bluuebunny/crossref_metadata_2025_split huggingface dataset:
An exact stationary axisymmetric vacuum solution within a metric-affine bumblebee gravity
Authors: Araújo Filho A.A. , Nascimento J.R. , Petrov A.Yu. , Porfírio P.J. 
Published: July 2024

Abstract
Within the framework of the spontaneous Lorentz symmetry breaking (LSB), we consider a metric-affine generalization of the gravitational sector of the Standard Model Extension (SME), including the Lorentz-violating (LV) coefficients u and sμν
. In this model, we derive the modified Einstein field equations in order to obtain a new axisymmetric vacuum spinning solution for a particular bumblebee's profile. Such a solution has the remarkable property of incorporating the effects of LSB through the LV dimensionless parameter X = ξb
2, with ξ is the nonminimal coupling constant, and b
2 = bμbμ
, with bμ
is the vacuum expectation value of the bumblebee field; as the LSB is turned off, X = 0, we recover the well-established result, the Kerr solution, as expected. Afterwards, we calculate the geodesics, the radial acceleration and thermodynamic quantities for this new metric. We also estimate an upper bound for X by using astrophysical data of the advance of Mercury's perihelion.
Interference of harmonics emitted by different tunneling momentum channels in laser fields
Authors: Zhang 张 Ling-Yu 玲玉 , Xie 谢 Zhuo-Xuan 卓璇 , Wang 王 Can 灿 , Ge 葛 Xin-Lei 鑫磊 , Guo 郭 Jing 静 
Published: July 2024

Abstract
By numerically solving the semiconductor Bloch equation (SBEs), we theoretically study the high-harmonic generation of ZnO crystals driven by one-color and two-color intense laser pulses. The results show the enhancement of harmonics and the cut-off remains the same in the two-color field, which can be explained by the recollision trajectories and electron excitation from multi-channels. Based on the quantum path analysis, we investigate contribution of different ranges of the crystal momentum k of ZnO to the harmonic yield, and find that in two-color laser fields, the intensity of the harmonic yield of different ranges from the crystal momentum makes a big difference and the harmonic intensity is depressed from all k channels, which is related to the interferences between harmonics from symmetric k channels.
AI-assisted detector design for the EIC (AID(2)E)
Authors: Diefenthaler M. , Fanelli C. , Gerlach L.O. , Guan W. , Horn T. , Jentsch A. , Lin M. , Nagai K. , Nayak H. , Pecar C. , Suresh K. , Vossen A. , Wang T. , Wenaus T. ,   the AID(2)E collaboration
Published: July 2024

Abstract
Artificial Intelligence is poised to transform the design of complex, large-scale detectors like ePIC at the future Electron Ion Collider. Featuring a central detector with additional detecting systems in the far forward and far backward regions, the ePIC experiment incorporates numerous design parameters and objectives, including performance, physics reach, and cost, constrained by mechanical and geometric limits.
This project aims to develop a scalable, distributed AI-assisted detector design for the EIC (AID(2)E), employing state-of-the-art multiobjective optimization to tackle complex designs. Supported by the ePIC software stack and using Geant4 simulations, our approach benefits from transparent parameterization and advanced AI features.
The workflow leverages the PanDA and iDDS systems, used in major experiments such as ATLAS at CERN LHC, the Rubin Observatory, and sPHENIX at RHIC, to manage the compute intensive demands of ePIC detector simulations. Tailored enhancements to the PanDA system focus on usability, scalability, automation, and monitoring.
Ultimately, this project aims to establish a robust design capability, apply a distributed AI-assisted workflow to the ePIC detector, and extend its applications to the design of the second detector (Detector-2) in the EIC, as well as to calibration and alignment tasks. Additionally, we are developing advanced data science tools to efficiently navigate the complex, multidimensional trade-offs identified through this optimization process.
Prospects of mono cellulosic and cellulosic-glass hybrid fillers reinforced polypropylene composites
Authors: Webo Wilson , Khoathane Moshibudi Caroline , Mhike Washington 
Published: July 2024

Abstract
The objective of the study was to investigate the flexural mechanical, thermal and morphological properties of polypropylene composites reinforced with cellulose and glass particles. Polypropylene lacks sufficient strength and stiffness for many applications. By reinforcing it with cellulose and glass particles, the study was aimed at enhancing these mechanical properties, addressing the need for stronger and more durable materials. These composites are likely to find applications in the automotive industry where light weight, strong and heat resistant materials are needed for bumpers, dashboards, and interior trims. Additionally, these composites can be used for consumer goods where strong and lightweight materials are needed for various consumer products such as furniture, sporting goods, and appliances. Finite Element Analysis (FEA) was used to explore the properties of the cellulosic composites and the experimental method was used to validate the results of FEA. The injection moulding process was used to fabricate the specimens for this study. The specimens were then characterized for their thermal behavior, morphology, and flexural properties. The thermal properties that were performed were thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). Moreover, the morphology of the fabricated samples was examined using the scanning electron microscopy (SEM). The composites were fabricated at filler volume fractions ranging from 0% to 50%. The flexural strength of both the wood powder/PP composites and the hybrid composites were found to be maximum for a filler volume fraction of 40% exhibiting 796.44 MPa and 1692.951 MPa, respectively. The research also noted from TGA that the melting temperature of all the fabricated samples were in the range of 150 °C to 160 °C. The glass transition temperature of neat polypropylene was around −20 °C.
Enhanced antimicrobial potency and stability of juglone/β-cyclodextrin inclusion complexes: a comparative study of formulation methods
Authors: Pelit Arayıcı Pelin , Acar Tayfun , Özbek Tülin , Acar Serap 
Published: July 2024

Abstract
Juglone (5-hydroxy-1,4-naphthoquinone), a natural antifungal and antibacterial agent derived from walnut trees, possesses significant therapeutic potential limited by its low water solubility and instability in varying pH and temperature conditions This study aims to address these limitations by enhancing juglone’s solubility, stability, and antimicrobial efficacy through the formation of inclusion complexes with β-cyclodextrin (β-CD). Employing methods such as co-precipitation, freeze-drying, and solvent evaporation, we synthesized these complexes and confirmed their formation using UV–vis, and FT-IR spectroscopy. The obtained optimum complex was characterized using SEM to reveal its structural properties, while NMR analysis showed significant chemical shift changes, indicative of complex formation between juglone and β-CD; additionally, XRD analysis confirmed the amorphous nature of the J-β-CD3-4 inclusion complex, providing direct evidence for its formation. Our findings reveal a notable enhancement in the pH and thermal stability of juglone within the β-CD inclusion complex, in comparison to its free form. Moreover, the antimicrobial activity of the juglone-β-CD complex surpassed that of juglone alone. The increased water solubility of juglone in the inclusion complex contributed to its enhanced antimicrobial activity. The inhibition zone diameters of J-β-CD3-4 inclusion complex against E. coli, S. aureus, and C. albicans were 7, 22, and 8.5 mm, respectively, relatively higher than juglone. Remarkably, in the broth microdluation method, the MIC and MBC values of the inclusion complex were determined to be much lower than those of free juglone, a significant fourfold decrease for S. aureus, and C. albicans and twofold for E. coli. These results underscore the potential of juglone-β-CD complexation in extending the applicability of juglone, especially in sectors such as food preservation, agriculture, and pharmaceuticals, where enhanced stability and efficacy of natural antimicrobial agents are crucial.
Enhanced degradation of tetracycline by gas-liquid discharge plasma coupled with g-C3N4/TiO2
Authors: WANG 王 Zhenhai 振海 , ZHOU 周 Zikai 子凯 , WANG 王 Sen 森 , FANG 方 Zhi 志 
Published: July 2024

Abstract
Plasma-catalysis is considered as one of the most promising technologies for antibiotic degradation in water. In the plasma-catalytic system, one of the factors affecting the degradation effect is the performance of the photocatalyst, which is usually restricted by the rapid recombination of electrons and holes as well as narrow light absorption range. In this research, a photocatalyst g-C3N4/TiO2 was prepared and coupled with gas-liquid discharge (GLD) to degrade tetracycline (TC). The performance was examined, and the degradation pathways and mechanisms were studied. Results show that a 90% degradation rate is achieved in the GLD with g-C3N4/TiO2 over a 10 min treatment. Increasing the pulse voltage is conducive to increasing the degradation rate, whereas the addition of excessive g-C3N4/TiO2 tends to precipitate agglomerates, resulting in a poor degradation efficiency. The redox properties of the g-C3N4/TiO2 surface promote the generation of oxidizing active species (H2O2, O3) in solution. Radical quenching experiments showed that ·OH, hole (h
+), play important roles in the TC degradation by the discharge with g-C3N4/TiO2. Two potential degradation pathways were proposed based on the intermediates. The toxicity of tetracycline was reduced by treatment in the system. Furthermore, the g-C3N4/TiO2 composites exhibited excellent recoverability and stability.
Vegetation reduces cooling demand in low-income neighborhoods on hot days in Chicago
Authors: Hardaway Kanaan C , Choi Minsoo , Nateghi Roshanak , McMillan Sara K , Ma Zhao , Hardiman Brady S 
Published: July 2024

Abstract
Cooling energy demand is sensitive to urban form and socioeconomic characteristics of cities. Climate change will impact how these characteristics influence cooling demand. We use random forest machine learning methods to analyze the sensitivity of cooling demand in Chicago, IL, to weather, vegetation, building type, socioeconomic, and control variables by dividing census tracts of the city into four groups: below-Q1 income–hot days; above-Q1 income–hot days; below-Q1 income–regular days; and above-Q1 income–regular days. Below-Q1 census tracts experienced an increase in cooling demand on hot days while above-Q1 census tracts did not see an increase in demand. Weather (i.e. heat index and wind speed) and control variables (i.e. month of year, holidays and weekends) unsurprisingly had the most influence on cooling demand. Among the variables of interest, vegetation was associated with reduced cooling demand for below-Q1 income on hot days and increased cooling demand for below-Q1 income on regular days. In above-Q1 income census tracts building type was the most closely associated non-weather or control variable with cooling demand. The sensitivity of cooling demand for below-Q1 income census tracts to vegetation on hot days suggests vegetation could become more important for keeping cities cool for low-income populations as global temperatures increase. This result further highlights the importance of considering environmental justice in urban design.
A deep transfer learning-based algorithm for concrete surface defect detection
Authors: Jin Zhisheng , Wang Lifeng 
Published: July 2024

Abstract
The integrity and safety of concrete structures are crucial in modern civil engineering. Traditional image-defect detection methods are significantly affected by light and noise. Methods based on deep learning, particularly convolutional neural networks (CNNs), offer new solutions for automated defect detection. This paper introduces a concrete surface defect detection algorithm based on deep transfer learning. Our model utilizes the ResNet50 architecture as its backbone and incorporates Atrous Spatial Pyramid Pooling (ASPP) to adapt to the diversity of defects and enhance recognition accuracy. In addition, the use of a self-attention mechanism effectively enhances the model’s focus on and analysis of key defect areas, improving its ability to perceive and select features for defects of various sizes, aiding precise localization and classification under complex conditions. Image preprocessing techniques such as resizing, conversion to grayscale, histogram equalization, and noise addition further enhance the robustness of the model in diverse real-world scenarios. On the publicly available COncrete DEfect BRidge IMage Dataset, our model achieved a mean average precision (mAP@0.5) of 0.90, showing a 3.4% improvement over the current best baseline method. Through transfer learning, it reached 0.92 on our custom dataset, significantly outperforming existing methods. These results demonstrate the effectiveness and superiority of the proposed model for detecting concrete defects. Additionally, we evaluated the impact of different architectures on model performance. Compared to traditional models using the VGG16 as the backbone, the ResNet50 architecture used in this study reduces parameter count by 5.41 times while improving performance by 6.1%.
Combining wavelet-enhanced feature selection and deep learning techniques for multi-step forecasting of urban water demand
Authors: Hao Wenjin , Cominola Andrea , Castelletti Andrea 
Published: July 2024

Abstract
Urban water demand (UWD) forecasting is essential for water supply network optimization and management, both in business-as-usual scenarios, as well as under external climate and socio-economic stressors. Different machine learning and deep learning (DL) models have shown promising forecasting skills in various areas of application. However, their potential to forecast multi-step ahead UWD has not been fully explored. Modelling uncertain UWD patterns and accounting for variations in water demand behaviors require techniques that can extract time-varying information and multi-scale changes. In this research, we comparatively investigate different state-of-the-art machine learning- and DL-based predictive models on 1 d- and 7 d-ahead UWD forecasting, using daily demand data from the city of Milan, Italy. The contribution of this paper is two-fold. First, we compare the forecasting performance of different machine learning and DL models on single- and multi-step daily UWD forecasting. These models include an artificial neural network, a support vector regression, a light gradient boosting machine (LightGBM), and long short-term memory networks with and without an attention mechanism (LSTM and AM-LSTM). We benchmark their prediction accuracy against autoregressive time series models. Second, we investigate the potential enhancement in predictive accuracy by incorporating the wavelet transform and feature selection performed by LightGBM into these models. Results show that, overall, wavelet-enhanced feature selection improves the model predictive performance. The hybrid model combining wavelet-enhanced feature selection via LightGBM with LSTM (WT-LightGBM-(AM)-LSTM) can achieve high levels of accuracy with Nash-Sutcliffe Efficiency larger than 0.95 and Kling–Gupta Efficiency higher than 0.93 for both 1 d- and 7 d-ahead UWD forecasts. Furthermore, performance is shown to be robust under the influence of external stressors causing sudden changes in UWD.
Hook lengths in self-conjugate partitions
Authors: Amdeberhan Tewodros , Andrews George , Ono Ken , Singh Ajit 
Published: July 2024

In 2010, G.-N. Han obtained the generating function for the number of size

t
t

hooks among integer partitions. Here we obtain these generating functions for self-conjugate partitions, which are particularly elegant for even

t
t

. If

n
t

(
λ
)

n_t(\lambda )

is the number of size

t
t

hooks in a partition

λ
\lambda

and

S
C

\mathcal {SC}

denotes the set of self-conjugate partitions, then for even

t
t

we have

∑

λ
∈

S
C

x

n
t

(
λ
)

q

|
λ
|

=
(
−
q
;

q
2

)

∞

⋅
(
(
1
−

x
2

)

q

2
t

;

q

2
t

)

∞

t
2

.

\begin{equation*} \sum _{\lambda \in \mathcal {SC}} x^{n_t(\lambda )} q^{\vert \lambda \vert } = (-q;q^2)_{\infty } \cdot ((1-x^2)q^{2t};q^{2t})_{\infty }^{\frac {t}{2}}. \end{equation*}

As a consequence, if

a
t

⋆

(
n
)

a_t^{\star }(n)

is the number of such hooks among the self-conjugate partitions of

n
n

, then for even

t
t

we obtain the simple formula

a
t

⋆

(
n
)
=
t

∑

j
≥
1

q

⋆

(
n
−
2
t
j
)
,

\begin{equation*} a_t^{\star }(n)=t\sum _{j\geq 1} q^{\star }(n-2tj), \end{equation*}

where

q

⋆

(
m
)

q^{\star }(m)

is the number of partitions of

m
m

into distinct odd parts. As a corollary, we find that

t
∣

a
t

⋆

(
n
)

t\mid a_t^{\star }(n)

, which confirms a conjecture of Ballantine, Burson, Craig, Folsom and Wen.
Security and Intergenerational Equity in the Net Zero Transition
Authors: Lucas Alastair R , Olugbemi Akinbobola Olukayode 
Published: July 2024

Abstract
This chapter examines the conflicting energy security and intergenerational equity implications of net zero transition for the development of energy and natural resources. It evaluates how resource-rich countries such as Canada can balance net zero ambitions with the goal of sustainable energy development in a manner that advances intergenerational equity. It examines concerns about faux law—unenforceable political pronouncements that may arise from Canada’s net zero ambitions, especially federal system jurisdictional limitations, including federal, provincial, and indigenous jurisdiction, rights-based limitations, particularly constitutional, statutory, civil, and indigenous rights. The chapter evaluates existing and potential international and domestic law and policy tools to reconcile and address intergenerational equity concerns in Canada’s net zero ambitions and its current position among developed states as a leading global hydrocarbon producer (focused on the Alberta oil sands).
Extractive Justice and the Net Zero Transition
Authors: Mostert Hanri , Moses Lindsay Taylah 
Published: July 2024

Abstract
This chapter examines how the security of supply of strategic mineral resources must be approached to position resource-rich countries in a global renewable energy supply chain. It argues that the regulatory systems in such countries must balance and manage the justice implications of the increased demand for energy transition minerals (ETMs) to avoid falling victim to the negative socio-environmental impacts, the energy- and resource-intensive aspects of mining, and the adverse human rights impacts of net zero policies. The chapter evaluates the extent to which existing natural resource laws support a justice-based extraction of ETMs in Zambia and South Africa. It points out where these jurisdictions already have supporting rules or frameworks in place, but also highlights sticking points in relation to five identified tenets of extractive justice in these jurisdictions that may hamper just resource extraction and responsible supply chains in the net zero age. In doing so, the chapter contributes to discourse about the meaning and concepts of justice within the ‘just transition’ thematic.
Regional Free Trade Agreements and Net Zero Transitions
Authors: González José Juan , Pacheco Ruiz Ana María 
Published: July 2024

Abstract
This chapter unpacks the role of regional free trade agreements, with clear and comprehensive natural resource and environmental provisions, as an instrument for decarbonizing natural resource supply value chains and advancing regional solidarity for net zero. Drawing lessons from the United States–Mexico–Canada Agreement (USMCA), this chapter proposes a roadmap for promoting regional solidarity for net zero through regional trade agreements that allow countries to move towards a net zero emissions economy, contribute to sustainable development, and guarantees access to affordable, reliable, sustainable, and modern energy for all. One of the key lessons highlighted in this chapter is that, although the USMCA is a trade agreement whose objective is not environmental protection, it could provide an ideal mechanism to establish an institutional structure that allows the definition of a regional policy to achieve the goal of zero emissions by 2050 based on the principle of climate solidarity.
Optimizing discharge antimicrobial therapy: Evaluation of a transitions of care process and electronic scoring system for patients with community-acquired pneumonia or chronic obstructive pulmonary disease
Authors: Belza-Mai Ana Christine , Efta Jessica , Kenney Rachel , MacDonald Nancy , Stine John , McCollom Robert , Ratusznik Martin , Patel Nisha 
Published: July 2024

Abstract

Purpose
Prescribing excess antibiotic duration at hospital discharge is common. A pharmacist-led Antimicrobial Stewardship Program Transition of Care (ASP TOC) intervention was associated with improved discharge prescribing. To improve the sustainability of this service, an electronic scoring system (ESS), which included the ASP TOC electronic variable, was implemented in the electronic medical record to prioritize pharmacist workload. The purpose of this study was to evaluate the implementation of the ASP TOC variable in the ESS in patients with community-acquired pneumonia (CAP) or chronic obstructive pulmonary disease (COPD).

Methods
This institutional review board–approved, retrospective quasi-experiment included patients discharged on oral antibiotics for CAP or COPD exacerbation (lower respiratory tract infection) from November 1, 2021, to March 1, 2022 (the preintervention period) and November 1, 2022, to March 1, 2023 (the postintervention period). The primary endpoint was optimized discharge antimicrobial regimen. A sample of at least 194 patients was required to achieve 80% power to detect a 20% difference in the frequency of optimized therapy. Multivariable logistic regression was used to identify factors associated with optimized regimens.

Results
Similar baseline characteristics were observed in both study groups (n = 100 for both groups). The frequency of optimized discharge regimens improved from 69% to 82% (P = 0.033). The percentage of ASP TOC interventions documented as completed by a pharmacist increased from 4% to 25% (P &lt; 0.001). ASP TOC intervention, female gender, and COPD were independently associated with an optimized discharge regimen (adjusted odds ratios, 6.57, 1.61, and 3.89, respectively; 95% CI, 1.51-28.63, 0.81-3.17, and 1.85-8.20, respectively).

Conclusion
After the launch of the ASP TOC variable, there was an increase in optimized discharge regimens and ASP TOC interventions completed. Pharmacists’ use of the ASP TOC variable through an ESS can aid in improving discharge prescribing.