bluuebunny/crossref_metadata_2025 huggingface dataset:
Price discovery and volatility spillovers in the interest rate derivatives market
Authors: Chen Congxiao , Chen Wenya , Shang Li , Wang Haiqiao , Tang Decai , Lansana David D.
Published: March 2024

The interest rate derivatives market is an important force in promoting the development of the bond market and is an effective tool to manage interest rate risk. The research on price discovery and volatility spillover of the market can help provide valuable reference information for investors. Based on treasury bond futures and interest rate swaps, the paper aims to discuss the price discovery function and spillover structure of the interest rate derivatives market. The paper establishes the information share model and spillover index model for empirical analysis. The results show that: First, the calculation results of the information share model show that the price discovery of treasury bond futures and interest rate swap markets is stronger than that of the spot market. Second, based on structural break analysis, treasury bond futures and interest rate swaps do not have breakpoints, while the treasury bond spot has three breakpoints. The paper divides the entire sample into four stages based on structural breakpoints and finds that the price discovery ability of the interest rate derivative market dynamically changed. Third, as a net spillover in the market, treasury bond futures have developed relatively stable. Both treasury bond futures and interest rate swaps have spillover effects on the spot market, indicating that China’s interest rate derivatives market can impact the treasury bond spot market.
Physics-based modeling and characterization of low frequency noise behavior for AlxGa1−xN/GaN HEMT
Authors: Cai Jing , Yao Ruo-He , Liu Yu-Rong , Geng Kui-Wei
Published: March 2024

A physics-based low frequency noise (LFN) model for AlxGa1−xN/GaN high electron mobility transistors (HEMTs) is proposed in this article. By treating the distributed low-density surface donor states as the responsible mechanism and exhibiting charge neutrality in combination with the electric field across the barrier layer, a compact expression for Schottky barrier height (SBH) capturing the physics behind the variations of AlxGa1−xN layer thickness is profiled, which incorporates the effect of strain relaxation caused by high Al fraction. Furthermore, the SBH is applied to develop VTH and IDS. The LFN model, dominated by the fluctuations of carriers and drain current in the channel caused by the trapping/detrapping process, is subsequently obtained. It is indicated that the larger threshold voltage, higher drain current, and normalized noise are observed by our model with respect to the traditional SBH expressed only by an interpolated linear function of x. The drain current noise behavior showing the 1/f spectrum down to very low frequencies is seriously subjected to the barrier thickness-dependent SBH of AlxGa1−xN/GaN HEMTs. The accuracy of the proposed model is also verified by comparison with the experimental results from different devices.
On-chip skyrmion synapse regulated by Oersted field
Authors: Qiu Shan , Zeng Junwei , Han Xiaotong , Liu Jiahao
Published: March 2024

Magnetic skyrmions are real-space topological spin textures, which have been frequently discussed in the context of information carriers for energy-efficient and high-integration spintronic memory and computing, such as neuromorphic computing. Toward future applications in neuromorphic computing, the design of efficient and reliable on-chip skyrmion synaptic devices is a crucial requirement, which is yet to be adequately addressed. Here, we propose an on-chip skyrmion artificial synaptic device by integrating an “Ω” shaped on-chip wire with a nanodisk in the wire. By applying current pulses to the wire, the size of the skyrmion in the nanodisk could be adjusted by the generated Oersted fields. Meanwhile, the perpendicular magnetization of the nanodisk varies simultaneously, which can serve as the weight for artificial synapses. Since no current flows through the skyrmion-hosting material, current-generated local heating is avoided, and hysteresis is limited as well. As a consequence, the designed skyrmion artificial synapse allows highly linear responses. In particular, the artificial neural network based on the synapse can achieve an accuracy of more than 95% in performing the handwritten digit recognition task. This study lays a theoretical foundation for the development of highly linear skyrmion-based artificial synaptic devices, which could also be implemented for designing novel on-chip neuromorphic computing devices based on spin textures.
Experimental identification of defect-induced destructive breakdown of AlGaN ultraviolet avalanche photodiodes
Authors: Yang Fan , Yang Fucheng , Xu Jintong , Li Xiangyang
Published: March 2024

The issue of destructive breakdown and high dark current in AlGaN ultraviolet avalanche photodiodes has conventionally been attributed to material defects, yet direct evidence supporting this claim has been absent. Examining damaged devices that experienced destructive breakdown revealed an intriguing finding: post-treatment with a potent alkali resulted in the emergence of corrosion pits on the device’s surface. Subsequently, a dry etching process was implemented in the targeted area to eliminate the corrosion pit. Remarkably, the current–voltage measurement subsequent to this treatment showcased a complete restoration of the damaged device’s previous performance. This unequivocally indicates that the destructive breakdown was localized, and the point of punch-through could be precisely identified through the corrosion pit. Consequently, it is now firmly believed that material defects constitute the primary cause of destructive breakdown in these instances.
Coupled coincidence best proximity point results for generalized Ciric contractions
Authors: Hussain Nawab , Asiri Asim , Shafqat Naeem , Hussain Aftab , Anees Zubair
Published: March 2024

In this paper, we define a generalized Ćiric contraction with respect to ℸ and prove some coupled coincidence best proximity point results in the setting of complete metric spaces. We also obtain some coupled best proximity point results for such contractions. We provide an example for the validity of our main result. Our results are the generalization of many results existing in the literature. As an application, we find the solution of the differential equation.
Navigating challenges in the transition to green transportation: A perception study exploring factors influencing drivers’ intentions for electric vehicle adoption
Authors: Lashram Yasir , Alkabaa Abdulaziz S.
Published: March 2024

Road transportation contributes ∼15% to global carbon emissions, necessitating a shift from fossil fuels to electric vehicles (EVs). In response, global communities and the automotive industry are actively pursuing strategies to phase out traditional vehicles in favor of electric alternatives. This research contributes by identifying and analyzing the significant factors influencing drivers’ perceptions of EV adoption. The study focuses on three primary categories: demographic information, environmental awareness, and factors encouraging or discouraging EV acquisition intent. To achieve these objectives, a survey-based study was conducted among 655 drivers in Saudi Arabia, considering diverse segments of age, gender, and education levels. Employing descriptive statistics, crosstab analysis, and nonparametric statistical tools (Mann–Whitney and Kruskal–Wallis tests), the study reveals substantial findings. Specifically, it highlights a significant gender disparity in perceptions of insufficient EV knowledge, with drivers of higher education exhibiting greater concern for the environmental impact and seeking more information about EVs. Results show a strong association between individuals with higher education levels and a willingness to pay more for an EV. Interestingly, no significant differences are found among different age groups, indicating that regardless of age, EV acquisition intent is associated with gender and education levels. The implications of these findings extend to policymakers, offering guidance on how drivers’ perceptions may influence EV promotion policies. Furthermore, the study enhances understanding of market dynamics surrounding EV adoption, unveiling challenges and opportunities associated with environmental factors.
Recent advances of spectrally selective absorbers: Materials, nanostructures, and photothermal power generation
Authors: Zhou Zhuo-Hao , He Cheng-Yu , Gao Xiang-Hu
Published: March 2024

With the increasing development of photothermal techniques in various fields, particularly concentrated solar power (CSP) systems and solar thermoelectric generators (STEGs), the demand for high-performance spectrally selective absorbers (SSAs) has grown significantly. These SSAs are essential in achieving high solar absorption and minimal infrared thermal loss, thereby significantly enhancing solar utilization efficiency. This need becomes particularly critical in CSP systems, where high temperatures are pivotal for improved efficiency. However, the necessity for high temperatures imposes stringent requirements on the fabrication of SSAs, given the inherent trade-off between optical performance and thermal stability. SSAs typically require nanoscale thin films, but they are prone to oxidation and diffusion at high temperatures. Recent developments in photothermal materials, including ceramic composites, MXenes, high-entropy materials, and graphene, offer promising solutions to enhance SSAs’ performance. This review article provides a comprehensive evaluation of the latest advancements in these emerging photothermal materials. We summarize the strategies for integrating these advanced materials with already established nanostructures, which is a highly promising approach for the development of advanced SSAs. Additionally, the review explores the application of SSAs in CSP systems and STEGs to boost power generation efficiency. We conclude by summarizing the challenges and opportunities in the field of high-temperature SSAs, offering valuable insights into the development of high-performance SSAs and their role in solar-thermal power generation systems.
A new spatial model for tracking plant spore dispersal and disease spread
Authors: Thaweewattananont Jirathun , Zarin Rahat , Humphries Usa Wannasingha , Khan Amir
Published: March 2024

Plant diseases caused by spores can cause severe damage to crop production, resulting in yield losses of up to 75%. Spores can be carried over long distances by wind, water, insects, and humans, meaning that even one infected agricultural field can spread the disease to neighboring fields. Although mathematical models exist to describe the spread of plant diseases, they often do not take into account the transport and location of spores, which limits the ability to make spatial forecasts. To address this limitation, we developed a spatial model based on Healthy sites H, Latent sites L, Infected sites I, Removed sites R, and spore sites X (HLIRX), which describes the spore movement between fields, allowing us to simulate the spatial invasion of plant diseases. We analyzed the existence and stability of steady states in the model using the finite difference method. Our findings reveal that the disease-free equilibrium is unstable, while the boundary and endemic equilibria are asymptotically stable, depending on the spore dispersion term. Moreover, we observed that the dynamics of the population in each field exhibit a consistent pattern, with leftward or rightward shifts depending on the distance from the source of infection, which cannot be captured from the temporal model. We also investigated the impact of two spatial parameters, the dispersal kernel parameter and spore migration rate, and found that both parameters lead to an increase in the number of infected plants but have no significant effect on disease severity. In addition, we discovered that the time until the infected population peaks is linearly related to the distance between each field and the source of infection, with a Pearson correlation coefficient greater than 0.99 (p < 0.001). Our developed model provides a useful tool for studying the spatial dispersion of plant diseases distributed by spores, as it considers the transport and location of spores and can be used to make spatial forecasts.
Optimal allocation method for MIES-based shared energy storage using cooperative game theory and CSP
Authors: Chen Wei , Lu Haonan , Wei Zhanhong
Published: March 2024

To further promote the efficient use of energy storage and the local consumption of renewable energy in a multi-integrated energy system (MIES), a MIES model is developed based on the operational characteristics and profitability mechanism of a shared energy storage station (SESS), considering concentrating solar power (CSP), integrated demand response, and renewable energy output uncertainty. We propose a corresponding MIES model based on co-operative game theory and the CSP and an optimal allocation method for MIES shared energy storage. The model considers the maximum operating benefit of the SESS as the upper objective function and the minimum operating cost of the MIES as the lower objective function. First, the Karush–Kuhn–Tucker conditions of the lower-layer model are transformed into constraints of the upper-layer model, and the Big-M method is used to linearize the nonlinear problem and convert the two-layer nonlinear model into a single-layer linear model. Second, based on the Nash negotiation theory, the benefits of each IES in the MIES are allocated. Finally, the fuzzy chance constraints are used to relax the power balance constraints, and the trapezoidal fuzzy numbers are transformed into a deterministic equivalence class to assess the impact of renewable energy output uncertainty on system operation. The validity and rationality of the proposed two-layer model are verified through simulation, and the results demonstrate that the proposed shared storage capacity leasing model can effectively reduce the total operation cost, increase the profitability of the shared storage operator, and increase the utilization rate of the SESS.
Reducing leakage current in GaN-Schottky diodes by suppressing hollow core nanopipes
Authors: Yang Qian , Yang Jing , Long Haoran , Liu Zongshun , Duan Lihong , Zhao Degang
Published: March 2024

The nanopipes in GaN films grown on sapphire substrates using metal-organic chemical vapor deposition were identified as leakage-related defects through investigations by PeakForce tunneling atomic force microscopy. An insertion layer of n-Al0.03Ga0.97N can prevent nanopipes from extending, thereby reducing the leakage current of Schottky diodes. By analyzing the element’s distribution in and out of nanopipes on epitaxial wafers, it is inferred that segregation of Ga around nanopipes may be responsible for the leakage.
Simultaneous diversity-oriented synthesis of benzothiazoles and related diverse analogues by iodine-catalyzed intramolecular cyclization from identical substrates
Authors: Cui Meng , Wang Xue-Lin , Wang Mengzhou , Xie Jian-Wu
Published: March 2024

A facile oxidative cyclization of β-ketothioamides for the simultaneous formation of a compound library similar to natural product benzothiazole derivatives has been developed. The oxidative cyclization of β-ketothioamides resulted in the simultaneous formation of four classes of previously unknown benzothiazole derivatives. This chemistry’s versatility adds a valuable component to the methodology for obtaining benzothiazole derivatives.
Cationic cholesterol-dependent LNP delivery to lung stem cells, the liver, and heart
Authors: Radmand Afsane , Kim Hyejin , Beyersdorf Jared , Dobrowolski Curtis N. , Zenhausern Ryan , Paunovska Kalina , Huayamares Sebastian G. , Hua Xuanwen , Han Keyi , Loughrey David , Hatit Marine Z. C. , Del Cid Ada , Ni Huanzhen , Shajii Aram , Li Andrea , Muralidharan Abinaya , Peck Hannah E. , Tiegreen Karen E. , Jia Shu , Santangelo Philip J. , Dahlman James E.
Published: March 2024

Adding a cationic helper lipid to a lipid nanoparticle (LNP) can increase lung delivery and decrease liver delivery. However, it remains unclear whether charge-dependent tropism is universal or, alternatively, whether it depends on the component that is charged. Here, we report evidence that cationic cholesterol-dependent tropism can differ from cationic helper lipid-dependent tropism. By testing how 196 LNPs delivered mRNA to 22 cell types, we found that charged cholesterols led to a different lung:liver delivery ratio than charged helper lipids. We also found that combining cationic cholesterol with a cationic helper lipid led to mRNA delivery in the heart as well as several lung cell types, including stem cell-like populations. These data highlight the utility of exploring charge-dependent LNP tropism.
Programming crystallization kinetics of self-assembled DNA crystals with 5-methylcytosine modification
Authors: Chen Jielin , Dai Zheze , Lv Hui , Jin Zhongchao , Tang Yuqing , Xie Xiaodong , Shi Jiye , Wang Fei , Li Qian , Liu Xiaoguo , Fan Chunhai
Published: March 2024

Self-assembled DNA crystals offer a precise chemical platform at the ångström-scale for DNA nanotechnology, holding enormous potential in material separation, catalysis, and DNA data storage. However, accurately controlling the crystallization kinetics of such DNA crystals remains challenging. Herein, we found that atomic-level 5-methylcytosine (5mC) modification can regulate the crystallization kinetics of DNA crystal by tuning the hybridization rates of DNA motifs. We discovered that by manipulating the axial and combination of 5mC modification on the sticky ends of DNA tensegrity triangle motifs, we can obtain a series of DNA crystals with controllable morphological features. Through DNA-PAINT and FRET-labeled DNA strand displacement experiments, we elucidate that atomic-level 5mC modification enhances the affinity constant of DNA hybridization at both the single-molecule and macroscopic scales. This enhancement can be harnessed for kinetic-driven control of the preferential growth direction of DNA crystals. The 5mC modification strategy can overcome the limitations of DNA sequence design imposed by limited nucleobase numbers in various DNA hybridization reactions. This strategy provides a new avenue for the manipulation of DNA crystal structure, valuable for the advancement of DNA and biomacromolecular crystallography.
RNA-catalyzed evolution of catalytic RNA
Authors: Papastavrou Nikolaos , Horning David P. , Joyce Gerald F.
Published: March 2024

An RNA polymerase ribozyme that was obtained by directed evolution can propagate a functional RNA through repeated rounds of replication and selection, thereby enabling Darwinian evolution. Earlier versions of the polymerase did not have sufficient copying fidelity to propagate functional information, but a new variant with improved fidelity can replicate the hammerhead ribozyme through reciprocal synthesis of both the hammerhead and its complement, with the products then being selected for RNA-cleavage activity. Two evolutionary lineages were carried out in parallel, using either the prior low-fidelity or the newer high-fidelity polymerase. The former lineage quickly lost hammerhead functionality as the population diverged toward random sequences, whereas the latter evolved new hammerhead variants with improved fitness compared to the starting RNA. The increase in fitness was attributable to specific mutations that improved the replicability of the hammerhead, counterbalanced by a small decrease in hammerhead activity. Deep sequencing analysis was used to follow the course of evolution, revealing the emergence of a succession of variants that progressively diverged from the starting hammerhead as fitness increased. This study demonstrates the critical importance of replication fidelity for maintaining heritable information in an RNA-based evolving system, such as is thought to have existed during the early history of life on Earth. Attempts to recreate RNA-based life in the laboratory must achieve further improvements in replication fidelity to enable the fully autonomous Darwinian evolution of RNA enzymes as complex as the polymerase itself.
Asymmetric optical transmission through periodic metallic hemisphere arrays on the transparent substrates
Authors: Yang Hua , Lou Chaogang , Huang Xiaodan
Published: March 2024

Asymmetric optical transmission is useful in various fields such as electromagnetic shielding, photovoltaic devices, and optical diodes owing to its directional selectivity for light. This work theoretically investigates asymmetric optical transmission by the periodic metallic hemisphere arrays on the transparent substrates. It is found that the formation of asymmetric optical transmission can be attributed to two aspects: the difference in the driving electric field and the first-order diffraction of the arrays. The maximum asymmetric optical transmission results from the match between the resonance wavelength of the arrays and the cut-off wavelength of the first-order diffraction inside the substrates. The bandwidth of asymmetric optical transmission is determined by the cut-off wavelength of the first-order diffraction inside the substrates. In addition, the effects of the structural parameters, including the radius of the metallic hemisphere and the material of the transparent substrate, on the maximum asymmetric optical transmission and the bandwidth are studied. This work provides design guidelines for practical devices to apply asymmetric optical transmission.
Development and evaluation of immersive VR laboratories of organic chemistry and physics for students education
Authors: Naz Zubaira , Azam Ayesha , Khan Muhammad Usman Ghani , Saba Tanzila , Al-Otaibi Shaha , Rehman Amjad
Published: March 2024

In science education, the use of laboratory experiments has a critical role. However, experiments can cause excessive material waste, and safety issues must be taken seriously. Virtual laboratories and simulations have become a useful and effective alternative to in-person, hands-on laboratories as a result of the educational possibilities afforded by information and communication technology. With virtual reality (VR), students can depict scientific phenomena through virtual practical experiments that use computer simulation. In this work, VR-based lab simulations of physics and chemistry experiments were introduced. Chemistry lab includes 3 experiments from organic chemistry (identify aldehydes using Tollen’s test, identify ketones using the 2,4-dinitrophenyl hydrazine test, and identify carboxylic acids using the sodium carbonate test) and physics lab includes 2 experiments on series and parallel current, accomplished through the use of the real-time 3D graphics and pre-rendered animations. Further, to assess the usability of the developed system, 20 students were surveyed as research subjects and they filled out the SUS survey after conducting the VR experiments in Oculus Quest 2. . The average score for the VR chemistry lab simulations was 92.63%, and, the average score for the physics lab was 93.38%, indicating a high level of performance and achievement among the participants. Further, in the comparative study evaluating knowledge retention and learning experience, the experimental group (VR, N=20) outperformed the control group (traditional, N=13), indicating a more favorable learning experience. All participants from the experiment group reported that virtual labs were easy to use. Overall, findings from the Knowledge Retention survey show that interactive laboratory activities enhance students’ understanding of chemical processes and practical skills.
Comprehensive DFT investigation of ternary thallium tetragonal crystals: assessing their viability for solar cell applications
Authors: Helaimia T , Maabed S , Benmakhlouf A , Bouhemadou A , Fares F , Bouchenafa M , Bentabet A , Bin-Omran S
Published: March 2024

To ascertain the suitability of the TlInX2 (X = S, Se, Te) tetragonal structures for photovoltaic applications, first-principles calculations were carried out using the pseudopotential plane wave method to assess the structural, electronic, elastic, and optical characteristics of the considered compounds via the DFT software CASTEP. For all three compounds, our calculated structural parameters were in excellent agreement with both the experimental and previous theoretical results. Our calculations provided the first predicted elastic constants for the TlInS2, TlInSe2 and TlInTe2 compounds. The three tetragonal systems were mechanically stable and exhibited pronounced and noticeable elastic anisotropy. Analysis of the optical properties revealed that TlInX2 (X = S, Se, Te) exhibited distinct absorption in the ultraviolet radiation range and pronounced optical anisotropy. The calculated bandgap values obtained using the HSE06 hybrid functional were 1.68 eV, 1.38 eV, and 1.36 eV for TlInS2, TlInSe2 and TlInTe2, respectively. These findings are of significant interest because they categorize all three compounds as promising candidates for use in photovoltaic cell applications.
Quasiparticles for the one-dimensional nonlocal Fisher-Kolmogorov-Petrovskii-Piskunov equation
Authors: Kulagin Anton E , Shapovalov Alexander V
Published: March 2024

We construct quasiparticles-like solutions to the one-dimensional Fisher-Kolmogorov-Petrovskii-Piskunov (FKPP) with a nonlocal nonlinearity using the method of semiclassically concentrated states in the weak diffusion approximation. Such solutions are of use for predicting the dynamics of population patterns using analytical or semi-analytical approach. The interaction of quasiparticles stems from nonlocal competitive losses in the FKPP model. We developed the formalism of our approach relying on ideas of the Maslov method. The construction of the asymptotic expansion of a solution to the original nonlinear evolution equation is based on solutions to an auxiliary dynamical system of ODEs. The asymptotic solutions for various specific cases corresponding to various spatial profiles of the reproduction rate and nonlocal competitive losses are studied within the framework of the approach proposed.
Innovative approaches to high school physics competitions: Harnessing the power of AI and open science
Authors: Borovský D , Hanč J , Hančová M
Published: March 2024

High school physics competitions serve as a platform for talented students to showcase their skills, engage in challenging problems, and foster a passion for science. This paper explores innovative approaches to enhance these competitions by harnessing the power of open science and artificial intelligence (AI) tools. Particularly we delve into the capabilities of state-of-the-art AI chatbots, i.e. ChatGPT, Bard, Claude, related to problem solving in physics. Together with open science tools like SageMath and Jupyter AI, they have the potential to serve as intelligent, powerful co-pilots, tutors, and assistants in understanding and applying physics, as well as knowledge from connected STEM fields. Furthermore, these innovative approaches can revolutionize high school physics competitions, providing students and their tutors with powerful resources to excel in their scientific pursuits.
Blended learning: A data-literate science teacher is a better teacher
Authors: Hanč J , Borovský D , Hančová M
Published: March 2024

The COVID-19 pandemic has underscored the importance of blended learning in contemporary physics and, more generally, STEM education. In this contribution, we summarize current pedagogical models of blended learning, such as rotational and flexible non-rotational models, and customizable configurations of physical and virtual learning spaces. With the inevitable integration of digital technology as one of the pillars of blended learning, teachers find themselves in an unprecedented position to not only obtain data more frequently but also analyze it and adjust instruction accordingly. Consequently, we discuss a crucial element of blended learning effectiveness: data management and usage. In this context, data literacy for teaching emerges as an essential skill for effective blended learning, encompassing the ability to transform various data types into actionable instructional knowledge and practices. In other words, current research in physics education shows that a data-literate science teacher is a more prosperous and effective teacher.
Adding more coherent light to the education
Authors: Šebelík V
Published: March 2024

The laser technology and its usage are often neglected in physics courses at high schools. However, not only Generation Z but also the subsequent generations will be surrounded by technologies using (albeit covertly) lasers. It is desirable that students know about this technology and are able to use it. There are a plethora of STEM experiments that can be done with the help of laser light. We successfully demonstrate some of these experiments together with a short presentation about laser principles to high school students who visit our faculty as part of various events. These experiments can also be performed in high schools, each of them showing one or more of the three basic features of laser light - coherence, monochromaticity, and directionality.
Study of circular and rotational motion with the help of experimentation and mathematical modeling enhanced by digital technologies
Authors: Kotvytska Klavdiia , Ješková Zuzana
Published: March 2024

Circular and rotational motion belongs to basic topics studied at upper secondary school and courses on Mechanics at University. Many studies show problems in understanding basic concepts related to kinematics and dynamics of these motions. In this paper we present a series of inquiry activities aimed at developing the understanding of these concepts and the laws of circular and rotating motion with the effective use of digital technologies. The activity on the videomeasurement of a uniform and decelerating bicycle wheel motion analyses the basic kinematic concepts. In the experiments carried out with the help of a centripetal force apparatus with the rotating system of carriages, the dynamics of circular motion can be investigated by observing and analysing the effect of various parameters on the centripetal force acting on the carriage. In addition to that, a mathematical model for decelerated motion of a bicycle wheel and a carriage can be designed. By manipulating and simulating the model for different parameters the best correspondence with experimental data can be found. The activities can be implemented at confirmation or guided inquiry level. Applying experimental as well as modelling approach to answer research questions students learn how science and physicists work.
Active learning in STEM education
Authors: Ješková Zuzana , Šnajder Ľubomír , Guniš Ján
Published: March 2024

Although inquiry-based learning originated in physics and science education, where students are involved in authentic scientific practices, it also occurs in mathematical or technological contexts. This approach to learning mirrors the procedure and thinking that scientists, engineers, and innovators use in the real world. As a result, inquiry-based learning naturally suits to related disciplines such as science, technology, engineering and mathematics or STEM disciplines. In this paper we present examples of STEM related projects designed for students in order to solve real-life problems using digital technologies to support inquiry represented by modelling or experimental approach. Examples of interdisciplinary projects involve motion of sportsmen, sky or scuba divers, or solving other problems using various programming platforms. Students working on interdisciplinary projects effectively use and deepen their knowledge from different subjects and develop skills to use smart technologies and coding. As a result, they move from the role of passive users to active learners and designers.
Is there a difference in the education of generations across time?
Authors: Spodniaková Pfefferová M , Hruška M , Raganová J , Holec S
Published: March 2024

An interesting reading tends to be a summary of the dominant characteristics of each generation, which can be found in scientific and vocational publications as well as in media with popularization texts. Very often, we also identify among them our own characteristics and qualities, or those of our peers, children, and possibly other descendants. It is natural that the development of science and technology has a significant role in shaping the personality profile of the members of each generation during the historical development of society (for example, from the “lost” generation to the “alpha” generation). This factor influences the content, methodological and didactic aspects of the teaching process, i.e. what and how to teach. The authors of the paper have worked on several aspects of the preparation of teaching materials and their use in school physics, often with overlap with other science subjects. One of these aspects is, for example, the need to influence the emotional side of the student in learning processes, which is an important prerequisite for more permanent “inscriptions” of information in the student’s memory. For this process to work, knowledge of the dominant characteristics of the target group of students and the environment in which they grow up is essential.
Rotational complexity across US counties is currently insufficient to observe yield gains in major crops
Authors: Burchfield Emily K , Crossley Michael S , Nelson Katherine S
Published: March 2024

Landscape complexity promotes ecosystem services and agricultural productivity, and often encompasses aspects of compositional or configurational land cover diversity across space. However, a key agricultural diversification practice, crop rotation, extends crop land cover complexity concurrently across space and time. Long-term experiments suggest that complex crop rotations can facilitate yield increases in major crops. Using a compiled county-annual panel dataset, we examined whether yield benefits of crop rotational complexity were apparent on a landscape scale in the conterminous US for four major crops between 2008 and 2020. We found that the benefit of rotational complexity was only apparent for cotton and winter wheat, and that the benefit for wheat was driven by one region. Corn exhibited the opposite pattern, wherein higher yields were consistently obtained with lower rotational complexity, while soybean yield appeared relatively insensitive to rotational complexity. Effects of rotational complexity were sometimes influenced by agrochemical usage. Positive effects of rotational complexity were only apparent with high fertilizer for soybean and wheat, and with low fertilizer for cotton. Corn yield in high-complexity, low-yielding counties appeared to improve with high fertilizer inputs. For the overwhelming majority of acres growing these major crops, crop rotation patterns were quite simple, which when combined with the short time span of available data, may explain the apparent discrepancy between long-term experiments and nationwide data. Current demand and incentives that promote highly intensified and specialized agriculture likely hinder realization of the benefits of rotational complexity for production of key crops in the US. Increasing rotational complexity where major crops are grown thus remains an underutilized approach to mitigate landscape simplification and to promote ecosystem services and crop yields.
Quercetin-coated biogenic selenium nanoparticles: synthesis, characterization, and in-vitro antioxidant study
Authors: Alex Ashika , Biju Tina Sara , Francis Arul Prakash , Veeraraghavan Vishnu Priya , Gayathri R , Sankaran Kavitha
Published: March 2024

In recent years, the interest in environmentally friendly and sustainable methods for producing nanoparticles has grown significantly due to their potential benefits. Among these nanoparticles, selenium nanoparticles (SeNPs) have gained attention for their potential applications in biomedicine. This research sheds light on the feasibility of eco-friendly synthesis approaches for generating quercetin-coated selenium nanoparticles (DQSN) and their potential applications in the field of biomedicine. The main objective of this study is to develop a green synthesis technique for SeNPs using Diospyros ebenum extract as a natural reducing agent and quercetin as a capping agent. The synthesised nanoparticles were subjected to a range of characterisation techniques including UV–vis spectroscopy, X-ray diffraction, Fourier-transform infrared spectroscopy, scanning electron microscopy, and energy-dispersive x-ray analysis. The antioxidant assay was employed to evaluate nanoparticle’s bioactivity. The results revealed the successful synthesis of DQSN with comprehensive characterisation confirming their morphology, crystallinity, functionalisation, elemental composition, size, and stability. In vitro, bioactivity studies demonstrated substantial antioxidant activity through DPPH radical scavenging. These findings underscore the potential utility of DQSN as promising candidates for biomedical applications; however, further extensive investigations are essential to ascertain their complete efficacy and toxicity profiles.
Mechanism of simultaneous photocatalytic degradation of Rhodamine B and Cr(VI) under visible light using WO3 nanotubes
Authors: Do T Anh Thu , Nguyen Duc Toan , Ho Truong Giang , Giang Hong Thai , Pham Quang Ngan , Nghiem T Ha Lien , Nguyen Trung Hieu , Man Minh Tan
Published: March 2024

A hydrothermal method was used to synthesise WO3 nanotubes, which were analysed using transmission electron microscopy (TEM), x-ray diffraction (XRD), Raman, and UV–Vis spectroscopy for morphological, structural, and optical properties. TEM revealed nanotubes several micrometers long with a diameter of 10–15 nm. These nanotubes effectively removed Rhodamine B (RhB) and Cr(VI) under visible light. The high photocatalytic efficiency of obtained WO3 material was attributed to the large surface area provided by the unique configuration in the form of nanotubes. The study identified reactive species through scavenger tests and proposed a photocatalytic mechanism. This approach offers efficient photocatalysts for the simultaneous sunlight-driven degradation of organic and inorganic pollutants in wastewater.
Automatic thoracic aorta calcium quantification using deep learning in non-contrast ECG-gated CT images
Authors: Guilenea Federico N , Casciaro Mariano E , Soulat Gilles , Mousseaux Elie , Craiem Damian
Published: March 2024

Thoracic aorta calcium (TAC) can be assessed from cardiac computed tomography (CT) studies to improve cardiovascular risk prediction. The aim of this study was to develop a fully automatic system to detect TAC and to evaluate its performance for classifying the patients into four TAC risk categories. The method started by segmenting the thoracic aorta, combining three UNets trained with axial, sagittal and coronal CT images. Afterwards, the surrounding lesion candidates were classified using three combined convolutional neural networks (CNNs) trained with orthogonal patches. Image datasets included 1190 non-enhanced ECG-gated cardiac CT studies from a cohort of cardiovascular patients (age 57 ± 9 years, 80% men, 65% TAC > 0). In the test set (N = 119), the combination of UNets was able to successfully segment the thoracic aorta with a mean volume difference of 0.3 ± 11.7 ml (<6%) and a median Dice coefficient of 0.947. The combined CNNs accurately classified the lesion candidates and 87% of the patients (N = 104) were accurately placed in their corresponding risk categories (Kappa = 0.826, ICC = 0.9915). TAC measurement can be estimated automatically from cardiac CT images using UNets to isolate the thoracic aorta and CNNs to classify calcified lesions.
An iterative deep learning procedure for determining electron scattering cross-sections from transport coefficients
Authors: Muccignat Dale L , Boyle Gregory G , Garland Nathan A , Stokes Peter W , White Ronald D
Published: March 2024

We propose improvements to the artificial neural network (ANN) method of determining electron scattering cross-sections from swarm data proposed by coauthors. A limitation inherent to this problem, known as the inverse swarm problem, is the non-unique nature of its solutions, particularly when there exists multiple cross-sections that each describe similar scattering processes. Considering this, prior methods leveraged existing knowledge of a particular cross-section set to reduce the solution space of the problem. To reduce the need for prior knowledge, we propose the following modifications to the ANN method. First, we propose a multi-branch ANN (MBANN) that assigns an independent branch of hidden layers to each cross-section output. We show that in comparison with an equivalent conventional ANN, the MBANN architecture enables an efficient and physics informed feature map of each cross-section. Additionally, we show that the MBANN solution can be improved upon by successive networks that are each trained using perturbations of the previous regression. Crucially, the method requires much less input data and fewer restrictive assumptions, and only assumes knowledge of energy loss thresholds and the number of cross-sections present.
A simple and highly efficient approach towards the degradation of methylene blue and study the impact of degraded water on seed germination of cicer arietinum
Authors: Ahlawat Amit , Rana Pawan S , Solanki Pratima R
Published: March 2024

The scarcity of fresh air, drinking water, and soil is a matter of serious concern worldwide owing to the presence of organic pollutants in the environment. The organic dye, such as methylene blue (MB) have enormous toxic effects on the environment and human health. Therefore, the degradation of non-biodegradable dyes is very important to reduce toxicity in water and-a step towards waste water management systems. This paper focuses on the degradation of non-biodegradable MB dye using carbon quantum dots (CQDs). CQDs were synthesized by a microwave irradiation method using citric acid and L-cysteine as precursor and confirmed by X-Ray Diffraction (XRD), Raman Spectrum, Fourier Transform Infrared Spectroscopy (FTIR) and Energy Dispersive x-ray (EDX) spectroscopy techniques. The optical properties of the synthesized CQDs of 2.56 nm, were investigated by UV-visible spectroscopy technique and the absorption peak appeared at 340 nm which corresponding to n → π* transition. In photoluminescence (PL) spectra analysis, the highest emission peak was obtained at 440 nm when excited at 345 nm. The synthesized CQDs were used for the dye degradation of MB in distilled water and degradation percentage was calculated and found to be 99.17% in 90 min under UV light irradiation. Also, studied the impact of degraded water in seed germination of Cicer arietinum (black gramme) and calculated the seed germination growth rate in degraded water was found to be 15%–20% more than the seed germination growth rate in MB containing dye water.
Green synthesis of silver nanoparticles using olive mill wastewater and olive stones extract and testing their antimicrobial activities against Escherichia coli and Staphylococcus epidermidis
Authors: Rigopoulos Nickolas , Gkaliouri Christina Megetho , Ioannou Zacharias , Giaouris Efstathios , Sakavitsi Viktoria , Gournis Dimitrios
Published: March 2024

Plant mediated synthesis of silver nanoparticles is eco-friendly and of low cost. The synthesis involves a reduction of silver ions and is controlled by several independent factors. In this work, silver nanoparticles (AgNPs) were successfully synthesized using olive stone extract (OSE) and olive mill wastewater (OMW) extract. The nanoparticle synthesis was monitored using the plasmon resonance observed in the UV–Vis absorption spectrum, in which a Voigt profile was fitted. The peak wavelength (λ
0), the peak area (A), and the Full Width at Half Maximum (FWHM) were the fitting parameters and were used as the response. The independent factors were the incubation temperature, the incubation time, the silver nitrate, extract, and sodium hydroxide concentrations. The influence of these factors was investigated ‘two factor at a time’, using interaction plots. Strong interaction was observed between all factors, with sodium hydroxide to have a crucial role. The optimum conditions for silver nanoparticle formation were a) OSE (1% v/v), AgNO3 (2 mM), and NaOH (0.2 mM), and b) OMW (2% v/v), AgNO3 (1 mM), and NaOH (7.9 mM), showing an absorption maximum at 414 nm, and 410 nm, respectively. The mean diameter of AgNPs using OMW, measured with Transmission Electron Microscopy was

12.87
±
4.84

nm. Both types of AgNPs showed antibacterial action against Staphylococcus epidermidis (S. epidermidis) and Escherichia coli (E. coli), using the broth microdilution assay. Both nanoparticle types inhibited bacterial growth up to one dilution higher than reference samples.
Innovative super-resolution in spatial transcriptomics: a transformer model exploiting histology images and spatial gene expression
Authors: Zhao Chongyue , Xu Zhongli , Wang Xinjun , Tao Shiyue , MacDonald William A , He Kun , Poholek Amanda C , Chen Kong , Huang Heng , Chen Wei
Published: March 2024

Spatial transcriptomics technologies have shed light on the complexities of tissue structures by accurately mapping spatial microenvironments. Nonetheless, a myriad of methods, especially those utilized in platforms like Visium, often relinquish spatial details owing to intrinsic resolution limitations. In response, we introduce TransformerST, an innovative, unsupervised model anchored in the Transformer architecture, which operates independently of references, thereby ensuring cost-efficiency by circumventing the need for single-cell RNA sequencing. TransformerST not only elevates Visium data from a multicellular level to a single-cell granularity but also showcases adaptability across diverse spatial transcriptomics platforms. By employing a vision transformer-based encoder, it discerns latent image-gene expression co-representations and is further enhanced by spatial correlations, derived from an adaptive graph Transformer module. The sophisticated cross-scale graph network, utilized in super-resolution, significantly boosts the model’s accuracy, unveiling complex structure–functional relationships within histology images. Empirical evaluations validate its adeptness in revealing tissue subtleties at the single-cell scale. Crucially, TransformerST adeptly navigates through image-gene co-representation, maximizing the synergistic utility of gene expression and histology images, thereby emerging as a pioneering tool in spatial transcriptomics. It not only enhances resolution to a single-cell level but also introduces a novel approach that optimally utilizes histology images alongside gene expression, providing a refined lens for investigating spatial transcriptomics.