bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling memory function of entangled photon and classical laser photon-count fluctuations using white noise integral analysis
Authors: Tey Lian Seng , Muniandy S V , Chong Wu Yi
Published: December 2024

This study investigates photon-count fluctuation dynamics of two light sources, namely a spontaneous parametric down-conversion (SPDC) light source and a 780 nm attenuated laser diode (LD). White noise integral with customizable memory function is used to model the mean square displacements (MSDs) and the probability density functions (PDFs) for both light sources. This approach overcomes the limitation of monofractal scaling of fractional Brownian motion (fBm) model characterized by a single Hurst exponent. The memory function used has an exponential-tempered power-law relation, parametrized by μ and β, where β modulates the extent of memory parameter μ. Although optical losses and detector inefficiencies degrade photon statistics to Poissonian at post-detection, our findings reveal notable memory effects at higher mean photon counts, especially in the SPDC source with memory parameter μ ⪆ 1.00, compared to the classical LD, which remained relatively constant at μ ⪅ 1.00. Both light sources shared similar correction parameters β, which indicates they have identical photon-count fluctuations at short time but diverge significantly at longer time. This work highlights the need for models beyond fBm, capable of capturing complex MSD behaviors of photon-count fluctuations.
Verification of uranium composite materials using active interrogation techniques for safeguards purposes
Authors: Tohamy M
Published: December 2024

This work is intended to verify a combination of a passive non-destructive technique and active neutron interrogation technique to characterize isotopic mass determination, uranium content, and possible enrichment. The interrogated samples were natural uranium (NU), low-enriched uranium (LEU), and depleted uranium (DU) all in the form of uranium dioxide. The emitted photon spectra under both techniques were obtained using a high-efficiency HPGe detector. Improved detector efficiency was obtained using the neural network (NN) method based on the intrinsic calibration data. The obtained enrichment results of passive measurements showed good agreement with certified samples to within 1.12% in the case of LEU, 1.03% in the case of NU, and 1.04% in the case of DU. Active interrogation of the samples was done using the neutron spectrum of a 5 Ci 241Am-Be neutron source. Seven short-lived fission products (FPs) (101Tc, 97Nb, 105Ru, 92Y, 91Sr, 92Sr, and 88Kr) were chosen as indicators to provide a complete characterization of isotopic mass determination, uranium content, and enrichment. Isotopic masses of the samples were calculated using thermal and fast interrogations. A comparison of the obtained results of 238U mass was found to agree within 0.2% with certified value based on fast interrogation, and within 0.3% of 235U mass based on thermal interrogation.
Design of spin-orbit controlled plasmonic circuits for selectively transporting photons
Authors: Cai Zimeng , Wu Jing , Zhang Yuhong , Wu Yongfeng , Li Jinhua , Ma Yuan , Ma Youqiao
Published: December 2024

The manipulation of spin-related photons is crucial for developing next-generation integrated circuits. However, the spin-orbit interaction of light is typically very weak at nanoscale due to the diffraction limit. Here, a dielectric-loaded plasmonic nanocircuit is proposed, utilizing a chiral cylindrical structure, to directionally couple and guide plasmonic waves through dual-branch waveguides. Optimized results reveal that the waveguide modes excited by circularly polarized light with different spin states can be selectively coupled to one of the two targeted branch waveguides, with a calculated unidirectional coupling efficiency as high as 0.95. The proposed structure could provide avenues for realizing on-chip integrated nanocircuits and developing advanced multifunctional nanocircuits with enhanced degrees of freedom.
Satellite image encryption using amalgamation of randomized three chaotic maps and DNA encoding
Authors: Dua Mohit , Bhogal Rahul , Dua Shelza , Chakravarty Nidhi
Published: December 2024

In today’s world of critical global connectivity, satellite communication plays a vital role for businesses, governments, and individuals. Key applications, including climate change monitoring, military surveillance, and real-time event broadcasting, heavily rely on transmitting image data rather than text. As a result, ensuring the secure transmission of images through efficient and robust encryption techniques has become a focal point of interest for both academia and industry. Image encryption is essential for securing sensitive visual data, protecting privacy, and making certain that only authorized users are able to access the required content. It prevents unauthorized access, tampering, and misuse of images, which is crucial for confidential and secure communications. The work in this paper develops a satellite image encryption scheme that employs a novel 1D Cosine Sinusoidal Chaotic (1DCSC) map, and two earlier proposed Sine-Tangent Chaotic (STC) and Improved Cosine Fractional Chaotic (ICFCM) maps, in conjunction with Deoxyribonucleic Acid (DNA) operations. The proposed scheme encrypts a given input image in four steps. In the initial step, 384-bit shared key and a 128-bit initial vector are used to create three different keys. In step two, three different chaotic sequences are produced using these keys and 1DCSC, STC, and ICFCM maps. These chaotic sequences chosen randomly to encrypt red, blue or green components of the given input image. In step three, these three chaotic sequences and the three components of the input image are DNA encoded. In the final step, DNA XOR based diffusion operation is applied between these DNA-encoded color image components and DNA encoded chaotic sequences to create green, red, and blue components of the cipher image. The proposed scheme obtains entropy value 7.9997, Unified Average Changing Intensity (UACI) value 33.32, and Number of Pixels Change Rate (NPCR) value 99.67%.
Study on spectral characterization of non-uniform PT symmetry Bragg gratings with duty-cycle modulation
Authors: Chen Ying , Li Mengxi , Shi Moqing , Mao Changhui
Published: December 2024

It is a great challenge to improve the detection efficiency of optical structures. In order to increase the reflection effect of Bragg grating, a non-uniform PT-symmetric Bragg grating structure based on duty cycle modulation is proposed. The grating exhibits PT symmetry by quantum doping technology and is optimized by analyzing the structural parameters which have great influence on the grating. Two methods of Odd-function Duty-cycle Modulation (ODC) and Even-function Duty-cycle Modulation (EDC) are proposed to obtain the non-uniform grating structure under duty cycle modulation. The results show that the reflectivity of the grating is obviously enhanced under odd-function duty cycle modulation. Our method improves the reflection characteristics of the Bragg grating to a great extent, and is conducive to designing more efficient reflectivity detection devices.
CO2 clusters: forming fragile dications in helium nanodroplets
Authors: Foitzik Florian , Ganner Lisa , Bergmeister Stefan , Zappa Fabio , Scheier Paul , Echt Olof , Gruber Elisabeth
Published: December 2024

For many atoms and molecules, small multiply charged clusters are unstable with respect to spontaneous charge separation. When bare CO2 clusters are ionized by electrons, the smallest detected dications contain 43 molecules. The same appearance size has been obtained when neutral CO2 clusters embedded in helium nanodroplets are electron ionized. Here we show that electron ionization of singly charged CO2 clusters solvated in helium nanodroplets drastically lowers the appearance size to n
a = 30. The combination of efficient cooling in superfluid helium, sequential ionization, and gentle collisions of the nanodroplets with helium gas makes it possible to form dications that are barely larger than the Rayleigh limit.
Nonlinear wave-wave interaction of quantized upper hybrid waves with low frequency modes
Authors: Nourina N , Rozina Ch , Iqbal Z , Poedts S , Abbas G
Published: December 2024

The impact of quantized magnetic energy is studied on the nonlinear scattering of quantized upper hybrid waves (QUH) from low-frequency quantized: ion-cyclotron (QIC), Alfvén (QA) and lower hybrid (QLH) waves in strongly magnetized degenerate electron-ion plasmas. The governing differential equations of pump QUH, QIC, QA and QLH wavesare derived in the presence of Landau quantization, symbolized by the parameter ξ. The equations are then Fourier analyzed and the phasor matching technique is applied to study the nonlinear parametric interactions. General dispersion relations are calculated and analyzed further to obtain both three-wave decay and modulational instabilities of the QIC, QA and QLH waves. The analytical results admit that the growth rate of both three-wave decay and the modulated wave packet of QA waves increases as a function of quantized magnetic energy, while the three-wave decay rate of QIC and QLH is found to decrease with the quantized B field. The present findings confirm that the quantized magnetic energy may play a vital role in enhancing the quantized Fermi and Alfvén speeds of plasma particles, hence affecting the associated growth rates of three-wave decay and modulational instabilities are modified significantly. The present findings can be important to understand the features of a quantized magnetic field in strongly magnetized quantum systems, such as neutron stars, magnetars, pulsars, etc.
Mercury’s Meteorite Mysteries: A Directional Statistical Guide to Mercury’s North Pole, Hidden Hazards and Roadmap to Safe Landing Havens Based on Solar Elevation, Ice Stability, Temperature
Authors: Chatterjee Debashis , Ghosh Prithwish
Published: December 2024

Studying meteoroid impact patterns on planetary surfaces is critical for understanding surface dynamics and selecting safe landing sites. Mercury, one of the least explored rocky planets, presents unique challenges due to its extreme temperatures and the angular nature of its surface data. Traditional linear statistical methods are often inadequate for analyzing such directional data. This study introduces a novel approach using directional data analysis techniques to interpret the cyclical nature of meteoroid impact locations on Mercury. We employed Watson’s test, Bayesian Information Criterion scores, and a mixture of von Mises–Fisher distributions to model the distribution of impact craters and solar elevations on Mercury’s surface. Our findings indicate that while location parameters adhere to the von Mises distribution, solar elevations do not exhibit directional distribution characteristics. Additionally, by filtering datasets based on temperature thresholds and crater diameters, we pinpointed areas with a high probability of providing suitable landing surfaces. These insights enhance our understanding of the surface conditions on Mercury and provide valuable groundwork for future exploration missions.
The Impact of Different Effective Models for Star Formation on the Properties of Simulated Milky Way-sized Galaxies
Authors: Wu Yiheng , Springel Volker
Published: December 2024

Hydrodynamical cosmological simulations of galaxy formation such as IllustrisTNG or Auriga have shown considerable success in approximately matching many galaxy properties, but their treatment of the star-forming interstellar medium (ISM) has relied on heuristic sub-grid models. However, recent high-resolution simulations of the ISM that directly resolve the regulation of star formation suggest different mean relations for the dependences of pressure and star formation rate on the average gas density. In this study, we adopt such a modern, physically grounded parameterization inspired by the TIGRESS small-scale simulations. We dub this model TEQS and use it for a detailed comparative analysis of the formation and evolution of a Milky Way-sized galaxy when compared with the widely used TNG model. By employing high-resolution simulations in tall box setups, we first investigate the structural differences expected for these two models when applied to different self-gravitating gas surface densities. Our results indicate that TEQS produces considerably thinner gaseous layers and can be expected to form stellar distributions with smaller scale-height than TNG, especially at higher surface density. To test whether this induces systematic structural differences in cosmological galaxy formation simulations, we carry out zoom-in simulations of 12 galaxies taken from the set of Milky Way-sized galaxies that have been studied in the Auriga project. Comparing results for these galaxies shows that disk galaxies formed with the TEQS model have on average very similar stellar mass but are more concentrated in their central regions and exhibit smaller stellar radii compared to those formed with the TNG model. The differences in the scale-heights of the formed stellar disks are only marginal, however, suggesting that other factors for setting the thickness of the disk are more important than the applied ISM equation-of-state model. Overall, the predicted galaxy structure is quite similar for TNG and TEQS despite significant differences in the employed star formation law, demonstrating that feedback processes are more important in regulating the stellar mass than the precise star formation law itself.
Synthetic conduits efficacy in neural repair: a comparative study of dip-coated polycaprolactone and electrospun polycaprolactone/polyurethane conduits
Authors: Katana Dzana , Jayasinghe Suwan N , Trbojevic Sara , Yin Casey M , Rodgers Vanessa R , Almarza Alejandro J , Marra Kacey G
Published: December 2024

Objectives. Peripheral nerve injuries (PNI) represent the most common type of nervous system injuries, resulting in 5 million injuries per year. Current gold standard, autografts, still carry several limitations, including the inappropriate type, size, and function matches in grafted nerves, lack of autologous donor sites, neuroma formation, and secondary surgery incisions. Polymeric nerve conduits, also known as nerve guides, can help overcome the aforementioned issues that limit nerve recovery and regeneration by reducing tissue fibrosis, misdirection of regenerating axons, and the inability to maintain long- distance axonal growth. Polymer-based double-walled microspheres (DWMSs) are designed to locally and in a sustainable fashion deliver bioactive agents. Lysozyme is a natural antimicrobial protein that shares similar physical and chemical properties to glial cell line-derived neurotrophic factor, making it an ideal surrogate molecule to evaluate the release kinetics of encapsulated bioagent from polymeric biodegradable microspheres embedded in polycaprolactone and polycaprolactone/polyurethane blend nerve conduits. Approach. Lysozyme was encapsulated in poly(lactic-co-glycolic acid)/poly(L-lactide) DWMSs fabricated through a modified water-oil-water emulsion solvent evaporation method. Lysozyme-loaded DWMS were further embedded in PCL and PCL-PU based nerve guides constructed via polymer dip-coating and electrospinning method respectively. Lysozyme DWMS and nerve guides were imaged using scanning electron microscopy (SEM). Released lysozyme concentration was determined by using a colorimetric micro-BCA protein assay and spectrophotometric quantitation. Tensile and suture pull-out tests were utilized to evaluate the mechanical properties of both dip-coated and electrospun nerve guides, embedded and free of lysozyme DWMS. Main results. The study revealed significant distinctions in the lysozyme release profiles, and mechanical properties of the manufactured polymer nerve guides. Both PCL dip-coated and PCL/PU electrospun DWMS-embedded nerve guides revealed biphasic protein release profiles. PCL/PU electrospun and PCL dip-coated nerve guides released 16% and 29% of the total protein concentration within 72 h, plateauing at week 16 and week 8, respectively. SEM analysis of the nerve guides confirmed the homogeneity and integrity of the polymer nerve guides’ structures. The electrospun guides were found to be more flexible with a higher extension under stress bending, while the dip-coated PCL nerve guides displayed more rigid behavior. Significance. This study provides useful insights on how to optimize nerve guide design and fabrication to enhance recovery progress of PNI.
Global analysis of the proposed benefits from REDD+ projects: influencing factors and discrepancies
Authors: Theresia Vania , Atmadja Stibniati Soeria , Lieberherr Eva
Published: December 2024

Reducing emissions from deforestation and forest degradation (REDD+) in developing countries was initially envisioned to incentivize forest protection through payments for ecosystem services (PES). Nevertheless, our global understanding of REDD+ project benefits proposed by proponents to local communities is limited. To address this gap, we ask: globally, how do REDD+ projects propose to provide local community benefits? We use and update the international database on REDD+ projects (ID-RECCO) to analyze the REDD+ benefits proposed by 347 REDD+ projects in 55 countries. Logistic regression and chi-square tests explore relationships between the probability of a benefit type being proposed and the influencing factors. Our global-level analysis can serve as a useful benchmark for empirical case studies. Our findings show the diversity of benefits REDD+ projects propose. Most REDD+ projects (89%) proposed a mix of monetary and non-monetary benefits; employment was proposed in >¾ of the projects, while forest restrictions were proposed in 52% of REDD+ projects. Many projects proposed infrastructure (107) or services (181). Factors that influence the probability a benefit type being proposed by a project include carbon certification standards, de facto forest user types, and country. PES-style conditional payments are no longer emblematic of benefits from REDD+ projects to local communities. Instead, REDD+ projects typically propose employment, livelihood activities, tenure clarification, and public goods and services. Further empirical research is needed to understand how meaningful these benefits are to local people, and their contribution in producing effective and equitable project outcomes. National policy and legal frameworks on benefit sharing, more explicit standards on benefit sharing among carbon standards, and better risk management related to community expectations from REDD+ projects are important avenues to ensure REDD+ benefits are aligned with the needs and realities of local communities.
Spatial heterogeneity and seasonality of phytoplankton responses to marine heatwaves in the Northeast Pacific
Authors: Shen Xinchen , Zhan Weikang , Zhang Ying , He Qingyou , Bo Yingjie , Liu Yunchen , Zhan Haigang
Published: December 2024

Marine heatwaves (MHWs) have emerged as a recurrent phenomenon in the Northeast Pacific (NEP) since 2013, with significant ecological and economic consequences. However, our understanding of the impact of these events on phytoplankton, the primary producers in the marine food web, remains incomplete. In this study, we elucidated the phytoplankton responses during MHWs in the NEP between 1998 and 2022 and revealed contrasting phytoplankton chlorophyll anomalies between the north and south of the Transition Zone Chlorophyll Front (TZCF). Specifically, chlorophyll shows a marked increase north of the TZCF but a decrease south of it, with the most pronounced negative anomalies centered on the TZCF. Additionally, this chlorophyll response exhibits a remarkable seasonality, consistent with the seasonal migration of the TZCF. Weakened subpolar southward Ekman transport, which may have resulted in reduced phytoplankton nutrient supply, is likely to be the major contributor to the negative chlorophyll response in this frontal region. Our results highlight the importance of previously unrecognized spatial and temporal heterogeneity of phytoplankton responses to MHWs in the NEP, which may provide insights for future ecosystem conservation and fisheries management in the NEP under MHWs.
Integrability of generalised skew-symmetric replicator equations via graph embeddings
Authors: Visomirski Matthew , Griffin Christopher
Published: December 2024

It is known that there is a one-to-one mapping between oriented directed graphs and zero-sum replicator dynamics (Lotka–Volterra equations) and that furthermore these dynamics are Hamiltonian in an appropriately defined nonlinear Poisson bracket. In this paper, we investigate the problem of determining whether these dynamics are Liouville–Arnold integrable, building on prior work in graph decloning by Evripidou et al (2022 J. Phys. A: Math. Theor.
55 325201) and graph embedding by Paik and Griffin (2024 Phys. Rev. E 107 L052202). Using the embedding procedure from Paik and Griffin, we show (with certain caveats) that when a graph producing integrable dynamics is embedded in another graph producing integrable dynamics, the resulting graph structure also produces integrable dynamics. We also construct a new family of graph structures that produces integrable dynamics that does not arise either from embeddings or decloning. We use these results, along with numerical methods, to classify the dynamics generated by almost all oriented directed graphs on six vertices, with three hold-out graphs that generate integrable dynamics and are not part of a natural taxonomy arising from known families and graph operations. These hold-out graphs suggest more structure is available to be found. Moreover, the work suggests that oriented directed graphs leading to integrable dynamics may be classifiable in an analogous way to the classification of finite simple groups, creating the possibility that there is a deep connection between integrable dynamics and combinatorial structures in graphs.
Influence of typical technological parameters on the processing quality of laser surface texturing technology for finger sealing
Authors: Chen Lingping , Zhang Yanchao , Chen Guoqiang , Li Jiewei , Zhang Bowei , Wang Mingfeng
Published: December 2024

In recent years, to achieve favorable tribological characteristics, surface texture technology for friction reduction has been extensively studied, and its effectiveness has been successfully validated. The quality of surface texture processing directly impacts the tribological performance of finger seal friction pairs. To investigate the influence of the laser process parameters on the finger seal surface texture of the GH4169 and improve its processability and process predictability, a comparative experiment and analysis involving multiple processing parameters, including the laser power (P), laser frequency (F), scanning speed (V), and scanning times (N), were conducted. To evaluate the quality of laser surface texturing processing technology, four processing morphology parameters were established. Uniform experiments and regression analysis were employed to analyze the influence and synergistic effects of laser processing parameters on processing quality. The research results indicate that laser power, scanning times, and scanning speed are the main process parameters that significantly affect laser surface deformation. The outer diameter is directly proportional to the laser power and inversely proportional to the scanning speed; the bottom diameter ratio is directly proportional to both the laser power and scanning times; and the pit depth initially increases and then decreases with increasing laser power and scanning times. The suitable range of processing parameters is as follows: laser power (10 ∼ 20%), speed range (400 ∼ 700 mm s−1), scanning times (8 ∼ 18 times), and laser frequency (20 ∼ 25 kHz). This research provides theoretical and experimental support for the precise control of surface texture prepared by laser processing of GH4169, laying the foundation for friction and wear tests of textured finger seals.
A comparative analysis of different surface tribological and electrochemical properties of TiAlN, TiAlSiN, and CrAlN thin film coatings in seawater
Authors: Liu Aihua , Wang Yanan , Tian Runzhou , Ge Dongliang , Deng Jianxin
Published: December 2024

To reveal the wear mechanisms of TiAlN, TiAlSiN, and CrAlN coatings in a seawater environment, the changes in frictional surfaces and the electrochemical characteristics of these coatings were compared and analyzed in this paper. The coatings were deposited on 316L stainless steel surfaces. Tribological tests were investigated using a ball-on-disk tribometer with Si3N4 ceramic balls as the counter material. Although the friction coefficient of 316L stainless steel was the lowest at 0.34, the order of wear rates was 316L stainless steel (7.38 × 10−5) > TiAlN(5.31 × 10−6) > TiAlSiN(4.23 × 10−6) > CrAlN(1.10 × 10−6) and the electrochemical protective efficiencies of TiAlSiN and CrAlN were both greater than 97%. Seawater penetrated through the grain boundaries of the TiAlN coating, which led to corrosion and delamination failure. Conversely, the grain refinement in TiAlSiN and CrAlN coatings can significantly slow down the penetration of seawater into the coating under frictional pressure, and the oxide lubricating layer formed during the friction process can become an effective barrier to isolate seawater. Therefore, mechanical wear was the main wear form of these two coatings. Additionally, among the oxides formed in the friction, Cr2O3 showed the strongest corrosion resistance, making the CrAlN coating exhibit superior wear resistance and the lowest wear rate in seawater.
Near-infrared-light mediated ZIF-8@Ti3C2Tx nanocomposite for synergistic antibacterial properties and biofilm ablation
Authors: Xu Baoyong , Hu Zhipeng , Liu Wangzi , Li Hong
Published: December 2024

Due to the explosive emergence of various bacteria, antibiotics-free strategies are much needed for the elimination of bacterial-associated infections. Herein, ZIF-8@Ti3C2Tx nanocomposite was synthesized via in situ growth against bacteria under near-infrared-light (NIR) mediation. The integrated ZIF-8@Ti3C2Tx nanocrystal retained its NIR absorption, which enabled photothermal effect and reactive oxygen species (ROS) generation. Upon NIR irradiation, a sterilization rate of nearly 100% and a biofilm reduction rate of about 82% were obtained when the nanocomposite was treated with E. coli. It is suggested that the integration of ZIF-8@Ti3C2Tx facilitated the transfer of valence electrons to generate ROS, and the localized photothermal effect increased the release of Zn2+. Combined the photothermal therapy (PTT) with its evoked photodynamic therapy (PDT) and metal ions therapy (MIT), ZIF-8@Ti3C2Tx realized superior bactericidal activity and created a novel antibiotic-independent nanoplatform for biofilm ablation.
An empirical study of object detection models for the detection of iron deficiency anemia using peripheral blood smear images
Authors: Navya K T , Akshatha K R , Prasad Keerthana , Singh Brij Mohan Kumar
Published: December 2024

Iron Deficiency Anemia (IDA) is the nutritional disorder that occurs when the body does not contain enough iron, an essential component of hemoglobin (Hb). The World Health Organization (WHO) estimated that IDA is the main cause of anemia in 1.62 billion cases worldwide [1]. Although IDA rarely results in death, it has significant adverse impacts on human health. During diagnosis, the hemoglobin indices show low mean corpuscular hemoglobin and mean corpuscular hemoglobin volume. On Peripheral Blood Smear (PBS) images viewed under a microscope by hematologists, IDA shows hypochromic and microcytic red cells. The purpose of the proposed research is to develop a computer-aided system that will allow hematologists to diagnose and detect diseases more accurately and quickly, therefore saving them time and effort. In order to diagnose or detect clinical disorders, non-invasive techniques like machine learning algorithms are employed. This work aims to identify IDA by utilizing the RetinaNet-Disentangled Dense Object Detector (DDOD) to localize hypochromic microcytes in PBS images. To the best of our knowledge, this is the first work using the object detection technique to detect IDA based on the Red Blood Cell (RBC) morphology. We carried out an extensive quantitative and qualitative evaluation of the model. Additionally, a comparison was made between the performance of our model and other object detection models. The results showed that our approach outperformed state-of-the-art techniques, with a mean average precision that was more than 8% higher.
Digital Twin for EEG seizure prediction using time reassigned Multisynchrosqueezing transform-based CNN-BiLSTM-Attention mechanism model
Authors: Ghosh Antara , Dey Debangshu
Published: December 2024

The prediction of epileptic seizures is a classical research problem, representing one of the most challenging tasks in the analysis of brain disorders. There is active research into digital twins (DT) for various healthcare applications, as they can transform research into customized and personalized healthcare. The widespread adoption of DT technology relies on ample patient data to ensure precise monitoring and decision-making, leveraging Machine Learning (ML) and Deep Learning (DL) algorithms. Given the non-stationarity of EEG recordings, characterized by substantial frequency variations over time, there is a notable preference for advanced time-frequency methods in seizure prediction. This research proposes a DT-based seizure prediction system by applying an advanced time-frequency analysis approach known as Time-Reassigned MultiSynchroSqueezing Transform (TMSST) to EEG data to extract patient-specific impulse features and subsequently, a Deep Learning strategy, CNN-BiLSTM-Attention mechanism model is utilized in learning and classifying features for seizure prediction. The proposed architecture is named as ‘Digital Twin-Net’. By estimating the group delay in the time direction, TMSST produces the frequency components that are responsible for the EEG signal's temporal behavior and those time-frequency signatures are learned by the developed CNN-BiLSTM-Attention mechanism model. Thus the combination acts as a digital twin of a patient for the prediction of epileptic seizures. The experimental results showed that the suggested approach achieved an accuracy of 99.70% when tested on 22 patients from the publicly accessible CHB-MIT dataset. The proposed method surpasses previous solutions in terms of overall performance. Consequently, the suggested method can be regarded as an efficient approach to EEG seizure prediction.
Quantification of urinary albumin in clinical samples using smartphone enabled LFA reader incorporating automated segmentation
Authors: Bhatt Sunita , Gupta Richa , Prabhakar Vijay R N , Shukla Prashant Kumar , Datta Sudip Kumar , Dubey Satish Kumar
Published: December 2024

Smartphone-assisted urine analyzers estimate the urinary albumin by quantifying color changes at sensor pad of test strips. These strips yield color variations due to the total protein present in the sample, making it difficult to relate to color changes due to specific analyte. We have addressed it using a Lateral Flow Assay (LFA) device for automatic detection and quantification of urinary albumin. LFAs are specific to individual analytes, allowing color changes to be linked to the specific analyte, minimizing the interference. The proposed reader performs automatic segmentation of the region of interest (ROI) using YOLOv5, a deep learning-based model. Concentrations of urinary albumin in clinical samples were classified using customized machine learning algorithms. An accuracy of 96% was achieved on the test data using the k-Nearest Neighbour (k-NN) algorithm. Performance of the model was also evaluated under different illumination conditions and with different smartphone cameras, and validated using standard nephelometer.
Investigation of organs dosimetry precision using ATOM phantom and optically stimulated luminescence detectors in computed tomography
Authors: Khallouqi Abdellah , Sekkat Hamza , El Rhazouani Omar , Halimi Abdellah
Published: December 2024

The primary objective of this study was to compare organ doses measured using optically stimulated luminescent dosimeters (OSLDs) with those estimated by the CT-EXPO software for common CT protocols. An anthropomorphic ATOM phantom was employed to measure organ doses across head, chest, and abdominal CT scans performed on a Hitachi Supria 16-slice CT scanner. These OSLD measurements were then compared to the estimates provided by the widely used CT-EXPO software. Organ doses were assessed using OSLDs placed in an adult anthropomorphic phantom, with calibration performed through a comprehensive process involving multiple tube potentials and sensitivity corrections. Results from three CT acquisitions per protocol were compared to estimates provided by CT-EXPO software. Findings reveal significant discrepancies between measured and estimated organ doses, with p-values consistently below 0.05 across all organs. For head CT, measured eye lens doses averaged 33.51 mGy, 6.0% lower than the estimated 35.65 mGy. In chest CT, the thyroid dose was 9.82 mGy, 13.5% higher than the estimated 8.65 mGy. For abdominal CT, the liver dose measured 12.11 mGy, 9.6% higher than the estimated 11.05 mGy. Measured doses for the rest of organs were generally lower than those predicted by CT-EXPO, showing some limitations in current estimation models and the importance of precise dosimetry. This study highlights the potential of OSLD measurements as a complementary method for organ dose assessment in CT imaging, emphasizing the need for more accurate organ dose measurement to optimize patient care.
Emerging trends in fluorescent nanodiamond quantum sensing
Authors: Hui Yuen Yung , Le Trong-Nghia , Yang Teng-I , Chen Jeson , Chang Huan-Cheng
Published: December 2024

Diamond is the natural hardest material and has an exceptionally high thermal conductivity, wide optical transparency, and extreme chemical resistance. Most of these outstanding properties are still preserved for diamond at the nanoscale. Nanodiamond (ND) is highly biocompatible and inherently low in cytotoxicity, genotoxicity, and animal toxicity. Moreover, ND often contains atomic defects or impurities known as color centers. In this review article, we highlight the diverse applications of nitrogen-vacancy (NV) color centers in ND, which is also called fluorescent nanodiamond (FND). This review article summarizes recent advances and achievements in applying NV-containing FND for sensing and imaging including, nanoscale magnetic field sensing, NV axis orientation tracking, magnetic resonance, relaxometry for biosensing, nanoscale temperature sensing, spin-enhanced immunosensors for ultrasensitive in vitro diagnosis, and extreme ultraviolet imaging.
Combining effective Hamiltonians and Brillouin–Wigner approach: a perturbative approach to spectroscopy
Authors: Bindech Oussama , Valentin Bastien , Yalouz Saad , Robert Vincent
Published: December 2024

The numerical cost of variational methods suggests using perturbative approaches to determine the electronic structure of molecular systems. In this work, a sequential construction of effective Hamiltonians drives the definition of approximate model functions and energies in a multi-state Rayleigh–Schrödinger perturbative scheme. A second step takes advantage of an updated partitioning of the Hamiltonian to perform a state-specific Brillouin–Wigner energy correction based on a well-tempered perturbation expansion. The multi-step RSBW method is exemplified on model-Hamiltonians to stress its robustness, efficiency and applicability to spectroscopy determination.
Low-temperature-field-assisted fabrication of cross-scale tissue engineering scaffolds
Authors: Ye Jing , Zhou Xingyu , Huang Zhuo , Zhang Xianglin , Huang Wei , Wu Bin , Zhou Huamin
Published: December 2024

In tissue engineering (TE), tissue-inducing scaffolds are a promising solution for organ and tissue repair owing to their ability to attract stem cells in vivo, thereby inducing endogenous tissue regeneration through topological cues. An ideal TE scaffold should possess biomimetic cross-scale structures, similar to that of natural extracellular matrices, at the nano- to macro-scale level. Although freeform fabrication of TE scaffolds can be achieved through 3D printing, this method is limited in simultaneously building multiscale structures. To address this challenge, low-temperature fields were adopted in the traditional fabrication processes, such as casting and 3D printing. Ice crystals grow during scaffold fabrication and act as a template to control the nano- and micro-structures. These microstructures can be optimized by adjusting various parameters, such as the direction and magnitude of the low-temperature field. By preserving the macro-features fabricated using traditional methods, additional micro-structures with smaller scales can be incorporated simultaneously, realizing cross-scale structures that provide a better mimic of natural organs and tissues. In this paper, we present a state-of-the-art review of three low-temperature-field-assisted fabrication methods—freeze casting, cryogenic 3D printing, and freeze spinning. Fundamental working principles, fabrication setups, processes, and examples of biomedical applications are introduced. The challenges and outlook for low-temperature-assisted fabrication are also discussed.
Life cycle assessment and thermodynamic performance of biomass-based combined cogeneration
Authors: Çetinkaya Afşın Yusuf , Yılmaz Fatih , Bilgili Levent
Published: December 2024

This study presents a thermodynamic and life cycle analysis of a biomass-based integrated energy system, comprising a biomass gasification cycle, a steam Rankine cycle, and an ammonia fluid Organic Rankine cycle. The primary objective of the system is to efficiently convert olive husk, a sustainable biomass source, into electricity and heating. The gasification process generates syngas, which fuels a gas turbine, producing high-temperature exhaust that drives a Rankine cycle. The thermodynamic analysis indicates that the overall system achieves an energy efficiency of 20.85% and an exergy efficiency of 11.70%. The Rankine cycle exhibits an energy efficiency of 23.91%, while the Organic Rankine cycle demonstrates a higher exergy efficiency of 68.87%. Parametric studies reveal that increasing the combustion chamber temperature significantly enhances system efficiency and output, with energy efficiency rising linearly as the temperature increases from 800 °C to 1000 °C. Additionally, the analysis emphasizes the importance of the compressor’s compression ratio on system performance. A life cycle assessment conducted using the ReCiPe methodology evaluates the environmental impact of the system throughout its lifecycle, revealing critical insights into its sustainability. This comprehensive evaluation highlights the potential of utilizing agricultural waste, such as olive husk, to produce renewable energy, thereby supporting environmental sustainability and waste management goals. The findings underscore the viability of the proposed system for enhancing energy production while minimizing environmental impacts, making it a promising solution for renewable energy generation in regions with abundant biomass resources.
High-fidelity simulation of FRP-confined concrete-filled steel tubes: the synergy of empirical and machine learning techniques
Authors: Alqubaysi Tariq , Ghazouani Nejib , Mabrouk Abdelkader , Raza Ali , Ahmed Mohd
Published: December 2024

The present research addresses a significant gap in the current literature by overcoming the limitations associated with small, noisy datasets commonly used to predict the axial load-carrying capacity (ALC) of fiber-reinforced polymer (FRP)-encased concrete-filled steel tube compression examples (FCFST). Specifically, the authors present a refined, large-scale database that facilitates the evaluation of the prediction accuracies of three modeling techniques: finite element modeling (FEM), analytical modeling, and artificial neural networks (ANN). This comprehensive comparative analysis, underpinned by a robust experimental dataset, not only enhances predictive accuracy but also provides valuable engineering insights. Unlike previous studies, which often lack data refinement or fail to compare multiple modeling approaches, our work offers a more rigorous and holistic evaluation. The current study aims to recommend and compare the estimates of FEM, analytical model, and ANN model for capturing the ALC of FCFST examples. A database comprising 335 FCFST columns was constructed from previous studies to propose FEM and ANN models while the analytical model was proposed based on a database of 698 samples and encasing mechanics of steel tube and FRP wraps. The concrete damage plastic model was used for concrete along with bilinear and linear elastic models for steel tubes and FRP wraps, respectively. Analytical and ANN models effectively considered the lateral encasing mechanism of FCFST columns for accurate predictions. The FEM exhibited high accuracy with statistical parameters: MAE = 223.76, MAPE = 285.32, R2 = 0.943, RMSE = 210.43, and a20-index = 0.83. In contrast, the ANN model outperformed, with MAE = 195, MAPE = 229.67, R2 = 0.981, RMSE = 174, and a20-index = 0.89. The R2 values between the models indicated strong correlations: FEM versus analytical (0.876), analytical versus ANN (0.914), and ANN versus FEM (0.945), with the ANN model showing the best accuracy.
Entropy production analysis of energy loss of centrifugal pump impeller with multi-objective optimization
Authors: Zhang Runqiang , Nan Lingbo , Chen Diyi , Han Wei , Huang Weining
Published: December 2024

Efficiency is the core index for evaluating centrifugal pumps, which reduces the overall energy power loss of the pump and enhances the economics. The efficiency and energy-saving performance of the pump can be improved with an optimal designed impeller. In this paper, the efficiency improvement optimization design method for pumps is proposed via the pump impeller multi-parameter multi-objective optimization. Firstly, the high accuracy simulation model of the pump is modelled and verified. Comparison with the experimental results verifies the accuracy of the numerical method. Then, the design parameters of the impeller blades are hub inlet angle of impeller β
1h, shroud inlet angle of impeller β
1s, outlet angle of impeller β
2, shroud leading edge LEs, hub leading edge LEh for as the optimal parameters for orthogonal design. As the result, the optimized pump efficiency is increased by 1.902% and head is increased by 0.931 m. The optimized impeller mitigates unstable vortex clusters at the trailing edges of the blades, resulting in a more uniform velocity distribution and reduced flow separation within the impeller. The vortex transport equation was employed to investigate changes in the vortex structure. Additionally, the energy loss associated with the optimized impeller was evaluated using entropy production. Results show that optimizing the impeller reduces entropy production in both the impeller and the pump, thereby minimizing overall energy loss. These findings highlight the primary sources of energy loss in the impeller as potential focal points for further optimization research.
Machine learning materials properties with accurate predictions, uncertainty estimates, domain guidance, and persistent online accessibility
Authors: Jacobs Ryan , Schultz Lane E , Scourtas Aristana , Schmidt KJ , Price-Skelly Owen , Engler Will , Foster Ian , Blaiszik Ben , Voyles Paul M , Morgan Dane
Published: December 2024

One compelling vision of the future of materials discovery and design involves the use of machine learning (ML) models to predict materials properties and then rapidly find materials tailored for specific applications. However, realizing this vision requires both providing detailed uncertainty quantification (model prediction errors and domain of applicability) and making models readily usable. At present, it is common practice in the community to assess ML model performance only in terms of prediction accuracy (e.g. mean absolute error), while neglecting detailed uncertainty quantification and robust model accessibility and usability. Here, we demonstrate a practical method for realizing both uncertainty and accessibility features with a large set of models. We develop random forest ML models for 33 materials properties spanning an array of data sources (computational and experimental) and property types (electrical, mechanical, thermodynamic, etc). All models have calibrated ensemble error bars to quantify prediction uncertainty and domain of applicability guidance enabled by kernel-density-estimate-based feature distance measures. All data and models are publicly hosted on the Garden-AI infrastructure, which provides an easy-to-use, persistent interface for model dissemination that permits models to be invoked with only a few lines of Python code. We demonstrate the power of this approach by using our models to conduct a fully ML-based materials discovery exercise to search for new stable, highly active perovskite oxide catalyst materials.
The Chang–Skjelbred lemma and generalizations
Authors: Franz Matthias
Published: December 2024

We review the Chang–Skjelbred lemma for torus-equivariant cohomology and discuss several generalizations of it: to other coefficients, other groups and also to syzygies in equivariant cohomology and the Atiyah–Bredon sequence.
Localization of equivariant cohomology rings of real and oriented Grassmannians
Authors: He Chen
Published: December 2024

We use GKM-type localization methods to describe the rational equivariant cohomology rings of real Grassmannians and oriented Grassmannians under certain canonical torus actions. We also relate these results to the equivariant Leray-Borel and Takeuchi descriptions which identify the ring generators to be equivariant Pontryagin classes, plus equivariant Euler classes in even dimensions and one more new type of classes in odd dimensions, as revived by Casian and Kodama in the non-equivariant case. Additive bases of the equivariant cohomology are given in terms of equivariant characteristic polynomials and equivariant Schubert classes. We also discuss Poincaré series, equivariant Littlewood-Richardson coefficients and equivariant characteristic numbers. Since these Grassmannians under the torus actions are equivariantly formal, the results for equivariant cohomology here imply similar statements for ordinary cohomology.