bluuebunny/crossref_metadata_2025_split huggingface dataset:
Superconductivity and phase transitions in Kagome compound Pd3P2S8 from first-principles calculation
Authors: Li Bin , Yang Yeqian , Fan Yuxiang , Zhu Cong , Liu Shengli , Shi Zhixiang 
Published: August 2023

Abstract
Pd3P2S8 is a semiconductor that contains Kagome lattices, which exhibits various physical phenomena. Structural searches of Pd3P2S8 in the pressure range from 0 to 120 GPa have revealed two phases of the space group

P

3
‾

m
1

(designated as

P

3
‾

m
1

-1 and

P

3
‾

m
1

-2) and two phases of the space group

C
2

/

m

(designated as

C
2

/

m

-1 and

C
2

/

m

-2), with all but

C
2

/

m

-2 phase being dynamically stable. Electron–phonon calculations combined with Bardeen–Cooper–Schrieffer’s argument have shown that both phases are superconductors. Notably, the

P

3
‾

m
1

-1 phase undergoes a semiconductor-to-superconductor transition, with superconducting critical temperature (

T

c

) increasing up to a maximum of 9.13 K at 70 GPa. Both

C
2

/

m

-1 and

P

3
‾

m
1

-2 phases exhibit superconductivity at 0 GPa. Our calculations demonstrate several new superconducting phases of Pd3P2S8, providing a pathway and platform for exploring superconductivity in materials with Kagome lattices and expanding the options for studying such lattices.
Optimal static light scattering detection angle for particulate matter size and concentration measurement
Authors: Zhao Heng , Wang Xingbo , Wang Ruofei , Hua Dengxin , Li Kun , Ji Feng 
Published: August 2023

Abstract
The serious pollution of particulate matter (PM) causes many adverse effects on human health and industrial production. High-precision, real-time monitor of atmospheric particulate concentration is becoming increasingly important. In this study, a method to find the optimal detection angle to measure the mass concentration of PM is proposed. To find an optimal angle, a motorized rotary system is used to measure the light scattering signal of particles from 0° to 180°. The new method obtains parameters such as mass concentration factor, deviation, mass concentration coefficient and deviation coefficient, which can be measured more accurately. Through theoretical calculation and experimental analysis, the optimal detection angle is 45°. At the optimal angle, the correlation between the scattered light intensity and the mass concentration of spherical SiO2 particles reaches 0.9836. Then, the mass concentration of PM is inverted and calculated at the optimal angle. The results showed that the correlation coefficient R2 of different particle sizes is larger than 0.952, and the measurement results were highly correlated.
Directional iDBSCAN to detect cosmic-ray tracks for the CYGNO experiment
Authors: Amaro F D , Antonietti R , Baracchini E , Benussi L , Bianco S , Borra F , Capoccia C , Caponero M , Cardoso D S , Cavoto G , Costa I A , D’Imperio G , Danè E , Dho G , Di Giambattista F , Di Marco E , Iacoangeli F , Kemp E , Lima Júnior H P , Lopes G S P , Maccarrone G , Mano R D P , Marcelo Gregorio R R , Marques D J G , Mazzitelli G , McLean A G , Meloni P , Messina A , Monteiro C M B , Nobrega R A , Pains I F , Paoletti E , Passamonti L , Petrucci F , Piacentini S , Piccolo D , Pierluigi D , Pinci D , Prajapati A , Renga F , Roque R J d C , Rosatelli F , Russo A , Saviano G , Spooner N J C , Tesauro R , Tomassini S , Torelli S , Tozzi D , dos Santos J M F 
Published: August 2023

Abstract
The CYGNO experiment aims to study rare events related to the search for low-mass dark matter and solar neutrino events. One of the main components of background comes from cosmic rays that generate long tracks in the detector’s images. The interaction of such particles with the gas releases a variable energy profile along its trajectory to form tracks with multiple cores that can be easily reconstructed erroneously by being split into more than one cluster. Thus, this work offers a newly adapted version of the well-known density-based spatial clustering of applications with noise (DBSCAN) algorithm, called iDDBSCAN, which exploits the directional characteristics of the clusters found by the DBSCAN to improve its clustering efficiency when dealing with multi-core tracks. This paper provides a detailed explanation of this algorithm, covering its parameter validation and evaluating its influence when integrated into the experiment’s event selection routine. To generate background events, data acquisition was performed with the detector installed in an overground laboratory, leaving it exposed to natural radiation. To produce signals in the energy range of interest for the experiment, a 55Fe radioactive source was used. The achieved results showed that the iDDBSCAN algorithm is capable of improving the background rejection of the experiment, through a more accurate reconstruction of the tracks produced by natural radiation such as cosmic rays, without deteriorating its signal detection efficiency and energy estimation.
Advances in field-effect biosensors towards point-of-use
Authors: Chen Sihan , Bashir Rashid 
Published: August 2023

Abstract
The future of medical diagnostics calls for portable biosensors at the point of care, aiming to improve healthcare by reducing costs, improving access, and increasing quality—what is called the ‘triple aim’. Developing point-of-care sensors that provide high sensitivity, detect multiple analytes, and provide real time measurements can expand access to medical diagnostics for all. Field-effect transistor (FET)-based biosensors have several advantages, including ultrahigh sensitivity, label-free and amplification-free detection, reduced cost and complexity, portability, and large-scale multiplexing. They can also be integrated into wearable or implantable devices and provide continuous, real-time monitoring of analytes in vivo, enabling early detection of biomarkers for disease diagnosis and management. This review analyzes advances in the sensitivity, parallelization, and reusability of FET biosensors, benchmarks the limit of detection of the state of the art, and discusses the challenges and opportunities of FET biosensors for future healthcare applications.
Nitrogen-doped hollow mesoporous carbon spheres for efficient oxygen reduction
Authors: Wang Hao , Zheng Caixia , Huang Bing , Jiang Nannan , Li Yaoxin , Wang Minghao , Wu Qirui , Wang Huiying , Guan Lunhui 
Published: August 2023

Abstract
Extensive investigations have been devoted to nitrogen-doped carbon materials as catalysts for the oxygen reduction reaction (ORR) in various conversion technologies. In this study, we introduce nitrogen-doped carbon materials with hollow spherical structures. These materials demonstrate significant potential in ORR activity within alkaline media, showing a half-wave potential of 0.87 V versus the reversible hydrogen electrode (RHE). Nitrogen-doped hollow carbon spheres (N-CHS) exhibit unique characteristics such as a thin carbon shell layer, hollow structure, large surface area, and distinct pore features. These features collectively create an optimal environment for facilitating the diffusion of reactants, thereby enhancing the exposure of active sites and improving catalytic performance. Building upon the promising qualities of N-CHS as a catalyst support, we employ heme chloride (1 wt%) as the source of iron for Fe doping. Through the carbonization process, Fe-N active sites are effectively formed, displaying a half-wave potential of 0.9 V versus RHE. Notably, when implemented as a cathode catalyst in zinc-air batteries, this catalyst exhibits an impressive power density of 162.6 mW cm−2.
Enhanced multi-band acoustic energy harvesting using double defect modes of Helmholtz resonant metamaterial
Authors: Xiao Hanjie , Tan Ting , Li Tianrun , Zhang Liang , Yuan Chaolian , Yan Zhimiao 
Published: August 2023

Abstract
Acoustic metamaterials (AMs) based on phononic crystals have been widely employed for acoustic energy harvesting, for their capacity to amplify incident sound waves and transfer them to piezoelectric devices. By substituting a resonator unit with a piezoelectric material having distinct characteristics, the periodicity of the AM is locally disrupted, resulting in the generation of defect bands within the band gap. At the frequencies corresponding to these defect bands, the AM exhibits the phenomenon of local resonance, which concentrates the incident acoustic energy at the defect sites and significantly enhances the output power of the piezoelectric devices. Conventional AMs primarily consist of elastic resonators, which can be regarded as spring-mass systems. The elastic resonances of these resonators lead to local resonance in the AM and are utilized for single-band acoustoelectric conversion. In contrast, Helmholtz resonators (HRs), in addition to demonstrating mechanical resonance, generate acoustic resonance at specific frequencies. By combining AM with HRs, the resulting Helmholtz AM (HAM) achieves energy localization effects within two defect bands, thereby increasing the output power and broadening the operational frequency range of the AM. This study aims to investigate the energy localization in HAM with multiple point defects within the two defect bands through numerical simulations and experimental analysis. Multiple HRs are intentionally removed from the HAM to introduce these multi-point defects. The interaction of elastic waves localized within these defects further enhances the energy harvesting efficiency of the HAM. Comparing the voltage frequency response functions, it is observed that, in both the first and second band gaps, the output voltage of the three double-defect HAM structures surpasses that of the single-defect HAM. As the distance between the two defects decreases, the energy harvesting at the defect modes intensifies due to a stronger coupling effect.
Resonant NLSE in the presence of spatio-temporal and intermodal dispersion is dominated by a myriad of nonlinearities
Authors: Ozisik Muslum , Secer Aydin , Bayram Mustafa 
Published: August 2023

Abstract
This article is dedicated to investigating a myriad of nonlinear forms of the resonant nonlinear Schrödinger equation, which is one of the essential examples of evolution equations, and providing some observations. The resonant nonlinear Schrödinger equation, in the presence of spatio-temporal and inter-modal dispersion, was addressed using the recently introduced Kudryashov’s method, and solution functions were obtained for eleven different nonlinear forms (Kerr, power, parabolic, dual-power, polynomial, triple-power, quadratic-cubic, generalized quadratic-cubic, anti-cubic, generalized anti-cubic, and parabolic law with non-local nonlinearity). The study will contribute to the literature not only by examining such a diverse set of nonlinear forms together but also by investigating the impact of the degree of nonlinearity and the coefficients of different nonlinearity terms on soliton behavior. Detailed examinations of all these points, the results obtained, observations, and necessary comments have been made in the relevant sections.
Numerical simulation study on pile expansion by shock waves of electrical wire explosion in liquids
Authors: Huang Shijie , Liu Yi , Zhao Yong , Xu Youlai , Wang Tianyu , Lin Fuchang 
Published: August 2023

Abstract
Compaction of the soil around the borehole filled with cement paste can build shaped pile foundations, effectively enhancing the bearing capacity of the pile foundations. Shock waves of electrical wire explosion in liquids can compact the soil and build expanded pile foundations, which has broad industrial application prospects. Electrical wire explosion in liquids has the advantages of high efficiency, good repeatability and controllability. In order to analyze the mechanism of pile expansion by electrical wire explosion in liquids, in this paper, a comprehensive test platform for pile expansion by electrical wire explosion was established, the voltage and current of the discharge channel were measured. The expanded piles were built through multiple discharges, and the size and bearing capacity of the piles were measured. Based on the finite element numerical method, a three-dimensional model of soil compaction by shock waves was established, and the material parameters, model dimensions were reasonably determined. The propagation and attenuation processes of shock waves in cement paste and soil were simulated, and the soil compaction process was obtained. The cumulative effect of pile expansion under multiple shock wave actions was analyzed and compared with test results.
State-of-the-art advances in vacancy defect engineering of graphitic carbon nitride for solar water splitting
Authors: Li Jie , Huang Kaige , Huang Yanbin , Ye Yumin , Ziółek Marcin , Wang Zhijie , Yue Shizhong , Ma Mengmeng , Liu Jun , Liu Kong , Qu Shengchun , Zhao Zhi , Zhang Yanjun , Wang Zhanguo 
Published: August 2023

Abstract
Developing low-cost, efficient, and stable photocatalysts is one of the most promising methods for large-scale solar water splitting. As a metal-free semiconductor material with suitable band gap, graphitic carbon nitride (g-C3N4) has attracted attention in the field of photocatalysis, which is mainly attributed to its fascinating physicochemical and photoelectronic properties. However, several inherent limitations and shortcomings—involving high recombination rate of photocarriers, insufficient reaction kinetics, and optical absorption—impede the practical applicability of g-C3N4. As an effective strategy, vacancy defect engineering has been widely used for breaking through the current limitations, considering its ability to optimize the electronic structure and surface morphology of g-C3N4 to obtain the desired photocatalytic activity. This review summarizes the recent progress of vacancy defect engineered g-C3N4 for solar water splitting. The fundamentals of solar water splitting with g-C3N4 are discussed first. We then focus on the fabrication strategies and effect of vacancy generated in g-C3N4. The advances of vacancy-modified g-C3N4 photocatalysts toward solar water splitting are discussed next. Finally, the current challenges and future opportunities of vacancy-modified g-C3N4 are summarized. This review aims to provide a theoretical basis and guidance for future research on the design and development of highly efficient defective g-C3N4.
Pressure manipulation of ultrafast carrier dynamics in monolayer WS2
Authors: Li Yao , Zhu Haiou , Song Zongpeng 
Published: August 2023

Abstract
Two-dimensional transition metal dichalcogenides (TMDs) have intriguing physic properties and offer an exciting platform to explore many features that are important for future devices. In this work, we synthesized monolayer WS2 as an example to study the optical response with hydrostatic pressure. The Raman results show a continuous tuning of the lattice vibrations that is induced by hydrostatic pressure. We further demonstrate an efficient pressure-induced change of the band structure and carrier dynamics via transient absorption measurements. We found that two time constants can be attributed to the capture process of two kinds of defect states, with the pressure increasing from 0.55 GPa to 2.91 GPa, both of capture processes were accelerated, and there is an inflection point within the pressure range of 1.56 GPa to 1.89 GPa. Our findings provide valuable information for the design of future optoelectronic devices.
Modeling and analysis of the tritium fuel cycle for ARC- and STEP-class D-T fusion power plants
Authors: Meschini Samuele , Ferry Sara E. , Delaporte-Mathurin Rémi , Whyte Dennis G. 
Published: August 2023

Abstract
The limited tritium resources available for the first fusion power plants (FPPs) make fuel self-sufficiency and tritium inventory minimization leading issues in FPP design. This work builds on the model proposed by Abdou et al (2020 Nucl. Fusion
61 013001), which analyzed the fuel cycle (FC) of a DEMOnstration nuclear FPP-class FPP with a time-dependent system-level model. Here, we use a modified version of their model to analyze the FC of an Affordable, Robust, Compact (ARC)-class tokamak and two versions of a Spherical Tokamak for Energy Production (STEP)-class tokamak. The ARC-class tokamak breeds tritium in a 2LiF + BeF2 liquid immersion blanket, while the STEP-class tokamak breeds tritium utilizing either a liquid-lithium blanket design or an encapsulated breeding blanket. A time-dependent system-level model is developed in Matlab Simulink® to simulate the evolution of tritium flows and tritium inventories in the FC. The main goals of this work are to assess tritium self-sufficiency of the ARC- and STEP-class designs and to determine quantitative design requirements that can be used to analyze the adequacy of a proposed FC system. These design requirements are aimed at achieving a low tritium inventory doubling time (

t

d

) and a low start-up inventory (

I

s
t
a
r
t
u
p

) while keeping the required tritium breeding ratio (TBR

r

) as low as possible. We also consider how improvements in FC technology and POs affect TBR

r

and

I

s
t
a
r
t
u
p

. The model results show that TBR

r

for ARC- and STEP-class FPPs should be achievable if the tritium burn efficiency (TBE) reaches 0.5%–1% (TBR

r

<

1.2). This assumes significant, but attainable, improvements over current abilities. However, the model results indicate that an FPP must achieve ambitious performance targets, including FPP availability

>

70%, tritium processing time

<

4 h, and the implementation of direct internal recycling (DIR). If future research yields major improvements to achievable TBE, it may be possible to achieve tritium self-sufficiency while operating at lower availability and without implementing DIR.
Improvement of Remote sensing image target detection algorithm based on YOLO V5
Authors: Li Meiyan , Aviles Joey S. 
Published: August 2023

Abstract
YOLO V5 algorithm is the current target detection algorithm, but the accuracy of target boundary regression is relatively low, and it cannot be used in scenarios with high requirement of prediction frame intersection ratio. Therefore, this paper proposes an improved YOLO V5 algorithm with high accuracy of target frame and fast convergence of model. The algorithm can avoid the loss of shallow semantic information, deepen the pyramid depth and increase the detection layer by using cross-hierarchy method and multiple feature fusion. By reducing network computation and parameter number, network lightweight processing is realized, and real-time performance loss caused by model complexity is avoided.
Lane Detection Network with Direction Context
Authors: Cheng Jingchun , Zhu Yi , Zhang Zhen , Huang Chenwei , Pan Xiong , Zhang Chunxi , Song Chen 
Published: August 2023

Abstract
Lane detection has been a research hot-spot these years for it is a key technique in autonomous driving. As lane detection requires real-time performance on car systems with limited computation ability and memorizer space, most algorithms employ small networks with higher speed but lower accuracy. These methods mostly rely on various distillation techniques or multi-task learning to enhance the overall precision, but few have exploited the direction context which is closely related to lane pixel distribution. In this paper, we tackle the problem of boosting lane detection performance by adding in direction context. For algorithm efficiency, we use the light-weight ERF-Net as our backbone network. Firstly, we incorporate spatial convolutions to propagate lane features directionally. Then we feed four supervision signals by a specially designed Cross-Sum Loss to train these features with rich direction context. We show that the proposed Cross-Sum Loss can enrich the direction sensitivity of lane features, improving both the precision and the interpretability of the lane detection network with negligible time and computation cost during inference. Besides, we also conduct a knowledge distillation step on the direction-sensitive features for a further precision gain. Extensive experiments and analyses conducted on the widely-used CULane dataset illustrate that the proposed method achieves state-of-the-art performance with real-time processing speed, demonstrating the effectiveness of adding in direction context with the Cross-Sum Loss.
Research on Intelligent Recognition Method of Egg cracks Based on EfficientNet Network Model
Authors: Liu Chao , Wen Hongyuan , Yin Gang , Ling Xiaoxiong , Ibrahim Shaikh Mohammed 
Published: August 2023

Abstract
Aiming at the egg crack detection task, a 6-position egg image acquisition method is proposed. EfficientNet was used to classify egg cracks. Using transfer learning technology, the model is pre-trained with CIFAR-10 data set to obtain initial weights. The efficiency of model training is improved. Compared with the current mainstream CNN models of Alexnet, VGG16 and ResNet50, in terms of egg crack recognition, the average correct recognition rate of EfficientNet model is as high as 98.6 %, which is significantly better than Alexnet, VGG16 and ResNet50 models. Among them, the correct recognition rate of EfficientNetB2 model is 99.5 %, the training time is only 29 min, and the comprehensive performance is the best. It is the most suitable method for egg crack detection. Finally, three learning rates are set for the EfficientNetB2 model. The experimental results show that the model has the best performance when the learning rate is 0.001. The improved model proposed in this paper improves the accuracy of egg crack detection and reduces the model training time.
Large-field Gesture Tracking and Recognition for Augmented Reality Interaction
Authors: Zhao Ruiyi , Ge Yangshi , Duan Ye , Jiang Quanhong 
Published: August 2023

Abstract
In recent years, with the continuous development of computer vision and artificial intelligence technology, gesture recognition is widely used in many fields, such as virtual reality, augmented reality and so on. However, the traditional binocular camera architecture is limited by its limited field of view Angle and depth perception range. Fisheye camera is gradually applied in gesture recognition field because of its advantage of larger field of view Angle. Fisheye cameras offer a wider field of vision than previous binocular cameras, allowing for a greater range of gesture recognition. This gives fisheye cameras a distinct advantage in situations that require a wide field of view. However, because the imaging mode of fisheye camera is different from traditional camera, the image of fisheye camera has a certain degree of distortion, which makes the calculation of gesture recognition more complicated. Our goal is to design a distortion correction processing strategy suitable for fisheye cameras in order to extend the range of gesture recognition and achieve large field of view gesture recognition. Combined with binocular technology, we can use the acquired hand depth information to enrich the means of interaction. By taking advantage of the large viewing Angle of the fisheye camera to expand the range of gesture recognition, make it more extensive and accurate. This will help improve the real-time and precision of gesture recognition, which has important implications for artificial intelligence, virtual reality and augmented reality.