bluuebunny/crossref_metadata_2025 huggingface dataset:
Highly sensitive photonic crystal fiber sensor for detection of hemoglobin and sucrose concentration
Authors: Monazah Seyede Mahboobeh Mousavi , Salehi Mohammad Reza
Published: November 2024

In this research, a flower-shape photonic crystal fiber sensor is proposed and designed. In this sensor, the most electromagnetic field is concentrated in the core part of the flower causing a surprising increase in the sensitivity of the sensor. Gold is used as a plasmonic material for stability in the environment. The analyte is placed outside the sensor and it makes the possibility of fabrication simple. The geometrical parameters of the sensor are optimized with the Nelder Mead algorithm. The detection power of the sensor is in the bio range and in this research, it is proposed to determine the concentration of sucrose and the concentration of hemoglobin. Taking advantage of the amazing geometry of nested circles to confine the electromagnetic field in the center of the fiber and increase the sensitivity of the sensor is a significant achievement. Using the optimal algorithm for design leads to the adaptation of the optimal geometry and the efficient construction of the sensor. The results show an excellent amplitude sensitivity of 5285 (RIU−1) and a suitable wavelength sensitivity of 11000 (nm RIU−1).
Tunable unidirectional reflectionlessness based on vanadium dioxide in a non-Hermitian metamaterial
Authors: Yuan Wenxuan , Zhang Ying Qiao , Jin Xing Ri
Published: November 2024

We propose a non-Hermitian metamaterial based on double split rings embedded in polymide and connected by vanadium dioxide blocks, and investigate the tunable unidirectional reflectionlessness at exceptional points in THz region. The conductivity of vanadium dioxide can vary from 2 × 102 S/m (insulator state) to 2 × 105 S/m (metal state) to shift the unidirectional reflectionlessnesses with unidirectional absorptions from 0.57 THz to 0.54 THz (the polarization angle θ = 0) and from 0.53 THz to 0.50 THz (the polarization angle θ = 90∘), respectively. In addition, unidirectional reflectionlessnesses also can be switched by adjusting the polarization angle θ of incident wave from 0 to 90∘. With these findings, this study may open an attractive direction for a wide range of design possibilities in terms of unidirectional invisibility, diode-like device, filters and so on.
The bispectrum in Lagrangian perturbation theory
Authors: Chen Shi-Fan , Vlah Zvonimir , White Martin
Published: November 2024

We study the bispectrum in Lagrangian perturbation theory. Extending past results for the power spectrum, we describe a method to efficiently compute the bispectrum in LPT, focusing on the Zeldovich approximation, in which contributions due to linear displacements are captured to all orders in a manifestly infrared (IR) safe way. We then isolate the effects of these linear displacements on oscillatory components of the power spectrum like baryon acoustic oscillations or inflationary primordial features and show that the Eulerian perturbation theory (EPT) prescription wherein their effects are resummed by a Gaussian damping of the oscillations arise as a saddle-point approximation of our calculation. These two methods of IR resummation are in excellent agreement at 1-loop in the bispectrum. At tree level, resummed EPT does less well to capture the nonlinear damping of the oscillations, and the LPT calculation does not require an artificial split of the power spectrum into smooth and oscillatory components, making the latter particularly useful for modeling exotic features. We finish by extending our analysis of IR resummation in LPT to N-point functions of arbitrary order.
Mass modeling and kinematics of galaxy clusters in modified gravity
Authors: Pizzuti Lorenzo , Boumechta Yacer , Haridasu Sandeep , Pombo Alexandre M. , Dossena Sofia , Butt Minahil Adil , Benetti Francesco , Baccigalupi Carlo , Lapi Andrea
Published: November 2024

The chameleon screening mechanism has been constrained many a time using dynamic and kinematic galaxy cluster observables. Current constraints are, however, insensitive to different mass components within galaxy clusters and have been mainly focused on a single mass density profile, the Navarro-Frenk-White mass density model. In this work, we extend the study of the Chameleon screening mechanism in galaxy clusters by considering a series of mass density models, namely: generalized-Navarro-Frenk-While, b-Navarro-Frenk-While, Burket, Isothermal and Einasto. The coupling strength (β) and asymptotic value of the chameleon field (ϕ
∞) are constrained by using kinematics analyses of simulated galaxy clusters, generated both assuming General Relativity and a strong chameleon scenario. By implementing a Bayesian analysis we comprehensively show that the biases introduced due to an incorrect assumption of the mass model are minimal. Similarly, we also demonstrate that a spurious detection of evidence for modifications to gravity is highly unlikely when utilizing the kinematics of galaxy clusters.
Neutrino emission in cold neutron stars: Bremsstrahlung and modified urca rates reexamined
Authors: Bottaro Salvatore , Caputo Andrea , Fiorillo Damiano F.G.
Published: November 2024

Neutrino emission in cold neutron stars is dominated by the modified urca (murca) process and nucleon-nucleon bremsstrahlung. The standard emission rates were provided by Friman and Maxwell in 1979, effectively based on a chiral Lagrangian framework with pion and rho meson exchange, supplemented by Landau parameters to describe short-range interactions. We reevaluate these rates within
the same framework, correcting several errors and removing
unnecessary simplifications, notably the triangular approximation — where the Fermi momenta of protons and leptons negligible compared to that of neutrons — in MURCA, and quantify their importance.
The impact of rho meson exchange, previously argued to cancel with interference effects, is actually quite relevant. Altogether, the cooling rates are reduced by as much as a factor 2. We provide comprehensive analytical formulas encompassing all contributions, designed for straightforward numerical implementation. Our results are particularly relevant for studies of physics beyond the standard model, where the emission of new particles — such as axions — is typically computed within the same framework we adopt here.
Systematic research on the ground state properties of medium-mass neutron-rich nuclei*
Authors: He 何 Chen 晨 , Cao 曹 Xue-Neng 雪能 , Zhou 周 Xian-Xian 鲜鲜
Published: November 2024

The recently developed relativistic-mean-field in complex momentum representation with the functional NL3* was used to explore the exotic properties of neutron-rich Pd, Cd, Te, and Xe isotopes. The results were compared with those obtained using the relativistic Hartree-Bogoliubov (RHB) calculations and available experimental data. The single-particle levels were obtained for the bound and resonant states. The two neutron separation energies

and root mean square (rms) radii agree with the experimental data. It is shown that there is a halo structure in extremely neutron-rich

Te and

Xe, as well as a thick neutron skin in extremely neutron-rich Pd and Cd isotopes. From the numbers of neutrons (

) and (

) occupying the levels above the Fermi surface and zero-potential energy level, it was found that pairing correlations play an important role in the formation of halo phenomena. These findings are further supported by investigating

, rms radii, occupation probabilities, contributions of single-particle levels to the neutron rms radii, and density distributions. The neutron rms radii increased sharply, evidently deviating from the traditional rule

, and the density distributions were very diffuse. Finally, the contributions of different single-particle levels to the total neutron density and wavefunction are discussed. It was found that the sudden increase in the neutron rms radii and diffuse density distributions mainly arise from the resonant levels with a lower orbital angular momentum near the continuum threshold.
Constraining symmetry energy from pygmy dipole resonances in 68Ni and 132Sn*
Authors: Liu 刘 Ling 玲 , Lu 卢 Yu-Wei 宇威 , Sun 孙 Shuai 帅 , Cao 曹 Li-Gang 李刚
Published: November 2024

We conduct a new investigation of the correlation at saturation (subsaturation) density between the density dependence of symmetry energy and the percentage of the energy-weighted sum rule (EWSR) exhausted by pygmy dipole resonances (PDR) in 68Ni and 132Sn. The calculations are performed within the Skyrme HF (or HF+BCS) plus random phase approximation (RPA) (or quasiparticle RPA) problem using SAMi-J effective interactions. The effect of pairing on the dipole strength distribution of 68Ni and density dependence of the symmetry energy is discussed. Slope parameter L and symmetry energy J at saturation (subsaturation) density are 41.8−90.2 MeV (39.3−64.1 MeV) and 28.0−32.5 MeV (23.0−23.8 MeV), respectively. They are consistent with the currently accepted values except for J at subsaturation density, which is slightly lower than the values obtained from nuclear mass difference measurements and electric dipole polarizability data.
Measurement of spherical tokamak plasma compression in the PCS-16 magnetized target fusion experiment
Authors: Howard S.J. , Reynolds M. , Froese A. , Zindler R. , Hildebrand M. , Mossman A. , Donaldson M. , Tyler T. , Froese D. , Eyrich C. , Epp K. , Bell K. , Carle P. , Gutjahr C. , Wong A. , Zawalski W. , Rablah B. , Sardari J. , McIlwraith L. , Bouchal R. , Wilkie J. , Ivanov R. , de Vietien P. , Khalzov I.V. , Barsky S. , Krotez D. , Delage M. , McNally C.P. , Laberge M.
Published: November 2024

A sequence of magnetized target fusion devices built by General Fusion has compressed magnetically confined deuterium plasmas inside imploding aluminum liners. Here we describe the best-performing compression experiment, PCS-16, which was the fifth of the most recent experiments that compressed a spherical tokamak plasma configuration. In PCS-16, the plasma remained axisymmetric with

δ

B
pol

/

B
pol

<
20
%

to a high radial compression factor (

C

R

>
8

) with significant poloidal flux conservation (77% up to

C

R

=

1.7, and

≈

30
%

up to

C

R

=
8.65

) and a total compression time of 167 

μ

s

. Magnetic energy of the plasma increased from 0.96 kJ poloidal and 17 kJ toroidal to a peak of 1.14 kJ poloidal and 29.9 kJ toroidal during the compression, while the thermal energy was in the range of 350 ± 25 J. Plasma equilibrium was a low-β state with

β
tor

≈
4
%

and

β
pol

≈
15
%

. Ingress of impurities from the lithium-coated aluminum wall was not the dominant effect. Neutron yield from D-D fusion increased significantly during compression. Thermodynamics during the early phase of compression (

C

R

<
1.7

) were consistent with increasing Ohmic heating of the electrons due to a geometric increase in the current density at near-constant resistivity, and with increasing ion cooling that approximately matched ion compression heating power. Ion cooling by electrons was significant because the electrons were much cooler than the ions (

T

e

=
200

eV

,

T

i

=
600

eV

). Magnetohydrodynamic simulations were used to model the emergence of instabilities that increase electron thermal transport in the final phase of compression. Conditions for ideal stability were actively maintained during compression through a current ramp applied to the central shaft and, after this current ramp reached its peak two-thirds of the way through compression, we measured a transition in plasma behavior across multiple diagnostics.
A novel translationally invariant supersymmetric chain with inverse-square interactions: partition function, thermodynamics and criticality
Authors: Basu-Mallick Bireswar , Finkel Federico , González-López Artemio
Published: November 2024

We introduce a novel family of translationally invariant

su

(
m

|

n
)

supersymmetric spin chains with long-range interaction not directly associated with a root system. We study the symmetries of this model, establishing in particular the existence of a boson–fermion duality characteristic of this type of system. Taking advantage of the relation of the new chains with an associated many-body supersymmetric spin dynamical model, we are able to compute their partition function in closed form for all values of m and n and for an arbitrary number of spins. When both m and n are even, we show that the partition function factorizes as the product of the partition functions of two supersymmetric Haldane–Shastry spin chains, which in turn leads to a simple expression for the thermodynamic free energy per spin in terms of the Perron eigenvalue of a suitable transfer matrix. We use this expression to study the thermodynamics of a large class of these chains, showing in particular that the specific heat presents a single Schottky peak at approximately the same temperature as a suitable k-level model. We also analyze the critical behavior of the new chains, and in particular, the ground-state degeneracy and the existence of low-energy excitations with a linear energy–momentum dispersion relation. In this way, we show that the only possible critical chains are those with

m
=
0
,
1
,
2

. In addition, using the explicit formula for the partition function we are able to establish the criticality of the

su

(
0

|

n
)

and

su

(
2

|

n
)

chains with even n, and to evaluate the central charge of their associated conformal field theory.
Analysis of flows in social media uncovers a new multi-step model of information spread
Authors: Serafino Matteo , Virginio Clemente Giulio , Flamino James , Szymanski Boleslaw K , Lizardo Omar , Makse Hernán A
Published: November 2024

Since the advent of the internet, communication paradigms have continuously evolved, resulting in a present-day landscape where the dynamics of information dissemination have undergone a complete transformation compared to the past. In this study, we challenge the conventional two-step flow communication model, a long-standing paradigm in the field. Our approach introduces a more intricate multi-step and multi-actor model that effectively captures the complexities of modern information spread. We test our hypothesis by examining the spread of information on the Twitter platform. Our findings support the multi-step and multi-actor model hypothesis. In this framework, influencers (individuals with a significant presence in social media) emerge as new central figures and partially take on the role previously attributed to opinion leaders. However, this does not apply to opinion leaders who adapt and reaffirm their influential position on social media, here defined as opinion-leading influencers. Additionally, we note a substantial number of adopters directly accessing information sources, suggesting a potential decline in influence in both opinion leaders and influencers. Finally, we found distinctions in the diffusion patterns of left-/right-leaning groups, indicating variations in the underlying structure of information dissemination across different ideologies.
Fabrication of a natural nanocomposite from Syzygium cumini and squid bone waste decorated with Cu-Nps for simultaneous use in the triple method of photodynamic/photothermal/chemotherapy
Authors: Mehrabi Mohsen , Shaygan Shirazi Ali , Gharibzadeh Fatemeh , Shirkani Hossein , Ghaedi Amirhossein , Khoradmehr Arezoo
Published: November 2024

This work reports a new nano platform made from natural materials for phototherapy (PT) applications. For this purpose, calcium carbonate nanoparticles (NPs) derived from Persian Gulf squid bones as a drug carrier, Syzygium cumini (dye extracted from the fruit of the Persian Gulf trees) as a photosensitizer, and Doxorubicin as a chemotherapy (CHT) drug have been used. In addition, copper NPs were added to the above nanocomposition to increase the efficiency of photothermal (PTT) treatment. For PT, samples were irradiated by an 808 nm laser (1 W cm−2). The results show that nanocomposites play an influential role in the reactive oxygen species process, and an increase of 21 degrees in temperature during 15 min of laser radiation is effective in photodynamic (PDT)/PTT therapy. The drug loading capacity of the nanocomposite was calculated as 49%. This new nanocomposite for simultaneous PDT/PTT/CHT holds great promise for future cancer treatment due to its excellent potential in treatment and reduced systemic toxicity.
Sensitivity of the impact of aeolian sand cover on permafrost degradation in the Qinghai–Xizang Plateau
Authors: Wang Luyang , Fu Ziteng , Jiang Guanli , Du Wenyan , Men Xinyu , Luo Dongliang , Wu Qingbai
Published: November 2024

Environmental transformations and intensifying desertification across the Qinghai–Xizang Plateau (QXP) are having a significant influence permafrost degradation, heightening the risks associated with carbon emissions, thermal hazards and infrastructural damage. However, the specific response of permafrost to desertification remains insufficiently understood. Here, we employed numerical modeling to examine the sensitivity of the impact of aeolian sand cover (ASC) on permafrost degradation. Our findings reveal that the thickness and moisture content of ASC profoundly affect permafrost degradation. Moreover, the thermal stability of permafrost and the rate of climatic warming modulate this degradation process. The simulation results identify two critical thickness thresholds for ASC: 20 cm and 80–120 cm. Specifically, dry ASC thinner than 20 cm accelerates permafrost degradation driven by desertification, whereas ASC thicker than 20 cm mitigates this effect. Furthermore, increased moisture in ASC extends the thickness threshold to 80–120 cm. These results suggest that climatic variations in the QXP, particularly transitions towards either warming–drying or warming–wetting, will markedly influence the response of permafrost to desertification. Notably, a warming–drying climate may reduce the potential degradation of permafrost caused by desertification. This study provides a critical reference for understanding the impact of aeolian desertification on permafrost in regions beyond the QXP. It holds significant policy implications for environmental conservation and infrastructure development within the plateau.
Improved water and sanitation in early life and cognition in adolescence: evidence from four countries*
Authors: Pakhtigian Emily L
Published: November 2024

Early life environmental exposures, such as drinking water quality and sanitation, can have long lasting effects on human capital accumulation. Using matched samples of over 8000 children across Ethiopia, India, Peru, and Vietnam, this paper examines the relationship between early life access to improved drinking water and improved sanitation and cognition at the age of fifteen. It finds that children with early life access to improved drinking water score 1.6–2.8 percentage points higher on math, reading, and vocabulary tests. A similar, yet less precisely measured, pattern emerges for early life access to improved sanitation. Analysis by gender shows that the effects of early life drinking water access are stronger and more precise among girls. An examination of pathways underlying these relationships provides preliminary evidence that learning over the life course is a leading mechanism. Quantifying these long-term cognitive benefits provides insight for directing and prioritizing resources for global efforts to increase equitable access to improved drinking water and sanitation.
The North China record-breaking rainfall in July 2021: the atmospheric influential factors and precursory signal
Authors: Ye Jiaxin , Zhao Ping , Wen Zhiping , Li Jiao
Published: November 2024

In July 2021, the southeastern part of North China (SENC) suffered a record-breaking extreme rainfall event that caused devastating flooding and enormous losses. In this study, the major atmospheric influential factors and the precursory signal of heavy rainfall in 2021 are investigated using the correlation, regression, power spectrum, and filtering methods, the quasi-geostrophic velocity equation, observational data and numerical simulation of a linear baroclinic model (LBM). The results show that the extremity of a quasi-barotropic high anomaly over Northeast Asia (NEA) contributes to the deep anomalous upward motion within SENC by inducing positive vorticity and temperature advections. On the other hand, the anomalous southeasterly flow at the southwestern flank of the NEA high anomaly transports sufficient moisture to SENC in the lower troposphere. The local deep upward motion combined with the lower-tropospheric moisture convergence directly leads to the occurrence of this extreme rainfall event. Further analysis shows that the intensification of the NEA high in July 2021 is closely tied to the westward migration of atmospheric disturbance originating from the vicinity of Northeast Pacific-North America, which could be supported by numerical simulation in LBM. The variation of the geopotential height anomaly over Northeast Pacific-North America precedes that of the NEA high by two weeks, which is likely to provide a potential source of predictability for the extreme rainfall in SENC.
Contrasting impact of single-year and multi-year El Niño on the Pacific-North American teleconnection pattern
Authors: Liu Yixuan , Tao Weichen , Huang Gang , Wang Ya , Hu Kaiming , Liu Yong
Published: November 2024

Distinct Pacific-North American (PNA) teleconnection patterns and their associated climate impacts in North America have been observed during single-year El Niño events, as well as during both the first and second years of multi-year El Niño events. The research highlights the critical role of PNA-related North Pacific circulation anomalies, which shift northwestward during multi-year events and reach their peak intensity in the second year. Multiple dynamical diagnostic methods are employed to elucidate the reasons behind the diverse subtropical circulation responses. Differences in the anomalous tropical heat sources influence the formation of Rossby wave sources through adjustments in divergent wind anomalies, subsequently modulating the position and intensity of the PNA patterns. Additionally, variations in the meridional range of sea surface temperature anomalies affect the edge of tropospheric temperature through moist-adiabatic adjustment, leading to distinct subtropical jet stream responses. This, in turn, modifies the position of North Pacific circulation anomalies through the advection of anomalous kinetic energy. Furthermore, synoptic-scale transient eddies act as a feedback mechanism, helping to maintain and intensify these diverse atmospheric anomalies.
Minimum time connection between non-equilibrium steady states: the Brownian gyrator
Authors: Patrón A , Plata C A , Prados A
Published: November 2024

We study the problem of minimising the connection time between non-equilibrium steady states of the Brownian gyrator. This is a paradigmatic model in non-equilibrium statistical mechanics, an overdamped Brownian particle trapped in a two-dimensional elliptical potential, with the two degrees of freedom (x, y) coupled to two, in principle different, thermal baths with temperatures Tx
and Ty
, respectively. Application of Pontryagin’s Maximum Principle reveals that shortest protocols belong to the boundaries of the control set defined by the limiting values of the parameters (k, u) characterising the elliptical potential. We identify two classes of optimal minimum time protocols, i.e. brachistochrones: (i) regular bang–bang protocols, for which (k, u) alternatively take their minimum and maximum values allowed, and (ii) infinitely degenerate singular protocols. We thoroughly investigate the minimum connection time over the brachistochrones in the limit of having infinite capacity for compression. A plethora of striking phenomena emerge: sets of states attained at null connection times, discontinuities in the connection time along adjacent target states, and the fact that, starting from a state in which the oscillators are coupled, uncoupled states are impossible to reach in a finite time.
A model of random sequential adsorption on a ladder graph
Authors: Došlić Tomislav , Puljiz Mate , Šebek Stjepan , Žubrinić Josip
Published: November 2024

In random sequential adsorption (RSA), objects are deposited on a substrate randomly, irreversibly, and sequentially. Attempts of deposition that lead to an overlap with previously deposited objects are discarded. The process continues until the system reaches a jammed state when no further additions are possible. We analyze a class of RSA models on a two-row square ladder graph in which landing on an empty site in a graph is allowed when at least b neighboring sites in the graph are unoccupied (

b
∈

N

). In this paper we complement this typical way of studying RSA models by analyzing also the structure of the set of all jammed states in a static way, disregarding the dynamics that led to a particular jammed state. In both considered settings (dynamic and static) we provide explicit expressions for key statistics that describe the average proportion of the substrate covered by deposited objects, and then we comment on significant differences between the two settings. We illustrate all of our findings through a toy model for ensembles of trapped Rydberg atoms with blockade range b.
Orthogonal flatbands in Hamiltonians with local symmetry
Authors: Ryu Jung-Wan , Andreanov Alexei , Chul Park Hee , Han Jae-Ho
Published: November 2024

We derive symmetry-based conditions for tight-binding Hamiltonians with flatbands to have compact localized eigenstates (CLS) occupying a single unit cell. The conditions rely on unitary operators commuting with the Hamiltonian and are associated with local symmetries that ensure the existence of orthogonal compact localized states and a flatband. We also demonstrate the inverse: orthogonal flatbands, whose CLS can be made to occupy a single unit cell, always have associated local symmetries that satisfy our conditions.We illustrate our analytical result with several model Hamiltonians with given local symmetries, including examples with finite-range hopping and higher-dimensional ones.
Drowsiness-detecting earbuds could help drivers stay safe at the wheel
Authors: Freeman Tami
Published: November 2024

Researchers at University of California Berkeley have developed techniques to detect signs of drowsiness in the brain via prototype earbuds that perform electroencephalography (EEG) and other physiological measurements.
Estonia becomes CERN full member
Authors: Banks Michael
Published: November 2024

Estonia is the first Baltic state to become a full member of the CERN particle-physics lab near Geneva.
Reducing measurement costs by recycling the Hessian in adaptive variational quantum algorithms
Authors: Ramôa Mafalda , Paulo Santos Luis , Mayhall Nicholas J , Barnes Edwin , Economou Sophia E
Published: November 2024

Adaptive protocols enable the construction of more efficient state preparation circuits in variational quantum algorithms (VQAs) by utilizing data obtained from the quantum processor during the execution of the algorithm. This idea originated with Adaptive Derivative-Assembled Problem-Tailored variational quantum eigensolver (ADAPT-VQE), an algorithm that iteratively grows the state preparation circuit operator by operator, with each new operator accompanied by a new variational parameter, and where all parameters acquired thus far are optimized in each iteration. In ADAPT-VQE and other adaptive VQAs that followed it, it has been shown that initializing parameters to their optimal values from the previous iteration speeds up convergence and avoids shallow local traps in the parameter landscape. However, no other data from the optimization performed at one iteration is carried over to the next. In this work, we propose an improved quasi-Newton optimization protocol specifically tailored to adaptive VQAs. The distinctive feature in our proposal is that approximate second derivatives of the cost function are recycled across iterations in addition to optimal parameter values. We implement a quasi-Newton optimizer where an approximation to the inverse Hessian matrix is continuously built and grown across the iterations of an adaptive VQA. The resulting algorithm has the flavor of a continuous optimization where the dimension of the search space is augmented when the gradient norm falls below a given threshold. We show that this inter-optimization exchange of second-order information leads the approximate Hessian in the state of the optimizer to be consistently closer to the exact Hessian. As a result, our method achieves a superlinear convergence rate even in situations where the typical implementation of a quasi-Newton optimizer converges only linearly. Our protocol decreases the measurement costs in implementing adaptive VQAs on quantum hardware as well as the runtime of their classical simulation.
Adoption of solar home lighting system: a behavioral paradigm shift from consumers to prosumers in the urban household energy transition of Punjab, India
Authors: Kaur Navdeep , Sharma Anupam
Published: November 2024

This research explores the question of what inspires households to adopt a solar home lighting system (SHS) in Punjab, one of the wealthiest states of India with adequate solar potential. This research leverages the framework of the extended unified theory of acceptance and use of technology (UTAUT2) to identify adoption drivers and their impact on behavioral intentions moderated by age, socioeconomic status, and usage, with a particular emphasis on urban households, as they have been the subject of very few studies. The proposed research model was tested using structural equation modeling (SEM) in Smart PLS4. The study verified that the UTAUT2 constructs are the drivers of SHS adoption and significantly impact behavioral intention (R2 = 0.730). The findings suggested that for fiscally conservative prosumers, reduced monthly electricity bills were the greatest motivator for adopting SHSs, and our assumption that all prosumers are earth-loving environmentalists was not the case, suggesting that environmental concerns are not enough to explain SHS adoption. Age (β = 0.137, p < 0.01) was found to have a significant moderation effect on the behavioral intention to adopt SHS, while usage (β = −0.115; p = 0.21) and socioeconomic status (β = 0.006; p value = 0.888) were found to have no moderating effect on the behavioral intentions of adoption drivers. The results could serve as a roadmap for policymakers while framing government policies to improve the penetration of this new and promising green technology for the coherent domestic energy transition of consumers to prosumers.
MNPM: research on metabolic neural network prediction model for predicting carbon emission accuracy
Authors: Luo Entao , Shi Li , Liu Jiyan , Wu Zheng , Duan Guoyun , Zeng Lingxuan , Huang Tangsen
Published: November 2024

The rapid development of the global economy and society relies on continuous energy demand, while the severe impact of carbon emissions on the ecological environment has garnered significant international attention. Accurately forecasting carbon emission trends is crucial for developing effective reduction strategies and ensuring sustainable green economic development. In this paper, we propose a Metabolic Neural Network Prediction Model (MNPM) for carbon emissions. This model comprehensively considers the impact of various carbon emission-related factors across different regions in China. By employing one-hot encoding, we address the difficulties traditional classifiers face when handling categorical data, enabling predictions under more realistic conditions. To optimize the nonlinear characteristics of the data and overcome the limitations of grey models, we utilize dynamic iterative time series training to address errors due to data inaccuracies effectively. Experimental results demonstrate that our approach outperforms other methods in filtering out irrelevant data, achieving an average relative residual of 0.055 and an average ratio bias of 0.049, translating to more precise prediction accuracy.
Decentralization of renewable energy sources based optimum scheduling and management through a virtual power plant
Authors: Pandey Anubhav Kumar , Jadoun Vinay Kumar , N S Jayalakshmi , Singh Manohar
Published: November 2024

In this paper, renewable resources and co-generation units are grouped together to perform optimized operational scheduling in a virtual power plant (VPP) system. Renewable sources consist of solar photovoltaic, wind, and fuel cell units that are equipped together with a cogenerating unit to intensify the system's dependency in case of power shortage from renewable sources. The uncertainty aspect is investigated for the developed system as renewables are associated, and its impact on network operation is discussed. Storage provision is facilitated in the form of flexible and spinning reserves in which electric vehicle (EV) and energy storage systems (ESS) increase the system reliability by ensuring continuity of power supply. Optimal scheduling is carried out from both economic and environmental perspectives in which the net profit of the system is improved and the generated emissions are reduced by considering dual scheduling i.e., day-ahead (DA) and proposed 15 min interval. Moreover, a nature-inspired metaheuristic red fox optimization (RFO) is employed to handle the VPP problem and the results with the context to net profit and emission are also compared with work available in the literature. Finally, the proposed approach is promising in terms of higher computational efficacy and reveals the suitability of the VPP system.
Global floating PV status and potential
Authors: Rodríguez-Gallegos Carlos D , Gandhi Oktoviano , Sun Huixuan , Paton Céline , Zhang Ji , Moideen Yacob Ali Jaffar , Alvarez-Alvarado Manuel S , Zhang Wenjie , Rodríguez-Gallegos César A , Chua Lloyd H C , Reindl Thomas
Published: November 2024

Floating photovoltaics (FPV) has been a rapidly growing source of renewable electricity for the past 15 years since first commercial systems were installed. In this work, the insights from SERIS FPV database are shared. This is likely the largest database of its kind and contains the information from 1142 FPV systems in operation, totalling 5.9 GWp, by the end of 2022. Mainland China has been leading FPV installation capacities since 2017 and comprises almost half of the cumulative installed capacity. Similar to land-based PV, FPV installation size has been increasing; the median size has grown from 0.09 MWp in 2013 to 1.40 MWp in 2022, while the median power density has increased from 82 Wp m−2 to 123 Wp m−2 in the same timeframe. The installation cost has fallen simultaneously – the lowest reported was 0.41 USD/Wp in India in 2021. Other pertinent insights from SERIS FPV database include float supplier market share, reported electricity price, water body types and characteristics, as well as its coverage ratio. Finally, the global FPV potential (capacity, energy production, and water saving), for different tilt angles, tracking configurations, and solar panel types are explored. By installing FPV on 10% of the area of 249 717 inland reservoirs, FPV capacity could reach up to 22 TWp and could fulfil the whole global electricity consumption and up to 5% of the world’s water demand. The use of trackers and bifacial panels are advantageous for energy generation in all locations, with trackers increasing specific energy yield of a typical fixed 10° tilt FPV by up to 50% for reservoirs within

±

40

∘

latitude, while the bifacial gains reach up to 4.5% for all analysed configurations within

±

40

∘

latitude. The insights from this global FPV market and potential analysis can serve as a reliable reference for FPV stakeholders, researchers, and regulators alike.
Putting the costs and benefits of carbon capture and storage into perspective: a multi-sector to multi-product analysis
Authors: Roussanaly Simon , Gundersen Truls , Ramirez Andrea
Published: November 2024

Carbon dioxide capture, transport, and storage (CCS) is essential in achieving the net-zero target. Despite this increasing recognition, current CCS deployments are far behind targeted ambitions. A key reason is that CCS is often perceived as too expensive. While assessments of the costs of CCS have traditionally looked at impact at the plant level, the present study seeks to understand the costs and environmental benefits that will be passed to consumers via end-products and services. In particular, nine end-products/services (bridge construction, electricity from onshore wind power, electricity from offshore wind power, transport of a container via ship, a magazine, the production and transport of an avocado, a beer can, waste treatment via waste-to-energy, and long-distance air travel) connected to ten potential areas of application for CCS (cement production, iron and steel production, oil and gas production, natural gas processing, refining, ship propulsion engines, pulp and paper production, urea production, waste-to-energy, and direct air capture). The evaluations highlight that significant emission reductions (beyond 50%) could be achieved at marginal costs for end-users in six end-products/services: bridge construction, electricity from onshore wind power, electricity from offshore wind power, transport by ship, magazine, and waste treatment. Moderate emission reductions (between 11 and 37%) could be achieved in two cases at virtually no cost (increase below 1%): beer can and avocado production. Finally, only the case of using direct air capture to compensate for emissions from air travel was found to raise the cost for end-users significantly. Although more research is still needed in this area, this work broadens our understanding of the real cost and benefits of CCS and provides useful insights for decision-makers and society.
Bearing fault diagnosis based on sparsity structure pruning graph attention network
Authors: Zhang Chenye , Shi Hui , Song Renwang , Yao Chenghao , Chen Linying
Published: November 2024

Graph neural networks have been widely used in the field of bearing fault diagnosis, which can deal with non-Euclidean space data and dig deep the relationship between signals. However, most graph neural networks do not distinguish the importance of nodes in information aggregation, and do not take edge noise and data redundancy into account when constructing the graph structure, which affects the diagnostic accuracy. To solve these problems, a fault diagnosis method of graph attention network based on sparsity structure pruning is proposed. Firstly, a sparsity coefficient is introduced to construct the graph structure, and pruning operations are carried out according to the coefficient and the weight of the edges to avoid invalid fusion of information. Then, a graph attention network model based on sparsity structure pruning is constructed, and features of different scales are aggregated into new node representations through multi-head attention mechanism. Finally, the fault diagnosis of bearing is carried out according to the extracted signal discrimination characteristics. To verify the effectiveness of the proposed method, experiments are performed on two different fault diagnosis datasets and compared with other graph neural network methods. The results show that the accuracy and stability of the proposed method are superior to other methods even under the condition of low signal to noise ratio (SNR).
Effects of overloading commercial vehicles on vehicle damage factor for the National Highways in Bihar
Authors: Kumar Aditya , Suman Sanjeev Kumar
Published: November 2024

Overloaded vehicles and traffic growth have a significant impact on the pavement’s performance and service life. As a result, pavement construction and rehabilitation costs have drastically increased. The paper presents the results of the research, including analysis of axle-wise commercial vehicles with 24 h axle-load survey data over a one-year period. The information was collected from two sections of National Highway Road using a weigh-in-motion machine. The fourth power rule is used to calculate the VDF value of over-loaded, legal-loaded, and actual-loaded vehicles by converting the all-vehicle load into a standard axle load. This paper presents the axle-wise impacts of overloaded vehicles on the calculated VDF value. The analysis has shown that when only over-loaded traffic is considered, the class-2 VDF value is higher than the other classes of vehicles, and the class-5 VDF value is higher when all types of collected traffic—legal-loaded and over-loaded traffic are considered. The study concluded that 20% overloaded weight of vehicles increases the VDF value by about 3–4 times. The study reveals that the actual loaded VDF value should be considered during the design of new pavement instead of the VDF value of over-loaded and legal-loaded vehicles. This result may assist the pavement designer in calculating the thickness of the pavement layer and the construction cost of the pavement.
Design and modeling of three-mode nonlinear hybrid piezoelectric-electromagnetic vibration energy harvester for harvesting multi-band vibration energy on the freight wagon axle box
Authors: Dong Wentao , Pan Xianghui , Huang Bo
Published: November 2024

With the rapid development of rail transit system, it is becoming more demanding for structural health monitoring (SHM) of the train. It is crucial to supply power for sensing devices on the freight wagon to ensure the safe operation of rail transit systems. Three-mode nonlinear hybrid piezoelectric-electromagnetic vibration energy harvester (TNHVEH) with a three-layer pickup system has been designed and applied to efficiently harvest vibration energy on the axle box of freight wagons for providing the power of the sensors for online SHM. Dynamic coupling model of the vehicle-harvester system is built to devote the relationship between the operation bandwidth and the nonlinear degree of TNHVEH for broadening the operation frequency band. Simulation and experimental results demonstrate that the resonant frequencies of the three pickup systems of TNHVEH are concentrated around 27, 70, and 120 Hz, matching the representative frequencies of axle box vibrations. A maximum output voltage of 2.97 V and output power of 29.4 μW under an optimal load of 300 kΩ at 0.5 g acceleration is achieved. It successfully lights up 53 LEDs with ‘ECJTU’ patterns, providing a solution to the power supply problem of microelectronic devices on freight wagons.
Complex product quality prediction based on ResNeSt model combining class-aware attention mechanism and dynamically updating class weights
Authors: Rao He , Zhan Hongfei , Yu Junhe , Wang Rui
Published: November 2024

The processing state data of complex products often exhibits high dimensionality, intricate feature relationships, and imbalanced distributions, hindering the accuracy of data-driven quality prediction models. To address these challenges, this paper proposes a complex product quality prediction model that integrates a class-aware attention mechanism and dynamic class weight update strategy. To handle the high dimensionality and complex correlations of the data, Pearson Correlation Coefficient and Gradient Boosting Decision Tree-based Recursive Feature Elimination (GBDT-RFE) algorithms are employed for feature selection. In response to the imbalanced distribution of data categories, a class-aware attention mechanism module is built upon the ResNeSt network, utilizing prior knowledge of data distribution to adjust the model’s focus. Furthermore, a loss function is designed to dynamically update class weights based on classification error rates, enabling the model to adaptively adjust the weight allocation for different classes, thereby enhancing its generalization capability. Experimental results on a semiconductor industry dataset demonstrate that the proposed model outperforms the original ResNeSt model in multiple metrics, with accuracy improved by 3.5%, AUC increased by 12.6%, F1 score raised by 18.9%, and recall enhanced by 24%, ultimately achieving an overall prediction accuracy of 98.7%. These multidimensional improvements make the model suitable for various complex product data scenarios such as electronics manufacturing, automotive industry, and biopharmaceuticals, demonstrating broad applicability.
Characterizing out-of-distribution generalization of neural networks: application to the disordered Su–Schrieffer–Heeger model
Authors: Cybiński Kacper , Płodzień Marcin , Tomza Michał , Lewenstein Maciej , Dauphin Alexandre , Dawid Anna
Published: November 2024

Machine learning (ML) is a promising tool for the detection of phases of matter. However, ML models are also known for their black-box construction, which hinders understanding of what they learn from the data and makes their application to novel data risky. Moreover, the central challenge of ML is to ensure its good generalization abilities, i.e. good performance on data outside the training set. Here, we show how the informed use of an interpretability method called class activation mapping, and the analysis of the latent representation of the data with the principal component analysis can increase trust in predictions of a neural network (NN) trained to classify quantum phases. In particular, we show that we can ensure better out-of-distribution (OOD) generalization in the complex classification problem by choosing such an NN that, in the simplified version of the problem, learns a known characteristic of the phase. We also discuss the characteristics of the data representation learned by a network that are predictors of its good OOD generalization. We show this on an example of the topological Su–Schrieffer–Heeger model with and without disorder, which turned out to be surprisingly challenging for NNs trained in a supervised way. This work is an example of how the systematic use of interpretability methods can improve the performance of NNs in scientific problems.
Introduction: How the Return to Industrial Policy Threatens to Undermine the WTO
Authors: Mavroidis Petros C
Published: November 2024

This chapter explains the content of the whole volume. It starts with the observation that we are witnessing “slowbalization” as the growth of trade has been halted. The main reason is the number of trade-impeding measures, many of which are in the name of national security. At this juncture, not much can be done against similar measures, as enforcement at the WTO level has been crippled: WTO members routinely adopt trade-restricting measures safe in the knowledge that, if challenged, they can always appeal hostile panel reports “into the void” as we explain later on, and thus deprive panel decisions of any legal significance. But the bigger problem is that correcting this defect is not much help. The law itself needs to be rethought, as it is outdated. Alas, there is no appetite for legislative action at the WTO.
Industrial Policy in the Eighties
Authors: Mavroidis Petros C
Published: November 2024

Semiconductors emerged as the apple of discord between Japan and the US in the 1980s. While the US was the first mover in this market, Japan managed to progress faster. The US did not want to leave this market, understanding its importance both to the national economy as well as to its own security. It refused Japanese investment in the US market and requested a fairer partition of the world market between them. A feud soon erupted between them, largely about rents, as national security was sparingly invoked. The agreements signed between the two litigants did not help the cause of the US. This was the first lesson that techno-nationalism does not work.