bluuebunny/crossref_metadata_2025 huggingface dataset:
Potential of Gossypetin Compounds and Organic Acids of Rosella Kombucha Tea as Immunomodulators in Malaria Cases: In Silico Study
Authors: Widiani Nurhaida , Mustika Andini Nidie , Firmansyah M.
Published: January 2024

Malaria is an infectious disease caused by Plasmodium. Cases of resistance to Artemisin-based Combination Therapy (ACT) have been found. Therefore, complementary therapy is needed. The content of flavonoids (gossypetin) and organic acids (acetic acid, gluconic acid, and lactic acid) in Rosella Kombucha tea may be used as complementary therapy for the treatment of malaria. The In Silico study used gossypetin, acetic acid, gluconic acid, and lactic acid as ligands. While the target protein is the crystal structure of the enzyme TCR - MHC II Complex. Applications used for docking insilico are AutodockTools 1.5.6, Autodock 4.2 and Discovery Studio Visualizer. The results showed that gossypetin and organic acids had the potential to increase the activity of immunocompetent cells because these compounds were able to bind to the TCR – MHC II complex receptor. Gossypetin is more potent than organic acid compounds. gossypetin has Free Energy Binding (∆Gbinding) value (-2.26 kcal/mol), inhibition constant value (22.21 nM) and RMSD value < 5 (2.58). Meanwhile, the most potent organic acid was lactic acid with a value of Free Energy Binding (∆Gbinding) (-1.76 kcal/mol), an inhibition constant value (51.69 nM) and an RMSD value < 5 (4.1).
The Effectiveness of the “CAFELM” Formulation on the Growth Stage of Bird’s Eye Chili
Authors: Yosilia Rani , Arofa Rahmatuka Maya , Ulmillah Aulia , Munawarah Panggabean Siti
Published: January 2024

The continual use of inorganic fertilizers can lead to decreased soil fertility, lower crop yields, and increased environmental pollution. CAFELM - Compost Ash Fertilizer Enriched with Leachate, Charcoal, and Local Microbes is a mixture of several organic compounds used to treat domestic trash. This study aimed to examine the impact of specific fertilizers on the growth of bird’s eye chili. A randomized experimental design with multiple replicates was used for this investigation. The application of the CAFELM formulation fertilizer resulted in significant improvements in plant growth, particularly when treatment T1 was applied (consisting of 80 grams of compost, 3 mL of leachate, 80 grams of wood charcoal, 20 grams of burned ash, and 8 mL local microbe’s banana weevil). Additionally, this fertilizer composition proved effective in increasing total phosphorus content.
Formulation and Effectivity of Noni Fruit (Morinda citrifolia) and Aloe vera Extract Gel (GEMOCA) for Burn Wounds in White Mouse (Mus musculus)
Authors: Alkausar Triawan , Denni Denni , Kamelia Marlina , Jaya Kesuma Andri
Published: January 2024

Burn wound is an anatomical defect on the skin that occurs due to contact with high-temperature objects. Noni fruit and Aloe vera are known to have various therapeutical activities, including burn wound healing. The research aims to determine the formulation and effects of noni fruit (Morinda citrifolia) and Aloe vera extract gel (GEMOCA) for burn wounds in white mice (Mus musculus). The method of this research was quantitative. Fifteen (n=15) male mice, weighing 40-50 grams were divided into five groups (three treatment groups and two control groups), which consisted of three mice for each group. The burn wounds were made by shaving a 3cm wide area on the back using a 20mm heated metal plate for three seconds. Three treatment groups were treated with Morinda citrifolia and Aloe vera extract (GEMOCA) gel with the following distinct concentration: 1% : 0.5% (F1), 3% : 0.5% (F2), and 5% : 0.5% (F3). Positive control (KP) group was administered with Bioplancenton® gel, whilst negative control (KN) received no treatment. All treatments were conducted every 6 hours for 15 days. Burn wound observation was carried out on day 1, 4, 8 and 15 by measuring the diameter of the wound. The obtained data were analyzed using one-way ANOVA. The result showed that the burn wound diameter in white mice applied with GEMOCA gel in F3 (4.04 cm) had no significant difference with KP group (3.94 cm) and was the fastest recovery time in wound healing among the other treatment groups. This signifies that GEMOCA gel could be an alternative treatment for burn wound healing. The lower result of wound diameter in treatment group compared to positive control group is presumably because of the low active agent content due to manual method for extraction. Therefore, further studies to find a better extraction method to obtain higher concentration of active agent were needed.
Reflection of Maqoshit Sharia on the Concept of Ancient Agriculture for a Sustainable Green Economy
Authors: Vidiati Cory , Lathiafaturahmah L. , Selasi Dini , Lesmana Deden , Nauroh Izzwah
Published: January 2024

This article describes eco-green farming as an implementation of maqashid al-syariah, especially the soul (al-nafs), property (al-mal), and offspring (al-nasl). Using a qualitative approach, primary data sources from interviews and secondary data sources obtained from YouTube, related articles that support this research. The findings are that environmentally friendly agriculture by utilizing surrounding natural resources and can be done even on unproductive land, and cheap can be done nationally and even reduce the use of chemical fertilizers so that it is in accordance with the objectives in maqhosid sharia, namely protecting the soul from a lot of chemical contamination, protecting property with cheap production costs and sustainability of agriculture and business, also protecting offspring by consuming halal and toyib. The novelty of this research is a stakeholder recommendation as a public policy for sustainable agriculture. The limitations of this research are the material for further research studies.
Identification and Study of Thermophilic Bacteria Found in the Sulfur-Infused Hot Springs of South Lampung
Authors: Sugiharta Iip , Satiyarti Rina Budi , Safitri Lina , Rinaldi Achi , Suri Fraulein Intan
Published: January 2024

Thermophilic bacteria are microorganisms with the capability to produce a specific enzyme known as amylase, which exhibits resistance to heat and is referred to as thermostable. This study aims to isolate, characterize, and assess the enzyme-producing activity of bacteria from the hot springs of Way Belerang, Lampung, specifically amylase. The research procedures encompassed sample collection, isolation of thermophilic bacteria incubated in NA media for 48 hours, amylum testing with iodine after a 24-hour incubation in NA media containing starch/amylose, biochemical tests including TSIA, SIM, SC, urea test, sugar fermentation test, and catalase test. The results of the study yielded two isolates successfully isolated from the hot spring source, and Gram staining indicated that both isolates were Gram-negative bacteria. The assessment of bacterial activity in producing amylase was demonstrated by the presence of clear zones, with the largest bacterial diameter measuring 1.04 mm as measured using a vernier caliper. Characterization of the bacteria identified them as belonging to the Pseudomonas genus for isolates AB2 and AB3. Thus, the bacteria obtained in this study produce amylase enzymes that can be utilized in various industrial applications, including the food, beverage, textile, detergent, paper, pharmaceutical, and other sectors.
Environmental Education through Islamic Lens: Values and Practices
Authors: Ayu Setianingrum Diah , Setiyo  , Dwiyanto Agus
Published: January 2024

Faced with mounting environmental issues, the convergence of religious beliefs and ecological consciousness appears as a critical domain for long-term solutions. This article examines environmental education via an Islamic lens, revealing the rich tapestry of environmental lessons woven within Islamic tradition. As global challenges such as climate change, deforestation, and pollution worsen, varied cultural and religious viewpoints become increasingly important for comprehensive understanding. Islam, as a holistic way of life, uniquely defines humanity’s interaction with the natural world, providing direction through the Qur’an and Prophet Muhammad’s teachings. This research looks on the ethical foundations of Islamic environmentalism, focusing on stewardship, interconnectedness, and moderation. It goes on to look at practical applications of environmental sustenance in everyday life, with a focus on water conservation, sustainable agriculture, and ethical consumption. The research also looks into the emotional well-being promoted by Islamic environmental education, focusing on mindfulness, purpose, and coping methods. Finally, the importance of Islamic environmental education in community involvement and social cohesion is examined, highlighting its ability to motivate collective action and develop links among various populations. This research contributes to a worldwide conversation on sustainable practises, across cultural and religious divides and establishing a shared commitment to environmental stewardship.
Data-driven modelling of brain activity using neural networks, diffusion maps, and the Koopman operator
Authors: Gallos Ioannis K. , Lehmberg Daniel , Dietrich Felix , Siettos Constantinos
Published: January 2024

We propose a machine-learning approach to construct reduced-order models (ROMs) to predict the long-term out-of-sample dynamics of brain activity (and in general, high-dimensional time series), focusing mainly on task-dependent high-dimensional fMRI time series. Our approach is a three stage one. First, we exploit manifold learning and, in particular, diffusion maps (DMs) to discover a set of variables that parametrize the latent space on which the emergent high-dimensional fMRI time series evolve. Then, we construct ROMs on the embedded manifold via two techniques: Feedforward Neural Networks (FNNs) and the Koopman operator. Finally, for predicting the out-of-sample long-term dynamics of brain activity in the ambient fMRI space, we solve the pre-image problem, i.e., the construction of a map from the low-dimensional manifold to the original high-dimensional (ambient) space by coupling DMs with Geometric Harmonics (GH) when using FNNs and the Koopman modes per se. For our illustrations, we have assessed the performance of the two proposed schemes using two benchmark fMRI time series: (i) a simplistic five-dimensional model of stochastic discrete-time equations used just for a “transparent” illustration of the approach, thus knowing a priori what one expects to get, and (ii) a real fMRI dataset with recordings during a visuomotor task. We show that the proposed Koopman operator approach provides, for any practical purposes, equivalent results to the FNN-GH approach, thus bypassing the need to train a non-linear map and to use GH to extrapolate predictions in the ambient space; one can use instead the low-frequency truncation of the DMs function space of L2-integrable functions to predict the entire list of coordinate functions in the ambient space and to solve the pre-image problem.
Diversity-induced trivialization and resilience of neural dynamics
Authors: Hutt Axel , Trotter Daniel , Pariz Aref , Valiante Taufik A. , Lefebvre Jérémie
Published: January 2024

Heterogeneity is omnipresent across all living systems. Diversity enriches the dynamical repertoire of these systems but remains challenging to reconcile with their manifest robustness and dynamical persistence over time, a fundamental feature called resilience. To better understand the mechanism underlying resilience in neural circuits, we considered a nonlinear network model, extracting the relationship between excitability heterogeneity and resilience. To measure resilience, we quantified the number of stationary states of this network, and how they are affected by various control parameters. We analyzed both analytically and numerically gradient and non-gradient systems modeled as non-linear sparse neural networks evolving over long time scales. Our analysis shows that neuronal heterogeneity quenches the number of stationary states while decreasing the susceptibility to bifurcations: a phenomenon known as trivialization. Heterogeneity was found to implement a homeostatic control mechanism enhancing network resilience to changes in network size and connection probability by quenching the system’s dynamic volatility.
Effect of outer spherical shell opening structure on the sensitivity of double spherical shell electric field sensor
Authors: Zhao Zhengang , Yang Xuanyi , Li Yitan , Luo Chuan
Published: January 2024

A double spherical shell (DSS) electric field sensor based on charge sensing has characteristics of small size and simple fabrication, which are appropriate for measuring complex electric field environments, but the sensitivity is low. To improve the sensitivity of the DSS electric field sensor, we theoretically analyze the effect of the diameter of the outer spherical shell opening on the sensitivity of the sensor. The sensors with outer spherical shell apertures of 2, 4, and 6 mm are designed and manufactured, and the sensor’s sensitivity, linearity, hysteresis, and repeatability are tested. The relative error of the sensor is evaluated by measuring the rotational characteristics of the sensor. The experimental results show that the sensor sensitivity increases with the increase in hole diameter, while the sensor has good linearity, hysteresis, and repeatability after opening the hole. The rotational characteristics experiments’ results show that the sensors’ relative errors with different apertures are 18, 23, and 31%, respectively. The DSS open-hole structure is more suitable for electric field measurements than the conventional flat plate structure.
Photonic neural networks and optics-informed deep learning fundamentals
Authors: Tsakyridis Apostolos , Moralis-Pegios Miltiadis , Giamougiannis George , Kirtas Manos , Passalis Nikolaos , Tefas Anastasios , Pleros Nikos
Published: January 2024

The recent explosive compute growth, mainly fueled by the boost of artificial intelligence (AI) and deep neural networks (DNNs), is currently instigating the demand for a novel computing paradigm that can overcome the insurmountable barriers imposed by conventional electronic computing architectures. Photonic neural networks (PNNs) implemented on silicon integration platforms stand out as a promising candidate to endow neural network (NN) hardware, offering the potential for energy efficient and ultra-fast computations through the utilization of the unique primitives of photonics, i.e., energy efficiency, THz bandwidth, and low-latency. Thus far, several demonstrations have revealed the huge potential of PNNs in performing both linear and non-linear NN operations at unparalleled speed and energy consumption metrics. Transforming this potential into a tangible reality for deep learning (DL) applications requires, however, a deep understanding of the basic PNN principles, requirements, and challenges across all constituent architectural, technological, and training aspects. In this Tutorial, we, initially, review the principles of DNNs along with their fundamental building blocks, analyzing also the key mathematical operations needed for their computation in photonic hardware. Then, we investigate, through an intuitive mathematical analysis, the interdependence of bit precision and energy efficiency in analog photonic circuitry, discussing the opportunities and challenges of PNNs. Followingly, a performance overview of PNN architectures, weight technologies, and activation functions is presented, summarizing their impact in speed, scalability, and power consumption. Finally, we provide a holistic overview of the optics-informed NN training framework that incorporates the physical properties of photonic building blocks into the training process in order to improve the NN classification accuracy and effectively elevate neuromorphic photonic hardware into high-performance DL computational settings.
Piezoelectric fields and martensitic transition in spontaneously ordered GaInP2/GaAs epi-layers
Authors: Ankudinov A. V. , Bert N. A. , Dunaevskiy M. S. , Galimov A. I. , Kalyuzhnyy N. A. , Mintairov S. A. , Myasoedov A. V. , Pavlov N. V. , Rakhlin M. V. , Salii R. A. , Toropov A. A. , Vlasov A. S. , Pirogov E. V. , Zhukovskyi M. A. , Mintairov A. M.
Published: January 2024

The effect of lattice relaxation instability (martensitic transition) on piezoelectric fields (EPE) in spontaneously ordered GaInP2/GaAs epitaxial layers was demonstrated using scanning Kelvin probe microscopy in combination with electron microscopy and optical spectroscopy measurements. The transition manifests itself in the dependence of the surface potential of the epi-layer on the mechanical (cleavage) and thermal (annealing) impacts. This is associated with a switching of the crystal lattice between relaxed and strained martensitic states, corresponding to a change in EPE in the epi-layer. The measured surface potential values (0.2–2.4 V) correspond to EPE within ±100 kV/cm and a strong decrease in |EPE| with increasing layer thickness, indicating the pinning of the Fermi level and piezoelectric doping. Our results open up the prospects for using spontaneously ordered semiconductor alloys to control electronic states in semiconductor nanostructures by controlling their piezoelectric fields.
Prediction of stability constants of metal–ligand complexes by machine learning for the design of ligands with optimal metal ion selectivity
Authors: Zahariev Federico , Ash Tamalika , Karunaratne Erandika , Stender Erin , Gordon Mark S. , Windus Theresa L. , Pérez García Marilú
Published: January 2024

The new LOGKPREDICT program integrates HostDesigner molecular design software with the machine learning (ML) program Chemprop. By supplying HostDesigner with predicted log K values, LOGKPREDICT enhances the computer-aided molecular design process by ranking ligands directly by metal–ligand binding strength. Harnessing reliable experimental data from a historic National Institute of Standards and Technology (NIST) database and data from the International Union of Pure and Applied Chemistry (IUPAC), we train message passing neural net algorithms. The multi-metal NIST-based ML model has a root mean square error (RMSE) of 0.629 ± 0.044 (R2 of 0.960 ± 0.006), while two versions of lanthanide-only IUPAC-based ML models have, respectively, RMSE of 0.764 ± 0.073 (R2 of 0.976 ± 0.005) and 0.757 ± 0.071 (R2 of 0.959 ± 0.007). For relative log K predictions on an out-of-sample set of six ligands, demonstrating metal ion selectivity, the RMSE value reaches a commendably low 0.25. We showcase the use of LOGKPREDICT in identifying ligands with high selectivity for lanthanides in aqueous solutions, a finding supported by recent experimental evidence. We also predict new ligands yet to be verified experimentally. Therefore, our ML models implemented through LOGKPREDICT and interfaced with the ligand design software HostDesigner pave the way for designing new ligands with predetermined selectivity for competing metal ions in an aqueous solution.
Superconductivity coupling of harmonic resonant oscillators: Homogeneous and heterogeneous extreme multistability with multi-scrolls
Authors: Fonzin Fozin T. , Tchamda A. R. , Sivaganesh G. , Srinivasan K. , Tabekoueng Njitacke Z. , Mezatio A. B.
Published: January 2024

Understanding and characterizing multistabilities, whether homogeneous or heterogeneous, is crucial in various fields as it helps to unveil complex system behaviors and provides insights into the resilience and adaptability of these systems when faced with perturbations or changes. Homogeneous and heterogeneous multistabilities refer, respectively, to situation in which various multiple stable states within a system are qualitatively similar or distinct. Generating such complex phenomena with multi-scrolls from inherent circuits is less reported. This paper aims to investigate extreme multistability dynamics with homogeneous and heterogeneous multi-scrolls in two coupled resonant oscillators through a shunted Josephson junction. Analysis of equilibrium points revealed that the system supports both hidden and self-excited attractors. Various dynamical tools, including bifurcation diagrams, spectrum of Lyapunov exponents, and phase portraits, are exploited to establish the connection between the system parameters and various complicated dynamical features of the system. By tuning both system parameters and initial conditions, some striking phenomena, such as homogeneous and heterogeneous extreme multistability, along with the emergence of multi-scrolls, are illustrated. Furthermore, it is observed that one can readily control the number of scrolls purely by varying the initial conditions of the investigated system. A multi-metastable phenomenon is also captured in the system and confirmed using the finite-time Lyapunov exponents. Finally, the microcontroller implementation of the system demonstrates strong alignment with the numerical investigations.
Flow control using hot splitter plates in the wake of a circular cylinder: A hybrid strategy
Authors: S Ajith Kumar , Murali Damu , Petha Sethuraman Vignesh Ram
Published: January 2024

A novel and effective hybrid technique, which involves active surface heating strategies in conjunction with the use of passive splitter plates in the wake of the cylinder, is proposed. In this report, we present the results of a numerical investigation on the two-dimensional, laminar mixed convection flow over a circular cylinder with a hot rigid splitter plate attached to it on the wake side. A projection algorithm-based finite volume method is employed to obtain the solution of the coupled, nonlinear governing partial differential equations subjected to Courant–Friedrichs–Lewy conditions. The isothermal heating of the splitter plate under the influence of the gravity field generates an upward buoyancy force in the wake of the cylinder. For different length-to-diameter (L/D) ratios, the effect of heating on aerodynamic, wake, and heat transfer characteristics has been studied for a wide range of parameters; 75 ≤Re≤ 150, 0 ≤Ri≤ 1, and 0.5 ≤L/D≤ 1 at Pr = 0.7. It is observed that the hot splitter plate would bring about conspicuous changes such as asymmetry in the vortex shedding behind the cylinder at low Reynolds numbers. The outcomes demonstrate a notable improvement in convective heat transfer and drag, with gains of up to 7% and 15%, respectively. It is found that the rate of heat transfer and vortex shedding frequency decrease with an increase in L/D ratio. Correlations for the estimation of Strouhal number and Nusselt number have also been proposed which helps provide a more thorough understanding of thermal and aerodynamic features of the hybrid approach.
High-order geometric integrators for the local cubic variational Gaussian wavepacket dynamics
Authors: Moghaddasi Fereidani Roya , Vaníček Jiří J. L.
Published: January 2024

Gaussian wavepacket dynamics has proven to be a useful semiclassical approximation for quantum simulations of high-dimensional systems with low anharmonicity. Compared to Heller’s original local harmonic method, the variational Gaussian wavepacket dynamics is more accurate, but much more difficult to apply in practice because it requires evaluating the expectation values of the potential energy, gradient, and Hessian. If the variational approach is applied to the local cubic approximation of the potential, these expectation values can be evaluated analytically, but they still require the costly third derivative of the potential. To reduce the cost of the resulting local cubic variational Gaussian wavepacket dynamics, we describe efficient high-order geometric integrators, which are symplectic, time-reversible, and norm-conserving. For small time steps, they also conserve the effective energy. We demonstrate the efficiency and geometric properties of these integrators numerically on a multidimensional, nonseparable coupled Morse potential.
Long-ionic-gated graphene synaptic transistor with enhanced memory, learning function and humidity perception
Authors: He X. , Xu M. , Shi Q. , Wang K. , Cao B. , Rao L. , Xin X.
Published: January 2024

With the development of neuromorphic electronics, much effort has been devoted to expand perception, memory, and computing integration capabilities. In this paper, an ionic-based graphene synaptic transistor with long-gate structure has been investigated to mimic memory, learning function and perceive humidity. By harnessing the tunable in-plane-field transport of charge carriers in graphene and ions motion in ion-gel, this transistor mimics various synaptic functionalities, including inhibitory postsynaptic current, excitatory postsynaptic current, paired-pulse facilitation, long-term depression, and long-term potentiation. Under short pules stimuli, the long-gate structure provides our transistor with an inertial assisted re-accumulation, generating two excitatory postsynaptic current peaks and enhanced paired-pule facilitation up to ∼265%. Furthermore, the presence of the long-gate structure enables our transistor to exhibit excellent learning and simulate Ebbinghaus' memory. In addition, physical mechanic about its humidity perception has been analyzed and discussed. This study provides a unique platform for designing high-performance carbon-based artificial synapses enabling integrated functions of sensing, storage, and computation for the neuromorphic system.
How adsorbed proteins at solid interfaces impact the droplet propagation through micro capillaries
Authors: Giefer P. , Heyse A. , Drusch S. , Fritsching U.
Published: January 2024

Proteins are used in food technology as biological emulsifiers which stabilize the liquid/liquid interface by lowering the interfacial tension due to their amphiphilic character. Due to the rising use of sensitive animal- and plant-based proteins in the food industry, homogenization methods with low-shear and low mechanical and thermal stresses like premix-membrane emulsification got more and more attention. However, one drawback remains: the proteins tend to adsorb to the membrane surfaces causing problems like fouling and pore-blocking. Recently, it was also found that the adsorbed proteins alter the wettability of the system which is suspected to affect the droplet breakup [Giefer et al., “Impact of wettability on interface deformation and droplet breakup in microcapillaries,” Phys. Fluids 35, 042110 (2023)], but the mechanism behind is still unknown. The study addresses the question of the extent to which proteins influence droplet propagation in micro-capillaries within membrane emulsification. Protein adsorption at liquid/liquid and liquid/solid interfaces is considered within molecular dynamic simulations and the effect on the interfacial tension is quantified. Considering the Young–Dupré equation [M. E. Schrader, “Young-dupre revisited,” Langmuir 11, 3585–3589 (1995)], interfacial energies are converted into contact angles, which are validated with experimental studies. For this purpose, idealized pore structures are considered under variation of the dynamic contact angle, for which the Kistler equation [S. Kistler, “Hydrodynamics of wetting,” Wettability (CRC Press, 1993), Vol. 6] is used. The results show that the protein adsorption to liquid/solid interfaces alters the wettability. Computational fluid dynamics reveal the dependence of the droplet propagation and interfacial instabilities in dependence on the wettability.
A GHz-frequency multistrip acoustic beam splitter for quantum applications
Authors: Dumur É. , Satzinger K. J. , Peairs G. A. , Chou M.-H. , Bienfait A. , Chang H.-S. , Conner C. R. , Grebel J. , Povey R. G. , Zhong Y. P. , Cleland A. N.
Published: January 2024

We demonstrate a microwave-frequency, two-track acoustic beam splitter, based on a multistrip coupler design matched to four unidirectional transducers, two on each of the two acoustic tracks that make up the device. We explain the device design and its experimental implementation, showing good agreement between our model and the measured device scattering spectra. The beam splitter regime, dividing an input signal at port 1 into closely equal outputs at ports 2 and 3, is reached over a 94.7 MHz bandwidth centered at 4.79 GHz, with an output power division ratio |S21/S31|2=1.1±0.2. The measured bandwidth of the device is limited by the bandwidth of the transducers, rather than that of the multistrip coupler.
Development of a dynamic gas lock inhibited model for EUV-induced carbon deposition
Authors: Hao Ming , Teng Shuai , Liu Jiaxing , Xie Yuanhua , Ba Dechun , Bian Xin , Ba Yaoshuai , Chen Zhengwei , Liu Kun
Published: January 2024

The optical surface of extreme ultraviolet (EUV) lithography machines is highly vulnerable to contamination by hydrocarbons, resulting in the formation of carbon deposits that significantly degrade the quality and efficiency of lithography. The dynamic gas lock (DGL) has been proven as an effective approach to alleviate carbon deposition. However, the majority of existing studies on carbon deposition neglect the influence of the DGL. This paper is dedicated to investigating the phenomena of hydrocarbon adsorption, desorption, and cleavage with considering the effects of the DGL. A comprehensive mathematical model of the carbon deposition process is established, and the impact of radiation intensity, temperature, and hydrocarbon types on the depositing rate is considered. The results suggest that the primary cause of carbon deposition is the direct cracking of hydrocarbons induced by photons with a wavelength range between 12.5 and 14.5 nm. Additionally, it has been observed that the carbon deposition rate decreases exponentially as clean gas flow increases when EUV radiation intensity exceeds 50 mW/mm2. Conversely, at low EUV radiation intensity, clean gas flow has little effect on the carbon deposition rate. An effective approach to mitigate carbon deposition is to elevate the temperature of the optical surface and employ light hydrocarbon materials in the EUV process.
Hyperchaos of neuron under local active discrete memristor simulating electromagnetic radiation
Authors: Lai Qiang , Yang Liang
Published: January 2024

Memristor enables the coupling of magnetic flux to membrane voltage and is widely used to investigate the response characteristics of neurons to electromagnetic radiation. In this paper, a local active discrete memristor is constructed and used to study the effect of electromagnetic radiation on the dynamics of neurons. The research results demonstrate that increasing electromagnetic radiation intensity could induce hyperchaotic attractors. Furthermore, this neuron model generates hyperchaotic and three points coexistence attractors with the introduction of the memristor. A digital circuit is designed to implement the model and evaluate the randomness of its output sequence. Neuronal models exhibit a rich dynamic behavior with electrical radiation stimulation, which can provide new directions for exploring the production mechanisms of certain neurological diseases.
Manipulation of photosynthetic energy transfer by vibrational strong coupling
Authors: Dong Jun-Yu , Kitahama Yasutaka , Fujita Takatoshi , Adachi Motoyasu , Shigeta Yasuteru , Ishizaki Akihito , Tanaka Shigenori , Xiao Ting-Hui , Goda Keisuke
Published: January 2024

Uncovering the mystery of efficient and directional energy transfer in photosynthetic organisms remains a critical challenge in quantum biology. Recent experimental evidence and quantum theory developments indicate the significance of quantum features of molecular vibrations in assisting photosynthetic energy transfer, which provides the possibility of manipulating the process by controlling molecular vibrations. Here, we propose and theoretically demonstrate efficient manipulation of photosynthetic energy transfer by using vibrational strong coupling between the vibrational state of a Fenna–Matthews–Olson (FMO) complex and the vacuum state of an optical cavity. Specifically, based on a full-quantum analytical model to describe the strong coupling effect between the optical cavity and molecular vibration, we realize efficient manipulation of energy transfer efficiency (from 58% to 92%) and energy transfer time (from 20 to 500 ps) in one branch of FMO complex by actively controlling the coupling strength and the quality factor of the optical cavity under both near-resonant and off-resonant conditions, respectively. Our work provides a practical scenario to manipulate photosynthetic energy transfer by externally interfering molecular vibrations via an optical cavity and a comprehensible conceptual framework for researching other similar systems.
X-ray absorption spectroscopy and theoretical investigations of the effect of extended ligands in potassium organic matter interaction
Authors: Richardson Jocelyn A. , Kim Hoshin , Kas Joshua J. , You Xiao , Andersen Amity , Ginovska Bojana , Bhattacharjee Arunima , Sarangi Ritimukta
Published: January 2024

Potassium (K) is an essential nutrient for plant growth, and despite its abundance in soil, most of the K is structurally bound in minerals, limiting its bioavailability and making this soil K reservoir largely inaccessible to plants. Microbial biochemical weathering has been shown to be a promising pathway to sustainably increase plant available K. However, the mechanisms underpinning microbial K uptake, transformation, storage, and sharing are poorly resolved. To better understand the controls on microbial K transformations, we performed K K-edge x-ray absorption near-edge structure (XANES) spectroscopy on K-organic salts, including acetate, citrate, nitrate, oxalate, and tartrate, which are frequently observed as low molecular weight organic acids secreted by soil microbes, as well as humic acid, which acts as a proxy for higher molecular weight organic acids. The organic salts display feature-rich K XANES spectra, each demonstrating numerous unique features spanning ∼13 eV range across the absorption edge. In contrast, the spectra for humic acid have one broad, wide feature across the same energy range. We used a combination of time-dependent density functional theory and the Bethe–Salpeter equation based approach within the OCEAN code to simulate the experimental spectra for K-nitrate (KNO3) and K-citrate [K3(C6H5O7)·H2O] to identify the electronic transitions that give rise to some of the outlying and unique spectral features in the organic salts. KNO3 has both the lowest and highest lying energy features, and K3(C6H5O7)·H2O is produced by several soil microbes and is effective at mineral weathering. Our results analyze the K-organic salt bonding in detail to elucidate why the spectral shapes differ and indicate that the K K-edge XANES spectra are associated with the entire ligand despite similar first-shell bonding environments around the K center. The improved understanding of K bonding environments with organic ligands and their use for interpretation of the K-XANES spectra provides an important toolkit to understand how K is transformed by microbial processes and made bioavailable for plant uptake.
Memory loss can prevent chaos in games dynamics
Authors: Bielawski Jakub , Chotibut Thiparat , Falniowski Fryderyk , Misiurewicz Michał , Piliouras Georgios
Published: January 2024

Recent studies have raised concerns on the inevitability of chaos in congestion games with large learning rates. We further investigate this phenomenon by exploring the learning dynamics in simple two-resource congestion games, where a continuum of agents learns according to a simplified experience-weighted attraction algorithm. The model is characterized by three key parameters: a population intensity of choice (learning rate), a discount factor (recency bias or exploration parameter), and the cost function asymmetry. The intensity of choice captures agents’ economic rationality in their tendency to approximately best respond to the other agent’s behavior. The discount factor captures a type of memory loss of agents, where past outcomes matter exponentially less than the recent ones. Our main findings reveal that while increasing the intensity of choice destabilizes the system for any discount factor, whether the resulting dynamics remains predictable or becomes unpredictable and chaotic depends on both the memory loss and the cost asymmetry. As memory loss increases, the chaotic regime gives place to a periodic orbit of period 2 that is globally attracting except for a countable set of points that lead to the equilibrium. Therefore, memory loss can suppress chaotic behaviors. The results highlight the crucial role of memory loss in mitigating chaos and promoting predictable outcomes in congestion games, providing insights into designing control strategies in resource allocation systems susceptible to chaotic behaviors.
The efficiency of terahertz radiation generated by two chirped femtosecond laser pulses at different pulse durations
Authors: Mahdy Abdelrahman I. , Eltayeb Hoda A.
Published: January 2024

A high optical-to-terahertz (THz) energy conversion efficiency is essential for the production of high-power ultra-broadband THz waves. In this work, we study the efficiency of THz radiation produced by two chirped femtosecond laser pulses in an air plasma. The primary objective is to compare the role of a chirped pulse with that of a non-chirped pulse in the conversion efficiency of the generated THz radiation and to examine the effect of increasing the initial duration of the pulse. Therefore, using the photocurrent model, we numerically evaluate the energy conversion efficiency of the generated THz radiation as a function of the input intensity for selected chirped and non-chirped pulse profiles with varying initial pulse durations. The obtained numerical results demonstrate the advantage of chirped over non-chirped pulses in enhancing the efficiency of the generated THz radiation within the 1013–1015 W/cm2 input intensity range. Moreover, with increasing pulse duration, the efficiency of the chirped pulse increases, reaching a conversion rate of 10−4.
Laser-induced shock inside a cylindrical water column
Authors: Tang Mao , Sun Muwen , Zhang Hongchao , Lu Jian
Published: January 2024

An investigation of laser-induced shock inside a water column is conducted. We focus on the reflection of the shock by the circle interface and discuss the dynamics of the wavefront at the different initial locations of the shock. Based on the approximation of linear geometrical acoustics, the wavefront is determined by a parametric equation, and the results agree well with our experiment. It is found that the dominant characteristic is the cusps (singularity), which is attributed to the caustics of the circle interface, and a singularity on the loci of the cusps indicates a more complex wavefront than a plane wave incident to a water column. In addition, the reflected wave-induced cavitation is observed, which is closer to the interface as the initial breakdown regions move away from the column center. Because of the circular interface, our wavefront dynamics results also provide a better understanding of an internal shock inside a spherical drop.
Surface plasmon resonance assisted donor–acceptor type covalent polymeric framework for hybrid photodetectors
Authors: C. J. Keerthi , Halder Sayan , Sahatiya Parikshit , Chakraborty Chanchal , Pal Subhradeep
Published: January 2024

In this paper, a surface plasmon resonance assisted hybrid photodetector (PD) made of a low bandgap covalent polymeric framework material is experimentally demonstrated. The PD demonstrated a broadband photodetection capability ranging between 350 and 1550 nm with subsecond transients. The fabricated hybrid PD offered a remarkable responsivity and external quantum efficiency of 42.87 A/W and 11 873% at 410 nm, respectively. The peak detectivity is recorded to be 7.43×1013 Jones at 400 nm. Up to 1550 nm, the hybrid PD offered a responsivity > 0.4 A/W, thereby showcasing its efficacy even for the near-infrared signals. The time-dependent photoresponse study estimated the rise time and fall time of the fabricated PD to be approximately 0.31 and 0.22 s, respectively.
Influence of intersection angle on nonlinear flow behavior and solute transport through three-dimensional crossed rock fractures
Authors: Li Yubo , Qian Jiazhong , Liu Yong , Deng Yaping , Fang Yunhai
Published: January 2024

Accurately evaluating the flow characteristics in fracture intersections is important to advance the understanding of groundwater flow and solute transport in crossed rock fractures. However, mainly two-dimensional (2D) intersection models have been adopted in previous studies, and the influence of intersection angles and related three-dimensional (3D) effects (channel flow and transverse flow) on the fracture seepage and the solute transport is still neglected. In this study, the 3D crossed fracture models, coupled with various intersection angles, were established through the intersection of two rough-walled fractures. The characteristic parameters of the fluid flow and the solute transport under different inlet velocity conditions were calculated by the Navier–Stokes equation and the advective–diffusion equation, respectively. The results indicated that the intricate geometry of the intersection in 3D rough-walled models led to channeling flows, which subsequently impacted mixing behavior depending on velocity. Due to the presence of channeling flows, the velocity ratio at the outlet was different from that of a 2D fracture as the inlet hydraulic conditions evolved. The coefficient matrices describing nonlinear flow behavior in different fracture intersection angles were quantified simultaneously. The reallocation of fluid pathways induced by intersecting angles affects mixing behavior by influencing the geometrical structure of fracture intersections. Moreover, the breakthrough curves and solute mixing process were significantly dependent on the intersection angle and the inlet velocity. In the linear region, the mixing ratio is random due to the intersection of heterogeneous, while in the nonlinear region, the mixing ratio decreases with the increase in water flow. Above all, the correlation established in this study between hydraulic parameters and the intersection angle parameter can enhance their efficacy in predicting solute transport in fractured rocks.
Enhancing hydrogen bubble release from a microelectrode through precise tuning of Marangoni forces with nonionic surfactant
Authors: Lu Xinlong , Nie Tengfei , Yadav Devendra , Li Xiaoping , Zhang Yiming , Ma Lijing , Jing Dengwei
Published: January 2024

Understanding and controlling hydrogen bubble growth and detachment during water electrolysis is crucial for improving its efficiency. This study investigates bubble dynamics for hydrogen evolution on a platinum microelectrode in an acidic electrolyte with different gas/electrolyte surface tensions by adding varying surfactant concentrations. Three hydrogen bubble evolution patterns were observed: periodic detachment of individual bubbles at low surfactant concentrations of 0 and 1 × 10−7 M, respectively; one or two small bubbles are formed at the foot of the bubble during the evolution of single main bubble at intermediate surfactant concentrations of 1 × 10−6 and 1 × 10−5 M; and periodic detachment of large bubbles with aperiodic release of tiny bubbles at higher surfactant concentrations of 1 × 10−4 M. The concentration Marangoni force on individual H2 bubbles decreases significantly with surfactant concentration. This results in shorter evolution cycles from 138.12 to 6.98 s at −0.6 V vs the saturated calomel electrode, reduced detachment radii from 765.95 to 359.54 μm at −0.6 VSCE, and accelerated hydrogen bubble growth. This finding offers a new way to control bubble dynamics during electrochemical bubble formation.
Dynamic graph convolutional networks for fluid identification of well logging data transformed through the gram angle field
Authors: Sun Youzhuang , Zhang Junhua , Zhang Yongan
Published: January 2024

Accurately predicting the fluids holds immense significance in exploration work, assisting in the identification of exploration targets, estimation of reserve potential, and evaluation of reservoirs. In our research, we employed an innovative approach by using the gram angle field (GAF) to transform logging parameters. By adeptly capturing time series information and converting one-dimensional data into two-dimensional matrix representations, GAF takes into account not only the values at each time point but also their relative position and order. This method effectively preserves the temporal evolution characteristics of the original data. The resulting Gram Angle Field matrix can be viewed as a two-dimensional image, facilitating visualization and analysis through image processing techniques. Additionally, we introduced the dynamic graph convolutional network (DGCN) to segment the transformed images. The DGCN structure, employed for feature learning, can extract more comprehensive and representative feature representations from the logging data. Since logging data demonstrate a time series relationship, indicating a temporal correlation between logging curves at different depths, DGCN utilizes dynamic graph structures to capture and comprehend this time series information. This capability enables DGCN to model the evolution process of well log data effectively. DGCN assigns varying weights to nodes and edges at each time step, updating the current node representation with information from neighboring nodes. This localized approach enables DGCN to meticulously focus on significant features at each time step, facilitating the identification of potential patterns and trends in the logging data. Our research not only paves the way for advancements in the field but also provides valuable insights for geologists and professionals engaged in oil and gas exploration.
Numerical study of turbulent kinetic energy amplification during shock-wave diffraction
Authors: Pal Ribhu , Roy Arnab , Sarkar Shreyashri , Ghoshal Pratip , Halder Pabitra
Published: January 2024

In this Letter, we are focusing on the understanding of turbulent kinetic energy (TKE) amplification during shock-wave diffraction over a 90° step corner through numerical simulation in OpenFOAM platform. It is observed that TKE amplification is dominant inside the transonic lambda shock, separated shear layer, and primary vortex. Analysis of the turbulence production term, Pk, which appears in the turbulent kinetic energy budget, shows that the term involving production of TKE due to (a) mean shear, Ps, is dominant inside the separated shear layer and (b) streamwise mean flow deceleration, Px, is dominant inside the transonic lambda shock wave.
Estimation of Heisenberg exchange interaction in rigid photoexcited chromophore–radical compound by transient EPR
Authors: Kandrashkin Yuri E.
Published: January 2024

The magnetic field dependence of the spin polarization in a photoexcited rigid chromophore–radical conjugate is theoretically investigated. The excitation of the chromophore–radical conjugate often populates the metastable doublet and quartet states formed by the interactions of the unpaired electrons of the triplet chromophore and the radical. The intensities of the +1/2 ↔ − 1/2 transitions of the doublet and quartet manifolds are sensitive to the ratio jω = 3J/ω0 between the triplet–doublet exchange interaction J and the Zeeman energy ω0. It is shown that the analytical expressions of these intensities previously found for the triplet mechanism of the initial spin polarization can be expanded and applied to a broader class of compounds that may have other intersystem crossing pathways of the depopulation of the excited singlet state of the chromophore. It is also shown that the exchange interaction can be evaluated not only by comparing the electron paramagnetic resonance spectra obtained in different microwave frequency bands but also by comparing the data obtained in the same microwave band but with a shift of the frequency of the resonator. The results obtained broaden the potential applications of the previously proposed approach for analyzing the correlation between the exchange coupling and the distance separating the radical and the chromophore spins, as well as the structure of the bridge connecting their fragments.