bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genome-wide association studies identifies genetic loci related to fatty acid and branched-chain amino acid metabolism and histone modifications under varying nitrogen treatments in safflower (Carthamus tinctorius)
Authors: Ali Fawad , Arif Mian A. R. , Ali Arif , Nadeem Muhammad A. , Aksoy Emre , Bakhsh Allah , Khan Shahid U. , Kurt Cemal , Tekdal Dilek , Ilyas Muhammad K. , Hameed Amjad , Chung Yong S. , Baloch Faheem S. 
Published: April 2024

Effective identification and usage of genetic variation are prerequisites for developing nutrient-efficient cultivars. A collection of 94 safflower (Carthamus tinctorius) genotypes (G) was investigated for important morphological and photosynthetic traits at four nitrogen (N) treatments. We found significant variation for all the studied traits except chlorophyll b (chl b) among safflower genotypes, nitrogen treatments and G × N interaction. The examined traits showed a 2.82–50.00% increase in response to N application. Biological yield (BY) reflected a significantly positive correlation with fresh shoot weight (FSW), root length (RL), fresh root weight (FRW) and number of leaves (NOL), while a significantly positive correlation was also observed among carotenoids (C), chlorophyll a (chl a), chl b and total chlorophyll content (CT) under all treatments. Superior genotypes with respect to plant height (PH), FSW, NOL, RL, FRW and BY were clustered into Group 3, while genotypes with better mean performance regarding chl a, chl b C and CT were clustered into Group 2 as observed in principal component analysis. The identified eight best-performing genotypes could be useful to develop improved nitrogen efficient cultivars. Genome-wide association analysis resulted in 32 marker-trait associations (MTAs) under four treatments. Markers namely DArT-45481731, DArT-17812864, DArT-15670279 and DArT-45482737 were found consistent. Protein–protein interaction networks of loci associated with MTAs were related to fatty acid and branched-chain amino acid metabolism and histone modifications.
The danger of the spread of
Ralstonia solanacearum
on potato crops worldwide and potential mitigation options
Authors: Okiro Lilian A. , Mulwa Richard M. , Oyoo Maurice E. , Nyalala Samuel 
Published: April 2024

Abstract

Potato is a major crop that is consumed by over one billion people worldwide. However, production is hampered by diseases such as viral infections, late blight, and bacterial wilt. Bacterial wilt disease caused by
Ralstonia solanacearum
is the second most prevalent disease after blight, and its effects are exacerbated by both global trade and climate change. The extent of the disease devastation varies by country, with more serious consequences evident in major potato-producing countries. The
Ralstonia
species complex (RSSC) is a group of pathogenic strains that spread through the use of infected seed potato, soils, water run-offs, plant debris, or contaminated farm equipment and propagation material. The elements that contribute to the rapid spread of bacterial wilt disease in potato are discussed in this review article, and a disease-control strategy is proposed. Understanding how
R. solanacearum
spreads through international trade is critical for developing effective mitigation and management techniques to control and limit the spread of this damaging phytopathogen.
Master constraint approach to quantum-reduced loop gravity
Authors: Mäkinen Ilkka 
Published: April 2024

Abstract
We introduce a master constraint operator on the kinematical Hilbert space of loop quantum gravity representing a set of gauge conditions which classically fix the densitized triad to be diagonal. We argue that the master constraint approach provides a natural and systematic way of carrying out the quantum gauge-fixing procedure which underlies the model known as quantum-reduced loop gravity. The Hilbert space of quantum-reduced loop gravity is obtained as a particular space of solutions of the gauge-fixing master constraint operator. We give a concise summary of the fundamental structure of the quantum-reduced framework, and consider several possible extensions thereof, for which the master constraint formulation provides a convenient starting point. In particular, we propose a generalization of the standard Hilbert space of quantum-reduced loop gravity, which may be relevant in the application of the quantum-reduced model to physical situations in which the Ashtekar connection is not diagonal.
Mitigating waveguide loss in Ge–Sb–Se chalcogenide glass photonics
Authors: Han Fengbo , Niu Yunfei , Zhang Yan , Gong Jue , Yu Shaoliang , Du Qingyang 
Published: April 2024

Abstract
Minimizing propagation loss within waveguides remains a central objective across diverse photonic platforms, impacting both linear lightwave transmission and nonlinear wavelength conversion efficiencies. Here, we present a method to mitigate waveguide loss in Ge28Sb12Se60 chalcogenide glass, a material known for its high nonlinearity, broad mid-infrared transparency, and significant potential for mid-IR photonics applications. By applying a sacrifical oxide layer to eliminate etching residues and a subsequent waveguide thermal reflow to smooth lithography-induced line edge roughness, we successfully reduced the waveguide loss down to 0.8 dB cm−1 at 1550 nm wavelength. This represents the best result in small-core and high-index-contrast Ge28Sb12Se60 channel waveguides. Our approach paves the way for low-loss, on-chip chalcogenide photonic devices.
Broad band modulation of two-dimensional Mo1-x
W
x
S2 by variational compositions
Authors: Huang Zuqiang , Zhao Hongquan , Liu Shaoxiang , Liang Xianxiao , Chen Yin , Wu Zepeng , Liu Xiu , Yuan Hongkuan , Wang Chunxiang , Shi Xuan 
Published: April 2024

Abstract
Precisely tuning bandgap enables tailored design of materials, which is of crucial importance for optoelectronic devices. Towards this end, ternary Mo1-x
W
x
S2 monolayers with continually variational transition metal compositions are synthesized by precisely control of the precursors and growth temperatures in the chemical vapor deposition process, and thus to manipulate the bandgap of the monolayers. Energy dispersive x-ray spectroscopy demonstrates that the composition of the ternary Mo1-x
W
x
S2 monolayers can be effectively modulated by the precursors and synthesizing temperatures. Frequency and intensity of the Raman and photoluminescent peaks of the Mo1-x
W

x

S2 monolayers are continually modulated by the variational Mo and W compositions. The maximum of 0.148 eV bandgap modulation is achieved by modulating the transition metal compositions, which is highly consistent to the calculated 0.158 eV by first-principles theory. Photodetectors based on the Mo1-x
W
x
S2 monolayers are fabricated and U-shape of photoresponse characteristics are demonstrated as x change from 0 to 1 under the same measurement conditions. The estimated photocurrent, photoresponsivity and external quantum efficiency show that the minimum values appear at the composition of x = 0.5, while the maximum values appear at x = 1. The results illustrate an excellent level of control on the band structure of two-dimensional ternary Mo1-x
W
x
S2 by precisely control of the transition metal compositions.
Plasma-deposited reactive species assisted synthesis of colloidal zinc-oxide nanostructures
Authors: Kutasi Kinga , Péter László , Tóth Zsolt 
Published: April 2024

Abstract
A surface-wave microwave discharge is applied to deposit reactive oxygen and nitrogen species (RONS) into the liquid subsequently used as a medium for laser ablation of a Zn metallic target. It is shown that during laser ablation in plasma-treated liquids the H2O2 concentration decreases, while in deionized water (DIW) significant H2O2 is produced. Meanwhile, the pH—initially adjusted by applying reductive metals—increases in the acidic liquids and decreases in the alkaline ones. During months of storage the pH of colloids stabilize around pH 6, which insures the long-term stability of RONS. It is demonstrated that in DIW metallic Zn NPs are created, which gradually oxidize during storage, while in the plasma-treated liquids ZnO NPs are produced with the mean size of 18 nm. In the alkaline plasma-treated liquid the NPs form large aggregates, which slows the dissolution of NPs. In the acidic and neutral solutions besides NPs nanosheets are also formed, which during storage evolve into nanosheet networks as a result of the dissolution of NPs. The band gap of the colloidal ZnO is found to decrease with the formation of aggregates and nanosheet networks. The ZnO NPs ablated in plasma-treated liquids exhibit a high-intensity visible emission covering the green-to-red spectral region. The photoluminescence spectra is dominated by the orange-red emission—previously not detected in the case of laser-ablated ZnO NPs and attributed to the interstitial Zn and oxygen sites—and the yellow emission, which can be attributed to the OH groups on the surface. It is shown that during months of storage, due to the dissolution of NPs and formation of nanosheets, the intensity of the visible emission decreases and shifts to the blue-green spectral region.
Carbon nanostructures synthesis by catalyst-free atmospheric pressure plasma jet
Authors: Neira-Velázquez María Guadalupe , Ku-Herrera José de Jesús , Narro-Céspedes Rosa Idalia , Flores-Villaseñor Sergio Enrique , Cortez-Garza Yuvicela Leticia , Cuellar-Gaona Claudia Gabriela , Soria-Arguello Gustavo 
Published: April 2024

Abstract
In this study, carbon nanostructures were synthesized utilizing a warm plasma jet at atmospheric pressure in a continuous and catalyst-free process. The procedure and apparatus were designed and constructed in our laboratory. Plasma was generated with 600 W of electrical energy, using a high-voltage, high-frequency alternating current power source. The working gas utilized was a propane/butane mixture, with a concentration ratio of 60:40, respectively. A production rate of 300 mg min−1 of powdered material was achieved, with a particle size between 20 and 100 nm. The product was characterized by Fourier transform infrared spectroscopy, thermogravimetric analysis, Raman spectroscopy, x-ray diffraction, and transmission electron microscopy. Results show the formation of multilayer carbon nanostructures with a low content of functional groups; the obtained material presented structural defects and amorphous carbon. This work demonstrates that, with adequate control, warm plasma jet discharges can be employed for the synthesis of carbon nanostructures. The process is scalable and can be utilized for hydrocarbon reforming and hydrogen production. However, further studies are needed to improve the quality of the nanostructures and process efficiency. The synthesized material can potentially be used in gas adsorption or in the manufacture of polymeric nanocomposites with enhanced thermal, electrical, and mechanical properties.
Chain dynamics of alternating polymers P(C
n
EG4)
Authors: Bichler Karin J , Jakobi Bruno , Schneider Gerald J 
Published: April 2024

Abstract
Alternating or sequence defined polymers attract the attention of an increasing number of researchers recently. Due to their different blocks, they are very customizable and material properties can be tuned. In this publication, we present dynamical studies with focus on polymer dynamics, investigated by rheology and fast field cycling (FFC) NMR. The molecular weight dependencies of the relaxation time and zero-shear viscosity could hint to entanglement effects; however, the spectral shape of the viscoelastic data resembles the polymer dynamics of unentangled melts. Taking both techniques into account, i.e. rheology and FFC NMR leads to the conclusion that the relaxation spectra of the alternating polymer are similar to those of linear polymers.
Spin-valley polarization and tunneling magnetoresistance in monomer, dimer, and trimer magnetic silicene superlattices
Authors: Rojas-Briseño J G , Villasana-Mercado P , Molina-Valdovinos S , Oubram O , Rodríguez-Vargas I 
Published: April 2024

Abstract
Monomer, dimer and trimer semiconductor superlattices are an alternative for bandgap engineering due to the possibility of duplicate, triplicate, and in general multiply the number of minibands and minigaps in a specific energy region. Here, we show that monomer, dimer, and trimer magnetic silicene superlattices (MSSLs) can be the basis for tunable magnetoresistive devices due to the multiplication of the peaks of the tunneling magnetoresistance (TMR). In addition, these structures can serve as spin-valleytronic devices due to the formation of two well-defined spin-valley polarization states by appropriately adjusting the superlattice structural parameters. We obtain these conclusions by studying the spin-valley polarization and TMR of monomer, dimer, and trimer MSSLs. The magnetic unit cell is structured with one seed A with positive magnetization, and one, two, or three seeds B with variable magnetization. The number of B seeds defines the monomer, dimer, and trimer superlattice, while its magnetic orientation positive or negative the parallel (PM) or antiparallel magnetization (AM) superlattice configuration. The transfer matrix method and the Landauer–Büttiker formalism are employed to obtain the transmission and transport properties, respectively. We find multiplication of TMR peaks in staircase fashion according to the number of B seeds in the superlattice unit cell. This multiplication is related to the multiplication of the minibands which reflects as multiplication of the descending envelopes of the conductance. We also find well-defined polarization states for both PM and AM by adjusting asymmetrically the width and height of the barrier-well in seeds A and B.
Thermal conductivity of irregularly shaped nanoparticles from equilibrium molecular dynamics
Authors: Li Hongfei , Zhu Yuanxu , Chu MengFan , Dong Haikuan , Zhang Guohua 
Published: April 2024

Abstract
The computation of thermal conductivity for finite nanoparticulate systems, particularly those of irregular shapes, poses significant challenges. The nonequilibrium molecular dynamics (NEMD) methods has been extensively utilized in numerous prior studies for the computation of thermal conductivity of nanoparticles. One of our recent works (Dong et al 2021 Phys. Rev. B 103 035417) proposed that equilibrium molecular dynamics (EMD) methods can be used for the simulation of thermal conductivity of finite-scale systems and demonstrated their equivalence to NEMD methods. In this study, we investigated the application of the (EMD) approach for the computation of thermal conductivity in zero-dimensional nanoparticles. In our initial step, we merged both methodologies to substantiate the equivalence in thermal conductivity calculation for cube and cylinder nanoparticles. After filtering the data, we confirmed the usefulness of EMD for evaluating the thermal conductivity of zero-dimensional materials. The NEMD method faces challenges in accurately predicting thermal conductivity in nanoparticle systems with a varying cross-sectional area along the transport direction, whereas EMD methods can be utilized to estimate thermal conductivity when the volume is known. In a subsequent study, we used the state-of-the-art machine learning potential to calculate the thermal conductivity of spherical nanoparticles and compared the results with those obtained using the classical Tersoff potential. Ultimately, we predicted the thermal conductivity of nanoparticles with various geometries in all directions. Our findings collectively demonstrate the simplicity and effectiveness of employing EMD methods for calculating thermal conductivity in nanoparticle systems, thereby opening up new avenues for investigating thermal transport properties in particle systems as well as nanopders.
Superconductivity in monolayer Janus titanium-sulfur hydride (TiSH) at ambient pressure
Authors: Munib ul Hassan Noor ul Taqi M , Pinsook Udomsilp 
Published: April 2024

Abstract
Janus two dimensional (2D) materials are new and novel materials. As they break out-of-plane symmetry, they possess several fascinating properties which can be applied in catalytic reactions and opto-electronics. Recent synthesis of MoSH and the prediction of phonon-mediated superconductivity have opened a new way to investigate the properties of hydrogenated Janus materials (Novoselov et al 2004 Science
306 666–9; Mehta et al 2023 Solid State Commun.
375 115347; Naik et al 2023 Comput. Theor. Chem.
1228 114278). In this work, we performed the density functional theory calculations to demonstrate that titanium sulfur hydride (TiSH) is dynamically stable and becomes phonon-mediated superconductor with the superconducting critical temperature, Tc
= 9.24 K with the corresponding value of electron–phonon coupling constant, λ = 0.71, in the weak interaction limits, under ambient conditions. Eliashberg spectral function

α
2

F

(
ω
)

was well converged for dense grid of q1 × q2 × q3 = 12 × 12 × 1 and nk1 × nk2 × nk3 = 140 × 140 × 1. The effect of smearing broadening was also considered for determining well converged value of Tc
and λ. Figure 5(b) shows that after smearing broadening of 0.02 Ry, λ shows convergent values, and subsequent changes are as low as less that 5% of the peak value. Overall, our findings predicted a new member in the 2D Janus hydride family with possible applications in 2D nanomaterials and superconducting devices applications.
Radar-optical fusion detection of UAV based on improved YOLOv7-tiny
Authors: Tang Hao , Xiong Wei , Dong Kai , Cui Yaqi 
Published: April 2024

Abstract
This study presents a radar-optical fusion detection method for unmanned aerial vehicles (UAVs) in maritime environments. Radar and camera technologies are integrated to improve the detection capabilities of the platforms. The proposed method involves generating regions of interest (ROI) by projecting radar traces onto optical images through matrix transformation and geometric centroid registration. The generated ROI are matched with YOLO detection boxes using the intersection-over-union (IoU) algorithm, enabling radar-optical fusion detection. A modified algorithm, called SPN-YOLOv7-tiny, is developed to address the challenge of detecting small UAV targets that are easily missed in images. In this algorithm, the convolutional layers in the backbone network are replaced with a space-to-depth convolution, and a small object detection layer is added. In addition, the loss function was replaced with a normalized weighted distance loss function. Experimental results demonstrate that compared to the original YOLOv7-tiny method, SPN-YOLOv7-tiny achieves an improved mAP@0.5 (mean average precision at an IoU threshold of 0.5) from 0.852 to 0.93, while maintaining a high frame rate of 135.1 frames per second. Moreover, the proposed radar-optical fusion detection method achieves an accuracy of 96.98%, surpassing the individual detection results of the radar and camera. The proposed method effectively addresses the detection challenges posed by closely spaced overlapping targets on a radar chart.
Semi-supervised method for visual detection of automotive paint defects
Authors: Jiang Weiwei , Chen Xingjian , He Yike , Wang Xiuxian , Hu Songyu , Lu Minhua 
Published: April 2024

Abstract
Automotive paint defect detection plays a crucial role in the automotive production process. Current research on visual defect detection methods is mainly based on supervised learning, which requires a large number of labeled image samples for model training. The labeling work is not only time consuming but also expensive, seriously hindering the testing and application of these models in practice. To address this issue, this study proposes a new method for automotive paint defect detection based on a semi-supervised training strategy. First, a semi-supervised automotive paint defect detection framework, which can use labeled and unlabeled samples to reduce the cost of data labeling effectively, is presented. Then, a spatial pyramid pooling fast external attention module that introduces an external attention mechanism is proposed to improve the traditional YOLOv7 network structure, called YOLOv7-EA, to obtain good detection performance. This network acts as a detector to generate high-quality pseudo labels for the unlabeled samples, providing additional data to train the model; meanwhile, it performs the final detection task. Lastly, a Wise-intersection over union loss function that considers the quality of the anchor box is introduced to reduce the interference of low-quality samples and improve the convergence speed and detection accuracy of the model. Using this method, we can accomplish the task of automotive paint defect detection with a small number of labeled image samples. Experimental results on the automotive paint defect dataset show that mean average precision (mAp)@.5, mAp@.75, and mAp@.5:.95 are superior to other methods under the condition of 10% and 15% labeled data, achieving good defect detection performance.
Determining the potato samples processed manner with an electronic nose system supported by a machine-learning approach
Authors: Amkor Ali , Aboulkacem Asmae , Bannay Omar El , El Barbri Noureddine 
Published: April 2024

Abstract
Through several studies, electronic nose (E-nose) devices have been demonstrated to serve as useful measurement equipment for the fast and reliable analysis of complex odour profiles in a wide range of fields, including the area of ensuring food safety. In the same perspective, i.e. checking food safety comes this work, where potatoes are assessed using an E-nose principally made of five metal oxide gas sensors supported with a machine learning algorithm, said evaluation is based on their origin fields: naturally treated, treated with chemical NPK fertilizers, or treated with chicken manure. The technique of support vector machines has been exploited for the data obtained from the multi-sensor system in order to distinguish the potato types mentioned by following two methods: a direct method where all the data have been exploited with a rate of success of 91.7%, and a composed method where the classification was first between naturally treated samples and those treated differently with a success rate of 96.7%, then a classification between those treated differently had a 92.5% success rate. A microbiological analysis was also carried out and its results were compared with those obtained by the E-nose. As per the two methods’ results, the distinction of the potato types by the nature of the cultivated fields is possible with the recording of the multisensory system superiority due to response time, low cost, simplicity, and portability.
FCS-YOLO: an efficient algorithm for detecting steel surface defects
Authors: Zhao Chunhua , Fan Yankun , Tan Jinling , Li Qian , Lin Zhangwen , Luo Shun , Chen Xi 
Published: April 2024

Abstract
Due to the imperfection of the manufacturing process and external factors, there may be some defects on the steel surface, which seriously affects the life and availability of the steel. Aiming at the problems of low precision and poor real-time performance in the inspection of steel surface defects in the past, an algorithm named FCS-you only look once (YOLO) was proposed for the inspection of steel surface defects. Firstly, the backbone feature extraction network is reconstructed using FasterNet to reduce the number of model parameters and weight size. Secondly, a new C2f-global attention mechanism module is proposed, which can focus image features more accurately by dynamically adjusting feature response. Finally, the attention mechanism SK is embedded in the feature extraction network to adjust the receptive field of the model, strengthen its feature recognition ability, and effectively improve the detection accuracy of steel surface defects. The test results show that FCS-YOLO has the best detection effect and the fastest detection speed among the comparison models. On the NEU-DET Dataset, the detection accuracy reached 81.8% and the detection speed reached 129.87 frames per second, which met the requirements of accurate and fast detection of strip surface defects.