bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine learning the in-medium correction factor on nucleon–nucleon elastic cross section
Authors: Wei Guojun , Li Pengcheng , Wang Yongjia , Li Qingfeng , Liu Fuhu
Published: November 2024

The nuclear equation of state cannot be directly measured in the heavy-ion collision experiments; it is usually inferred from the comparison between transport model simulations and experimental measurements. The in-medium correction factor (F, which is defined as the ratio of the cross section in the nuclear medium to that in free space) on the nucleon–nucleon elastic cross section is one of the important inputs of the transport model, and its magnitude is still debated. The advent of machine learning (ML) has profoundly influenced the way scientists study the natural world and has provided a new paradigm that merges traditional investigation with advanced data-driven techniques. The aim of this work is to present a ML-based method to study the in-medium correction factor F. The ultra-relativistic quantum molecular dynamics (UrQMD) transport model is used to simulate

132

Sn

+

124

Sn

collisions at beam energy of 0.27 GeV/nucleon with different impact parameters. The value of F is randomly selected from 0.4 to 0.8 for the simulation of each event. Several observables simulated by the UrQMD model with different F, which are thought to be probably sensitive to the in-medium nucleon–nucleon cross sections, are fed into the LightGBM (Light Gradient Boosting Machine, which is a modern decision tree-based ML algorithm) to establish the mapping between the observables and F. The mean absolute error (MAE), which is the absolute difference between the true and the predicted F, is about 0.080 and 0.021 by using event-by-event and 40-event summed observables, respectively. It indicates that ML can recognize information about the F factor. Furthermore, according to the results of Shapley Additive exPlanations, an interpretability analysis method in ML, features that have the greatest effect on the F are identified. ML combined with the transport model may open a new venue to study the F factor. In addition, the interpretability analysis of the ML algorithm may also offer valuable insights for subsequent research.
α-decays of even–even actinides and superheavy nuclei to the first rotational 2+ states of daughter nuclei
Authors: Seif W M , Adamian G G , Antonenko N V , Abdulghany A R , Nasr A
Published: November 2024

The alpha-decays of even–even isotopes of actinides and superheavy nuclei to the ground 0+ and first 2+ states of their daughter nuclei are studied. The conditions for the maximum intensity of alpha-decay from the ground state to the lowest 2+ state are analyzed in detail based on existing experimental data. The decays to the first 2+ states reach their maximum intensity relative to those to corresponding ground states of daughter nuclei at N

D
= 136, due to the corresponding increasing Q

α
(2+). This correlates with relatively strong negative octupole deformation of daughter nucleus and is also accompanied by decreasing E(2+). For the alpha-decays of heavy nuclei up to Og, the half-lives and population probabilities of the 0+ and 2+ states of the daughter nucleus are described and predicted employing the preformed cluster model.
Radiation in the coffee cup
Authors: Ferreira João Paulo M
Published: November 2024

It is commonly assumed that radiative heat transfer only plays a relevant role in situations involving temperatures of several hundred degrees Celsius and above. Other common misconceptions relate to the cooling of metallic vs non-metallic objects, and the effect of their colour. A series of alternative demonstrations that counteract these beliefs and show the role played by radiation in the cooling of common tableware containing hot liquids are described here. The experiments require basic equipment, easily available even at home. The cooling curves obtained can be modelled with Newton´s law of cooling and the corresponding heat transfer coefficients estimated. The results elucidate the influence of surface emissivity on radiative heat transfer, and that this mechanism has a non-minor share on cooling processes even at temperatures below the normal boiling point of water. A final demonstration concerns heating of the same systems and corroborates the previous conclusions.
Many-body localization in the age of classical computing*
Authors: Sierant Piotr , Lewenstein Maciej , Scardicchio Antonello , Vidmar Lev , Zakrzewski Jakub
Published: November 2024

Statistical mechanics provides a framework for describing the physics of large, complex many-body systems using only a few macroscopic parameters to determine the state of the system. For isolated quantum many-body systems, such a description is achieved via the eigenstate thermalization hypothesis (ETH), which links thermalization, ergodicity and quantum chaotic behavior. However, tendency towards thermalization is not observed at finite system sizes and evolution times in a robust many-body localization (MBL) regime found numerically and experimentally in the dynamics of interacting many-body systems at strong disorder. Although the phenomenology of the MBL regime is well-established, the central question remains unanswered: under what conditions does the MBL regime give rise to an MBL phase, in which the thermalization does not occur even in the asymptotic limit of infinite system size and evolution time? This review focuses on recent numerical investigations aiming to clarify the status of the MBL phase, and it establishes the critical open questions about the dynamics of disordered many-body systems. The last decades of research have brought an unprecedented new variety of tools and indicators to study the breakdown of ergodicity, ranging from spectral and wave function measures, matrix elements of observables, through quantities probing unitary quantum dynamics, to transport and quantum information measures. We give a comprehensive overview of these approaches and attempt to provide a unified understanding of their main features. We emphasize general trends towards ergodicity with increasing length and time scales, which exclude naive single-parameter scaling hypothesis, necessitate the use of more refined scaling procedures, and prevent unambiguous extrapolations of numerical results to the asymptotic limit. Providing a concise description of numerical methods for studying ETH and MBL, we explore various approaches to tackle the question of the MBL phase. Persistent finite size drifts towards ergodicity consistently emerge in quantities derived from eigenvalues and eigenvectors of disordered many-body systems. The drifts are related to continuous inching towards ergodicity and non-vanishing transport observed in the dynamics of many-body systems, even at strong disorder. These phenomena impede the understanding of microscopic processes at the ETH-MBL crossover. Nevertheless, the abrupt slowdown of dynamics with increasing disorder strength provides premises suggesting the proximity of the MBL phase. This review concludes that the questions about thermalization and its failure in disordered many-body systems remain a captivating area open for further explorations.
Method for identifying damage to stay cables based on local beam deflection
Authors: Yang Yanxiao , Su Mubiao , Li Wenping
Published: November 2024

In this study, for the problem of difficulty in identifying the damage of diagonal cable using the overall beam deflection, a method of identifying the cable based on the flexibility matrix of local beam segments is proposed. The range of influence of cable damage on the deflection of beams under self-weight is investigated and analysed using the finite element method , and the results show that the damage of cables mainly affects the deflection in their vicinity, while the change of deflection at other locations is minimal; with the change of the location of damaged cables, the influence of the range also changes accordingly. Building on this, the relationship between the difference in deflection of local beams and the change in cable force before and after the cable damage is deduced by combining with the principle of structural mechanics, and the damage index

∆
F

is proposed, and the validity of the method is confirmed by experiments. The experimental results indicate that the deflection of the local beam can be utilized to assess the change in cable force, allowing for the identification of the damaged cable’s location, specifically where the change in cable force is negative. The method is highly resistant to interference. The method can quickly and accurately locate the damaged cable.
Reassessment of 3D synchro-resonant detector for high-frequency gravitational waves
Authors: Woods R C
Published: November 2024

Previously reported results for a gravity wave detector regarding photon generation arising from the interaction between an incident high-frequency gravitational wave, a locally-generated Gaussian electromagnetic beam, and a local steady magnetic field, are reassessed using symmetry and a rigorous interpretation of Poynting’s theorem. The conclusions are that transverse photon generation in this geometry is impossible, and that wave impedance cannot be used as the basis for distinguishing weak photon generation from other spuriae.
Interpolating supersymmetric pair of Fokker-Planck equations
Authors: Ho Choon-Lin
Published: November 2024

We consider Fokker-Planck equations that interpolate a pair of supersymmetrically related Fokker-Planck equations with constant diffusion coefficients. Based on the interesting property of shape-invariance, various one-parameter interpolations of the solutions of the supersymmetric pair of Fokker-Planck systems can be directly constructed.
Tailoring masses to artificial molecules based on the shape of their wavefunctions
Authors: Shushi Tomer
Published: November 2024

In this short paper, we examine artificial molecules composed of coupled artificial atoms such as quantum dots. Similar to artificial atoms, which have position-dependent effective masses for electrons, artificial molecules exhibit this characteristic while comprising more than one artificial atom. While in the literature, such artificial molecules are focused on the kinetic term of the electrons in such a setup, we consider the full description that includes the kinetic and potential terms that involve the nuclei. The proposed artificial molecules consist of nuclei and electrons coupled through Coulomb potentials and kinetic energy influenced by electronic position-dependent effective masses that also depend on the positions of the nuclei and the other electrons in the system. We demonstrate how the Schrödinger equation for such systems can be solved by assuming the entire shape of the molecular wavefunction, guided by a tailored non-parabolic energy-momentum relation for at least one electron within the molecular structure. Additionally, we show that instead of pre-specifying the entire form of the molecular wavefunction, we can consider the coupling between the electrons and nuclei to obtain the wavefunction of the system.
Development and investigation of DMDG-MOSFET biosensor for charged biomolecule detection
Authors: Das Satish Kumar , Biswal Sudhansu M , Giri LalatIndu , Pahi Ipsita , Nanda Umakanta
Published: November 2024

The paper explores the analog and sensitivity parameter of a n-channel gate stack Dual Material Double Gate (DMDG) MOSFET biosensor, specifically focusing on its response to a wide range of charged biomolecule introduced into its cavity region. This novel structure offers improved sensitivity and selectivity due to its ability to modulate the threshold voltage and control the electrostatic environment more precisely compared to conventional MOSFET-based biosensors. The analysis includes a thorough examination of the surface potential, electric field, transconductance, and threshold voltage variations influenced by the presence of charged biomolecules. By applying a parabolic-potential technique to solve the 2D Poisson’s equation, the expression for surface potential can be found. The minimal surface potential model is used to calculate the threshold voltage. Using SILVACO ATLAS, the simulation findings suggest that the proposed gate stack DMDG-MOSFET structure demonstrates sensitivity of 0.123 V and 0.607 V for neutral and charged biomolecules respectively emphasizing the impact of gate material engineering on the biosensor’s performance.
Chaos suppression of a Seven-dimensional power system based on the predefined-time sliding mode control method
Authors: Fang Jie , Zhang Shaohui , Wu Yang , Zhao Kaihui
Published: November 2024

To suppress chaotic oscillation in the seven-dimensional power system model, the predefined-time sliding mode control of disturbed seven-dimensional chaotic power system is studied in this paper. Firstly, the dynamic characteristics of the seven-dimensional power system are analyzed, and the existence of chaotic attractors is demonstrated. Then, the seven-dimensional power system is divided into three subsystems according to control outputs, and the chaotic control of the seven-dimensional power system is decomposed into the control problem of three subsystems. For each subsystem, a predefined-time sliding mode controller is designed to regulate the system states converge to the desired values. Compared with other existing control methods, the proposed predefined-time sliding mode controller can control the chaotic power system to the expected states at any predefined time. The minimum upper bound of the convergence time is determined by the adjustable parameters of this controller, which make it meet the control requirements conveniently. Finally, the effective and excellent control performance of the predefined-time control scheme is proved by numerical simulation.
Multi-stability and dynamical analysis of Zhanbota-IIA equation with couple of integrating architectures
Authors: Rashid Butt Asma , Farooq Fozia Bashir , Abbas Hafsa , Alqahtani Nouf Abdulrahman , Imran Muhammad , Bekir Ahmet
Published: November 2024

This research delves into exploring the Zhanbota-IIA equation, which has applications in medical imaging and diagnostics, power systems, and fuzzy logic processing. This study employs two analytical techniques, namely the variational method that emerges from the variational principle and the improved Cham method, to find various types of exact traveling wave solutions. These algorithms yield periodic, dark, singular, and bright soliton solutions as well as combinations of these forms Appropriate parametric values are chosen to make 2D and 3D plots to illustrate how the retrieved solutions behave. Chaotic phenomena are analyzed using different initial conditions and constant parameters through multi-stability analysis. The extracted results illustrate the efficiency of the outlined techniques in resolving exact solutions in nonlinear areas.
Implication of nano-Hertz stochastic gravitational wave background on ultralight axion particles
Authors: Yang Jing , Xie Ning , Huang Fa Peng
Published: November 2024

Recently, the Hellings Downs correlation has been observed by different pulsar timing array (PTA) collaborations, such as NANOGrav, European PTA, Parkes PTA, and Chinese PTA.
These PTA measurements of the most precise pulsars within the Milky Way show the first evidence for the stochastic gravitational wave background of our Universe.
We study the ultralight axion interpretation of the new discovery by investigating the gravitational wave from axion transitions
between different energy levels of the gravitational atoms, which are composed of cosmic populated Kerr black holes and their surrounding axion clouds formed through the superradiant process.
By Bayesian analysis,
we demonstrate that
this new observation naturally admits an ultralight axion interpretation around 10-21 eV, which
is consistent in magnitude with the typical mass of fuzzy dark matter.
Dark matter (h)eats young planets
Authors: Croon Djuna , Smirnov Juri
Published: November 2024

We study the effect of dark matter annihilation on the formation of Jovian planets. We
show that dark matter heat injections can slow or halt Kelvin-Helmholtz contraction, preventing
the accretion of hydrogen and helium onto the solid core. The existence of Jupiter in our solar
system can therefore be used to infer constraints on dark matter with relatively strong
interaction cross sections. We derive novel constraints on the cross section for both
spin-dependent and spin-independent dark matter. We highlight the possibility of a positive
detection using future observations by JWST, which could reveal strongly varying planet
morpholoiges close to our Galactic Center.
Cryptanalysis and Improvement to the Quantum Private Query Protocol for Enhancing Database Privacy
Authors: Shen Zhengda , Shao Wenzhu , Li Zhigang , Peng Xiaoyu , Mu Nankun , Miraj Mahabubur Rahman , Liu Bin
Published: November 2024

In order to protect the privacy of query user and database, some QKD-based quantum private query (QPQ) protocols were proposed. One example is the protocol proposed by Zhou et al., in which the user makes initial quantum states and derives the key bit by comparing the initial quantum state and the outcome state returned from the database by ctrl or shift mode instead of announcingtwo non-orthogonal qubits as others which may leak part secret information. In some extent, the security of the database and the privacy of the user are strengthened. Unfortunately, we find that in this protocol, the dishonest user can obtain, utilizing unambiguous state discrimination, much more database information than that is analyzed in Zhou et al.’s original research. To strengthen the database security, we improved the mentioned protocol by modifying the information returned by the database in various ways. The analysis indicates that the security of the improved protocols is greatly enhanced.
Sudden change of interferometric power for X-shape states
Authors: Zhu 朱 Dian 典 , Zhang 张 Fu-Lin 福林 , Chen 陈 Jing-Ling 景灵
Published: November 2024

Quantum interferometric power (IP), a discordlike measure, plays an important role in quantum metrology. We study the dynamics of IP for two-qubit X-shape states under different noisy environments. Our study shows that IP exhibits sudden change, and one side quantum channel is enough for the occurrence of a sudden change of IP. In particular, we show that the initial state having no sudden change of quantum discord exhibits a sudden change of IP under the dynamics of amplitude noise, but the converse is not true. Besides, we also investigate the dynamics of IP under two different kinds of composite noises. Our results also confirm that sudden change of IP occurs under such composite noises.
Critical station identification of metro networks based on the integrated topological-functional algorithm: A case study of Chengdu
Authors: Zeng 曾 Zi-Qiang 自强 , He 何 Sheng-Jie 圣洁 , Tian 田 Wang 旺
Published: November 2024

As a key mode of transportation, urban metro networks have significantly enhanced urban traffic environments and travel efficiency, making the identification of critical stations within these networks increasingly essential. This study presents a novel integrated topological-functional (ITF) algorithm for identifying critical nodes, combining topological metrics such as K-shell decomposition, node information entropy, and neighbor overlapping interaction with the functional attributes of passenger flow operations, while also considering the coupling effects between metro and bus networks. Using the Chengdu metro network as a case study, the effectiveness of the algorithm under different conditions is validated. The results indicate significant differences in passenger flow patterns between working and non-working days, leading to varying sets of critical nodes across these scenarios. Moreover, the ITF algorithm demonstrates a marked improvement in the accuracy of critical node identification compared to existing methods. This conclusion is supported by the analysis of changes in the overall network structure and relative global operational efficiency following targeted attacks on the identified critical nodes. The findings provide valuable insight into urban transportation planning, offering theoretical and practical guidance for improving metro network safety and resilience.
Improving subject transfer in EEG classification with divergence estimation
Authors: Smedemark-Margulies Niklas , Wang Ye , Koike-Akino Toshiaki , Liu Jing , Parsons Kieran , Bicer Yunus , Erdoğmuş Deniz
Published: November 2024

Objective. Classification models for electroencephalogram (EEG) data show a large decrease in performance when evaluated on unseen test subjects. We improve performance using new regularization techniques during model training. Approach. We propose several graphical models to describe an EEG classification task. From each model, we identify statistical relationships that should hold true in an idealized training scenario (with infinite data and a globally-optimal model) but that may not hold in practice. We design regularization penalties to enforce these relationships in two stages. First, we identify suitable proxy quantities (divergences such as Mutual Information and Wasserstein-1) that can be used to measure statistical independence and dependence relationships. Second, we provide algorithms to efficiently estimate these quantities during training using secondary neural network models. Main results. We conduct extensive computational experiments using a large benchmark EEG dataset, comparing our proposed techniques with a baseline method that uses an adversarial classifier. We first show the performance of each method across a wide range of hyperparameters, demonstrating that each method can be easily tuned to yield significant benefits over an unregularized model. We show that, using ideal hyperparameters for all methods, our first technique gives significantly better performance than the baseline regularization technique. We also show that, across hyperparameters, our second technique gives significantly more stable performance than the baseline. The proposed methods require only a small computational cost at training time that is equivalent to the cost of the baseline. Significance. The high variability in signal distribution between subjects means that typical approaches to EEG signal modeling often require time-intensive calibration for each user, and even re-calibration before every use. By improving the performance of population models in the most stringent case of zero-shot subject transfer, we may help reduce or eliminate the need for model calibration.
Experimental investigation of the radial structure of energetic particle driven GAM in TCV
Authors: Dreval M.B. , Sharapov S.E. , Jansen van Vuuren A. , Karpushov A.N. , Mazzi S. , Podesta M. , Sheikh U.A. , Simons L. , Ochoukov R. , Poley J. , Testa D. ,   the TCV Team,   the EUROfusion Tokamak Exploitation Team
Published: November 2024

High amplitude energetic particle geodesic acoustic mode (EGAM) oscillations driven by Neutral Beam (NBI) injected in the direction counter to the toroidal plasma current are observed in the TCV tokamak. The modes appear at frequencies close to the geodesic acoustic mode (GAM) frequency, corresponding to the mode radii calculated without plasma elongation corrections. The spatial structure of the EGAM density oscillation is analyzed using multichannel soft x-ray (SXR) and broadband light emission diagnostics. The analysis of spatiotemporal emission data shows a non-rotating structure of the density oscillations. The non-rotating mode discrimination is the additional new capability of the multichannel spatiotemporal SXR data analysis technique in TCV. We present the discrimination method of assessing the standing character of the EGAM wave. The structure of EGAM density oscillations in TCV is consistent with the theoretical GAM poloidal structure, namely a m= 1 standing wave with density oscillations amplitude proportional to sin(θ), where the poloidal angle θ is measured from the equatorial plane. The poloidal structure of magnetic the field oscillations is analyzed using a poloidal array of magnetic coils. The structure of the EGAM-induced magnetic field oscillations in TCV is a m = 2 standing wave. Time evolution of EGAMs suggests that a nonlinear EGAM chirping is observed. The chirping depends on the EGAM radial location, which varies as the NBI deposition is varied through a vertical shift of the plasma magnetic axis. The chirping disappears at the plasma periphery. A fast periodic radial shift of the EGAMs radial location is also observed to occur during the single chirp.
Identifying drivers of storage dynamics of lakes and reservoirs in the arid Central Asia
Authors: Zhao Gang , Liu Suxia , Deng Haoxin , Tang Qiuhong , Zhang Chi , Su Yanan , Chen Fahu
Published: November 2024

Knowing the storage variations in lakes and reservoirs are essential for water resources and environmental management, especially in the regions facing water scarcity. However, the quantification of the storage changes is limited by sparse in-situ observations and spatial coverage of space (air)-borne altimetric sensors that have been used conventionally in storage retrieval. This hampers the attribution analysis of lake storage changes. Here, we combined long-term optical remote sensing and multi-source terrain elevation data to derive the monthly storage time series from 1990 to 2020 for 8544 lakes and reservoirs in Central Asia, where water scarcity has been bottle-necking local socioeconomic sustainability. The regional total storage has been decreasing with a rate of −4.78 ± 0.88 km3 yr−1 mainly owing to the desiccation of the Aral Sea. For other lakes, 26% of them show decreasing while 22% show increasing trends. At a watershed-scale, the long-term changes in small to medium-sized (<5000 km2) lakes are primarily caused by the changes in surface runoff, jointly affected by precipitation and temperature changes. We also found that 29% lakes in Central Asia experienced frequent seasonal dry out in the past decades. Such seasonal dry out is mainly caused by fast evaporation losses during the summer months. For the majority (63 ± 8%) of these lakes, their evaporation water losses are larger than the seasonal storage drawdown. Our analysis highlights the co-regulation of surface runoff and lake evaporation in the storage losses in arid and semi-arid regions.
Burst flooding in Singapore: an emerging urban flooding type revealed by high-temporal-resolution observations
Authors: Lommen Dave , Jingyu Wang , Su Hui , Xiefei Zhi , Xianfeng Wang , Park Edward , Zhang Hugh , Lee Joshua , Chyi Wong Meei
Published: November 2024

Urbanisation significantly alters the interaction between land surface and the lower troposphere, impacting occurrences of natural hazards. The influence of urbanisation on natural hazards like heatwaves, hailstorms, and flooding remains debated. However, it is well established that impervious surfaces in urban areas can lead to flooding amplification. Singapore, amidst rapid urbanisation, experiences frequent flooding, exacerbated by its tropical-monsoon climate and climate change. Utilising high-temporal-resolution rainfall data from 2017 onwards, we examined the dynamics of urban flooding in Singapore. In total, 108 flooding events were reported for the period 2017–2023, all of a transient nature, primarily linked to cloudbursts. Based on the unique precipitation characteristics associated with urban flash flooding, the term ‘burst flooding’ is introduced to refer to urban floods caused by intense, short-duration rainfall events. A notable increase in cloudburst occurrences in November and December during La Niña years emphasises the role of global climate phenomena in local weather.
Some non-algebraic forms of exp

(

A
^

+

B
^

)
Authors: Tapia-Valerdi M A , Ramos-Prieto I , Soto-Eguibar F , Moya-Cessa H M
Published: November 2024

We present examples where expressions for

exp
⁡
(

A
^

+

B
^

)

can be derived even though operators (or superoperators)

A
^

and

B
^

do not commute in a manner that leads to known factorizations. We apply our factorization to the case of a Lindblad operator modeling single-photon decay and to a binary Glauber–Fock photonic lattice.
Casting more light in the shadows: dual Somos-5 sequences
Authors: Harrow J W E , Hone A N W
Published: November 2024

Motivated by the search for an appropriate notion of a cluster superalgebra, incorporating Grassmann variables, Ovsienko and Tabachnikov considered the extension of various recurrence relations with the Laurent phenomenon to the ring of dual numbers. Furthermore, by iterating recurrences with specific numerical values, some particular well-known integer sequences, such as the Fibonacci sequence, Markoff numbers, and Somos sequences, were shown to produce associated ‘shadow’ sequences when they were extended to the dual numbers. Here we consider the most general version of the Somos-5 recurrence defined over the ring of dual numbers

D

with complex coefficients, that is the ring

C

[
ε
]

modulo the relation ɛ
2 = 0. We present three different ways to present the general solution of the initial value problem for Somos-5 and its shadow part: in analytic form, using the Weierstrass sigma function with arguments in

D

; in terms of the solution of a linear difference equation; and using Hankel determinants constructed from

D

-valued moments, via a connection with a Quispel–Roberts–Thompson map over the dual numbers.
Effect of tissue viscoelasticity on delivered mechanical power in a physical respiratory system model: distinguishing between airway and tissue resistance
Authors: Walzel Simon , Roubik Karel
Published: November 2024

Understanding the mechanics of the respiratory system is crucial for optimizing ventilator settings and ensuring patient safety. While simple models of the respiratory system typically consider only flow resistance and lung compliance, lung tissue resistance is usually neglected. This study investigated the effect of lung tissue viscoelasticity on delivered mechanical power in a physical model of the respiratory system and the possibility of distinguishing tissue resistance from airway resistance using proximal pressure measured at the airway opening. Three different configurations of a passive physical model of the respiratory system representing different mechanical properties (Tissue resistance model, Airway resistance model, and No-resistance model) were tested. The same volume-controlled ventilation and parameters were set for each configuration, with only the inspiratory flow rates being adjusted. Pressure and flow were measured with a Datex-Ohmeda S/5 vital signs monitor (Datex-Ohmeda, Madison, WI, USA). Tissue resistance was intentionally tuned so that peak pressures and delivered mechanical energy measured at airway opening were similar in Tissue and Airway Resistance models. However, measurements inside the artificial lung revealed significant differences, with Tissue resistance model yielding up to 20% higher values for delivered mechanical energy. The results indicate the need to revise current methods of calculating mechanical power delivery, which do not distinguish between tissue resistance and airway flow resistance, making it difficult to evaluate and interpret the significance of mechanical power delivery in terms of lung ventilation protectivity.
Influence of physical and material parameters on switching current density in perpendicular STT-MTJ: a micromagnetic study
Authors: Shaw Abhishree , Kumar Joshi Vinod
Published: November 2024

Switching in magnetic tunnel junctions (MTJs) is considered to be coherent according to the macrospin model but above a critical characteristic length (R
c
) this process becomes incoherent. As a result, switching becomes a complex process and affects the switching current density (J
c
). We designed a spin transfer torque (STT) based single barrier perpendicular MTJ (SMTJ) and observed the influence of the junction size and exchange stiffness constant (Aex) on the switching process through micromagnetic simulations performed on Object Oriented Micromagnetic Framework (OOMMF). It was found that coherent switching occurred only for junction diameter ≤20nm and showed dependence on Aex as well. The influence of damping constant and anisotropy on J
c
is studied and the mechanism of magnetic reversal through domain formation is revisited in this work. Furthermore, Double barrier MTJ (DBMTJ) stack was designed, which showed increased STT efficiency in switching time with a requirement of J
c
lower by 42.86% compared to SMTJ.
Relationships between microbial characteristics and the arsenic cycle in high-arsenic groundwater
Authors: Yang Jingru , Zhang Yanyan , Li Qiao , Su Yanpeng , Tao Hongfei , Jiang Youwei , Mahemujiang Aihemaiti
Published: November 2024

Microbial activities play a pivotal role in the migration and transformation of arsenic (As) within groundwater systems, particularly at high concentrations. Focusing on the Kuitun River Basin, this study used high-throughput sequencing to unravel the intricate diversity of microbial communities and their influence on As enrichment. Groundwater with elevated As hosted richer and more diverse microbial populations compared to that with lower As levels. The Sobs and Shannon diversity indices for the high-As group initially declined before rising with increasing As concentrations. Key microbial taxa dominating these ecosystems included Pseudomonas, Acinetobacter, Aquabacterium, Novosphingobium, and Sphingobium, with Pseudomonas showing substantial variation in abundance across different As concentrations. Distance-based redundancy analysis emphasized the importance of dissolved oxygen in shaping the microbial landscape, followed closely by the interplay between iron and As concentrations. Flavobacteriaceae and Burkholderiaceae displayed inverse correlations with As levels, highlighting the multifaceted relationship between microbial communities and groundwater chemistry. This investigation underscores the profound impact of As concentration gradients on microbial biodiversity and elucidates a complex regulatory framework where environmental parameters and microorganisms collaborate in governing As accumulation in groundwater. The results enrich our understanding of the biogeochemical dynamics underlying arsenic behavior in subterranean aquatic habitats.
The major role of riverine outflows in shaping the current and future habitats of Harmful Algal Blooms: the case of the North Sea
Authors: Duteil Olaf , Macias Diego , Stips Adolf , Polimene Luca
Published: November 2024

This study investigates the extension of the potential habitat of Harmful Algal Blooms (HABs) in the North Sea using observational data and model experiments under current and future climate scenarios. We assess the combined effects of temperature, salinity, and nutrient availability, particularly the nitrogen-to-phosphorus ratio, on HABs in the region. Climate change projections indicate a decrease in salinity concomitant with an increase in surface temperature, potentially leading to an offshore extension of HAB habitat. Reducing nitrogen and phosphorus loads in rivers differentially affects dissolved inorganic nitrogen (DIN) and phosphorus (DIP) levels, with DIN being more sensitive to load reduction, thereby constraining HAB habitat extension. We underscore the importance of considering both physical and biogeochemical factors in assessing HAB habitat dynamics and the potential impacts of climate change and nutrient reduction measures on HAB expansion in the North Sea. These findings have significant implications for environmental policy and management.
Advancing life cycle assessment of bioenergy crops with global land use models
Authors: Arvesen Anders , Humpenöder Florian , Navarrete Gutierrez Tomás , Gibon Thomas , Baustert Paul , Dietrich Jan Philipp , Stadler Konstantin , Iordan Cristina-Maria , Luderer Gunnar , Popp Alexander , Cherubini Francesco
Published: November 2024

Bioenergy crops can cut greenhouse gas (GHG) emissions, yet often bring hard-to-quantify environmental impacts. We present an approach for integrating global land use modeling into life cycle assessment (LCA) to estimate effects of bioenergy crops. The approach involves methodological choices connected to time horizons, scenarios of GHG prices and socioeconomic pathways, and flexible data transfer between models. Land-use change emissions are treated as totals, avoiding uncertain separation into direct and indirect emissions. The land use model MAgPIE is used to generate scenarios up to 2070 of land use, GHG emissions, irrigation and fertilizer use with different scales of perennial grass bioenergy crop deployment. We find that land use-related CO2 emission for bioenergy range from 2 to 35 tonne TJ−1, depending on bioenergy demand, policy context, year and accounting method. GHG emissions per unit of bioenergy do not increase with bioenergy demand in presence of an emission tax. With a GHG price of 40 or 200 $ tonne−1 CO2, GHG per bioenergy remain similar if the demand is doubled. A carbon tax thus has a stronger effect on emissions than bioenergy demand. These findings suggest that even a relatively moderate GHG price (40 $ tonne−1 CO2) can prevent significant emissions, highlighting the critical role governance plays in securing the climate benefits of bioenergy. However, realizing these benefits in practice will depend on a coherent policy framework for pricing CO2 emissions from land-use change, which is currently absent. Overall, our approach addresses direct and indirect effects associated with irrigation, machinery fuel and fertilizer use as well as emissions. Thanks to a global spatial coverage and temporal dimension, it facilitates a systematic and consistent inclusion of indirect effects in a global analysis framework. Future research can build on our open-source data/software to study different regions, bioenergy products or impacts.
Optimizing wireless sensor network routing with Q-learning: enhancing energy efficiency and network longevity
Authors: Jain Amit Kumar , Jain Sushil , Mathur Garima
Published: November 2024

WSNs have gained importance in the recent years in the fields of industries, automobiles, military, agriculture and health care sectors, and others for data acquisition and monitoring. WSNs are made up of a large number of low-power nodes implemented with requisite sensing, computational, and wireless communication functionalities in relation to other nodes or a BS. LEACH is hierarchical routing protocol that adapts nodes into clusters, with an objective of achieving an equal distribution of energy load. However, the drawback of LEACH is that the selection of cluster head (CH) and the usage of single hop data transmission to the base station (BS) depends on the random probability, which is not efficient in large network. New additions involve the integration of a k-means clustering algorithm and reinforcement learning Q-learning for the selection of CHs and routing of data. For instance, Q-Learning improves the reliability and flexibility of a given network as it allows for acquisition of the best routes that involve multi-hope communication. An assessment of Q-Learning based routing is conducted on WSNs, based on energy depletion rate, node duration, and packet delivery ratio. Theoretical analysis shows that the Q-Learning based algorithm outperforms the traditional algorithms such as LEACH and k-means by adopting better energy utilization, reduced node mortality and high throughput. Overall, this study exposes the ability of Q-Learning algorithm in enhancing WSN life and efficiency in the modern world, and thus could be considered an optimal solution for changeability and limited resources in WSN networks.
Comparing advanced and traditional machine learning algorithms for construction duration prediction: a case study of Addis Ababa’s public sector
Authors: Liben Soreti M , Belachew Demiss A , Elsaigh Walied A
Published: November 2024

Accurate prediction of construction durations is crucial for effective project management, particularly in rapidly urbanizing areas such as Addis Ababa. However, there exists a notable research gap regarding the comparative analysis of advanced machine learning (ML) algorithms against traditional methods for this purpose. This study aims to develop and evaluate various advanced ML algorithms to predict construction completion times in Addis Ababa, with the goal of improving resource allocation and enhancing client satisfaction. Data were collected through surveys administered to multiple construction organizations within the city, which served as the foundation for training, validating, and comparing a range of ML models. The research utilized the caret package in R for model development and assessment, incorporating methodologies such as artificial neural networks (NN), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Classification and Regression Trees (CART). To evaluate variable importance, multivariate visualizations, including correlation and scatter plot matrices, were employed, while performance metrics such as mean absolute error (MAE), root mean square error (RMSE), and R-squared (R2) were utilized for model comparison. The findings indicated that the RF model achieved an RMSE of 74 days and an R2 of 0.97, while the KNN model also demonstrated strong performance with an RMSE of 81 days and an R2 of 0.97, marking them as the most accurate models for predicting construction durations. In contrast, the NN model exhibited subpar performance, likely due to constraints related to training data and variable selection. As a result, the RF model was further optimized to improve its predictive accuracy. The study concludes that while the RF model proves to be highly effective for predicting construction durations in Addis Ababa, there is a critical need to expand the dataset and incorporate additional variables to enhance the performance of deep learning and other ML algorithms in this field.
A curvature and temperature simultaneous measurement sensor based on micro-taper formed MZI and an embedded FBG
Authors: Xuelan He , Li Jiahui , Liu Shuyu , Jian Xing , Yuan Libo
Published: November 2024

A compact fiber Bragg grating (FBG) and Mach-Zehnder interferometer (MZI) compound for simultaneous measurement of bending and temperature is described. The FBG and MZI are fabricated in fiber, forming a compact device that is different from the previously prepared axial cascade of multiple structures. Experimental results show that the FBG and MZI have different sensitivity to temperature and bending response, allowing this device to measure bending and temperature simultaneously. The proposed sensor has the advantages of simple preparation steps, small size, low cost, short preparation cycle, etc. Due to these advantages, it is competitive in the future sensing field where bending and temperature are measured simultaneously.
Investigation of tool wear behavior in CFRP drilling by using different tool materials
Authors: Sarfraz Sana , Husnain Naveed , Asif Tahir , Ashraf Ghulam Abbas , Sultan Tahir , Sahar Muhammad Sana Ullah , Imran Muhammad , Zaheer Mansoor Ali , Ahmad Rauf
Published: November 2024

The industrial usage of Carbon fiber reinforced polymers (CFRP) has increased significantly over the past few years due to its distinguished characteristics like great strength-to-weight ratio, fatigue resistance, superior damage tolerance, excellent corrosion resistance, etc Machining of CFRP differs from traditional machining due to its structure. This experimental study aims to investigate the effect of drill bit material on tool wear and to optimize the material selection process of twist drill bits during CNC drilling of CFRP regarding the output of tool wear, thrust forces, and torque generated during the drilling process. Four twist drill bits with dissimilar materials (i.e., HSS-4341, HSS-M2, HSS-Co, and Tungsten Carbide) having the same size and diameter (3 mm) were selected and used for CNC drilling on CFRP plates. During the drilling process, thrust forces and torque were calculated with the help of a dynamometer for each drilled hole. Moreover, the tool wear was seen and compared after the 1st hole and 20th hole for each drill bit to analyze the behavior of different tool materials toward CFRP machining. The results showed that Tungsten Carbide is the most suitable tool material for CFRP drilling as it yielded the lowest thrust forces and lowest torque for all 20 holes. Moreover, the Tungsten Carbide had the lowest tool wear among all the drill bits. These results imply that tool life can be significantly elevated if Tungsten Carbide is to be used for machining of CFRP.
A comprehensive review on sensor supported monitoring of machining processes
Authors: Javvadi Eswara Manikanta , S Santosh , Ambhore Nitin , Nalawade Dattatraya
Published: November 2024

Online monitoring of machining processes is revealed as a critical tool for detecting tool wear, influencing the determination of the remaining useful lifetime of cutting tools. Embracing the ethos of Industry 4.0, the study emphasizes the automatic monitoring of cutting forces, surface roughness, power consumption, tool wear, and tool life, citing their indispensable role in mitigating unfavourable machining conditions such as chatter vibrations, tool breakage, and compromised dimensional accuracy. The paper underscores the pivotal role played by advanced sensor systems in achieving enhanced machining characteristics, characterized by reduced human effort, minimized errors, and streamlined production times. The exploration extends to a comprehensive overview of online detection systems, encompassing sensors and signal processing software tailored for mechanical machining operations. Commencing with an up-to-date literature introduction, the paper systematically navigates through the types of sensors employed in machining, online detection methods, and addresses pertinent challenges while offering insightful suggestions. In a nutshell, the paper summarized its findings and provided future insights, particularly centered on the industry 4.0 theme. It is important to note that this review offers significant assistance to researchers and academics in the industrial sectors.
AKS-YOLOv8: a lightweight and accurate network model for infrared ship detection
Authors: Chen Qi , Lv Zixiang
Published: November 2024

Combining infrared technology and artificial intelligence technology to achieve efficient ship detection is practically important for monitoring and scheduling of ships in harbours. Due to the infrared image texture features are fewer and the background is complex, these lead to the algorithm model having the problems of complex structure, high amount of memory consumption and not being easy to deploy. To address these problems, we propose a lightweight and accurate infrared ship detection model named AKS-YOLOv8, which is based on YOLOv8 design. Firstly, the Split Asymptotic Feature Pyramid Network (SA-FPN) is used in the neck network. It improves model to detect multi-scale infrared ship in large scenes while keeping the model lightweight. Secondly, we introduced the dynamic convolution module KernelWarehouse Dynamic Convolution (KConv) in the backbone network for enhancing the recognition of small targets in infrared images. And we also used FasterBlock instead of Bottleneck to reduce feature map redundancy and improve inference speed. Finally, we adopt Simple, Parameter-free Attention Module (SimAM) to improve the feature extraction ability for key information of infrared ships. To verify the effectiveness of AKS-YOLOv8, a comprehensive test is performed on the infrared ship target recognition database issued by Yantai iraytek Co., Ltd in comparison with some widely-used detection algorithms. The model precision of AKS-YOLOv8 is improved by 1%, and the parameters and model size are reduced by 37.2% and 32.1%, respectively. The results of the experiment indicate that AKS-YOLOv8 has successfully struck a favorable equilibrium between being lightweight and maintaining accuracy. It can provide a valuable technical reference for infrared ship detection technology.