to the forecast is measured. This study investigates the impact of observations on atmospheric state estimation in weather forecasting systems by developing a novel graph neural network (GNN) model specialized for analyzing the heterogeneous relations between observations and atmospheric states. The observation impact can then be assessed by applying explainable methods to the proposed GNN model, which is independent of forecasting systems. Further, we develop a novel application called ‘CloudNine,’ a system that provides impact analysis for individual observations with visualization. Our GNN model comprises hierarchical message-passing modules that separately analyze spatial correlations between observations at close locations and atmospheric states at close locations and then examine correlations between observations and atmospheric states. To consider the different factors influencing these correlations, we utilized geo-coordinates and types of observations in the attention mechanism of the modules with their feature vectors. We then applied gradient-based explainability methods to quantify the significance of the different observations in the estimation. Evaluated using data from 11 satellites and land-based observations, the results highlight the effectiveness of the proposed model and the visualization of observation impacts, enhancing the understanding and optimization of observational data in weather forecasting.
Rapid likelihood free inference of compact binary coalescences using accelerated hardware
Authors: Chatterjee D , Marx E , Benoit W , Kumar R , Desai M , Govorkova E , Gunny A , Moreno E , Omer R , Raikman R , Saleem M , Aggarwal S , Coughlin M W , Harris P , Katsavounidis E 
Published: October 2024

Abstract
We report a gravitational-wave parameter estimation algorithm, AMPLFI, based on likelihood-free inference using normalizing flows. The focus of AMPLFI is to perform real-time parameter estimation for candidates detected by machine-learning based compact binary coalescence search, Aframe. We present details of our algorithm and optimizations done related to data-loading and pre-processing on accelerated hardware. We train our model using binary black-hole (BBH) simulations on real LIGO-Virgo detector noise. Our model has

∼

6

million trainable parameters with training times

≲

24

h. Based on online deployment on a mock data stream of LIGO-Virgo data, Aframe + AMPLFI is able to pick up BBH candidates and infer parameters for real-time alerts from data acquisition with a net latency of

∼

6

s.
Efficient ensemble uncertainty estimation in Gaussian processes regression
Authors: Christiansen Mads-Peter Verner , Rønne Nikolaj , Hammer Bjørk 
Published: October 2024

Abstract
Reliable uncertainty measures are required when using data-based machine learning interatomic potentials (MLIPs) for atomistic simulations. In this work, we propose for sparse Gaussian process regression (GPR) type MLIPs a stochastic uncertainty measure akin to the query-by-committee approach often used in conjunction with neural network based MLIPs. The uncertainty measure is coined ‘label noise’ ensemble uncertainty as it emerges from adding noise to the energy labels in the training data. We find that this method of calculating an ensemble uncertainty is as well calibrated as the one obtained from the closed-form expression for the posterior variance when the sparse GPR is treated as a projected process. Comparing the two methods, our proposed ensemble uncertainty is, however, faster to evaluate than the closed-form expression. Finally, we demonstrate that the proposed uncertainty measure acts better to support a Bayesian search for optimal structure of Au20 clusters.
The Concept of Emotional Disorder
Authors: Sibson Ayob Gloria 
Published: October 2024

Abstract
This book examines judgements about emotional health and pathology, with the aim of understanding the conceptual structure of these judgements. This is essential for adjudicating the debate about whether psychiatry (over)-pathologizes ordinary emotional experiences, and more broadly, for understanding the place of emotions—especially distressing and unpleasant emotions—in a form of life in which flourishing, personal and moral agency, and self-identity matter. This investigation into the concept of emotional disorder promises to enrich our understanding of the value of emotions in human life. It also introduces new considerations that are germane to the debate about the concept of mental disorder.
Setting out the Basic Evaluative Dimensions (BED) Framework
Authors: Sibson Ayob Gloria 
Published: October 2024

Abstract
The central claim in this chapter is that the concept of emotional disorder is meta-evaluative, and thus that judgements of emotional disorder are opaque. This claim is established by means of the ‘Basic Evaluative Dimension’ (BED) analytical framework presented in this chapter. In slightly more detail: the chapter identifies five basic evaluative dimensions along which we appraise our emotional experiences (these are the rationality or otherwise of our emotional responses, the valence quality of our emotional experiences, their existential significance, as well as the roles they play in agential efficacy and interpersonal functioning), and it shows that the judgement of emotional disorder is always rooted in the negative appraisal we make of an emotional experience along one or more of these basic evaluative dimensions. This judgement is constrained and counterweighed by any positive appraisal made of the emotional experience, again along one or more of these basic evaluative dimensions. In this way, the judgement of emotional disorder is a meta-evaluative judgement that signifies a negotiation (either implicitly or explicitly) between the various appraisals made of an emotional experience along these more basic dimensions of evaluation.