bluuebunny/crossref_metadata_2025_split huggingface dataset:
New mathematical model based on geometric algebra for physical power flow in theoretical two-dimensional multi-phase power circuits
Authors: Montoya Francisco G. , Prado Xabier , Arrabal-Campos Francisco M. , Alcayde Alfredo , Mira Jorge 
Published: January 2023

AbstractThis study proposes an explanation for the physical power flow in planar circuits by analogy to theoretical two-dimensional circuits using a new mathematical model based on Geometric Algebra (GA) and 2D Maxwell’s equations. In contrast with traditional 3D physics in the observable real world, the magnetic field can be defined as a bivector instead of an axial vector allowing to obtain the Poynting Vector directly in a 2D flat world, where physical variables of planar circuits can be obtained. This approach is presented here for the first time to the best of the author’s knowledge. Previous investigations have focused on simplifications and symmetries of real 3D circuits studied mainly in the phasor and frequency domain. In this work, the electromagnetic power flow phenomenon is analyzed on a completely 2D time-domain basis and derived directly from the undisputed Maxwell equations, formulated in two dimensions. Several cases of special interest in AC multi-phase circuits are presented using the proposed technique, bringing a new simplified approach to the measurement of power flow exchange between the source and the load. It suggests a new way to understand energy propagation from a purely physical point of view.
A comprehensive deep learning method for empirical spectral prediction and its quantitative validation of nano-structured dimers
Authors: Verma Sneha , Chugh Sunny , Ghosh Souvik , Rahman B. M. Azizur 
Published: January 2023

AbstractNanophotonics exploits the best of photonics and nanotechnology which has transformed optics in recent years by allowing subwavelength structures to enhance light-matter interactions. Despite these breakthroughs, design, fabrication, and characterization of such exotic devices have remained through iterative processes which are often computationally costly, memory-intensive, and time-consuming. In contrast, deep learning approaches have recently shown excellent performance as practical computational tools, providing an alternate avenue for speeding up such nanophotonics simulations. This study presents a DNN framework for transmission, reflection, and absorption spectra predictions by grasping the hidden correlation between the independent nanostructure properties and their corresponding optical responses. The proposed DNN framework is shown to require a sufficient amount of training data to achieve an accurate approximation of the optical performance derived from computational models. The fully trained framework can outperform a traditional EM solution using on the COMSOL Multiphysics approach in terms of computational cost by three orders of magnitude. Furthermore, employing deep learning methodologies, the proposed DNN framework makes an effort to optimise design elements that influence the geometrical dimensions of the nanostructure, offering insight into the universal transmission, reflection, and absorption spectra predictions at the nanoscale. This paradigm improves the viability of complicated nanostructure design and analysis, and it has a lot of potential applications involving exotic light-matter interactions between nanostructures and electromagnetic fields. In terms of computational times, the designed algorithm is more than 700 times faster as compared to conventional FEM method (when manual meshing is used). Hence, this approach paves the way for fast yet universal methods for the characterization and analysis of the optical response of nanophotonic systems.
Predicting mortality and visualizing health care spending by predicted mortality in Danes over age 65
Authors: Hansen Anne Vinkel , Mortensen Laust Hvas , Ekstrøm Claus Thorn , Trompet Stella , Westendorp Rudi 
Published: January 2023

AbstractHealth care expenditure in the last year of life makes up a high proportion of medical spending across the world. This is often framed as waste, but this framing is only meaningful if it is known at the time of treatment who will go on to die. We analyze the distribution of health care spending by predicted mortality for the Danish population over age 65 over the year 2016, with one-year mortality predicted by a machine learning model based on sociodemographics and use of health care services for the two years before entry into follow-up. While a reasonably good model can be built, extremely few individuals have high ex-ante probability of dying, and those with a predicted mortality of more than 50% account for only 2.8% of total health care expenditure. Decedents outspent survivors by a factor of more than ten, but compared to survivors with similar predicted mortality they spent only 2.5 times as much. Our results suggest that while spending in the last year of life is indeed high, this is nearly all spent in situations where there is a reasonable expectation that the patient can survive.
Essential oil composition and total phenolic content in Cupressus arizonica G. in response to microbial inoculation under water stress conditions
Authors: Aalipour Hamed , Nikbakht Ali , Sabzalian Mohammad R. 
Published: January 2023

AbstractArizona Cypress is one of the drought-resistant, aromatic, and aesthetically pleasing trees having several pharmacological uses. Certain microorganisms contribute to the secondary metabolism and synthesis of bioactive compounds in aromatic and medicinal plants. This study aimed to determine the photosynthetic pigments, total phenolic content, antioxidant capacity, and essential oil composition of Arizona cypress under two irrigation regimes and microbial inoculations. We established a factorial experiment with three mycorrhizae inoculations (Rhizophagusirregularis, Funneliformismosseae, and a mixture of R.irregularis and F.mosseae), a rhizobacterium inoculation (Pseudomonasfluorescens), and two irrigation regimes (well-watered and water stress). Under the water stress regime, seedlings inoculated with F.mosseae (0.46%) and non-inoculated control plants (0.29%) had the highest and lowest essential oil contents, respectively. GC–MS analysis revealed that limonen, a-pinene, terpinen-4-ol, and umbellulone were the most abundant compounds in the seedlings and treatments under study. The water stress regime had a significant and dominant effect on essential oil and antioxidant capacity, whereas seedling growth and photosynthetic pigments tended to decrease under stress conditions. However, co-inoculation of seedlings with mycorrhizae and the bacterium resulted in an increase in phenolic compounds and carotenoids. Under conditions of water stress and mycorrhizal symbiosis, the results of the current study may help increase the level of valuable compounds in Arizona cypress for further pharmaceutical applications.
Association of IL-4 with pachychoroid neovasculopathy
Authors: Baba Takashi , Koyama Ayumi , Uotani Ryu , Miyake Hitomi , Inata Kodai , Sasaki Shin-ichi , Shimizu Yumiko , Inoue Yoshitsugu , Adachi Kaori , Nanba Eiji , Miyazaki Dai 
Published: January 2023

AbstractThe purpose of this study was to identify the inflammatory cytokines that were associated with pachychoroid neovasculopathy (PNV). Seventy-five eyes of 75 patients with PNV, 145 eyes of 145 patients with neovascular age-related macular degeneration without pachyvessels, and 150 eyes of 150 normal subjects were examined for the levels of intraocular cytokines. In eyes with PNV, the levels of IL-1α, IL-1β, IL-2, IL-4, IL-10, and VEGF were significantly higher than that of the controls. Logistic regression analysis showed that the highest association with the pachyvessels was found for IL-4, IL-2, and IL-1α. In eyes with PNV, the levels of IL-4, IL-2, IL-5, IL-13, IL-1α, and IL-1β were significantly higher in eyes with both increased choroidal thickness and choroidal vessel diameter. The strongest correlation with the choroidal thickness and vessel diameter was observed for IL-4. In PNV eyes with polypoidal lesions, the levels of IL-4, IL-17, and TNFβ were significantly correlated with the number of polypoidal lesions. Of these cytokines, IL-4 was especially associated with the thickness of the choroidal vessels and the formation of polypoidal lesions. We conclude that IL-4 is most likely involved in establishing the clinical characteristics of PNV and polypoidal vascular remodeling.
Research on optimization of control parameters of gravity shaking table
Authors: You Keshun , Liu Huizhong 
Published: January 2023

AbstractWhen image processing and machine vision technology are used to extract features from the image of the ore belt of the shaking table, so as to realize the analysis of the processing indictors and mapping of control parameters. To realize the adaptive optimization of the multiple control parameters of the shaking table, it is necessary to have thorough access to the parameters of the internal and external properties of the gravity shaker, such as internal control parameters and external ore zone characteristics, as well as the processing indicators. In this study, information on the multi-scale characteristics of the zone is obtained through a visual experimental system, and the data-driven model of the separation process is constructed to characterize the relationship between the properties of the internal and external parameters of the shaking table, eventually, an adaptive optimization method of control parameters of the shaking table based on maximizing beneficiation efficiency is proposed. The research results show that the data from the geometric characteristics of the ore belts obtained from practical experiments all satisfy the statistical distribution requirements. In the three optimized support vector regression (SVR) models, the sparrow search algorithm optimized SVR (SSA-SVR) has the best comprehensive performance, which overcomes the limits of data samples under objective conditions and basically meets the existing industrial requirements. With these helps, the proposed optimization method has realized the continuous optimization of multiple control parameters of the shaking table, and the optimization results have a good guarantee.
IMU-based human activity recognition and payload classification for low-back exoskeletons
Authors: Pesenti Mattia , Invernizzi Giovanni , Mazzella Julie , Bocciolone Marco , Pedrocchi Alessandra , Gandolla Marta 
Published: January 2023

AbstractNowadays, work-related musculoskeletal disorders have a drastic impact on a large part of the world population. In particular, low-back pain counts as the leading cause of absence from work in the industrial sector. Robotic exoskeletons have great potential to improve industrial workers’ health and life quality. Nonetheless, current solutions are often limited by sub-optimal control systems. Due to the dynamic environment in which they are used, failure to adapt to the wearer and the task may be limiting exoskeleton adoption in occupational scenarios. In this scope, we present a deep-learning-based approach exploiting inertial sensors to provide industrial exoskeletons with human activity recognition and adaptive payload compensation. Inertial measurement units are easily wearable or embeddable in any industrial exoskeleton. We exploited Long-Short Term Memory networks both to perform human activity recognition and to classify the weight of lifted objects up to 15 kg. We found a median F1 score of $$90.80\%$$

90.80
%

(activity recognition) and $$87.14\%$$

87.14
%

(payload estimation) with subject-specific models trained and tested on 12 (6M-6F) young healthy volunteers. We also succeeded in evaluating the applicability of this approach with an in-lab real-time test in a simulated target scenario. These high-level algorithms may be useful to fully exploit the potential of powered exoskeletons to achieve symbiotic human–robot interaction.
Energetic and behavioral consequences of migration: an empirical evaluation in the context of the full annual cycle
Authors: Brown J. Morgan , Bouten Willem , Camphuysen Kees C. J. , Nolet Bart A. , Shamoun-Baranes Judy 
Published: January 2023

AbstractSeasonal migrations are used by diverse animal taxa, yet the costs and benefits of migrating have rarely been empirically examined. The aim of this study was to determine how migration influences two ecological currencies, energy expenditure and time allocated towards different behaviors, in a full annual cycle context. We compare these currencies among lesser black-backed gulls that range from short- (< 250 km) to long-distance (> 4500 km) migrants. Daily time-activity budgets were reconstructed from tri-axial acceleration and GPS, which, in conjunction with a bioenergetics model to estimate thermoregulatory costs, enabled us to estimate daily energy expenditure throughout the year. We found that migration strategy had no effect on annual energy expenditure, however, energy expenditure through time deviated more from the annual average as migration distance increased. Patterns in time-activity budgets were similar across strategies, suggesting migration strategy does not limit behavioral adjustments required for other annual cycle stages (breeding, molt, wintering). Variation among individuals using the same strategy was high, suggesting that daily behavioral decisions (e.g. foraging strategy) contribute more towards energy expenditure than an individual’s migration strategy. These findings provide unprecedented new understanding regarding the relative importance of fine versus broad-scale behavioral strategies towards annual energy expenditures.
Sediment vibration characteristics based on accelerometer measurements
Authors: Wang Pingyi , Yuan Jun , Wang Meili , Wang Mi 
Published: January 2023

AbstractThe study of the vibration phenomenon of pebbles under turbulence is still a gap despite recent technological advancements in measurement capabilities. In this study, the vibration process of a fully exposed, isolated smart pebble on a rough bed was measured using a miniature inertial accelerometer and combined with simultaneous local measurements of the near-bed velocities. The paper conducts a series of experimental studies with different flow conditions. The test data match well with the manually observed phenomena, indicating the authenticity of the sediment vibration data collected by the measurement system. The test results show that the pebble motion (before entrainment) subjected to turbulence is a nonlinear vibration process, and its vibration types include in-situ vibration and ex-situ strong vibration. The probability distribution for the amplitude of vibration acceleration is well parameterized by the normal distribution. The vibration intensity tends to increase before approaching the threshold, but it weakens when approaching the point. The sediment vibration frequency is within 20–25 Hz, similar to the flow pulsation frequency and belongs to low-frequency vibration. The data indicate that the near-bed flow velocity is most directly related to the particle vibration events.
Low complexity symmetric-coded based sphere decoding for low-rate polar codes
Authors: Liu Yuanbo , Chen Haiqiang , Chen Jichang , Liao Lanjuan , Huang Fuyi , Sun Youming , Li Xiangcheng 
Published: January 2023

AbstractThe sphere decoding (SD) algorithm can provide (sub)optimal solutions with reduced computational complexity of maximum likelihood (ML) detection for multi-input multi-output (MIMO) communication systems. In this paper, we propose a novel low complexity symmetric-coded based SD algorithm for short polar codes with low rate. At the encoding stage, the first N/2 sub-channels transmit the frozen bits, while the information bits are selected from the latter N/2 sub-channels. Two symmetric codes are generated due to the mathematical structure of the generator matrix, which is well conditioned to the SD search. At the decoding stage, the presented SD algorithm computes the Euclidean distance value by the combined signals to estimate the latter N/2 input bits. Furthermore, the backtrack operation starts from the earlier $$(N/2+1)$$

(
N
/
2
+
1
)

-th bit, which can significantly reduce the average visited nodes (AVN). Simulation results show that, compared to the original SD algorithm, the presented variant of the SD algorithm can reduce the AVN to $$0.9\%$$

0.9
%

for the polar code P(64, 14) at SNR = 1 dB with a performance loss within 0.2 dB. The presented SD algorithm may find applications in MIMO systems where the complexity of the standar ML detection increases exponentially with the transmitting antennas.
Feasibility study of automated cardiac motion quantification to assess left ventricular function in type 2 diabetes
Authors: Li Yiming , Wu Cungang , Li Yuhong 
Published: January 2023

AbstractThe global incidence of diabetes and related complications is gradually increasing, with cardiovascular complications being the leading cause of death in the diabetic population. The purpose of this study was to examine left ventricular function in individuals with type 2 diabetes mellitus (T2D) and conduct a feasibility analysis using automated cardiac motion quantification (aCMQ) approach. A total of 150 T2D patients with a history of diabetes mellitus dating back more than 10 years were chosen, and we treated 87 patients with T2D that had been present for less than 15 years as group I, 63 patients with T2D that had been present for more than 15 years as group II, and 50 healthy volunteers as the control group. From the three groups, clinical information, conventional ultrasonography parameters, and mitral annular plane systolic excursion (MAPSE) parameters were gathered. aCMQ technique was used to collect longitudinal strain and circumferential strain in the left ventricle. Tissue motion mitral annular displacement technique (TMAD) in aCMQ was used to collect parameters related to TMAD, and cardiac motion quantification (CMQ) was used to collect two-dimensional global longitudinal strain (2D-GLS) to compare the degree of difference between the aforementioned three groups. The differences between longitudinal strain groups in aCMQ were all statistically significant and gradually decreased with increasing disease duration. Most TMAD parameters were lower in groups I and II than in the control group, and TMAD parameters gradually decreased with increasing disease duration. The results of the LV global longitudinal strain and 2D-GLS using Bland–Altman analyses showed high agreement between and within groups, Pearson correlation analysis showed a significant positive correlation (r = 0.18, P < 0.05), and the AUC of ROC curves predicting the value of left ventricular function in patients with T2D was 0.723 and 0.628, respectively. With significant positive correlations between MAPSE, s', and the majority of the TAMD parameters (P < 0.05), TAMD, MAPSE, and s' demonstrated high inter- and intra-group agreement using Bland–Altman analyses, and the three had predictive value in assessing left ventricular function in T2D patients by ROC curve. Reduced longitudinal strain and reduced mitral annular displacement were seen in patients with different disease stages of T2D, so the application of aCMQ and TAMD was effective in detecting altered left ventricular function in patients with T2D. aCMQ had higher value in predicting left ventricular function in patients with T2D compared to CMQ for overall longitudinal strain, and the software performed the depiction automatically, reducing manual errors. MAPSE parameters and s ' can replace the TMAD technique for assessing mitral annular motion and was simpler to perform, saving operational time.
T2* quantification using multi-echo gradient echo sequences: a comparative study of different readout gradients
Authors: Shin Seonyeong , Yun Seong Dae , Shah N. Jon 
Published: January 2023

AbstractTo quantify T2*, multiple echoes are typically acquired with a multi-echo gradient echo sequence using either monopolar or bipolar readout gradients. The use of bipolar readout gradients achieves a shorter echo spacing time, enabling the acquisition of a larger number of echoes in the same scan time. However, despite their relative time efficiency and the potential for more accurate quantification, a comparative investigation of these readout gradients has not yet been addressed. This work aims to compare the performance of monopolar and bipolar readout gradients for T2* quantification. The differences in readout gradients were theoretically investigated with a Cramér-Rao lower bound and validated with computer simulations with respect to the various imaging parameters (e.g., flip angle, TR, TE, TE range, and BW). The readout gradients were then compared at 3 T using phantom and in vivo experiments. The bipolar readout gradients provided higher precision than monopolar readout gradients in both computer simulations and experimental results. The difference between the two readout gradients increased for a lower SNR and smaller TE range, consistent with the prediction made using Cramér-Rao lower bound. The use of bipolar readout gradients is advantageous for regions or situations where a lower SNR is expected or a shorter acquisition time is required.
Influence of Dzyaloshinskii–Moriya interaction and perpendicular anisotropy on spin waves propagation in stripe domain patterns and spin spirals
Authors: Gruszecki Pawel , Kisielewski Jan 
Published: January 2023

AbstractTexture-based magnonics focuses on the utilization of spin waves in magnetization textures to process information. Using micromagnetic simulations, we study how (1) the dynamic magnetic susceptibility, (2) dispersion relations, and (3) the equilibrium magnetic configurations in periodic magnetization textures in a ultrathin ferromagnetic film in remanence depend on the values of the Dzyaloshinskii–Moriya interaction and the perpendicular magnetocrystalline anisotropy. We observe that for large Dzyaloshinskii–Moriya interaction values, spin spirals with periods of tens of nanometers are the preferred state; for small Dzyaloshinskii–Moriya interaction values and large anisotropies, stripe domain patterns with over a thousand times larger period are preferable. We observe and explain the selectivity of the excitation of resonant modes by a linearly polarized microwave field. We study the propagation of spin waves along and perpendicular to the direction of the periodicity. For propagation along the direction of the periodicity, we observe a bandgap that closes and reopens, which is accompanied by a swap in the order of the bands. For waves propagating in the perpendicular direction, some modes can be used for unidirectional channeling of spin waves. Overall, our findings are promising in sensing and signal processing applications and explain the fundamental properties of periodic magnetization textures.