Miracle-dz/UniFAR-FTUs huggingface dataset:
Changes in Length/Height Deficit Level Children to Stunting in Indonesia

Background: Stunting is the most prevalence form of childhood undernutrition, with an estimated 155 million children worldwide falling below 2 SD from the WHO standard length/height-for-age median in 2016. Child stunting and linear growth faltering have declined over the past few decades and several countries have made exemplary progress. This study aimed to examine if Indonesia had made progress in reducing childhood stunting based on data taken from Basic Health Research (Riskesdas) in 2013 and 2018, respectively. Subjects and Method: These were two cross-sectional studies conducted in 2013 and 2018, respectively. Samples of 30,616 and 28,727 children were selected from Basic Health Research (Riskesdas) in 2013 and 2018, respectively. The dependent variable was deficit in height for age (cm) as compared with the WHO standard for stunted and normal children by age. The difference in mean deficit of height for age between 2013 and 2018 for both male and female children was tested by t-test. Results: Mean deficit of height for age in 2018 male children (Mean= 2.89; SD= 2.92) was smaller than that in 2013 (Mean= 3.86; SD= 3.55), and it was statistically significant (p< 0.001). Likewise, mean deficit of height for age in 2018 female children (Mean=2.87; SD= 3.01) was smaller than that in 2013 (Mean= 3.84; SD= 3.61), and it was statistically significant (p< 0.001). Conclusion: Mean deficit of height for age as compared with the WHO standard in 2018 is smaller than that in 2013 for both male and female children under five years of age. Indonesia has made progress in reducing childhood stunting based on data taken from Basic Health Research (Riskesdas) in 2013 and 2018, respectively.
Kangfuxiaoyanshuan alleviates uterine inflammation and adhesion via inhibiting NF-κB p65 and TGF-β/MMP-2 signaling pathway in pelvic inflammatory disease rats

Background and aims: Pelvic inflammatory disease (PID) is infection-induced inflammation of the female upper reproductive tract that results in high fever, ectopic pregnancy, infertility, and varying degrees of chronic pelvic pain. Recent clinical studies have shown that Kangfuxiaoyanshuan (KFXYS), a Traditional Chinese Medicine (TCM) formulation, may short the course of the disease and reduce the occurrence of PID sequelae, but its pharmacological action and potential mechanism have not been fully elucidated. Here, we aimed to investigate the therapeutic effects and mechanism of KFXYS in rats with PID. Materials and Methods: A PID rat model was constructed through endometrial mechanical injury and pathogen infection. The rectal temperature was measured during the 14-days course of treatment, and the white blood cell (WBC) count in the blood and the levels of cytokines (IFN-γ, IL-1β, IL-4, TNF-α) in the serum were evaluated by ELISA. Hematoxylin and eosin (HE) staining was performed to analyze pathological changes, and transmission electron microscopy (TEM) was used to observe ultrastructural changes. The p-p65/p65 protein expression was evaluated by western blotting and the levels of MMP-2 and TGF-β in adhesion tissues were assessed by immunohistochemistry. Results: KFXYS lowered the rectal temperature and the WBC counts in the blood in the acute stage of PID and alleviated inflammatory cell infiltration of the uterus, especially when combined with levofloxacin. KFXYS significantly decreased the levels of proinflammatory cytokines (IFN-γ, IL-1β, IL-4) and adhesion-related factors (TNF-α) and protected the ultrastructure of endometrial epithelial cells. Mechanistically, KFXYS inhibited the NF-κB activation by decreasing phosphorylation of p65, thus the alleviation of inflammation further reduced the expression of TGF-β and MMP-2, and inhibited the occurrence of uterine adhesions. Conclusion: These results revealed that KFXYS alleviated pelvic inflammation and effectively inhibits inflammation-associated adhesion, which indicated the potential role of KFXYS for treatment of PID and the prevention of PID sequelae.
Semisupervised Hyperspectral Image Classification via Superpixel-Based Graph Regularization With Local and Nonlocal Features

Although a graph-based semisupervised learning (SSL) approach can utilize limited numbers of labeled samples for hyperspectral image (HSI) classification, it is difficult to use the large amount of pixels in an HSI to construct a large-scale graph. In this article, we therefore propose a superpixel-based graph model for HSI classification, using anchor graph regularization to improve the extraction of local and nonlocal spatial information. To avoid the large-scale graph problem, the superpixel-based graph model constructs a scalable anchor graph using a small number of anchor points for graph-based SSL. The proposed approach consists of three key components: First, local and nonlocal features are extracted from the principal components of an HSI using the locally grouped order pattern and the nonlocal binary pattern approaches. Second, the extracted features are combined with the original spectral information and used as input to an improved simple line iteration clustering method to obtain superpixels, the centers of which are used as anchors in the anchor graph approach. Third, we use superpixel-based graph regularization to model the global information among the superpixels for better predictions of the label of each unlabeled pixel sample. Experimental results demonstrate that the proposed approach outperforms other state-of-the-art semisupervised HSI classification approaches for cases with a limited quantity of labeled samples.
Increasing Trends of Polypharmacy and Potentially Inappropriate Medication Use in Older Lung Cancer Patients in China: A Repeated Cross-Sectional Study

Objectives: Polypharmacy and potentially inappropriate medication (PIM) use are frequent in older lung cancer patients. This study aimed to examine the trends of polypharmacy and PIM use and explore risk factors for PIM use based on the 2019 Beers criteria in older Chinese lung cancer outpatients with multimorbidity. Methods: A repeated cross-sectional study was conducted using electronic medical data consisting of the prescriptions of older lung cancer outpatients in China from January 2016 to December 2018. Polypharmacy was defined as the use of five or more medications. The 2019 Beers criteria were used to evaluate the PIM use of older cancer outpatients (age ≥65 years), and multivariate logistic regression was used to identify the risk factors for PIM use. Results: A total of 3,286 older lung cancer outpatients and their prescriptions were included in the study. The prevalence of polypharmacy was 14.27% in 2016, 16.55% in 2017, and 18.04% in 2018. The prevalence of PIM use, according to the 2019 Beers criteria, was 31.94% in 2016, 35.78% in 2017, and 42.67% in 2018. The two most frequently used PIMs in older lung cancer outpatients were estazolam and tramadol. The logistic regression demonstrated that age 75 to 79, polypharmacy, irrational use of drugs, and lung cancer accompanied by sleep disorders, anxiety or depression, or pain were positively associated with PIM use in older lung cancer outpatients. Conclusion: The prevalence of polypharmacy and PIM use in older lung cancer outpatients with multimorbidity was high in China, and polypharmacy and PIM use increased over time. Further research on interventions rationing PIM use in the older lung cancer patient population is needed.
Design of license plate recognition system based on FPGA

In recent years, with the improvement of people's living standards, the number of vehicles is also increasing, and the effective management and identification of vehicles has a very important practical significance. To quickly identify and manage the vehicles, this paper has designed a license plate recognition system based on the field programmable logic gate array. By setting the binarization threshold, the license plate image binarization, the license plate information from the image, using the horizontal vertical projection method statistics the license plate information pixel statistics, separate the characters from the license plate information, then through the digital feature identification algorithm, and then the statistical results and character matching, so as to identify the specific content of the license plate. Experiments show that the system frame processing speed is 65fps, which can meet the real-time requirements, while the license plate recognition accuracy is 96.2%, with a low false alarm rate.
Mejora del diagnóstico y de la hemodinámica en la revascularización carotídea : aplicación de la dinámica de fluidos computacional mediante el OpenFOAM® y otras herramientas de libre distribución

Stroke is a major cause of death and disability in Spain and in the Western world. It is often caused by an accumulation of atherosclerotic plaques on the walls of carotid arteries. Carotid revascularization may be the solution chosen by the specialist. This choice depends directly on the symptoms, the diagnosis and the potential benefits vs. costs of performing surgery. Hemodynamics plays a crucial role in all decision making. The conventional methods for analyzing hemodynamics are Doppler ultrasound, computed tomography angiography (CTA) and magnetic resonance angiography (MRA). These methods may be enriched with the numerical simulation of blood flow in the area of interest, using techniques of computational fluid dynamics (CFD). The result of the simulations can be used to improve diagnosis and to propose hemodynamic improvement during surgery or treatment. It can also provide conclusions on the progress of the patient. However, it is currently very difficult to perform these simulations and reach valid conclusions. This difficulty is due to the state of the technique and to the lack of scientific consensus in regard to clinical aspects, data gathering and processing, reproduction of geometries, construction of models, and execution of the simulations, among other aspects. Furthermore, obtaining results and drawing conclusions from them requires a high degree of specialization and the use of software that is often expensive. The present thesis uses numerical simulation to replicate the blood flow in the carotid arteries. It uses the results to guide the diagnosis and prognosis of patient progress. It develops a methodology for the creation of numeric models using data provided by CTA and Doppler ultrasound, both of which are used in routine clinical practice. From the images contained in the files with DICOM format resulting from the CTA, the geometries of carotid arteries of patients are reproduced. The data provided by the ultrasound velocities are used to obtain velocity curves in the inputs, outputs and areas of interest within the carotid artery. Models of carotid arteries are also built with CAD tools. OpenFOAM®; is used for model meshing, solving the equations that govern the fluid movement and obtaining the relevant hemodynamic variables such as carotid wall shear stress. The Womersley boundary condition for velocities, which is the most suitable one for simulating pulse flows in carotid arteries, is implemented in this software environment. In cases of moderate stenosis, a diagnosis by a specialist is added. A comparison between a pre- and postoperative situation was made in order to take it into account for any proposals of hemodynamic improvement. The pre-processing, processing and post-processing were performed almost entirely with open source tools such as vmtk, enGrid, ParaView and OpenFOAM®.
Sputtered Ultrathin TiO2 as Electron Transport Layer in Silicon Heterojunction Solar Cell Technology

This work presents the implementation of ultrathin TiO2 films, deposited at room temperature by radio-frequency magnetron sputtering, as electron-selective contacts in silicon heterojunction solar cells. The effect of the working pressure on the properties of the TiO2 layers and its subsequent impact on the main parameters of the device are studied. The material characterization revealed an amorphous structure regardless of the working pressure; a rougher surface; and a blue shift in bandgap in the TiO2 layer deposited at the highest-pressure value of 0.89 Pa. When incorporated as part of the passivated full-area electron contact in silicon heterojunction solar cell, the chemical passivation provided by the intrinsic a-Si:H rapidly deteriorates upon the sputtering of the ultra-thin TiO2 films, although a short anneal is shown to restore much of the passivation lost. The deposition pressure and film thicknesses proved to be critical for the efficiency of the devices. The film thicknesses below 2 nm are necessary to reach open-circuit values above 660 mV, regardless of the deposition pressure. More so, the fill-factor showed a strong dependence on deposition pressure, with the best values obtained for the highest deposition pressure, which we correlated to the porosity of the films. Overall, these results show the potential to fabricate silicon solar cells with a simple implementation of electron-selective TiO2 contact deposited by magnetron sputtering. These results show the potential to fabricate silicon solar cells with a simple implementation of electron-selective TiO2 contact.
Millimeter-Wave Antennas Directivity Enhancement and Feeding Network Reduction Techniques

We present a comprehensive review of the recent advancements in directivity enhancement and feeding network reduction techniques. The presented techniques focus on providing a low-cost solution while maintaining high radiation efficiency. The solutions also provide physical insight to further explain the structures radiation mechanism. The provided solutions counter many challenges faced in designing mm-Wave antennas.
3-Hom–Lie Yang–Baxter Equation and 3-Hom–Lie Bialgebras

In this paper, we first introduce the notion of a 3-Hom–Lie bialgebra and give an equivalent description of the 3-Hom–Lie bialgebras, the matched pairs and the Manin triples of 3-Hom–Lie algebras. In addition, we define O-operators of 3-Hom–Lie algebras and construct solutions of the 3-Hom–Lie Yang–Baxter equation in terms of O-operators and 3-Hom–pre-Lie algebras. Finally, we show that a 3-Hom–Lie algebra has a phase space if and only if it is sub-adjacent to a 3-Hom–pre-Lie algebra.
Interaction Analysis Based on Shapley Values and Extreme Gradient Boosting: A Realistic Simulation and Application to a Large Epidemiological Prospective Study

Background SHapley Additive exPlanations (SHAP) based on tree-based machine learning methods have been proposed to interpret interactions between exposures in observational studies, but their performance in realistic simulations is seldom evaluated. Methods Data from population-based cohorts in Sweden of 47,770 men and women with complete baseline information on diet and lifestyles were used to inform a realistic simulation in 3 scenarios of small (ORM = 0.75 vs. ORW = 0.70), moderate (ORM = 0.75 vs. ORW = 0.65), and large (ORM = 0.75 vs. ORW = 0.60) discrepancies in the adjusted mortality odds ratios conferred by a healthy diet among men and among women. Estimates were obtained with logistic regression (L-ORM; L-ORW) and derived from SHAP values (S-ORM; S-ORW). Results The sensitivities of detecting small, moderate, and large discrepancies were 28, 83, and 100%, respectively. The sensitivities of a positive sign (L-ORW > L-ORM) in the 3 scenarios were 93, 100, and 100%, respectively. Similarly, the sensitivities of a positive discrepancy based on SHAP values (S-ORW > S-ORM) were 86, 99, and 100%, respectively. Conclusions In a realistic simulation study, the ability of the SHAP values to detect an interaction effect was proportional to its magnitude. In contrast, the ability to identify the sign or direction of such interaction effect was very high in all the simulated scenarios.
Investigating and Predicting Intentions to Continue Using Mobile Payment Platforms after the COVID-19 Pandemic: An Empirical Study among Retailers in India

The Indian retail industry has registered tremendous growth recently. The sudden emergence of Coronavirus Disease 2019 (COVID-19) and the related measures that were taken by the authorities to curb the pandemic have compelled retailers and their consumers to transact using digital platforms. This study investigates the critical precursors to retailers’ behavioral intention to use mobile platforms for their business transactions in the post-pandemic era. This study adopted a framework that combined the theory of planned behavior (TPB) and self-determination theory (SDT) to predict behavioral intentions. A hybrid approach combining partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) techniques was used to test and validate the proposed framework. Four hundred and ninety-six participants from different central Indian cities participated in the study. PLS-SEM results confirmed that the motivational factors (need satisfaction [NS] and need frustration [NF]) significantly influence the attitude (AT), subjective norms (SN), perceived behavioral control (PBC), and behavioral intention (BI). Furthermore, the findings also established the partial mediating effect of AT, SN, and PBC on the relationship between motivational construct (NS and NF) and BI. Finally, the relationship established by SEM was successfully validated by ANN in the existence of a nonlinear relationship in the data. The findings may help retail stakeholders to support retail owners in their pursuit to continue using mobile payment systems in the post-COVID-19 world.
SAR Tomography Based on Atomic Norm Minimization in Urban Areas

Synthetic aperture radar (SAR) tomography (TomoSAR) is a powerful tool for the three-dimensional (3D) reconstruction of buildings in urban areas. At present, the compressed sensing (CS) technique has been widely used in the TomoSAR inversion of urban areas because of the sparsity of the backscattering power of buildings along the elevation direction. However, this algorithm discretizes the elevation and assumes that the scatterers are located on predetermined finite grids. In fact, scatterers can lie anywhere in the elevation direction, regardless of grid point constraints. The phenomenon of scatterer positioning errors due to elevation discretization is called the off-grid effect, which will affect the height estimation accuracy of TomoSAR. To overcome this problem, we proposed a TomoSAR reconstruction algorithm based on atomic norm minimization (Tomo-ANM) in this paper. Tomo-ANM employs ANM, a continuous compressed sensing technique, to obtain scatterer positions on the continuous dictionary, thus eliminating the off-grid effect. Baseline compensation is necessary to obtain the data of virtual uniform baselines or the samples of uniform data during preprocessing. A fast realization of ANM, IVDST, is utilized to accelerate the process. Tomo-ANM was tested through simulation experiments, and the results confirmed the validity of eliminating the influence of off-grid effects and exhibited an improved location accuracy and detection rate in less time compared with the on-grid TomoSAR algorithm SL1MMER. Real data experiments based on eight staring spotlight TerraSAR-X images showed that Tomo-ANM can improve the accuracy of building height estimation by 4.83% relative to its real height.
Augmented Reality Technology for Vocational Education the Disruption Era

The purpose of this paper is to explain information and communication technology that can support the field of education in the disruption era, namely Augmented Reality (AR). The contribution of AR in education can provide a learning experience. Vocational education is an education that requires balance between acquiring knowledge and building experiences. In this way, AR can be one of the technologies that support vocational education. We will explain the potential case of AR game development in AR game development that is applied in education, especially in learning chemistry. Keywords— augmented reality, vocational education
Characterization in Inhibitory Effectiveness of Carbamazepine in Voltage-Gated Na+ and Erg-Mediated K+ Currents in a Mouse Neural Crest-Derived (Neuro-2a) Cell Line

Carbamazepine (CBZ, Tegretol®) is an anticonvulsant used in the treatment of epilepsy and neuropathic pain; however, several unwanted effects of this drug have been noticed. Therefore, the regulatory actions of CBZ on ionic currents in electrically excitable cells need to be reappraised, although its efficacy in suppressing voltage-gated Na+ current (INa) has been disclosed. This study was undertaken to explore the modifications produced by CBZ on ionic currents (e.g., INa and erg-mediated K+ current [IK(erg)]) measured from Neuro-2a (N2a) cells. In these cells, we found that this drug differentially suppressed the peak (transient, INa(T)) and sustained (late, INa(L)) components of INa in a concentration-dependent manner with effective IC50 of 56 and 18 μM, respectively. The overall current–voltage relationship of INa(T) with or without the addition of CBZ remained unchanged; however, the strength (i.e., ∆area) in the window component of INa (INa(W)) evoked by the short ascending ramp pulse (Vramp) was overly lessened in the CBZ presence. Tefluthrin (Tef), a synthetic pyrethroid, known to stimulate INa, augmented the strength of the voltage-dependent hysteresis (Hys(V)) of persistent INa (INa(P)) in response to the isosceles-triangular Vramp; moreover, further application of CBZ attenuated Tef-mediated accentuation of INa(P)’s Hys(V). With a two-step voltage protocol, the recovery of INa(T) inactivation seen in Neuro-2a cells became progressively slowed by adding CBZ; however, the cumulative inhibition of INa(T) evoked by pulse train stimulation was enhanced during exposure to this drug. Neuro-2a-cell exposure to CBZ (100 μM), the magnitude of erg-mediated K+ current measured throughout the entire voltage-clamp steps applied was mildly inhibited. The docking results regarding the interaction of CBZ and voltage-gate Na+ (NaV) channel predicted the ability of CBZ to bind to some amino-acid residues in NaV due to the existence of a hydrogen bond or hydrophobic contact. It is conceivable from the current investigations that the INa (INa(T), INa(L), INa(W), and INa(P)) residing in Neuro-2a cells are susceptible to being suppressed by CBZ, and that its block on INa(L) is larger than that on INa(T). Collectively, the magnitude and gating of NaV channels produced by the CBZ presence might have an impact on its anticonvulsant and analgesic effects occurring in vivo.