Miracle-dz/UniFAR-FTUs huggingface dataset:
Dexamethasone Modulates the Dynamics of Wnt Signaling in Human Trabecular Meshwork Cells

Trabecular meshwork (TM) tissue is highly specialized, and its structural integrity is crucial for maintaining homeostatic intraocular pressure (IOP). The administration of glucocorticoids, such as dexamethasone (DEX), can perturb the TM structure and significantly increase IOP in susceptible individuals, resulting in ocular diseases such as steroid-induced glaucoma, a form of open-angle glaucoma. Although the exact mechanism involved in steroid-induced glaucoma remains elusive, increasing evidence suggests that DEX may act through various signaling cascades in TM cells. Despite uncertainty surrounding the specific process by which steroid-induced glaucoma occurs, there is growing evidence to indicate that DEX can impact multiple signaling pathways within TM cells. In this study, we examined the impact of DEX treatment on the Wnt signaling pathway in TM cells, given that Wnt signaling has been reported to play a crucial role in regulating extracellular matrix (ECM) levels in the TM. To further elucidate the role of Wnt signaling in the glaucomatous phenotype, we examined mRNA expression patterns between Wnt signaling markers AXIN2 and sFRP1 and DEX-mediated induction of myocilin (MYOC) mRNA and protein levels over 10 days in DEX-treated primary TM cells. We observed a sequential pattern of peak expression between AXIN2, sFRP1, and MYOC. Based on the study, we propose that sFRP1 upregulation could be a result of a negative feedback mechanism generated by stressed TM cells to suppress abnormal Wnt signaling activities.
Comparison of Two Time-Integration Algorithms for an Anisotropic Damage Model Coupled with Plasticity

In this work, two time integration algorithms for the anisotropic damage model proposed by Lemaitre et al. (2000) are compared. Specifically, the standard implicit Euler scheme is compared to an algorithm which implicitly solves the elasto-plastic evolution equations and explicitly computes the damage update. To this end, a three dimensional bending example is solved using the finite element method and the results of the two algorithms are compared for different time step sizes.
MALDI MSI and Raman Spectroscopy Application in the Analysis of the Structural Components and Flavonoids in Brassica napus Stem

Nod factors among the signaling molecules produced by rhizobia in response to flavonoids to induce root nodule formation in the legumes. It is, however, hypothesized that they might increase the yield and positively impact the growth of non-legumes. To evaluate this statement, rapeseed treated with Nod factor-based biofertilizers were cultivated, their stems was collected, and the metabolic changes were investigated using Raman spectroscopy and MALDI mass spectrometry imaging. Biofertilizer proved to increase the concentration of lignin in the cortex, as well as hemicellulose, pectin, and cellulose in the pith. Moreover, the concentration of quercetin derivatives and kaempferol derivatives increased, while the concentration of isorhamnetin dihexoside decreased. The increase in the concentration of the structural components in the stem might therefore increase the lodging resistance, while the increase in concentration of the flavonoids might increase their resistance to fungal infection and herbivorous insects.
Partisan Asymmetries in Earmark Representation

This paper examines how Republicans and Democrats in the U.S. House of Representatives vary in their earmarking behavior. After a 10-year moratorium, Congress enabling members to request small grants for community programs in their districts in the 2021 appropriations process. As part of a reform designed to limit corruption and wasteful spending, members had to submit written justifications for the grants, which provides insight into how members of Congress view their role as representatives. In performing a content analysis on 3007 earmark justifications, we find that Democrats are more likely to name the specific social groups comprising their party coalition in their justifications; Republicans rarely do so. Democrats are also more likely to request grants on their core partisan priorities, while Republicans tend to focus on large local infrastructure projects that are seemingly unrelated to their national priorities. Finally, we find some, but limited, evidence that earmark requests are a result of the different kinds of districts that members represent.
Charge Transport Characterization of PbS Quantum Dot Solids for High Efficiency Solar Cells

The PbS quantum dot is an emerging photovoltaic material, which may provide high efficiency breakthroughs. The most crucial element for the high efficiency solar cells's development is to understand charge transport characteristics of PbS quantum dot solids, which are also important in planning strategic research. We have investigated charge transport characteristics of PbS quantum dot solids thin films using space charge limited conduction analysis and assessed thickness dependent photovoltaic performances. The extracted carrier drift mobility was $low-10^{-2}cm^2/Vs$ with the estimated diffusion length about 50 nm. These and recently reported values were compared with those from a commercial photovoltaic material, and we present an essential element in further development of PbS quantum dot solids materials.
A Simple Integrated and Low-Radiation Receiver for Inductive Power Transfer

It is promising to pursue an integrated low-profile receiver (RX) for inductive power transfer applications. However, the existing integration solutions suffer from the complicated structure and the insertion of dielectric material. This article proposes a novel excitation approach for the classical three-layer RX, and the structure inductance and capacitance are utilized for self-resonance. Without using additional dielectric material, proper magnetic material is evaluated and selected toward enhancing the structure capacitance and reducing the dielectric losses. The circuit model, radiation performance, and structure optimization are discussed in the simulation and experiment. A 750-kHz 100-W system is demonstrated to have a 92.4% coupler efficiency and 87.5% system efficiency. Compared to a classical RX, the proposed RX would slightly improve the shielding effect for the magnetic field and dramatically reduce the electric-field radiation by 15 dBm.
Hardware Design and Implementation of Multiagent MLP Regression for the Estimation of Gunshot Direction on IoBT Edge Gateway

The advancements in the Internet of Things (IoT), artificial intelligence, and state-of-the-art computing techniques are the main pillars of the next-generation defense technology. The Internet of Battlefield Things (IoBT) with edge intelligence offers new opportunities for defense professionals for smart and effective military operations. The IoBT network connects soldiers by placing smart sensors on armor, weapons, bodies, and surroundings. This article presents a novel edge intelligence-based estimation of gunshot direction from the sensor-enabled glove for smart IoBT wearables. A multiagent multilayer perceptron (MA-MLP) and other regression models are developed and tested on the experimental dataset collected during this study. The MA-MLP model consists of two distinct MLP networks and a fusion block to estimate the gunshot direction. This article demonstrates the effect of multiple subjects, sensor positions, and gun material on the mean absolute error (MAE) of MA-MLP prediction. The software simulation results show that our proposed MA-MLP model has outperformed traditional machine-learning techniques such as linear regression (LR), SVM, and MLP with an MAE of 4.09°. Two different hardware designs, that is, intellectual property (IP) cores of the pretrained MA-MLP model are implemented and tested on a field-programmable gate array (FPGA) for a system on a chip (SoC)-based edge gateway. The first IP core requires 280 ns with a power consumption of 354 milliwatts, while the second IP core requires 380 ns with 178 milliwatts power consumption per inference. Prediction accuracy (PA) of 97.48% with a reduction of throughput to 92.2% is achieved for both IP cores. This work is one of the first attempts to implement FPGA-based edge intelligence for IoBT wearables. The short computation time, low power consumption, small footprint, significant throughput reduction, desired accuracy, and processor offloading are achieved by both flexible hardware models designed explicitly for edge intelligence.
Subspace Memory Clustering

We present a new subspace clustering method called SuMC (Sub-space Memory Clustering), which allows to eﬃciently divide a dataset D ⊂ R N into k ∈ N pairwise disjoint clusters of possibly diﬀerent dimensions. Since our approach is based on the memory compression, we do not need to explicitly specify dimensions of groups: in fact we only need to specify the mean number of scalars which is used to describe a data-point. In the case of one cluster our method reduces to a classical Karhunen-Loeve (PCA) transform. We test our method on some typical data from UCI repository and on data coming from real-life experiments.
A High-Gain Dual-Band Multibeam Antenna System for MIMO Wi-Fi Application

A compact dual-band multibeam antenna system with high gain is presented for multiple-input-multiple-output (MIMO) wireless fidelity (Wi-Fi) application. The antenna system is composed of four rotationally symmetric antenna panels occupying a compact size of <inline-formula> <tex-math notation="LaTeX">$60\times 200\times7.2$ </tex-math></inline-formula> mm<sup>3</sup>. Two series-fed microstrip patch antenna (MPA) arrays are proposed to operate at the 5-GHz band. They are fed with ±90° phase difference signals for two directional radiation patterns with about 45° horizontal 3-dB beamwidth and distinct radiation directions. Two dual-function metasurface based on periodically loaded parallel lines is designed and compactly placed between the two MPA arrays. The metasurface works as a 2.4-GHz antenna with about 90° 3-dB beamwidth in the azimuth. Besides, the application of metasurface improves the gains at the 5-GHz band. Then, four antenna panels are placed in a rotating arrangement with an electric size of <inline-formula> <tex-math notation="LaTeX">$0.59\lambda _{\mathrm {L}} \times 0.59\lambda _{\mathrm {L}} \times 1.57\lambda _{\mathrm {L}}$ </tex-math></inline-formula> (<inline-formula> <tex-math notation="LaTeX">$\lambda _{\mathrm {L}}$ </tex-math></inline-formula> is the free-space wavelength at the lowest operating frequency). The antenna system was manufactured and demonstrated the characteristics of 360° pattern coverage in azimuth and high gain. The measured average gains are, respectively, higher than 8 and 12 dB at the 2.4- and 5-GHz bands.
Evaluating Robustness to Noise and Compression of Deep Neural Networks for Keyword Spotting

Keyword Spotting (KWS) has been the subject of research in recent years given the increase of embedded systems for command recognition such as Alexa, Google Home, and Siri. Performance, model size, processing time, and robustness to noise are fundamental in these systems. Furthermore, applications in embedded systems demand computationally efficient models that can be implemented in current technology. In this work, an approach for keyword recognition is evaluated using three deep learning models namely LeNet-5, SqueezeNet, and EfficientNet-B0. We evaluate transfer learning, pruning and quantization strategies in training and test using noisy and clean speech signals. In addition, compression techniques such as pruning and quantization were assessed in terms of the size reduction of the model footprint and the accuracy obtained in each case. Using the Google’s Speech Commands dataset and additive babble noise signal, our keyword recognition approach achieves an accuracy of 94.6% using an unstructured pruning of 80% of the parameters of the original SqueezeNet network with a reduction of 70% in the model size.
Eigenvector Analysis of Monthly Mean Surface Data

Abstract Eigenvector or principal component analysis has been carried out on monthly means of surface pressure, temperature, and rainfall defined on grids extending over both hemispheres and the tropical belt. In each case, 10 out of a possible 120 components were sufficient to account for more than 80% of the observed variance regardless of whether the annual cycle was first removed. The major pressure components can be interpreted in terms of meridional and land-sea temperature gradients, and reflect a basic difference in the seasonal cycle in the Northern and Southern Hemispheres. While both pressure and temperature show coherent departures on a hemispheric scale, rainfall components are regional in character, and the variance reduction is more evenly distributed over the major components. The use of principal components as climatological indices merits greater attention than has so far been given.
FGO-GIL: Factor Graph Optimization-Based GNSS RTK/INS/LiDAR Tightly Coupled Integration for Precise and Continuous Navigation

As a relative positioning technique, light detection and ranging (LiDAR)-inertial odometry (LIO) is known to suffer from drifting and can only provide local coordinates. To compensate for these shortages of LIO, an effective way is to integrate a global navigation satellite system (GNSS) with LIO. In this contribution, we proposed a tightly coupled GNSS real-time kinematic (RTK)/inertial navigation system (INS)/LiDAR system under the factor graph optimization framework, termed FGO-GIL, to achieve high-precision and continuous navigation in urban environments. This integration system fuses raw GNSS measurements (i.e., pseudorange and carrier phase measurements) with inertial measurement unit (IMU) and LiDAR information at the observation level atop a factor graph. Moreover, a keyframe-based nonlinear optimization scheme is designed to efficiently utilize measurements from the mixed heterogeneous sensors. Specifically, nonkeyframes are united with IMU preintegration for interframe optimization, which can provide accurate and high-frequency state predictions for the scan-matching of keyframes. Sparse keyframes are used to construct LiDAR factors by matching with the submap for sliding window optimization. To evaluate the effectiveness of our approach, real-world experiments are conducted in both campus and urban environments. The results demonstrate that our system can achieve continuous decimeter-level positioning accuracy in these complex environments, outperforming other state-of-the-art frameworks.
Sociaal kapitaal en de performantie van lokale ontwikkelingsprojecten: twee Nicaraguaanse dorpen van dichterbij bekeken

Associational life is generally considered an important aspect of social capital. In this article we argue that, in the Nicaraguan context, trust, reciprocity and cooperation are not necessarily linked with formal organisational patterns. Getting a grip on both the structure and the content of social capital implies studying informal relations and networks. The article highlights how informal patterns can influence the functioning and performance of development projects. Based on the evaluations of several development projects, two rural communities (Nicaragua) were investigated on their informal support networks. Since peasants regularly need extra labour force on the field, the research focuses on how these needs are dealt with. The different transactional mechanisms found in the field indicate a variety of informal patterns. Furthermore the data suggest that villages can differ greatly in displaying dominant mechanisms. Informal labour-exchange mechanisms can give a good (though partial) indication of social capital in both villages.
A high resolution NV/TVD Hermite polynomial upwind scheme for convection‐dominated problems

A high‐order convection‐bounded scheme is constructed by combining the total variational diminishing constraint and convection boundedness criterion condition in the normalized variable formulation. It employs the Hermite polynomial interpolation to design its characteristic line in the normalized variable diagram. Numerical results of the convection‐dominated problems with smooth or discontinuous initial distributions demonstrate the present scheme possesses high resolution and good robustness. Copyright © 2012 John Wiley & Sons, Ltd.
Temporal Dynamic Alterations of Regional Homogeneity in Parkinson’s Disease: A Resting-State fMRI Study

Brain activity is time varying and dynamic, even in the resting state. However, little attention has been paid to the dynamic alterations in regional brain activity in Parkinson’s disease (PD). We aimed to test for differences in dynamic regional homogeneity (dReHo) between PD patients and healthy controls (HCs) and to further investigate the pathophysiological meaning of this altered dReHo in PD. We included 57 PD patients and 31 HCs with rs-fMRI scans and neuropsychological examinations. Then, ReHo and dReHo were calculated for all subjects. We compared ReHo and dReHo between PD patients and HCs and then analyzed the associations between altered dReHo variability and clinical/neuropsychological measurements. Support vector machines (SVMs) were also used to assist in differentiating PD patients from HCs using the classification values of dReHo. The results showed that PD patients had increased ReHo in the bilateral medial temporal lobe and decreased ReHo in the right posterior cerebellar lobe, right precentral gyrus, and supplementary motor area, compared with controls. The coefficient of variation (CV) of dReHo was considerably higher in the precuneus in PD patients compared with HCs, and the CV of dReHo in the precuneus was found to be highly associated with HAMD, HAMA, and NMSQ scores. Multiple linear regression analysis controlling for demographic, clinical, and neuropsychiatric variables confirmed the association between altered dReHo and HAMD. Using the leave-one-out cross validation procedure, 98% (p < 0.001) of individuals were properly identified using the SVM classifier. These results provide new evidence for the aberrant resting-state brain activity in the precuneus of PD patients and its role in neuropsychiatric symptoms in PD.
PERENNIALITY OF BRAZILIAN NURSING JOURNALS: RECOVERY AND REAFFIRMATION OF THE JOURNALS’ SOCIAL COMMITMENT TO SCIENCE

ABSTRACT Objective: to reflect upon the challenges that permeate the development and perenniality of nursing journals published in Brazil for becoming entities at the service of the scientific community and heritage of the history of science for future generations. Method: the reflective method grounded on the principles of complexity and pertinent literature was adopted. Results: the perennial commitment to scientific publishing emerged as the starting point for this reflection; hence, the role played by sponsoring institutions as the guardians of scientific journals, the need for investments, and to valorize the management, professionalization, and internationalization of the editorial team are emphasized, along with the ability to expand communication breaking paradigms in the connections between science and society. Conclusion: this reflection is expected to reaffirm the concept of scientific periodicals being perennial devices and, thus, survive the dynamics of time amidst the challenges science faces worldwide. In this sense, it indicates the importance of institutions supporting scientific journals as a condition to ensure their perenniality.
Interaction of Rhus typhina Tannin with Lipid Nanoparticles: Implication for the Formulation of a Tannin–Liposome Hybrid Biomaterial with Antibacterial Activity

Tannins are natural plant origin polyphenols that are promising compounds for pharmacological applications due to their strong and different biological activities, including antibacterial activity. Our previous studies demonstrated that sumac tannin, i.e., 3,6-bis-O-di-O-galloyl-1,2,4-tri-O-galloyl-β-D-glucose (isolated from Rhus typhina L.), possesses strong antibacterial activity against different bacterial strains. One of the crucial factors of the pharmacological activity of tannins is their ability to interact with biomembranes, which may result in the penetration of these compounds into cells or the realization of their activity on the surface. The aim of the current work was to study the interactions of sumac tannin with liposomes as a simple model of the cellular membrane, which is widely used in studies focused on the explanation of the physicochemical nature of molecule–membrane interactions. Additionally, these lipid nanovesicles are very often investigated as nanocarriers for different types of biologically active molecules, such as antibiotics. In the frame of our study, using differential scanning calorimetry, zeta-potential, and fluorescence analysis, we have shown that 3,6-bis-O-di-O-galloyl-1,2,4-tri-O-galloyl-β-D-glucose interacts strongly with liposomes and can be encapsulated inside them. A formulated sumac–liposome hybrid nanocomplex demonstrated much stronger antibacterial activity in comparison with pure tannin. Overall, by using the high affinity of sumac tannin to liposomes, new, functional nanobiomaterials with strong antibacterial activity against Gram-positive strains, such as S. aureus, S. epidermitis, and B. cereus, can be formulated.
3-D Reconstruction and Measurement of Blade Profiles With Laser-Scanning Sensor via Multiview Registration Based on Dynamic Encoding of Feature-Coordinate Information

Currently, optical-based method provides a feasible means for blade reconstruction and measurement. However, as the key step, multiview registration is still heavily reliant on the measurement system's motion stability and geometric accuracy. Moreover, the complex and high-reflective freeform surface of blades may result in both insufficient overlaps and less prominent overlap-area features between adjacent views, making accurate multiview data alignment difficult. Thus, we propose a method to realize accurate 3-D reconstruction and measurement of blade profiles based on a scanning system with a laser sensor and a coarse-to-fine registration strategy. First, coarse alignment of the multiview data is achieved by calibrating the system's rotational axis using the blade datum plane feature, which can provide a good initial value for the fine registration and improve the reconstruction efficiency. Then, a fine registration algorithm based on the dynamic encoding of feature-coordinate fusion information is proposed to refine the coarsely aligned data and reduce the effect of system motion error on registration accuracy. Here, the introduction of fusion information can effectively eliminate the redundant correspondences to continuously optimize the matching probability between multiview data in each iteration, improving registration accuracy and efficiency. Finally, experiments on typical blades and comparison with the other fine registration algorithms demonstrate the accuracy and robustness of the proposed method.