bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting 28Si projectile fragmentation cross sections with Bayesian neural network method*
Authors: Dang 党 Ying-Hua 英华 , Li 李 Jun-Sheng 俊生 , Zhang 张 Dong-Hai 东海 
Published: August 2024

Abstract
This study utilizes the Bayesian neural network (BNN) method in machine learning to learn and predict the cross-sectional data of 28Si projectile fragmentation for different targets at different energies and to quantify the uncertainty. The detailed modeling process of the BNN is presented, and its prediction results are compared with those of the Cummings, Nilsen, EPAX2, EPAX3, and FRACS models and experimental measurement values. The results reveal that, compared with other models, the BNN method achieves the smallest root-mean-square error (RMSE) and the highest agreement with the experimental values. Only the BNN method and FRACS model show a significant odd-even staggering effect; however, the results of the BNN method are closer to the experimental values. Furthermore, the BNN method is the only model capable of reproducing data features with low cross-section values at Z = 9, and the average ratio of the predicted to experimental values of the BNN is close to 1.0. These results indicate that the BNN method can accurately reproduce and predict the fragment production cross sections of 28Si projectile fragmentation and demonstrate its ability to capture key data characteristics.
Operational differences lead to longer lifetimes of satellite detectable contrails from more fuel efficient aircraft
Authors: Gryspeerdt Edward , Stettler Marc E J , Teoh Roger , Burkhardt Ulrike , Delovski Toni , Driver Oliver G A , Painemal David 
Published: August 2024

Abstract
Clouds produced by aircraft (known as contrails) contribute over half of the positive radiative forcing from aviation, but the size of this warming effect is highly uncertain. Their radiative effect is highly dependent on the microphysical properties and meteorological background state, varying strongly over the contrail lifecycle. In-situ observations have demonstrated an impact of aircraft and fuel type on contrail properties close to the aircraft, but there are few observational constraints at these longer timescales, despite these having a strong impact in high-resolution and global models. This work provides an observational quantification of these contrail controlling factors, matching air traffic data to satellite observations of contrails to isolate the role of the aircraft type in contrail properties and evolution. Investigating over 64 000 cases, a relationship between aircraft type and contrail formation is observed, with more efficient aircraft forming longer-lived satellite-detectable contrails more frequently, which could lead to a larger climate impact. This increase in contrail formation and lifetime is primarily driven by an increase in flight altitude. Business jets are also found to produce longer-lived satellite-detectable contrails despite their lower fuel flow, as they fly at higher altitudes. The increase in satellite-detected contrails behind more efficient aircraft suggests a trade-off between aircraft greenhouse gas emissions and the aviation climate impact through contrail production, due to differences in aircraft operation.
Hybrid heat pumps avoid extreme marginal abatement costs of electrifying peak heating loads in cold regions
Authors: Smillie Sean , Vaishnav Parth , Wade Cameron , Jordan Katherine , Venkatesh Aranya , Sinha Aditya , Apt Jay 
Published: August 2024

Abstract
Electrification with heat pumps is often cited as a preferred pathway to decarbonize US space heating in the transition to a net-zero energy system. However, fully electrifying building heat may significantly increase peak electric system loads during cold weather, thus challenging extensive adoption. A hybrid home heating system uses both heat pumps and conventional natural gas furnaces, where the gas appliance operates during peak heating periods. Here, we assess the marginal abatement costs of fully electrifying peak heating demands as opposed to allowing hybrid heating in current gas connected and ducted homes. We use a least-cost energy system optimization model that considers household, electric, and gas system costs, including electric distribution system expansion and gas system cost recovery. To ensure the cost of sufficient low-carbon dispatchable electric capacity is captured, the model includes historical days with peak heating demands and low wind and solar availability. We find hybrid heat pumps can achieve substantial decarbonization, with US natural gas residential heating consumption decreasing 70% to 95% from 2020 levels at marginal abatement costs below $200 per tonne CO2e. The cost of fully electrifying heating in cold regions is very high, with the marginal abatement cost of eliminating the last 1% of natural gas consumption exceeding $1000 per tonne CO2e even in scenarios designed to be favorable to electrification. The robust value of hybrid heat pumps in northern cold climates indicates the importance of flexible building heat decarbonization policies such as clean heat standards.
Sensitivity and vulnerability to summer heat extremes in major cities of the United States
Authors: Li Xiaojiang , Wang Guoqing , Zaitchik Benjamin , Hsu Angel , Chakraborty TC 
Published: August 2024

Abstract
Many cities are experiencing increases in extreme heat because of global temperature rise combined with the urban heat island effect. The heterogeneity of urban morphology also leads to fine-scale variability in potential for heat exposure. Yet, how this rise in temperature and local variability together impacts urban residents differently at exposure-relevant scales is still not clear. Here we map the Universal Thermal Climate Index, a more complete indicator of human heat stress at an unprecedentedly fine spatial resolution (1 m), for 14 major cities in the United States using urban microclimate modeling. We examined the different heat exposure levels across different socioeconomic and racial/ethnic groups in these cities, finding that income level is most consistently associated with heat stress. We further conducted scenario simulations for a hypothetical 1 °C increase of air temperature in all cities. Results show that a 1 °C increase would have a substantial impact on human heat stress, with impacts that differ across cities. The results of this study can help us better evaluate the impact of extreme heat on urban residents at decision-relevant scales.
Automated quantification of periodic discharges in human electroencephalogram
Authors: McGraw Christopher M , Rao Samvrit , Manjunath Shashank , Jing Jin , Brandon Westover M 
Published: August 2024

Abstract
Periodic discharges (PDs) are pathologic patterns of epileptiform discharges repeating at regular intervals, commonly detected in the human electroencephalogram (EEG) signals in patients who are critically ill. The frequency and spatial extent of PDs are associated with the tendency of PDs to cause brain injury, existing automated algorithms do not quantify the frequency and spatial extent of PDs. The present study presents an algorithm for quantifying frequency and spatial extent of PDs. The algorithm quantifies the evolution of these parameters within a short (10–14 second) window, with a focus on lateralized and generalized periodic discharges. We test our algorithm on 300 ‘easy’, 300 ‘medium’, and 240 ‘hard’ examples (840 total epochs) of periodic discharges as quantified by interrater consensus from human experts when analyzing the given EEG epochs. We observe 95.0% agreement with a 95% confidence interval (CI) of [94.9%, 95.1%] between algorithm outputs with reviewer clincal judgement for easy examples, 92.0% agreement (95% CI [91.9%, 92.2%]) for medium examples, and 90.4% agreement (95% CI [90.3%, 90.6%]) for hard examples. The algorithm is also computationally efficient and is able to run in 0.385 ± 0.038 seconds for a single epoch using our provided implementation of the algorithm. The results demonstrate the algorithm’s effectiveness in quantifying these discharges and provide a standardized and efficient approach for PD quantification as compared to existing manual approaches.
Impact of soil and water quality on the sustainable management of mangrove-compatible brackishwater aquaculture practices in Indonesia
Authors: Tarunamulia  , Ilman Muhammad , Sammut Jesmond , Paena Mudian , Basir  , Kamariah  , Taukhid Imam , Asaf Ruzkiah , Athirah Admi , Akmal  , Syaichudin Mohammad 
Published: August 2024

AbstractThe widespread degradation of mangroves has been attributed to their conversion into other land uses and purposes, most notably their destruction to construct extensive brackishwater aquaculture ponds. This study investigated the relationship between environmental factors and management alternatives for an integrated mangrove-aquaculture system in Derawan Island District, Berau Regency, East Kalimantan Province, Indonesia. The study collected a total of 56 soil and water samples from around 50 ha to assess environmental limiting factors for integrated mangrove-brackishwater aquaculture management. The measured soil quality variables included field pH (pHF), pH of hydrogen peroxide extract (pHFOX), peroxide oxidizable sulfur (SPOS), pyrite (FeS2), organic matter (OM), nitrogen-total (N-TOT), iron (Fe), and aluminum (Al). Water quality variables included salinity, temperature, pH, dissolved oxygen (DO), different forms of nitrogen (NH3–ammonia, NO3–nitrate, and NO2–nitrite), phosphate (PO4), Fe, and total organic matter (TOM). The study employed a hydrological restoration approach to suggest a mangrove-friendly aquaculture pond design and layout. The study generally showed that Acid Sulfate Soils (ASS) significantly restricted the existing mixed-mangrove aquaculture pond management by negatively impacting water quality. This study highlights that, given the characteristics of ASS-affected aquaculture ponds, reducing pond size for shrimp culture (mangrove-to-pond ratio of 80% and 20%) will simplify managing ASS environmental limiting factors through cost-effective remediation techniques and a Balanced Fertilization Strategy (BFS). The reduced shrimp pond size will also provide direct opportunities for mangrove restoration and allow effective hydrological restoration. The economic benefit of the proposed pond design and management model focuses on diversifying production units which include shrimp aquaculture ponds, milkfish or tilapia culture in the peripheral canals of the mangrove compartment, juvenile shrimp production, and periodic harvest from the primary pond canal. The study findings are particularly applicable to ponds that have already been built in ASS to improve productivity in addition to supporting the mangrove rehabilitation program. Converting mangrove and ASS-affected land is not advisable for constructing new aquaculture ponds.
Effect of atmospheric response induced by preceding typhoon on movement of subsequent typhoon over Northwestern Pacific
Authors: Lee Su-Jung , Lee Joon-Ho , Kim Kuk Jin 
Published: August 2024

Abstract
This study investigates the atmospheric interactions between two closely located typhoons in 2019. Typhoons in the Western Pacific significantly impact Eastern and Southeastern Asian countries, leading to various damages. As global warming is expected to increase typhoon intensity, accurate track forecasting becomes crucial for coastal disaster management. Despite the existing knowledge about the influence of typhoon activities on the atmospheric background, limited research addresses the atmospheric response between two typhoons. The study focuses on the cases of LEKIMA and KROSA, occurring simultaneously in 2019, and utilizes the Weather Research and Forecasting (WRF) model for simulations. The experimental setup involves comparing two scenarios: one with both typhoons and one with LEKIMA removed. Results reveal LEKIMA-induced distinctive atmospheric responses, including the closure of the western North Pacific subtropical high (WNPSH) boundary and the formulation of a wave train, influencing KROSA’s stagnation. The absence of LEKIMA allows KROSA to move more freely along the steering flow. Furthermore, the study highlights the potential of atmospheric models for understanding typhoon effects at regional to mesoscale levels. A comprehensive analysis of similar cases could enhance typhoon predictions, contributing to better damage mitigation strategies.
Self-similarity of quantum transport in graphene using electrostatic gate and substrate
Authors: Miniya Mohammed , Gaggero-Sager Luis M , Mora-Ramos Miguel E , Pérez-Álvarez Rolando , Oubram Outmane 
Published: August 2024

Abstract
A particular design for multibarrier structure in graphene, yielding a self-similar transport response, is proposed. The potential profile is based on rectangular wells and barriers, generated according independent nth order scaling laws for their heights and widths. The barriers are constructed by means of two distinct approaches (electrostatic or substrate). Dirac equation and transfer matrix approach are used to calculate transmission properties which, in turn, allow to evaluate the conductance via Landauer–Büttiker formalism. It is found that self-similarity with determined scaling rules between nth and

(
n
+
1
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th generations of transport properties appears when the order of generating laws is equal or greater than n = 7. Our proposal would be the first in which the self-similarity property is transferred from geometry to the spectrum, and consequently, to the transport properties of a quantum heterostructure. Possible ways of practical realization for the proposed structures are commented.
Productive use of electricity in agriculture in sub-Saharan Africa: a systematic review
Authors: Raji Tunmise , Allee Andrew , Williams Nathaniel J 
Published: August 2024

Abstract
Sub-Saharan African (SSA) countries often prioritize electrification as an important component of their infrastructure development, anticipating that electricity access will stimulate local economies. Agriculture, a significant contributor to employment and Gross Domestic Product in many of these countries, stands out as a crucial sector that could benefit from the expansion of electricity infrastructure. Thus, integrating electricity into agricultural practices presents a promising pathway for regional development. This review systematically analyzes the academic literature on the productive use of electricity in SSA’s agricultural sector, focusing on dominant trends, opportunities, and challenges at the electricity-agriculture nexus. Primary production activities, particularly irrigation, emerged as the most extensively studied application of electricity in the agricultural sector, and there was a limited number of studies focused on countries in Central Africa. Solar energy was the most assessed source of electricity, likely due to the abundance of solar resources in Africa. Less than half of the studies considered the economic or environmental impact of their proposed productive use activity, focusing more on the technical and operational feasibility of these initiatives. Also, we found that the productive use of electricity in agriculture is hindered by constraints such as a lack of technical expertise, unreliable power supply, limited market access, and inadequate financial services, and we quantitatively assessed the prevalence of each constraint in the selected studies. The review concludes by highlighting opportunities for future research and proposing strategic policy recommendations aimed at fostering the adoption of electrical technologies in agriculture across SSA, thereby enhancing the sector’s efficiency and productivity.
Protonic conduction on oxide surfaces—role and applications in electrochemical energy conversion
Authors: Norby Truls 
Published: August 2024

Abstract
Protonic conduction on surfaces of oxides has over the last two decades drawn attention for its possible utilisation in electrolytes for energy conversion at low temperatures and for its roles in enhancement of catalytic activity. This has led to deeper investigation and increased understanding of the phenomenon and development of quantifiable models. Along with this has emerged apparent demonstrations of use of such conduction in low-drain fuel cells as well as acknowledgement of the role of surface protonic conduction in electrodes for solid-state electrochemical and photoelectrochemical cells. Here is provided a brief review and elaboration of the fundamentals of the interaction of water and hydrogen with oxide surfaces, and models for the resulting protonic conduction in chemisorbed and physisorbed layers. We finally discuss aspects of surface protonic conduction in a range of applications, including sensors, catalysis, and electrochemical and photoelectrochemical energy conversion.
One dimensional multilayer structure for kerosene adulteration detection in petrol and diesel
Authors: Monika  , Prakash Suraj 
Published: August 2024

Abstract
We aim to design a multilayer periodic structure to detect the kerosene adulteration in the petrol and diesel fuels on a single processing setup. We built the structure by arranging TiO2 and SiO2 layers periodically in alternate manner with empty space at the middle. The optical response of the designed structure is then theoretically studied using transfer matrix method. Empty space of the design is filled with different kerosene adulterated petrol and diesel samples for inspecting structure response to incident electromagnetic waves. Theoretical calculations affirm that the proposed structure is capable to detect the fuel adulteration efficiently. Critical performance parameters like sensitivity, quality factor, figure of merit and limit of detection are calculated to check the effectiveness of the sensor. We also optimized the sensitivity of sensors design through modifying the defect thickness as well as angle of incidence of electromagnetic waves, and provides poly fit formula. It is observed that the sensitivity of sensor to detect kerosene adulteration in fuels highly depends on defect thickness and light incidence angle. An efficient sensor possessing high quality factor and figure of merit is realized from the designed structure that is capable of detecting

10

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5

RIU.
Application of novel hybrid deep learning architectures combining Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN): construction duration estimates prediction considering preconstruction uncertainties
Authors: Demiss Belachew A , Elsaigh Walied A 
Published: August 2024

Abstract
Construction duration estimation plays a pivotal role in project planning and management, yet it is often fraught with uncertainties that can lead to cost overruns and delays. To address these challenges, this review article proposes three advanced conceptual models leveraging hybrid deep learning architectures that combine Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) while considering construction delivery uncertainties. The first model introduces a Spatio-Temporal Attention CNN-RNN Hybrid Model with Probabilistic Uncertainty Modeling, which integrates attention mechanisms and probabilistic uncertainty modeling to provide accurate and probabilistic estimates of construction duration, offering insights into critical areas of uncertainty. The second model presents a Multi-Modal Graph CNN-RNN Hybrid Model with Bayesian Uncertainty Integration, which harnesses multi-modal data sources and graph representations to offer comprehensive estimates of construction duration while incorporating Bayesian uncertainty measures, facilitating informed decision-making and optimized resource allocation. Lastly, the third model introduces a Hierarchical Spatio-Temporal Transformer CNN-RNN Hybrid Model with Fuzzy Logic Uncertainty Handling, which addresses the inherent vagueness and imprecision in construction duration estimates by incorporating hierarchical spatio-temporal transformer architecture and fuzzy logic uncertainty handling, leading to more nuanced and adaptable project management practices. These advanced models represent significant advancements in addressing construction duration challenges, providing valuable insights and recommendations for future research and industry applications. Moreover, this review article critically examines the application of hybrid deep learning architectures, specifically the combination of CNNs RNNs, in predicting construction duration estimates at the preconstruction stage while considering uncertainties inherent in construction delivery systems.
Zinger, Clunker, Clanger, Flunker: On Two-Point Comparisons, and Why we Love Them
Authors: Landy Joshua 
Published: August 2024

Abstract
According to a now-standard theory, ‘Juliet is the sun’ is supposed to be a ‘pregnant’ metaphor, ready at any moment to beget a sprawling heap of adorable semantic puppies. Its two parts—‘Juliet’ and ‘the sun’—ostensibly meet at a virtually endless number of points, and it’s allegedly illuminating, enjoyable, or at least interesting to sit there all day spelling them out. But what if none of that is true? What if, instead, a successful creative comparison tends to offer exactly two points of contact, the first of which makes it adequate, while the second gives it power? To put it metaphorically (as is only appropriate): such an image is neither an iceberg (à la Cavell) nor a simple triangle (à la Aristotle) but a tetrahedron, a muscle, a covalent bond. And the telos of such images isn’t to transmit additional information but intensify, or disorient, or even—surprisingly—make us feel at home in this miserable world.
Continuity and Evolution in Vermeule on Legal Interpretation
Authors: Casey Conor 
Published: August 2024

Abstract
This article is a constructive interpretation of Adrian Vermeule’s thought on legal interpretation, putting his previous work on these issues in conversation with his explicit embrace of the classical legal tradition so prominently on display in Common Good Constitutionalism. What emerges is a picture of Vermeule’s contemporary thinking on interpretation that has an interesting core of continuity, one running concurrently with several significant conceptual and normative evolutions brought about by his more explicit embrace of a classical legal framework. Part I offers a synthesis of Vermeule’s treatment of core questions of legal interpretation pre-Common Good Constitutionalism. Part II begins by outlining Vermeule’s express turn to the classical legal tradition and how this tradition approaches important public law issues linked to interpretation. Part II then proceeds to pick out and elaborate on themes of continuity and evolution. I argue here that while Vermeule’s embrace of the classical legal tradition has involved several significant conceptual and normative shifts in his thinking, this has not involved repudiation of his prior work on legal interpretation. Rather, the thrust and insights of much of his previous public law thought on interpretation retain vibrancy within the explicitly classical framework he has now adopted. Overall, I suggest Common Good Constitutionalism, and the works accompanying and building upon it, can be profitably read as providing a form of retroactive coherence to Vermeule’s long-standing arguments concerning legal interpretation, offering them a unifying conceptual framework. From the perspective of a classical natural law jurist at least, Vermeule’s embrace of the classical tradition provides his extensive body of scholarship in this area a more explicit and robust conceptual and normative anchor.