bluuebunny/crossref_metadata_2025_split huggingface dataset:
Theoretical investigation of the impact of apodized fiber Bragg grating and machine learning approaches in quasi-distributed sensing
Authors: Mandal Himadri Nirjhar , Sidhishwari Soumya 
Published: June 2023

Abstract
An apodized fiber Bragg grating (FBG) is designed to investigate the impacts of side lobe elimination in quasi-distributed sensing for the estimation of measurands (like temperature and strain) to assess the condition of civil structures, such as bridges. The adjacent FBG spectrums may overlap with each other because of the impacts of temperature and strain due to the presence of a high range of side lobes in a quasi-distributed sensing network. Therefore, elimination of side lobes is necessary, by introducing a method of apodization. The sensitivity of the designed apodized FBG is estimated by analyzing the variations in the Bragg wavelength due to the impacts of temperature and strain. The changes in Bragg wavelength due to the measurands can affect the grating period and the grating index of the FBG. The period of the grating and the grating index of the FBG are simultaneously varied by temperature and strain. To measure the physical parameters effectively, it is essential to distinguish whether the changes in the Bragg wavelength are owing to the impacts of temperature or to the impacts of strain. The effect of cross-sensitivity between the temperature and the strain is a key problem in any FBG-based sensing application as both the measurands can affect the Bragg wavelength. In this work, machine learning methods (the support vector machine, K-nearest neighbors, logistic regression, naïve Bayes, decision tree, and ensemble models) are introduced to differentiate between the effects of temperature and strain on a single Bragg wavelength shift measurement. An artificial neural network is used for the predictive analysis of physical parameters, to identify any measurements of potential concern. It has been noted that the performance of the proposed ensemble model is higher compared to other models for the classification of temperature and strain.
A do-it-yourself approach for developing a magnetic field mapping setup using a 3D printer
Authors: Omelyanchik Alexander , Marqués Jose Luis , Rivas Montserrat , Rodionova Valeria , Canepa Fabio , Peddis Davide 
Published: June 2023

Abstract
The mapping of magnetic fields is an important task for characterizing permanent magnets, their systems, and the various devices that use magnets. However, commercial devices for this task are quite expensive and difficult to acquire. In this study, a design process for an automatized magnetic mapping setup utilizing a 3D printer was proposed via a do-it-yourself approach using common parts found in a laboratory. We used a 3D printer for two purposes: to create instrument parts to fix the Hall probe instead of the printer extruder, and to use the same 3D printer as the position controller of the magnetic probe. We describe the device assembly process, including hardware and software aspects. Several tests of the assembled setup were performed on samples with different magnetic texture dimensions from several centimeters (graduated permanent magnet) to tens of micrometers (flexible magnet with a planar Halbach structure and a 5¼ inch floppy disk). The spatial resolution was in the sub-millimeter range. The parameters of the mapping, such as the number of points and data acquisition time, were optimized for such samples.
An in-situ thermoelectric measurement apparatus inside a thermal-evaporator
Authors: Nguyen Kien Trung , Bui-Thanh Giang , Pham Hong Thi , Nguyen-Tran Thuat , Hoang Chi Hieu , Nguyen Hung Quoc 
Published: June 2023

Abstract
At the ultra-thin limit below 20 nm, a film’s electrical conductivity, thermal conductivity, or thermoelectricity depends heavily on its thickness. In most studies, each sample is fabricated one at a time, potentially leading to considerable uncertainty in later characterizations. We design and build an in-situ apparatus to measure thermoelectricity during their deposition inside a thermal evaporator. A temperature difference of up to 2 K is generated by a current passing through an on-chip resistor patterned using photolithography. The Seebeck voltage is measured on a Hall bar structure of a film deposited through a shadow mask. The measurement system is calibrated carefully before loading into the thermal evaporator. This in-situ thermoelectricity measurement system has been thoroughly tested on various materials, including Bi, Te, and Bi2Te3, at high temperatures up to 500 K. Working reliably and precisely, the in-situ measurement system would help to study physics during film growth or speedup our search for better thermoelectric materials.
A novel two-stage kinetic model for surface DBD simulations in air
Authors: Pierotti Giacomo , Piferi Cecilia , Popoli Arturo , Cavedon Marco , Cristofolini Andrea , Martines Emilio , Riccardi Claudia 
Published: June 2023

Abstract
In this work, a novel 0D model for the evaluation of O3 and NO2 produced by a surface dielectric barrier discharge (SDBD) in a closed environment is presented. The model is composed by two coupled sub-models, a discharge sub-model and an afterglow one. The first one, simulating the discharge regime and consequently including electron impact reactions, aims to calculate the production rates of a set of key species (atomic oxygen, excited states of molecular oxygen and molecular nitrogen). These latter are the input of the afterglow sub-model, that simulates the afterglow regime. We introduce a methodology to relate the production rates of the above mentioned species to the input power of the SDBD reactor. The simulation results are validated by a comparison with experimental data from absorption spectroscopy. The experimental measurements are carried out as follows. First, the discharge is turned on until the NO2 number density reaches steady state. Then, the discharge is turned off for several minutes. Finally, the discharge is turned on again to observe the effects of the NO2 concentration on ozone dynamics. The entire process is done without opening the box. The system operating in all the above-listed conditions is simulated for three different levels of input power.
Diatomic molecule in a strong infrared laser field: level-shifts and bond-length change due to laser-dressed Morse potential
Authors: Varró Sándor , Hack Szabolcs , Paragi Gábor , Földi Péter , Barna Imre F , Czirják Attila 
Published: June 2023

Abstract
We present a general mathematical procedure to handle interactions described by a Morse potential in the presence of a strong harmonic excitation. We account for permanent and field-induced terms and their gradients in the dipole moment function, and we derive analytic formulae for the bond-length change and for the shifted energy eigenvalues of the vibrations, by using the Kramers–Henneberger frame. We apply these results to the important cases of H2 and LiH, driven by a near- or mid-infrared laser in the 1013 W cm−2 intensity range.
Phantom attractors in kinetic gravity braiding theories: a dynamical system approach
Authors: Borislavov Vasilev Teodor , Bouhmadi-López Mariam , Martín-Moruno Prado 
Published: June 2023

Abstract
We revise the expansion history of the scalar field theories known as Kinetic Gravity Braiding. These theories are well-known for the possibility of driving the expansion of the cosmos towards a future self-tuning de Sitter state when the corresponding Lagrangian is invariant under constant shifts in the scalar field. Nevertheless, this is not the only possible future fate of these shift-symmetric models. Using a dynamical system formulation we show that future cosmological singularities can also appear in this framework. Moreover, we present explicit examples where the future attractor in the configuration space of the theory corresponds to a big rip singularity.
Dark Sector extensions of the Littlest Seesaw in the presence of Primordial Black Holes
Authors: Coleppa Baradhwaj , Loho Kousik , Shil Sujay 
Published: June 2023

Abstract
The Littlest Seesaw model is a very well motivated dark matter model. Here we consider an extension of that model with an additional scalar and an additional fermionic particle under the freeze-in scenario. Formation of black hole of a certain mass range at primordial times can act as an alternate production mechanism for the dark matter particles as it evaporates via Hawking radiation. Furthermore, the presence of primordial black holes with substantial energy density gives rise to non-standard cosmology which also modifies the freeze-in production. In this paper, we have investigated the extended Littlest Seesaw model under the freeze-in scenario in the presence of a primordial black hole for various interesting cases and constrained the parameter space accordingly. If the universe is primordial black hole dominated at any point in the evolution of the universe, we find that the final relic in that case is dominated mostly by the evaporation component for a high dark matter mass and by the freeze-in component for a low dark matter mass.
Corrigendum: EAST discharge prediction without integrating simulation results (2022 Nucl. Fusion 62 126060)
Authors: Wan Chenguang , Yu Zhi , Pau Alessandro , Liu Xiaojuan , Li Jiangang 
Published: June 2023

Abstract
In the published paper titled ‘EAST discharge prediction without integrating simulation results’ (2022 Nucl. Fusion 62 126060), figure 5 used the wrong plot, and is not matched with table 3. We used the plot discussed with referees, the case when we do not use IC 1 as a proxy. This corrigendum provides the correct plot for figure 5.
Optimized silk fibroin nanoparticle functionalization with anti-CEA nanobody enhancing active targeting of colorectal cancer cells
Authors: Fan Xiying , Peng Xinying , Wang Tingting , Gu Yi , Sun Guochuan , Shou Qinghui , Song Haipeng , Nian Rui , Liu Wenshuai 
Published: June 2023

Abstract
This work aimed to establish a simple and feasible method to obtain silk fibroin nanoparticles (SFNPs) with uniform particles size, and then modify the SFNPs with nanobody (Nb) 11C12 targeting the proximal membrane end of carcinoembryonic antigen on the surface of colorectal cancer (CRC) cells. The regenerated silk fibroin (SF) was isolated using ultrafiltration tubes with a 50 kDa molecular weight cut-off, and the retention fraction (named as SF > 50 kDa) was further self-assembled into SFNPs by ethanol induction. Scanning electron microscope (SEM) and high-resolution transmission electron microscop showed that the SFNPs with uniform particles size were formed. Due to electrostatic adsorption and pH responsiveness, SFNPs have been proved to effectively load and release the anticancer drug doxorubicin hydrochloride (DOX) (DOX@SFNPs). Further, targeting molecule Nb 11C12 was used to modify these nanoparticles, constituting the targeted outer layer of the drug delivery system (DOX@SFNPs-11C12), achieving precise localization to cancer cells. The release amount of DOX observed from in vitro drug release profiles increased as follows: pH 7.4 < pH 6.8 < pH 5.4, demonstrating that the DOX release could be accelerated in a weakly acidic environment. In vitro cytotoxicity experiments displayed that SFNPs-11C12 nanoparticles exhibited good safety and biocompatibility. Drug-loaded nanoparticles, DOX@SFNPs-11C12, led to higher LoVo cells apoptosis compared to DOX@SFNPs. Fluorescence spectrophotometer characterization and confocal laser scanning microscopy further showed that the internalization of DOX was highest in the DOX@SFNPs-11C12, certifying that the introduced targeting molecule enhanced the uptake of drug delivery system by LoVo cells. This study provides a simple and operational approach to developing an optimized SFNPs drug delivery system modified by targeting Nb, which can be a good candidate for CRC therapy.
Using GEDI as training data for an ongoing mapping of landscape-scale dynamics of the plant area index
Authors: Ziegler Alice , Heisig Johannes , Ludwig Marvin , Reudenbach Chris , Meyer Hanna , Nauss Thomas 
Published: June 2023

Abstract
Leaf or plant area index (LAI, PAI) information is frequently used to describe vegetation structure in environmental science. While field measurements are time-consuming and do not scale to landscapes, model-based air- or space-borne remote-sensing methods have been used for many years for area-wide monitoring. As of 2019, NASA’s Global Ecosystem Dynamics Investigation (GEDI) mission delivers a point-based LAI product with 25 m footprints and periodical repetition. This opens up new possibilities in integrating GEDI as frequently generated training samples with high resolution (spectral) sensors. However, the foreseeable duration of the system installed on the ISS is limited. In this study we want to test the potential of GEDI for regional comprehensive LAI estimations throughout the year with a focus on its usability beyond the lifespan of the GEDI mission. We study the landscape of Hesse, Germany, with its pronounced seasonal changes. Assuming a relationship between GEDI’s PAI and Sentinel-1 and -2 data, we used a Random Forest approach together with spatial variable selection to make predictions for new Sentinel scenes. The model was trained with two years of GEDI PAI data and validated against a third year to provide a robust and temporally independent model validation. This ensures the applicability of the validation for years outside the training period, reaching a total RMSE of 1.12. Predictions for the test year showed the expected seasonal and spatial patterns indicated by RMSE values ranging between 0.75 and 1.44, depending on the land cover class. The overall prediction performance shows good agreement with the test data set of the independent year which supports our assumption that the usage of GEDI’s PAI beyond the mission lifespan is feasible for regional studies.
Africa’s ecosystems exhibit a tradeoff between resistance and stability following disturbances
Authors: Lauer Daniel A , McGuire Jenny L 
Published: June 2023

Abstract
Environmental disturbances may prevent ecosystems from consistently performing their critical ecological functions. Two important properties of ecosystems are their resistance and stability, which respectively reflect their capacities to withstand and recover from disturbance events (e.g. droughts, wildfires, pests, etc). Theory suggests that resistant and stable ecosystems possess opposing characteristics, but this has seldom been established across diverse ecosystem attributes or broad spatial scales. Here, we compare the resistance and stability of >1000 protected area ecosystems in Africa to disturbance-induced losses in primary productivity from 2000 to 2019. We quantitatively evaluated each ecosystem such that following disturbances, an ecosystem is more resistant if it experiences lower-magnitude losses in productivity, and more stable if it returns more rapidly to pre-disturbance productivity levels. To compare the characteristics of resistant versus stable ecosystems, we optimized random forest models that use ecosystem attributes (representing their climatic and environmental conditions, plant and faunal biodiversity, and exposure to human impacts) to predict their resistance and, separately, stability values. We visualized each attribute’s relationship with resistance and stability after accounting for all other attributes in the model framework. Ecosystems that are more resistant to disturbances are less stable, and vice versa. The ecosystem attributes with the most predictive power in our models all exhibit contrasting relationships with resistance versus stability. Notably, highly resistant ecosystems are generally more arid and exhibit high habitat heterogeneity and mammalian biodiversity, while highly stable ecosystems are the opposite. We discuss the underlying mechanisms through which these attributes engender resistance or, conversely, stability. Our findings suggest that resistance and stability are fundamentally opposing phenomena. A balance between the two must be struck if ecosystems are to maintain their identity, structure, and function in the face of environmental change.
First-principles study of electronic properties of two-dimensional metal mixed perovskites solar cell and water resistance performance
Authors: Ma Zi-Qian , Cheng Sen , Chen Wenzhou , Zhang Xiaodong , Zhu Xiuli 
Published: June 2023

Abstract
Two-Dimensional (2D) layered hybrid organic-inorganic perovskite (HOIP) materials have been considered as potential photoconductive materials for solar cells owing to extraordinary conversion efficiency and easy preparation process. In this study, we perform first-principles design on metal mixed 2D HOIPs (BA2(Cs1-x
Rb
x
)2Sn1.5Pb1.5I10 with different proportions of composition (x = 0, 0.5 and 1)) to investigate their electronic properties and stability against moisture. We find that the band gap and effective mass of BA2(Cs1-x
Rb
x
)2Sn1.5Pb1.5I10 increases as the concentrations of mixed Rb atoms increases. Moreover, the result of calculated adsorption energy indicates that the metal mixed 2D HOIPs with different composition ratios of Rb atom exhibit better capacity on the resistance of water than the pure one (BA2MA2Sn3I10). The metal mixed 2D HOIPs shows great potential to be a new generation of solar cell with low-cost, suitable band gap, high thermal stability, and desirable power conversion efficiency.
Analysing the impact of cloth fabrics on skin temperature during and after exercise using an FDM model
Authors: Patidar Neelam , Makrariya Akshara 
Published: June 2023

Abstract
This study presents a 1D finite difference model that examines the influence of cloth fabrics on skin temperature during and after exercise, considering the complex nature of the human body and its susceptibility to infections and viruses. The aim is to design comfortable, high-quality fabrics that minimize potential issues caused by body temperature fluctuations. The model incorporates various physical, physiological, and thermal parameters of cloth to develop protective clothing suitable for exercise. Numerical results were compared to previous studies that analyzed skin temperature without clothing to validate the model’s accuracy. The findings indicate a minimal difference in skin temperature when wearing cotton and polyester cloth, with polyester fabric demonstrating superior characteristics such as stretchability, durability, and sweat resistance. The thermal information obtained from this model can be utilized to design appropriate clothing for diverse weather conditions, ultimately enhancing the performance and comfort of athletes, military personnel, and individuals engaged in physically demanding work. Additionally, the model can aid in developing thermal stress protocols for infection treatment and provide guidelines for physical activity to promote healthy living. This research contributes to the field of materials research by offering valuable insights into the design and development of protective clothing for exercise. By understanding the impact of cloth fabrics on skin temperature, advancements can be made in creating clothing that optimizes human comfort and performance.
A new experimental setup to measure hydraulic conductivity of plant segments
Authors: Krieger Louis , Schymanski Stanislaus J 
Published: June 2023

Abstract
Plant hydraulic conductivity and its decline under water stress are the focal point of current plant hydraulic research. The common methods of measuring hydraulic conductivity control a pressure gradient to push water through plant samples, submitting them to conditions far away from those that are experienced in nature where flow is suction driven and determined by the leaf water demand. In this paper, we present two methods for measuring hydraulic conductivity under closer to natural conditions, an artificial plant setup and a horizontal syringe pump setup. Both approaches use suction to pull water through a plant sample while dynamically monitoring the flow rate and pressure gradients. The syringe setup presented here allows for controlling and rapidly changing flow and pressure conditions, enabling experimental assessment of rapid plant hydraulic responses to water stress. The setup also allows quantification of dynamic changes in water storage of plant samples. Our tests demonstrate that the syringe pump setup can reproduce hydraulic conductivity values measured using the current standard method based on pushing water under above-atmospheric pressure. Surprisingly, using both the traditional and our new syringe pump setup, we found a positive correlation between changes in flow rate and hydraulic conductivity. Moreover, when flow or pressure conditions were changed rapidly, we found substantial contributions to flow by dynamic and largely reversible changes in the water storage of plant samples. Although the measurements can be performed under sub-atmospheric pressures, it is not possible to subject the samples to negative pressures due to the presence of gas bubbles near the valves and pressure sensors. Regardless, this setup allows for unprecedented insights into the interplay between pressure, flow rate, hydraulic conductivity and water storage in plant segments. This work was performed using an Open Science approach with the original data and analysis to be found at https://doi.org/10.5281/zenodo.7322605.
Predicting phonological information in language comprehension: evidence from ERP representational similarity analysis and Chinese idioms
Authors: Wei Wei , Huang Zirui , Feng Chen , Qu Qingqing 
Published: June 2023

Abstract
Do comprehenders predict the meaning and even the phonological form of upcoming words during language comprehension? With a growing body of evidence suggesting that semantic representations may be predicted, the evidence for phonological prediction is less clear and largely derived from studies conducted in languages utilizing an alphabetic script. In this research, we aim to examine the prediction of phonological information in the processing of Chinese idioms through the use of ERP representational similarity analysis (RSA). The study utilizes four-character Chinese idioms, and phonological overlap was manipulated by varying the syllable at the idiom-final part between idiom pairs so that pairs of idioms share a syllable (i.e. within-pairs) or not (between-pairs). We quantified the similarity between patterns of neural activity of idioms for within- and between-pairs. RSA results revealed greater similarity in neural activity patterns for idioms within-pairs, compared with between-pairs, and critically this similarity effect was observed prior to the presentation of the phonological similarity, providing evidence for the pre-activation of upcoming phonological information, under circumstances that encourage predictive processing.