bluuebunny/crossref_metadata_2025 huggingface dataset:
Water-wave diffractions by three-dimensional periodic rectangular blocks: Fourier modal analysis
Authors: Wang Jiyong , Chung Fei Fang , Ong Muk Chen
Published: July 2024

Water-wave diffractions caused by three-dimensional (3D) periodic rectangular blocks are analytically modeled with a Fourier modal analysis method using full-linear potential theory. The boundary conditions in the dimension of periodic extent are conjugated into the other two dimensions in terms of Toeplitz matrices. The elements of the Toeplitz matrices are the Fourier harmonics of vertical and horizontal eigenfunctions converted to special-frequency domains. This allows us to reduce the 3D model system to an ordinary two-dimensional counterpart. The boundary matchings finally lead to a general form of block centrosymmetric matrix for the rectangular topography. A fair consistency between the present results and the data from the literature validates such a Fourier modal analysis. Effects of different parameters on multiple-modal diffraction efficiencies of reflected and transmitted wave energy are computed and analyzed. This study is useful for the designers of coastal breakwaters and focusing lens of water waves.
Charge exchange recombination spectroscopy on the alkali beam of Wendelstein 7-X
Authors: Csillag B. G. , Anda G. , Cseh G. , Dunai D. , Ford O. P. , Flom E. , Gradic D. , Henke F. , Krychowiak M. , Nagy D. , Otte M. , Réfy D. I. , Tőkési K. , Vécsei M. , Zoletnik S. ,   the W7-X Team
Published: July 2024

Measurements of ion temperature profiles are required to assess the energy and particle transport processes in the Wendelstein 7-X stellarator. This device is equipped with a diagnostic alkali beam, which can be utilized to determine local impurity temperatures and densities by Charge Exchange Recombination Spectroscopy (CXRS). It could provide such profiles in the edge plasma, where other diagnostics are less efficient. With this contribution, first results of CXRS measurements on the sodium beam from the scientific operation phase OP2.1 are presented. The spectroscopic system was in commissioning phase lacking some of the final optical components. Thus, the aim of the diagnostics during this campaign was to explore the measurement capabilities. Based on the processed spectra, the prospects of C5+ and C6+ ion temperature and concentration measurements are discussed. The results indicate that with the final optical setup under installation, the diagnostics could provide ion temperature profiles in the edge with 3 mm radial resolution and at least 1 s temporal resolution.
Suppression of oscillatory fluid forces in cylinder wake: Optimal jet control position designed through resolvent analysis
Authors: Ma Rongchi , Gao Chuanqiang , Ren Kai , Yuan Hao , Zhang Weiwei
Published: July 2024

The flow around a circular cylinder is a typical case of unstable separated flow, and controlling its stability has long been a focus of flow control research. This study proposes an optimal control parameter design method based on resolvent analysis, which provides precise design criteria for jet position through effective gain. First, resolvent analysis of cylinder wake flow is conducted. The effective gain is obtained by formulating the velocity excitation corresponding to the local tangential jet, imposing it on the forcing mode, and subsequently multiplying it by the resolvent gain. Subsequently, a steady tangential jet is applied to the optimal control position guided by the effective gain, achieving complete suppression of oscillatory loads. Concurrently, the sensitivity of jet effective control position parameters is validated by computational fluid dynamics. Finally, the effective gain accurately identified the optimal jet control position for different Reynolds numbers (Re≤120). It is observed that the optimal control position shifts upstream with increasing Reynolds number. This study demonstrates that resolvent analysis can accurately capture the critical sensitivity characteristics of flows, providing precise and direct guidance for optimal control position parameter design.
Airfoil aerodynamic/stealth design based on conditional generative adversarial networks
Authors: Jin Shi-Yi , Chen Shu-Sheng , Che Shi-Qi , Li Jin-Ping , Lin Jia-Hao , Gao Zheng-Hong
Published: July 2024

Aerodynamic/stealth design is becoming an important factor in the advanced airfoil design. In this work, a supervised machine learning method is proposed for aerodynamic and stealth integrated airfoil design. The conditional generative adversarial network (CGAN) is constructed for the multidisciplinary design of airfoil. Then, the generator and discriminator simply using deep neural network have good robustness and stability in training. The CGAN model also shows good generalization capability in the test set, with less than 1% error in fitting to the airfoil profile data, and the generated airfoils are within 10% error compared to the test airfoil aerodynamic stealth characteristics. In addition, the optimization results based on the CGAN model demonstrate that aerodynamic performance improvement would increase the airfoil camber and stealth performance improvement would sharpen the airfoil leading edge.
Individual tree detection and classification from RGB satellite imagery with applications to wildfire fuel mapping and exposure assessments
Authors: Bennett L. , Yu Z. , Wasowski R. , Selland S. , Otway S. , Boisvert J.
Published: July 2024

Background Wildfire fuels are commonly mapped via manual interpretation of aerial photos. Alternatively, RGB satellite imagery offers data across large spatial extents. A method of individual tree detection and classification is developed with implications to fuel mapping and community wildfire exposure assessments. Methods Convolutional neural networks are trained using a novel generational training process to detect trees in 0.50 m/px RGB imagery collected in Rocky Mountain and Boreal natural regions in Alberta, Canada by Pleiades-1 and WorldView-2 satellites. The workflow classifies detected trees as ‘green-in-winter’/‘brown-in-winter’, a proxy for coniferous/deciduous, respectively. Key results A k-fold testing procedure compares algorithm detections to manual tree identification densities reaching an R2 of 0.82. The generational training process increased achieved R2 by 0.23. To assess classification accuracy, satellite detections are compared to manual annotations of 2 cm/px drone imagery resulting in average F1 scores of 0.85 and 0.82 for coniferous and deciduous trees respectively. The use of model outputs in tree density mapping and community-scale wildfire exposure assessments is demonstrated. Conclusion & Implications The proposed workflow automates fine-scale overstorey tree mapping anywhere seasonal (winter and summer) 0.50 m/px RGB satellite imagery exists. Further development could enable the extraction of additional properties to inform a more complete fuel map.
A therapy for suppressing canonical and noncanonical SARS-CoV-2 viral entry and an intrinsic intrapulmonary inflammatory response
Authors: Leibel Sandra L. , McVicar Rachael N. , Murad Rabi , Kwong Elizabeth M. , Clark Alex E. , Alvarado Asuka , Grimmig Bethany A. , Nuryyev Ruslan , Young Randee E. , Lee Jamie C. , Peng Weiqi , Zhu Yanfang P. , Griffis Eric , Nowell Cameron J. , James Brian , Alarcon Suzie , Malhotra Atul , Gearing Linden J. , Hertzog Paul J. , Galapate Cheska M. , Galenkamp Koen M. O. , Commisso Cosimo , Smith Davey M. , Sun Xin , Carlin Aaron F. , Sidman Richard L. , Croker Ben A. , Snyder Evan Y.
Published: July 2024

The prevalence of “long COVID” is just one of the conundrums highlighting how little we know about the lung’s response to viral infection, particularly to syndromecoronavirus-2 (SARS-CoV-2), for which the lung is the point of entry. We used an in vitro human lung system to enable a prospective, unbiased, sequential single-cell level analysis of pulmonary cell responses to infection by multiple SARS-CoV-2 strains. Starting with human induced pluripotent stem cells and emulating lung organogenesis, we generated and infected three-dimensional, multi-cell-type-containing lung organoids (LOs) and gained several unexpected insights. First, SARS-CoV-2 tropism is much broader than previously believed: Many lung cell types are infectable, if not through a canonical receptor-mediated route (e.g., via Angiotensin-converting encyme 2(ACE2)) then via a noncanonical “backdoor” route (via macropinocytosis, a form of endocytosis). Food and Drug Administration (FDA)-approved endocytosis blockers can abrogate such entry, suggesting adjunctive therapies. Regardless of the route of entry, the virus triggers a lung-autonomous, pulmonary epithelial cell–intrinsic, innate immune response involving interferons and cytokine/chemokine production in the absence of hematopoietic derivatives. The virus can spread rapidly throughout human LOs resulting in mitochondrial apoptosis mediated by the prosurvival protein Bcl-xL. This host cytopathic response to the virus may help explain persistent inflammatory signatures in a dysfunctional pulmonary environment of long COVID. The host response to the virus is, in significant part, dependent on pulmonary Surfactant Protein-B, which plays an unanticipated role in signal transduction, viral resistance, dampening of systemic inflammatory cytokine production, and minimizing apoptosis. Exogenous surfactant, in fact, can be broadly therapeutic.
Haploinsufficiency in PTPN2 leads to early-onset systemic autoimmunity from Evans syndrome to lupus
Authors: Jeanpierre Marie , Cognard Jade , Tusseau Maud , Riller Quentin , Bui Linh-Chi , Berthelet Jérémy , Laurent Audrey , Crickx Etienne , Parlato Marianna , Stolzenberg Marie-Claude , Suarez Felipe , Leverger Guy , Aladjidi Nathalie , Collardeau-Frachon Sophie , Pietrement Christine , Malphettes Marion , Froissart Antoine , Bole-Feysot Christine , Cagnard Nicolas , Rodrigues Lima Fernando , Walzer Thierry , Rieux-Laucat Frédéric , Belot Alexandre , Mathieu Anne-Laure
Published: July 2024

An exome sequencing strategy employed to identify pathogenic variants in patients with pediatric-onset systemic lupus or Evans syndrome resulted in the discovery of six novel monoallelic mutations in PTPN2. PTPN2 is a phosphatase that acts as an essential negative regulator of the JAK/STAT pathways. All mutations led to a loss of PTPN2 regulatory function as evidenced by in vitro assays and by hyperproliferation of patients’ T cells. Furthermore, patients exhibited high serum levels of inflammatory cytokines, mimicking the profile observed in individuals with gain-of-function mutations in STAT factors. Flow cytometry analysis of patients’ blood cells revealed typical alterations associated with autoimmunity and all patients presented with autoantibodies. These findings further supported the notion that a loss of function in negative regulators of cytokine pathways can lead to a broad spectrum of autoimmune manifestations and that PTPN2 along with SOCS1 haploinsufficiency constitute a new group of monogenic autoimmune diseases that can benefit from targeted therapy.
Numerical relativity multimodal waveforms using absorbing boundary conditions
Authors: Buchman Luisa T , Duez Matthew D , Morales Marlo , Scheel Mark A , Kostersitz Tim M , Evans Andrew M , Mitman Keefe
Published: July 2024

Errors due to imperfect boundary conditions in numerical relativity simulations of binary black holes (BBHs) can produce unphysical reflections of gravitational waves which compromise the accuracy of waveform predictions, especially for subdominant modes. A system of higher order absorbing boundary conditions which greatly reduces this problem was introduced in earlier work (Buchman and Sarbach 2006 Class. Quantum Grav.
23 6709). In this paper, we devise two new implementations of this boundary condition system in the Spectral Einstein Code (SpEC), and test them in both linear multipolar gravitational wave and inspiralling mass ratio 7:1 BBH simulations. One of our implementations in particular is shown to be extremely robust and to produce accuracy superior to the standard freezing-Ψ0 boundary condition usually used by SpEC.
Ab initio study of helium behavior near stacking faults in 3C-SiC
Authors: Wang Rongshan , Zhang Limin , Jiang Weilin , Daghbouj Nabil , Polcar Tomas , Ejaz Ahsan , Wang Zhiqiang , Chen Liang , Wang Tieshan
Published: July 2024

First-principles calculations are used to investigate the effects of stacking faults (SFs) on helium trapping and diffusion in cubic silicon carbon (3C-SiC). Both extrinsic and intrinsic SFs in 3C-SiC create a hexagonal stacking sequence. The hexagonal structure is found to be a strong sink of a helium interstitial. Compared to perfect 3C-SiC, the energy barriers for helium migration near the SFs increase significantly, leading to predominant helium diffusion between the SFs in two dimensions. This facilitates the migration of helium towards interface traps, as confirmed by previous experimental reports on the nanocrystalline 3C-SiC containing a high density of SFs. This study also reveals that the formation of helium interstitial clusters near the SFs is not energetically favored. The findings from this study enhance our comprehension of helium behavior in faulted 3C-SiC, offering valuable insights for the design of helium-tolerant SiC materials intended for reactor applications.
Hydrodynamics of a disk in a thin film of weakly nematic fluid subject to linear friction
Authors: Daddi-Moussa-Ider Abdallah , Tjhung Elsen , Richter Thomas , Menzel Andreas M
Published: July 2024

To make progress towards the development of a theory on the motion of inclusions in thin structured films and membranes, we here consider as an initial step a circular disk in a two-dimensional, uniaxially anisotropic fluid layer. We assume overdamped dynamics, incompressibility of the fluid, and global alignment of the axis of anisotropy. Motion within this layer is affected by additional linear friction with the environment, for instance, a supporting substrate. We investigate the induced flows in the fluid when the disk is translated parallel or perpendicular to the direction of anisotropy. Moreover, expressions for corresponding mobilities and resistance coefficients of the disk are derived. Our results are obtained within the framework of a perturbative expansion in the parameters that quantify the anisotropy of the fluid. Good agreement is found for moderate anisotropy when compared to associated results from finite-element simulations. At pronounced anisotropy, the induced flow fields are still predicted qualitatively correctly by the perturbative theory, although quantitative deviations arise. We hope to stimulate with our investigations corresponding experimental analyses, for example, concerning fluid flows in anisotropic thin films on uniaxially rubbed supporting substrates.
Demonstrating beat phenomenon and Lissajous figures with hard disk drive voice-coil motors
Authors: Hu Lian
Published: July 2024

Voice coil motors (VCMs) in mechanical hard disk drives can be used as the adjustable-electric tuning fork driven by alternating signals due to their unique structure and movement. The VCM component is modified to pull the laser or mirror for phase-adjustable simple harmonic motion (SHM). Lissajous experiments using the traditional tuning fork for active vibration can be achieved by VCMs with the help of a laser and a scrollable phosphorescent screen. The demonstrations of beat and Lissajous figures with the double oscillating mirrors method are analysed. The VCM can not only drive the mirror but also drive the laser or another VCM component. Based on this carrying capacity, the demonstration method of a single oscillating mirror has been proposed. Furthermore, one VCM can support another with a laser, which will exhibit the composition of two rotary SHMs more intuitively. The new method is beneficial for students to understand and practice the composition of SHMs from a new perspective.
Unpacking the factors that influence secondary students’ attitudes towards physics in nine different countries - a cross-cultural analysis
Authors: Pongsophon Pongprapan
Published: July 2024

It is crucial to comprehend the factors that affect attitudes towards physics to improve academic performance in the subject. This research aims to identify significant predictors of these attitudes by analysing the Trends in International Mathematics and Science Study Advanced 2015 data from nine countries: the USA, Italy, Lebanon, Norway, Portugal, Russia, Slovenia, Sweden, and France. The study employs multiple regression analyses to examine the influence of predictive variables on students’ attitudes toward physics, taking into account weighting features a large-scale survey. The findings suggest that there are significant differences across cultures. In all the countries surveyed, female students appear to have a less favourable attitude toward physics than male students, making gender a significant factor. In most countries, students who spend more time on physics homework have a more positive attitude, highlighting the importance of outside-of-class engagement. The perception of engaging teaching and the value that students place on physics are solid and positive determinants of attitudes, emphasizing the role of instructional quality and relevance of the subject matter. These findings provide a better understanding of how different factors contribute to students’ attitudes toward physics and can help design targeted educational interventions.
Extracting actigraphy-based walking features with structured functional principal components
Authors: Werkmann Verena , Glynn Nancy W , Harezlak Jaroslaw
Published: July 2024

Objective. We extract walking features from raw accelerometry data while accounting for varying cadence and commonality of features among subjects. Walking is the most performed type of physical activity. Thus, we explore if an individual’s physical health is related to these walking features. Approach. We use data collected using ActiGraph GT3X+ devices (sampling rate = 80 Hz) as part of the developmental epidemiologic cohort study, I = 48, age =

78.7
±
5.7

years, 45.8% women. We apply structured functional principal component analysis (SFPCA) to extract features from walking signals on both, the subject-specific and the subject-spectrum-specific level of a fast-paced 400 m walk, an indicator of aerobic fitness in older adults. We also use the subject-specific level feature scores to study their associations with age and physical performance measures. Specifically, we transform the raw data into the frequency domain by applying local Fast Fourier Transform to obtain the walking spectra. SFPCA decomposes these spectra into easily interpretable walking features expressed as cadence and acceleration, which can be related to physical performance. Main results. We found that five subject-specific and 19 subject-spectrum-specific level features explained more than 85% of their respective level variation, thus significantly reducing the complexity of the data. Our results show that 54% of the total data variation arises at the subject-specific and 46% at the subject-spectrum-specific level. Moreover, we found that higher acceleration magnitude at the cadence was associated with younger age, lower BMI, faster average cadence and higher short physical performance battery scores. Lower acceleration magnitude at the cadence and higher acceleration magnitude at cadence multiples 2.5 and 3.5 are related to older age and higher blood pressure. Significance. SFPCA extracted subject-specific level empirical walking features which were meaningfully associated with several health indicators and younger age. Thus, an individual’s walking pattern could shed light on subclinical stages of somatic diseases.
Study of atoms and multiply charged ions features in the nanosecond laser produced Mo plasma in vacuum using optical emission spectroscopy and time-of-flight electrostatic energy analyzer
Authors: Li Yu , Wu Ding , Wang Xinyue , Hu Xiaohan , Xu Ke , Wu Huace , Hai Ran , Li Cong , Feng Chunlei , Ding Hongbin
Published: July 2024

The species including atoms and multiply charged ions in the laser produced molybdenum (Mo) plasma are investigated in this work using optical emission spectroscopy and time-of-flight electrostatic energy analyzer (TOF-EEA). Nanosecond laser (5 ns, 1064 nm,) pulses were focused on the Mo target surface with a spot size of 0.4 mm2, energy of ∼150 mJ/pulse (corresponding to a power density of ∼7.5 GW cm−2) to generate the Mo plasma in vacuum environment. Time-resolved spectral analysis was carried out to investigate the temporal evolution of continuous background, atomic, and monovalent ionic spectral signals. The Saha–Boltzmann method is applied for spectral fitting, providing insight into the temporal evolution of electron temperature (T
e) and electron density (n
e). Over the time from 40 ns to 500 ns, the T
e decreases from 3.6 eV to 0.52 eV, and the n
e decreases from 2.5 × 1020 cm−3–1.0 × 1015 cm−3. Linear fitting extrapolation predicts the T
e and n
e could be even up to 6.3 eV and 2.5 × 1022 cm−3, respectively, at the early stage of 10 ns. This indicates the generation of multiply charged ions during the laser ablation process. The multiply charged ions up to 6 charge states were observed by the TOF-EEA and the energy distributions for the different charged ions were also obtained. It was found the ion kinetic energy is positively related to the number of charge state indicates the existence of acceleration electric field. The equivalent accelerating potential is determined as approximately 570 V at the current laser power density. This research provides a significant reference for the establishment of models for laser ablation plasmas and a profound understanding of the underlying physical processes.
Photon discerner: adaptive quantum optical sensing near the shot noise limit
Authors: Bao Fanglin , Bauer Leif , López Adrián E Rubio , Yang Ziyi , Wang Xueji , Jacob Zubin
Published: July 2024

Photon statistics of an optical field can be used for quantum optical sensing in low light level scenarios free of bulky optical components. However, photon-number-resolving detection to unravel the photon statistics is challenging. Here, we propose a novel detection approach, that we call ‘photon discerning’, which uses adaptive photon thresholding for photon statistical estimation without recording exact photon numbers. Our photon discerner is motivated by the field of neural networks where tunable thresholds have proven efficient for information extraction in machine learning tasks. The photon discerner maximizes Fisher information per photon by iteratively choosing the optimal threshold in real-time to approach the shot noise limit. Our proposed scheme of adaptive photon thresholding leads to unique remote-sensing applications of quantum degree of linear polarization camera and quantum LiDAR. We investigate optimal thresholds and show that the optimal photon threshold can be counter-intuitive (not equal to 1) even for weak signals (mean photon number much less than 1), due to the photon bunching effect. We also put forth a superconducting nanowire realization of the photon discerner which can be experimentally implemented in the near-term. We show that the adaptivity of our photon discerner enables it to beat realistic photon-number-resolving detectors with limited photon-number resolution in certain applications. Our work suggests a new class of detectors for information-theory driven, compact, and learning-based quantum optical sensing.
Conceptional proposal of a microwave-only quantum magnetic head by phase-induced tunneling magnetoresistance effects and of a 3-dimensional multilayer platter
Authors: Fujii Genji
Published: July 2024

Tunneling magnetoresistance effects result in a high-performance magnetic head, enabling a high magnetic domain density in a platter. This conventional method of using magnetic flux to read or write is close to the magnetic domain density limit. Herein, we propose a conceptional method for developing a magnetic head by controlling phase-induced tunneling magnetoresistance effects. The developed magnetic head can be read out in units of 1 qubit. However, because recording data per BEC qubit is difficult due to thermal fluctuations, we evaluated the robustness of the method and concluded that it is robust to bit flips. Our method does not use a magnetic field for reading or writing, further suggesting that one may use a microwave instead. This is a distinguishing feature, allowing further integration of the magnetic domain density in a platter.
Light-field modulation and optimization near metal nanostructures utilizing spatial light modulators
Authors: Cao 曹 Zini 子倪 , Lin 林 Hai 海 , Cheng 程 Yuqing 宇清 , Xu 徐 Yixuan 艺轩 , Gong 龚 Qihuang 旗煌 , Lü 吕 Guowei 国伟
Published: July 2024

Plasmonic modes within metal nanostructures play a pivotal role in various nanophotonic applications. However, a significant challenge arises from the fixed shapes of nanostructures post-fabrication, resulting in limited modes under ordinary illumination. A promising solution lies in far-field control facilitated by spatial light modulators (SLMs), which enable on-site, real-time, and non-destructive manipulation of plasmon excitation. Through the robust modulation of the incident light using SLMs, this approach enables the generation, optimization, and dynamic control of surface plasmon polariton (SPP) and localized surface plasmon (LSP) modes. The versatility of this technique introduces a rich array of tunable degrees of freedom to plasmon-enhanced spectroscopy, offering novel approaches for signal optimization and functional expansion in this field. This paper provides a comprehensive review of the generation and modulation of SPP and LSP modes through far-field control with SLMs and highlights the diverse applications of this optical technology in plasmon-enhanced spectroscopy.
Warm inflation triggered by entropies of some recent dark energy models within
gravity
Authors: Saleem Rabia , Rasool Muhammad Hamza , Aslam M. Israr , Shahid Iqra
Published: July 2024

This manuscript aims to study cosmic warm inflation (WI) in the framework of

- gravity, where Q represents the nonmetricity (NM) scalar. To accomplish this task, we introduce the Tsallis, Renyi, and Barrow holographic dark energy (HDE) entropies into the standard Friedmann equations. Utilizing the slow-roll (SR) approximation, we find exact analytic solutions for the inflaton field, the effective potential necessary to produce inflation, and the scale factor for both low- and high-dissipative regimes. We calculate key parameters, including SR parameters, the number of e-folds, the scalar spectral index and its running, and finally tensor-to-scalar ratio to assess the accuracy of the chosen DE models in light of the published observational data. The allowed ranges of the involved free parameters are found from the limits on inflationary observables imposed by the Planck data. It is concluded that the obtained results are consistent with proposed theoretical predictions up to the

confidence level.
Tidal force effects and bound orbits in null naked singularity spacetime
Authors: Madan Siddharth , Bambhaniya Parth
Published: July 2024

Naked singularities form during the gravitational collapse of inhomogeneous matter clouds. The final nature of the singularity depends on the initial conditions of the matter properties and types of matter profiles. These naked singularities can also be divided into two types: null-like and timelike singularities. The spacelike singularity of the Schwarzschild black hole can be distinguished from the null and timelike naked singularity spacetimes. In light of this, we investigate the precession of timelike bound orbits in the null naked singularity spacetime, as well as tidal force effects and geodesic deviation features. As a result, we find that the orbital precession of the timelike bound orbits in null naked singularity spacetime could be distinguished from the Schwarzschild precession case. The radial component of the tidal force has an intriguing profile, whereas the angular component has a profile that is comparable to that of a Schwarzschild black hole scenario. The geodesic deviation equation is then solved numerically, yielding results that resemble Schwarzschild black holes. These characteristic features can then be used to discern among these singularities.
Radiative leptonic decay of heavy quarkonia*
Authors: Pei 裴 Junle 俊乐 , Lou 娄 Xinchou 辛丑 , Fang 方 Yaquan 亚泉 , Wu 吴 Jinfei 金飞 , Ruan 阮 Manqi 曼奇
Published: July 2024

In this study, the properties of heavy quarkonia X are examined by treating them as bound states of Q and

at the leading-order level within the non-relativistic quantum chromodynamics (NRQCD) framework, where Q represents either a charm or bottom quark. The branching ratios for the radiative leptonic decays

are revisited, and the angular and energy/momentum distributions of the final state particles are analyzed in the rest frame of X. Furthermore, we apply Lorentz transformations from the rest frame of X to the center-of-mass frame of

to establish the connection between the widths

and

. The comparison of the connection to those documented in literature (divided by

) for various X states, such as

,

,

, and

, shows relative differences typically around or below 10%, comparable to the next-to-leading order corrections of

and

. However, we observe a significant disparity in the ratio between

and

, with our prediction being four times larger than those in literature. The outcomes derived from this study have practical implications in describing the quantum electrodynamics radiative processes and contribute to the investigation of QCD processes associated with the decays of heavy quarkonia and searches for new physics.
Corrigendum: Tritium burn efficiency in deuterium–tritium magnetic fusion (2023 Nucl. Fusion 63 126019)
Authors: Whyte D.G. , Delaporte-Mathurin R. , Ferry S.E. , Meschini S.
Published: July 2024

The controlling parameters regarding tritium burn efficiency (TBE) are derived from first principles and shown to depend fundamentally on the permitted He gas fraction in the divertor and effective pumping speeds of He ash and unburned hydrogenic fuel. The analysis is generic to any equilibrated magnet fusion plasma using a divertor for particle exhaust. The He gas fraction in the plasma limits the maximum TBE due to the link between ash dilution effects in the core plasma and fusion performance. High TBE in magnetic fusion devices is counter-correlated to achieving high gain and power density for commercial fusion. The impact of TBE on fusion performance for several figures of merit are derived, including power density, required

n
−

τ
e

product, and plasma energy gain

Q

p

. The TBE formulation presented here is applied to existing devices, based on published data of enrichment and

τ

He

∗

from research tokamaks. This assessment strongly motivates exploration of technologies that would enhance the effective pumping speed of He to fuel out of the plasma.
A Enhancing Data Security Solutions for Smart Energy Systems in IoT-Enabled Cloud Computing Environments through Lightweight Cryptographic Techniques
Authors: Naga Rani Bandaru Venkata , Gayatri Sarman Kaligotla V S H , Dhana Satya Prathap Varma Uddarraju , Prasadaraju Kantheti , Sugumaran S
Published: July 2024

There are chances for creative applications when Internet of Things (IoT) devices are integrated with cloud computing (CC) settings, but there are also privacy and data security concerns. In order to overcome these issues, this research suggests lightweight cryptographic methods designed specifically for IoT-enabled CC systems. The limited resources of Internet of Things devices make typical encryption techniques unfeasible. Our goal is to provide efficient, low-resource, secure data transmission techniques using lightweight cryptography between Internet of Things devices and the cloud. These methods are intended to protect confidentiality and integrity, which are necessary for safe protocols of communication in Internet of Things contexts. We suggest combining the 98% processing efficiency of SIMON, a lightweight encryption, with current CC security systems like block chain. By protecting sensitive data without taxing IoT device resources, this integration improves data integrity and accountability. Our method promotes strong data protection in IoT-enabled CC situations by striking a balance between efficiency and security, guaranteeing the longevity and dependability of smart energy systems. IoT-based sustainable smart energy systems employ networked devices to minimize environmental impact, maximize renewable energy sources, and effectively control energy usage. These systems can include energy monitoring devices that track use in real time, smart appliances that modify their operation based on energy availability and cost, and smart grids that balance supply and demand. We can increase the utilization of renewable resources and reduce waste by incorporating IoT technologies into energy infrastructure.
Conservation of the Alaban tree (Vitex pinnata L) in the coastal landscapes at Banyak Island, Aceh Province
Authors: Lubis T , Sibarani R , Amalia  , Junaidi  , Abus A A , Abus A F
Published: July 2024

The diversity of coastal vegetation on Banyak Island is differentiated from the diversity of vegetation in other areas based on its characteristics. The Alaban tree (Vitex pinnata L), which grows abundantly along the coast of Banyak Island, is one example. As the primary raw material for making ships and ship accessories, the Alaban tree is famous among fishermen who live in Haloban. On this basis, the Alaban tree’s status as a plant creates sustainable development. By examining the cultural perspectives and experiences of the Haloban ethnic group, this research seeks to understand smart people and their local indigenous of the formation of the coastal landscape ecosystem on Banyak Island. The cultural significance of the Haloban community in the coastal landscape ecosystem of Banyak Island has a significant influence on the long-term survival of Alaban trees, according to the findings of this study. This coastal landscape ecosystem is very stable and can provide food for humans indefinitely. This landscape is formed by community involvement and perspectives shaped by indigenous culture. This consists of local wisdom and practices continuously observed in everyday life.
Waste Bank management as an alternative community-based waste management strategy in Langsa City, Aceh Province
Authors: Abus N A A , Suriadi A , Lubis T , Abus A A , Abus A F
Published: July 2024

Garbage is an inseparable component of daily existence; waste is generated from conception to mortality, and each stage of life affects the environment. Ensuring that citizens are knowledgeable and proficient in waste management through applying the 4R concept (Reduce, Reuse, Recycle, and Replant) is crucial for addressing waste issues via source-reduction waste management. Capital Waste Bank is a social based management of regional waste, namely the construction of forts. One of them concerns environmental problems in urban areas which are very vulnerable to various types of damage, such as rubbish. One effort to improve the quality of the urban environment is the Smart Environment concept. Engaging in dialogue with community members and providing counseling, education, and training in emancipatory participation methods (communication and interaction) to empower citizens. Waste Bank has initiated a waste management socialization initiative in Langsa City to achieve zero emissions for the city and promote environmental health that is clearer, greener, more comfortable, and healthier. Integrated waste management can also inspire innovation and creativity within the community, thereby contributing to the general welfare of the populace.
11-Level Cascaded half-bridge Multilevel inverter with Capacitor Switched Technology for Photovoltaic Systems
Authors: Palleswari Y. T. R. , Siva A. , Kalyan Sagar K. , Ramu B. , Deenakonda Mamatha , Vijetha Inti V. V.
Published: July 2024

Power generation through PV is a promising alternative energy source for meeting power demand as it is environmentally friendly, abundantly available, and has alternative characteristics. In power generation through photovoltaic, multilevel inverters are vital in the conversion of power. The primary objective of this paper is analysing the cascaded half-bridge multilevel inverter (CHMLI) at different load conditions. The secondary objective of this paper aims to implement the CHMLI for a photovoltaic system and to observe the proposed system can able to export the generated PV power to the load. To extract maximum power from the solar source, a Perturb and Observe (P & O) implemented on conventional boost converter. MATLAB/Simulink presents the performance of the proposed converter in terms of reduced component count, THD, and performance of the converter with solar PV under various irradiation conditions.
A Modified VIRT with Planar Transformer for Energy-Saving Applications
Authors: Anandh B , Ramesh Naicker Aabhishek , Jayanth S K , Mohana Sundaram N
Published: July 2024

Electric circuit converters are mostly used in the conversion of power sources from AC to DC or from DC to AC. These are done with inverters and rectifiers in the current electrical systems. There is no unique concept or integrated system to maintain all these conversions in a single concept. It requires more space and high losses of supply due to major conversions. The VIRT is the model where all the converters, like rectifiers and inverters, are commonly housed in a single box and do all the work of the inverter and rectifier. The VIRT (Variable-Inverter-Rectifier-Transformer) is used to reduce the required space for conversion and reduce the required energy losses. The specialty of the conversion is done with the planar transformer instead of the regular coiled transformer; it generally works in the partial-turn ratio method. These partial turns are used for variable AC-to-AC conversions. The VIRT can be used as a replacement for electric vehicle chargers and UPS systems. It provides precious control over the conversion and utilization of the rectifier and inverter. The planar transformer plays a major role as it neglects the magnetic flux of a regular coiled transformer. The existing coiled transformer with a planar transformer to reduce the space requirement and losses.
Research on dynamic positioning of navigation system using K nearest neighbor algorithm and bayesian fusion based on visible light communication
Authors: Wang Jiaan , Gu Siwen , Zhang Siqi , Wu Linghao , Sun Shiwen
Published: July 2024

This study presents a novel Bayesian-K Nearest Neighbor (B-KNN) fusion algorithm aimed at mitigating dynamic positioning errors in navigation systems that utilize visible light communication. The proposed fusion methodology leverages a fingerprint database constructed from the received signal strength data acquired by a mobile receiver. Through the selection of the nearest navigation path points for clustering and the utilization of a Bayesian algorithm with Gaussian fitting, the posterior probability of each cluster is computed to facilitate the prediction of the location of navigation path points via fingerprint matching. The results indicate that 89.8% of simulations exhibit a dynamic positioning error below 1 m within a

20 m

×

5 m

×
4

 m

model, achieving a success rate of 89.8%. Comparative analysis reveals that the B-KNN fusion algorithm enhances dynamic positioning accuracy by 68.3% while reducing computational overhead by approximately 48.3% in contrast to conventional KNN algorithms. Experimental assessments demonstrate that in scenarios involving ambient light interference within a

2 m

×
1

 m

×
1.5

 m

model, the majority (95%) of dynamic positioning errors exceed 9 cm, with a significant portion surpassing 10 cm. Conversely, under conditions devoid of ambient light interference, only 4% of errors exceed 9 cm, with 14% falling below 5 cm, indicative of a marked 39.81% improvement in accuracy.
Effect of T6I6 tempering on the coherence between core/shell precipitates and a solid solution in the 2024 aluminium alloy
Authors: Stegliński M , Petrova A N , Brodova I G , Adamczyk-Cieślak B
Published: July 2024

Heat treatment of materials, including—in particular—two-stage T6I6 treatment, enables the nucleation of precipitates with a two-phase structure: core and shell. The above-mentioned treatment can be used to harden materials by selecting suitable treatment parameters and the chemical composition of the material that initiates a selective diffusion of the alloying elements. In this paper, tests of the T6I6 treatment were carried out on the EN AW-2024 alloy. The aluminium alloy was subjected to T6I6 treatment, and then the element distribution map was examined within the precipitate using the EDS method. The mechanical properties of the precipitate were tested using the nanoindentation method, and the kinetics of the formation of the precipitate were analysed using DSC. The impact of two-phase precipitates on the mechanical properties was determined through a static strength test, whereas the impact of the structure on the above-mentioned mechanical properties was determined based on HR-TEM observations. The results of the study confirmed the formation of a precipitate with a two-phase structure (shell; core) in the EN AW-2024 alloy, as well as the kinetics of their formation as a function of the parameters of the T6I6 process, such as temperature, duration and cooling rate. Strength tests confirmed an increase in the strength of the alloy to Rm = 520 MPa, with elongation remaining the same at A = 13.2%. HR-TEM observations, in turn, proved that the shell forming on the core is coherent with solid solution α, which means that the hardening of the alloy may occur as a sum of the Mott-Nabarro, Friedel and Ashby-Orowan mechanisms.
An improved clock synchronization model for typical IoT applications
Authors: Upadhyay Divya , Dubey Ashwani Kumar
Published: July 2024

In today’s scenario, the Internet of Things (IoT) has transformed people’s lives by enabling data exchange among pervasive devices in various applications. However, clock synchronization is essential to ensure seamless transmission and synchronization among IoT entities involved in processing and communication. This paper proposes a clock synchronization algorithm based on linear-quadratic regression (LQR) to address synchronization-errors in IoT applications. The algorithm uses a linear model of skew and offsets to estimate clock parameters, and performance is evaluated in terms of R-square error (RSE) and Root Mean Square Error (RMSE). Our proposed algorithm outperformed traditional algorithms with an R-Square Error of 0.71% and RMSE of 0.379%. This paper also evaluated the stability of the proposed model using the correlation coefficient, which indicated a high correlation among the variables at 86%. The results below demonstrate the proposed algorithm’s effectiveness and goodness of fit in addressing clock synchronization errors for IoT applications.
Prediction and modelling marshall stability of modified reclaimed asphalt pavement with rejuvenators using latest machine learning techniques
Authors: Ayazi Mohammad Farhad , Singh Maninder , Kumar Rajiv
Published: July 2024

The primary problem with the experimental evaluation of Marshall stability (MS) of reclaimed asphalt pavement (RAP) is the inherent complexity and variability involved in the process. Traditional experimental methods for predicting MS can be time-consuming, labor-intensive, and costly. In the present research, an effort has been made to assess the most appropriate machine learning model for the prediction of MS of RAP. The study addresses the problem of accurately predicting MS by using a variety of input parameters derived from experimental work. The data for models was split in 7:3 for training and testing of models. Bitumen content (BC %), virgin binder percentage (VB %), virgin binder performance grade (VB-PG), RAP percentage (RAP %), RAP binder percentage (RAPB %), RAP binder PG (RAPB-PG), rejuvenator type (Rej type) and rejuvenator percentage (Rej %) were applied as input parameters for MS prediction. Several machine learning models including random tree (RT), M5P, Gaussian process (GP), support vector machine (SVM), and random forest (RF) were utilized for determining the most appropriate prediction model. Seven metrics were used for assessing the performance of these models, such as CC, MAE, RMSE, RA, RRSE, WI, and NSE. Based upon these metrics, the RF model is found to outperform the other applied models with the values of CC = 0.9959 and 0.9763, MAE = 0.3129 and 0.7847, RMSE = 0.3976 and 1.0492, RAE = 9.0062 and 21.8247, RRSE = 9.3624 and 23.6832, WI = 0.998 and 0.984 and NSE = 0.991 and 0.944 for training and testing stages, respectively. Also, box plots and sensitivity analysis confirm the superiority of the RF model over other models. Finally, the sensitivity analysis suggests the importance of bitumen content in the prediction of MS of reclaimed asphalt pavement modified with rejuvenators.
Computation of the least primitive root
Authors: McGown Kevin , Sorenson Jonathan
Published: July 2024

Let

g
(
p
)

g(p)

denote the least primitive root modulo

p
p

, and

h
(
p
)

h(p)

the least primitive root modulo

p
2

p^2

. We computed

g
(
p
)

g(p)

and

h
(
p
)

h(p)

for all primes

p
≤

10

16

p\le 10^{16}

. As a consequence we are able to prove that

g
(
p
)
>

p

5

/

8

g(p)>p^{5/8}

for all primes

p
>
3

p>3

and that

h
(
p
)
>

p

2

/

3

h(p)>p^{2/3}

for all primes

p
p

. More generally, we provide values of

p
α

p_\alpha

where

g
(
p
)
>

p
α

g(p)>p^\alpha

when

p
>

p
α

p>p_\alpha

, for various values of

α
\alpha

with

1

/

2
>
α
>
5

/

8

1/2>\alpha >5/8

. Additionally, we give a log-histogram of

g
(
p
)

g(p)

when

g
(
p
)
≥
100

g(p)\ge 100

and empirical evidence that

g
(
p
)
≪
(
log
⁡
p
)
(
log
⁡
log
⁡
p

)
2

g(p)\ll (\log p)(\log \log p)^2

.
Intersection graph and writhe polynomial
Authors: Cheng Zhiyun
Published: July 2024

We prove that two virtual knots have equivalent intersection graphs if and only if they have the same writhe polynomial.
On random polynomials with an intermediate number of real roots
Authors: Michelen Marcus , O’Rourke Sean
Published: July 2024

For each

α
∈
(
0
,
1
)

\alpha \in (0, 1)

, we construct a bounded monotone deterministic sequence

(

c
k

)

k
⩾
0

(c_k)_{k \geqslant 0}

of real numbers so that the number of real roots of the random polynomial

f
n

(
z
)
=

∑

k
=
0

n

c
k

ε
k

z
k

f_n(z) = \sum _{k=0}^n c_k \varepsilon _k z^k

is

n

α
+
o
(
1
)

n^{\alpha + o(1)}

with probability tending to one as the degree

n
n

tends to infinity, where

(

ε
k

)

(\varepsilon _k)

is a sequence of i.i.d. (real) random variables of finite mean satisfying a mild anti-concentration assumption. In particular, this includes the case when

(

ε
k

)

(\varepsilon _k)

is a sequence of i.i.d. standard Gaussian or Rademacher random variables. This result confirms a conjecture of O. Nguyen from 2019. More generally, our main results also describe several statistical properties for the number of real roots of

f
n

f_n

, including the asymptotic behavior of the variance and a central limit theorem.
A note on the expectation of zeros of random harmonic polynomials: The Kac model
Authors: Lu Dawei , Wang Yuchen
Published: July 2024

Motivated by the questions posed by W. V. Li and A. Wei [Proc. Amer. Math. Soc. 137 (2009), pp. 195–204] and the conjecture of E. Lundberg and A. Thomack [On the average number of zeros of random harmonic polynomials with iid coefficients: precise asymptotics, Preprint, https://arxiv.org/ abs/2308.10333, 2023], we study the expected number of zeros of random harmonic polynomials

H

n
,
m

(
z
)
=

p

n

(
z
)
+

q

m

(
z
)

¯

H_{n,m}(z)= p_{n}(z)+\overline {q_{m}(z)}

with independently and identically distributed Gaussian coefficients. In this paper we verify the conjecture of E. Lundberg and A. Thomack that the expectation is

O
(
n
)

O(n)

when

deg
⁡
p
=
α
deg
⁡
q

\deg p = \alpha \deg q

, where

0
≤
α
>
1

0\leq \alpha >1

. This result extends the previous estimates when

m
m

is a fixed constant or

m
=
n

m=n

to more general case.