bluuebunny/crossref_metadata_2025_split huggingface dataset:
One Medicine vs One Health: Policy disconnect in India
Authors: Yasobant Sandul , Memon Farjana , Kalpana Pachillu , Saxena Deepak 
Published: January 2024

Abstract

One Health is an integrated, unifying approach to balancing and optimizing the health of people, animals, and ecosystems in a sustainable manner. It is a global movement to align our thinking and policy on human, animal, and environmental health, which is critical for effectively combating diseases at the human-animal-environmental interfaces. The Indian government intends to implement the much-needed and globally recognized ‘
One Nation, One Health System’
policy by 2030; however, given the complexity of India’s healthcare system in terms of One Health implementation, it seems to be a long way to go move and accelerate the collaboration among system stakeholders at various levels. Government of India aims to integrate modern and traditional medical systems such as allopathy, ayurveda, and homeopathy in education, medical practice, and research in the larger domain of One Health. Basically, their larger focus is on intra-human health systems integration rather than inter-system integration, which is also not aligned with the principles of One Medicine. Perhaps this could be the foundation for launching the One Health concept, and which will include more relevant stakeholders working at the human-animal-ecosystem interface in the coming years. The current initiative neither fulfils the essential principle of the One Medicine or One Health concept nor will it serve the purpose of the Global One Health joint plan of action. There is an urgent need for broadening the inter-systems stakeholders at all levels and adopting the principles of One Health more holistically in alignment with the global movement.

One Health impact statement
One Health, a comprehensive approach to human, animal, and ecosystem well-being, is well-recognized worldwide. India’s visionary ‘One Nation, One Health System’ policy targets 2030, focusing on integrating diverse medical practices like allopathy, ayurveda, and homeopathy. This marks a foundational stride towards broader engagement across the human-animal-ecosystem interface. Nonetheless, the current proposal has been marked as a shortfall for global One Health principles and objectives. While recognizing the significant room for improvement, this article delicately underscores the need for more comprehensive implementation aligning with One Health principles and considering inter-system harmony beyond the intra-system.
Preparation of robust superhydrophobic surface on PET substrate using Box-Behnken design and facile sanding method with PTFE powder
Authors: Wang Xin , Wang Tao , Sheng Jie , Wang Ziting , Yang Weizhi , Li Meng , Shi Liping 
Published: January 2024

Abstract
Superhydrophobic surfaces have attracted increasing interests due to their excellent features, while achieving facile preparation of superhydrophobic surface with good mechanical stability is still a challenging work. In this paper, we prepared a superhydrophobic surface by sanding polytetrafluoroethylene powder directly onto the surface of a polyethylene terephthalate (PET) film by means of a simple sanding method with sandpaper. The fabrication parameters were firstly optimized using response surface methodology. Surface morphology and chemical composition of the fabricated surface were characterized by field emission scanning electron microscopy, Fourier transform infrared and x-ray photoelectron spectroscopy. The mechanical performance of the superhydrophobic PET surfaces was evaluated by tape peeling test, and potential applications of this surface in self-cleaning and anti-icing were finally carried out. The results showed that the water contact angle up to 153.5° and sliding angle less than ∼3° on PET surface could be prepared under the optimum conditions, and its superhydrophobicity of surfaces was attributed to the synergistically effect of low surface energy and surface roughness. The fabricated superhydrophobic surfaces also exhibited good resistance to abrasion, and they have great potential for application in the fields of self-cleaning and anti-icing.
Effect of high voltage discharge on germination characteristics of vetch seeds at high altitude
Authors: Shi Jinqiang , Jin Fubao , Ma Shangang , Liu Xinhe , Leng Xuejian 
Published: January 2024

Abstract
High-voltage electrostatic fields and low-temperature plasma technology at atmospheric pressure have an important impact on biological growth promotion. Therefore, a multi-needle-column-plate corona plasma generator is proposed in this paper. The negative corona voltammetry characteristics of multi-needle-plate electrodes and multi-needle-column-plate electrodes with different electrode spacing are investigated experimentally, and the electric field distribution of the device is simulated. The device was also applied to vetch seeds at high altitudes to investigate the effect of discharge on germination and root length. The results show that the introduction of column electrodes can effectively improve the electric field distribution of the device so that the device can provide two modes of high voltage electrostatic field and corona plasma field, and ensure the uniform treatment of seeds when the electrode spacing is 3 cm. The treatment of this device accelerates seed germination and promotes root growth, and is more effective under the combined influence of higher electric field strength, ionic wind generated by the discharge, and the active species than a single factor with a lower electric field, as well as shortening the duration of action. The high voltage electrostatic fields at −3 kV, −6 kV, and −9 kV and the corona discharge plasma fields at −12 kV, −15 kV, and −18 kV can effectively accelerate the germination of vetch seeds as well as promote the root growth under the treatment time of 10 min, 20 min, and 30 min. The optimal conditions were −9 kV for 30 min and −15 kV for 10 min, respectively.
Activation of the hair follicle stem cells by low temperature pulsed plasma jet
Authors: Fu Yongqiang , Kong Deqiang , Xu Guowang , Wang Jingze , Wu Yaojiong , Zhang Ruobing 
Published: January 2024

Abstract
The issue of hair loss has become an increasing concern due to growing societal pressures. Currently available hair loss treatments often produce unsatisfactory results, cause significant physical damage, and are costly. Non-thermal atmospheric pressure plasma has been widely used in various biomedical fields, including sterilization, coagulation promotion, and cancer treatment. This paper pioneered the use of a kind of portable pulsed plasma jet power supply in the resting period of mouse hair follicle, and found that plasma jet can effectively shorten the resting period of mouse hair follicle, so that they re-enter the regeneration period and grow hair. Plasma jet provides a new treatment method for hair loss that is cheap, simple, highly effective, has no side effects and has broad application prospects.
Manipulating spin-polarization of Co-doped ZnFe2O4 for photocatalytic TC degradation
Authors: Xie Qijing , Huang Huimin , Zhang Chengliang , Zheng Xiangyang , Shi Haifeng 
Published: January 2024

Abstract
The rapid recombination of photogenerated electrons and holes was an enormous hindrance constraining the photocatalytic efficiency of photocatalysis, which could be effectively solved by inducing electron spin-polarization. Herein, a series of gradient ZnFe2-x
Co
x
O4 (ZFCO-x) magnetic compounds with spin-polarization properties were synthesized by doping Co cation into ZnFe2O4, as well as the diffraction of x-rays characterization confirmed the successful synthesis of the samples. In photodegradation experiments, ZFCO-0.8 manifested improved photocatalytic degradation efficiency in TC removal experiments with visible-light exposure and external magnetic field. Furthermore, the photodegradation experiments exhibited that the degradation efficiency of ZFCO-x could be raised through Co doping and the photocatalytic degradation efficiency was significantly improved under an external magnetic field. The sample exhibiting the most prominent enhancement was ZFCO-x with doping content of x = 0.8, which displayed 48% photocatalytic degradation performance enhancement with a magnetic field. Density functional theory was used to calculate the density of states (DOS) of materials. The calculated DOS indicated that ZFCO-0.8 exhibited the most intense spin-polarization consistent with the results of the experiment. This work is anticipated to deliver an operating method for manipulating spin-polarization in photocatalytic semiconductors to improve photocatalytic degradation efficiency.
Reliable extraction of x-ray refraction and dark-field signals with a large field of view, multi-modal scanning system at spectral energies up to 150 kVp
Authors: Partridge T , Astolfo A , Buchanan I , Kallon G K , Munro P R T , Hagen C K , Endrizzi M , Bate D , Olivo A 
Published: January 2024

Abstract
Multi-modal x-ray scanning allows the simultaneous acquisition of attenuation, refraction and ultra-small angle scattering or dark field images. While many examples of multi-modal x-ray scanning exist in the literature, extension to high x-ray energy, necessary to investigate dense and high-Z materials, still poses challenges. We present the investigation of attenuation, refraction and dark field images taken at 90, 120 and 150 kVp, using a scanning, large field of view multi-modal imaging system. Increases in tube voltage reduce both contrast and signal to noise but still produce satisfactory results suitable for quantitative analysis. On top of benchmarking against phantoms made of known materials, we illustrate this by scanning a 9 V PP3 battery; a highly absorbing sample which causes photon starvation at lower energies.
Small-modulus worms surface defect detection method based on YOLOv7
Authors: Li Yan , Zheng Peng , Yu Menghao , Li Jicun , He Qingze 
Published: January 2024

Abstract
Small-modulus worms are widely used in precision transmission mechanisms. The detection of surface defects on processed small-modulus worms mainly relies on manual inspection. However, this detection method has low detection efficiency and low accuracy. In response to this issue, this paper proposed a surface defect detection method for small-modulus worms based on deep learning. Firstly, based on the geometric features and material properties of small-modulus worms, designed a two-cameras worms image acquisition system to capture small-modulus worm images. And the captured images were annotated and classified to construct a small-modulus worms defect dataset. Secondly, the you only look once version 7 (YOLOv7) network model algorithm was studied and improved. A three-stage image preprocessing algorithm was added to the YOLOV7 model to reduce the interference in distorted areas. Next, Ghost-convolution, batch normalization, Silu activation (CBS) structures were employed to replace some of the conventional CBS structures, reducing computational complexity. And we also added a width–height balance weights and alpha structure to the efficient-IoU (EIOU) loss function. Improve the fitting performance of the model on the bounding box with large aspect ratio. Furthermore, three SimAM attention modules were added to the backbone, increasing the network’s focus on key areas. Finally, experimental validation was conducted, and the results demonstrated that the performance of our proposed method is better than other existing methods. The detection accuracy reached 95.7%, with a map@50 of 94.6%. Overall, the performance met the requirements for worm defect detection.
Fabrication and structural and magnetic properties of spark plasma sintered group-IV diluted magnetic semiconductor Fe-doped SiGe alloys
Authors: Li Jiafei , Zhang Xi , Wang Xiaolian , Wang Xiaofeng , Xiang Gang 
Published: January 2024

Abstract
Fe-doped SiGe bulk alloys are fabricated using non-equilibrium spark plasma sintering (SPS) and their structure and ferromagnetic and magneto-transport properties are investigated. X-ray diffraction and high-resolution transmission electron microscope measurements show that the obtained alloys are composed of SiGe polycrystals. Magnetization measurements reveal that the Fe-doped SiGe alloys exhibit ferromagnetism up to 259 K, and their Curie temperature increases with Fe doping concentration up to 8%. Moreover, transport measurements of the Fe-doped SiGe alloys show typical metal-insulator transition characteristics of doped semiconductors as well as anomalous Hall effect and intriguing positive-to-negative magnetoresistance, indicating that the obtained alloys are diluted magnetic semiconductors (DMSs). Our results provide insight into the SPS-prepared Fe-doped SiGe bulk alloys and may be useful for the design, fabrication, and application of group-IV DMSs.
Giant enhancement of fluorescence resonance energy transfer based on nanoporous gold with small amount of residual silver
Authors: Cui Lianmin , Zhang Ling , Li Zhexiao , Jing Zhiyu , Huang Luyi , Zeng Heping 
Published: January 2024

Abstract
Fluorescence resonance energy transfer (FRET) was found strongly enhanced by plasmon resonance. In this work, Nanoporous Gold with small amount of residual silver was used to form nanoporous gold/organic molecular layer compound with PSS and PAH. The ratio of its specific gold and silver content is achieved by controlling the time of its dealloying. Layered films of polyelectrolyte multilayers were assembled between the donor–acceptor pairs and NPG films to control distance. The maximum of FRET enhancement of 80-fold on the fluorescence intensity between the donor–acceptor pairs (CFP-YFP) is observed at a distance of ∼10.5 nm from the NPG film. This Nanoporous Gold with small amount of residual silver not only enhanced FRET 4-fold more than nanoporous gold of only gold content almost, but also effectively realized the regulation of FRET enhancement. The ability to precisely measure and regulate the enhancement of FRET enables the rational selection of plasmonic nanotransducer dimensions for the particular biosensing application.
A cascade transformer-based model for 3D dose distribution prediction in head and neck cancer radiotherapy
Authors: Gheshlaghi Tara , Nabavi Shahabedin , Shirzadikia Samireh , Moghaddam Mohsen Ebrahimi , Rostampour Nima 
Published: January 2024

Abstract

Objective. Radiation therapy is one of the primary methods used to treat cancer in the clinic. Its goal is to deliver a precise dose to the planning target volume while protecting the surrounding organs at risk (OARs). However, the traditional workflow used by dosimetrists to plan the treatment is time-consuming and subjective, requiring iterative adjustments based on their experience. Deep learning methods can be used to predict dose distribution maps to address these limitations. Approach. The study proposes a cascade model for OARs segmentation and dose distribution prediction. An encoder–decoder network has been developed for the segmentation task, in which the encoder consists of transformer blocks, and the decoder uses multi-scale convolutional blocks. Another cascade encoder–decoder network has been proposed for dose distribution prediction using a pyramid architecture. The proposed model has been evaluated using an in-house head and neck cancer dataset of 96 patients and OpenKBP, a public head and neck cancer dataset of 340 patients. Main results. The segmentation subnet achieved 0.79 and 2.71 for Dice and HD95 scores, respectively. This subnet outperformed the existing baselines. The dose distribution prediction subnet outperformed the winner of the OpenKBP2020 competition with 2.77 and 1.79 for dose and dose–volume histogram scores, respectively. Besides, the end-to-end model, including both subnets simultaneously, outperformed the related studies. Significance. The predicted dose maps showed good coincidence with ground-truth, with a superiority after linking with the auxiliary segmentation task. The proposed model outperformed state-of-the-art methods, especially in regions with low prescribed doses. The codes are available at https://github.com/GhTara/Dose_Prediction.
Pencil beam kernel-based dose calculations on CT data for a mixed neutron-gamma fission field applying tissue correction factors
Authors: Sommer Lucas B , Kampfer Severin , Chemnitz Tobias , Breitkreutz Harald , Combs Stephanie E , Wilkens Jan J 
Published: January 2024

Abstract

Objective. For fast neutron therapy with mixed neutron and gamma radiation at the fission neutron therapy facility MEDAPP at the research reactor FRM II in Garching, no clinical dose calculation software was available in the past. Here, we present a customized solution for research purposes to overcome this lack of three-dimensional dose calculation. Approach. The applied dose calculation method is based on two sets of decomposed pencil beam kernels for neutron and gamma radiation. The decomposition was performed using measured output factors and simulated depth dose curves and beam profiles in water as reference medium. While measurements were performed by applying the two-chamber dosimetry method, simulated data was generated using the Monte Carlo code MCNP. For the calculation of neutron dose deposition on CT data, tissue-specific correction factors were generated for soft tissue, bone, and lung tissue for the MEDAPP neutron spectrum. The pencil beam calculations were evaluated with reference to Monte Carlo calculations regarding accuracy and time efficiency. Main results. In water, dose distributions calculated using the pencil beam approach reproduced the input from Monte Carlo simulations. For heterogeneous media, an assessment of the tissue-specific correction factors with reference to Monte Carlo simulations for different tissue configurations showed promising results. Especially for scenarios where no lung tissue is present, the dose calculation could be highly improved by the applied correction method. Significance. With the presented approach, time-efficient dose calculations on CT data and treatment plan evaluations for research purposes are now available for MEDAPP.
Modeling of high-field-side high-density regime in the Globus-M2 tokamak
Authors: Dolgova K , Vekshina E , Rozhansky V 
Published: January 2024

Abstract
Formation of a high-field-side high-density (HFSHD) regime and the role of the high-field-side (HFS) poloidal electric field in the scrape-off layer of the spherical tokamak Globus-M2 are analyzed using SOLPS-ITER edge plasma simulations. The dependence of the HFS poloidal electric field sign and, consequently, radial drift fluxes on the discharge density is discussed. It is demonstrated that the HFS poloidal electric field is the key element in the formation of a HFSHD regime in the Globus-M2 tokamak as in ASDEX Upgrade. It is demonstrated that the physics of HFSHD formation in a small spherical tokamak is similar to that suggested by Kaveeva et al (2009 36th EPS Conf. on Plasma Physics) and is in line with experimental observations and modeling, performed later on ASDEX Upgrade.
High-velocity micromorphological observation and simulation of magnetorheological gel using programmable magneto-controlled microfluidics system and micro-tube dynamic models
Authors: Yu Miao , Gan Ruyi , Fu Jie , Qi Song , Han Jinyu , Li Haitao 
Published: January 2024

Abstract
Application of magnetorheological gel (MRG) is a promising tool for high performance mitigation due to its outstanding energy absorption and dissipation properties. However, the lack of recognition on micromorphological variation for MRG and its magneto-mechanical coupling mechanism limits its extensive application. Herein, combined with the magnetic sensitivity nature of MRG, we develop a magneto-controlled microfluidic system for flexible simulation toward ms-level impact conditions. Microstructural changes of MRG, prepared with solid–liquid composite method, are characterized from variable magnet-field setups and gradual velocities. Experiments reveal that the increasing magnetic flux density can effectively enhance the stability of chains in as-fabricated MRG, while the chains can support excessive velocities up to 4.5 m s−1 before breaking. Meanwhile, under the preset velocity range, the maximum change rates of the average and standard deviation for inclinations are 183.71% and 40.06%, respectively. Successively, an experiment-conducted microdynamic model is developed for numerical simulation of the MRG mechanical behaviors. During that, high-velocity MRG behaviors are explored with a tubular rather than regular flat-structure boundary condition setups, to pursue more trustable results. Simulation readouts meet nicely with those from experiments in revealing the magneto-mechanical coupling mechanism of MRG under multiphysics. The interaction between magnetic force, repulsive force and viscous resistance is mainly illustrated. This work provides a reliable observation basis for micromorphological variation of MRG, also suggests a new method for the mechanism of magneto-mechanical coupling at extreme velocities.
Optimized design for absorption metasurface based on autoencoder (AE) and BiLSTM-Attention-FCN-Net
Authors: Zhu Lei , Du Wenchen , Dong Liang , Wei Jinxu 
Published: January 2024

Abstract
In order to speed up the process of optimizing design of metasurface absorbers, an improved design model for metasurface absorbers based on autoencoder (AE) and BiLSTM-Attention-FCN-Net (including bidirectional long-short-term memory network, attention mechanism, and fully-connection layer network) is proposed. The metasurface structural parameters can be input into the forward prediction network to predict the corresponding absorption spectra. Meantime, the metasurface structural parameters can be obtained by inputting the absorption spectra into the inverse prediction network. Specially, in the inverse prediction network, the bidirectional long-short-term memory (BiLSTM) network can effectively capture the context relationship between absorption spectral sequence data, and the attention mechanism can enhance the BiLSTM output sequence features, which highlight the critical feature information. After the training, the mean square error (MSE) value on the validation set of the reverse prediction network converges to 0.0046, R2 reaches 0.975, and our network can accurately predict the metasurface structure parameters within 1.5 s with a maximum error of 0.03 mm. Moreover, this model can achieve the optimal design of multi-band metasurface absorbers, including the single-band, dual-band, and three-band absorptions. The proposed method can also be extended to other types of metasurface optimization design.
Optical ladder operators in the Glauber-Fock oscillator array
Authors: Bocanegra-Garay I A , Hernández-Sánchez L , Ramos-Prieto I , Soto-Eguibar F , Moya-Cessa H M 
Published: January 2024

Abstract
In this study, we investigate the stationary states of the Glauber-Fock oscillator waveguide array. We begin by transforming the associated Hamiltonian into the form of a quantum harmonic oscillator Hamiltonian, allowing the implementation of a supersymmetric (SUSY) approach. By considering the simplest case for the intertwining operator, the optical ladder operators are straightforwardly constructed and shown to map eigensolutions into eigensolutions of the corresponding Hamiltonian operator, in pretty much the same manner as it is done for the quantum harmonic oscillator case. The ladder of the corresponding (eigen) supermodes is then easily established.