Miracle-dz/UniFAR-FTUs huggingface dataset:
A Simplified Main Beam Linearization Angle Widening Method for 5G Massive MIMO Systems With OTA Feedback

In this paper, we propose a simplified main beam linearization angle widening method for a 5G massive MIMO mm-wave transmitter with over-the-air feedback. The proposed method simplifies the original linearization angle widening method of the beam-oriented digital predistortion (BO-DPD). In linearization, multiple feedback signals measured from different target angles near the main beam are not directly combined into a large-scale basis function matrix, but combined into a small matrix by accumulating, and then the BO-DPD method is employed. Therefore, the scale of the basis function matrix can be greatly reduced when solving DPD coefficients by the least square method. The method is verified on a $\mathbf{1}\times \mathbf{64}$ large-scale mm-wave transmitter, which is excited by a 5G new radio (NR) FR2 signal with the carrier frequency of 26 GHz and the band-width of 100 MHz. The experimental results show that compared with the linearization angle widening method of BO-DPD, the simplified method can achieve similar DPD results, but the computational complexity is lower.
Status and Prospects of Heterojunction-Based HEMT for Next-Generation Biosensors

High electron mobility transistor (HEMT) biosensors hold great potential for realizing label-free, real-time, and direct detection. Owing to their unique properties of two-dimensional electron gas (2DEG), HEMT biosensors have the ability to amplify current changes pertinent to potential changes with the introduction of any biomolecules, making them highly surface charge sensitive. This review discusses the recent advances in the use of AlGaN/GaN and AlGaAs/GaAs HEMT as biosensors in the context of different gate architectures. We describe the fundamental mechanisms underlying their operational functions, giving insight into crucial experiments as well as the necessary analysis and validation of data. Surface functionalization and biorecognition integrated into the HEMT gate structures, including self-assembly strategies, are also presented in this review, with relevant and promising applications discussed for ultra-sensitive biosensors. Obstacles and opportunities for possible optimization are also surveyed. Conclusively, future prospects for further development and applications are discussed. This review is instructive for researchers who are new to this field as well as being informative for those who work in related fields.
High-resolution image reconstruction from a low-resolution image sequence in the presence of time-varying motion blur

We address the problem of reconstruction of a high-resolution image from a sequence of low-resolution images containing arbitrary relative motion, excluding occlusion effects. We develop a formulation that simultaneously takes into account blurring due to relative sensor-object motion, sensor integration, and additive noise. We propose a POCS-based algorithm for performing the high-resolution reconstruction, and provide experimental results. <<ETX>>
Reliability and Validity of the Korean Version of the Ask Suicide-Screening Questions (ASQ)

Background The Ask Suicide-Screening Questions (ASQ) tool is a simple suicide screening tool developed to screen patient suicide risk (SR). The purpose of this study was to verify the reliability and validity of the ASQ tool in hospitalized patients. Methods The internal consistency and test-retest reliability of the South Korean version of the ASQ tool were verified in 99 hospitalized patients admitted to a tertiary medical institution in Seoul. To verify the correlations and validity of each convergence with other scales, the Mini-International Neuropsychiatric Interview (MINI), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Satisfaction with Life Scale (SWLS) were also conducted to determine convergent and discriminant validity. Then, the receiver operating characteristic (ROC) curve diagnosis values for suicide and depression levels with the highest correlations were analyzed. Results As a result, Cronbach’s alpha was 0.826, and when each item was removed sequentially, Cronbach’s alpha ranged from 0.736–0.840, showing stable internal consistency. Most of the corrected item-total correlation were over 0.500; however, a relatively low correlation was shown for the fourth and fifth questions, which had values of 0.429 and 0.410, respectively. The test-retest reliability was 0.830, and the MINI and PHQ-9 showed high values of 0.872 and 0.672, respectively. The area under the curve (AUC) according to the ASQ diagnosis value was also the highest for the MINI (0.936). Conclusion The validity and reliability of the South Korean version of the ASQ tool were demonstrated. Through this validation, the ASQ tool can be used for simple suicide risk screening (SRS) in hospitalized patients.
Targets of Immune Escape Mechanisms in Cancer: Basis for Development and Evolution of Cancer Immune Checkpoint Inhibitors

Simple Summary The tumor immune escape mechanisms are key factors in cancer progression and metastasis. They are an undeniable hurdle for successful cancer treatment in patients. It has been widely recognized that cancer cells can escape immune surveillance and antitumor immunity. Despite host immunity, tumor cells can escape antitumor immune cell responses by several different mechanisms, such as the loss of the antigen presentation capacity by some immune cells, which promotes tumor progression and resistance to immunotherapy. A few monotherapies or combinational therapies have been approved for use in cancer treatment, but the majority of patients are not responsive to currently used immunotherapies, thus presenting a need to discover new targets to achieve efficacious immune responses to benefit cancer patients. This review focuses on some of the most important classical immune checkpoint targets and also sheds light on some of the recently discovered, promising immunotherapeutic targets and strategies. Abstract Immune checkpoint blockade (ICB) has emerged as a novel therapeutic tool for cancer therapy in the last decade. Unfortunately, a small number of patients benefit from approved immune checkpoint inhibitors (ICIs). Therefore, multiple studies are being conducted to find new ICIs and combination strategies to improve the current ICIs. In this review, we discuss some approved immune checkpoints, such as PD-L1, PD-1, and CTLA-4, and also highlight newer emerging ICIs. For instance, HLA-E, overexpressed by tumor cells, represents an immune-suppressive feature by binding CD94/NKG2A, on NK and T cells. NKG2A blockade recruits CD8+ T cells and activates NK cells to decrease the tumor burden. NKG2D acts as an NK cell activating receptor that can also be a potential ICI. The adenosine A2A and A2B receptors, CD47-SIRPα, TIM-3, LAG-3, TIGIT, and VISTA are targets that also contribute to cancer immunoresistance and have been considered for clinical trials. Their antitumor immunosuppressive functions can be used to develop blocking antibodies. PARPs, mARTs, and B7-H3 are also other potential targets for immunosuppression. Additionally, miRNA, mRNA, and CRISPR-Cas9-mediated immunotherapeutic approaches are being investigated with great interest. Pre-clinical and clinical studies project these targets as potential immunotherapeutic candidates in different cancer types for their robust antitumor modulation.
Forest Canopy Height Extraction Method Based on ICESat-2/ATLAS Data

Ice, cloud, and land elevation satellite (ICESat-2)/Advanced Topographic Laser Altimeter System (ATLAS) multibeam micropulse photoncounting light detection and ranging (LiDAR) can be effectively applied to extract forest canopy height. However, the ICESat-2/ATLAS photon point cloud interfered with the signal-to-noise ratio (SNR), fraction vegetation coverage (FVC), and terrain slope. The main challenge of this research is to extract high-precision canopy heights. Therefore, this article improves the canopy height extraction method based on the ICESat-2/ATL08 theoretical algorithm. First, an adaptive filter, Threshold Segmentation based on Spatial Clustering and Bimodal Reconstruction (TS-SCABR), is proposed, which can adapt to different SNR scenarios. Then, combined with the gradient method, the discontinuous data are detrended in sections to eliminate the edge mutation problem of the detrended data. Based on the detrended data, the iterative filtering algorithm of the local terrain is employed to fit the ground curve, and the mutation detection and empirical mode decomposition (EMD)-digital smoothing polynomial (DISPO) filtering remove the pseudoground photons to identify the data of ground and nonground photons accurately. Finally, the percentile statistics method is utilized to extract the canopy-top photons from the nonground photons according to their elevation difference. The results indicate that, under different natural conditions, the improved algorithm has better adaptability than the previous algorithm. Compared with the original ATL08 ATBD algorithm, the canopy height accuracy is significantly improved, especially in low FVC and high slope scenarios. When the FVC is lower than 25%, $R_{2}$ increases by 50.3%, and the root mean square error (RMSE) is reduced by 2.175 m, and when the slope is higher than 45°, it increases by 41.7%, and the RMSE is reduced by 2.159 m. Therefore, the algorithm has apparent advantages in inverting the canopy height in a mountainous environment with lush forests.
Adaptive Latent Transformation (ALT) for classification of resting state - fMRI

Classification of resting state - functional Magnetic Resonance Imaging (rs-fMRI) data using deep learning algorithms is a challenging problem. Previous studies using latent space transformations to project the data into a discriminant space have shown promising results. However, their reliance on mathematical modelling of the latent space have limited their performance and generalization ability. Learnable latent space transformations have provided a new approach to solve such problems. In this paper, Adaptive Latent Transformation (ALT) method is proposed to address the shortcomings in literature. The ALT proposes an adaptable latent space transformation that can project the input data into a discriminant latent space of any pre-determined dimension using a learnable projection function. The ALT latent space transformation function is integrated into a convolutional neural network algorithm and its weights are updated using the backpropagation based learning strategy to minimize the error in the classification performance. Further, to prevent overfitting of the deep network classifier a novel Confidence based Sample Selection Strategy (CSSS) is proposed to selectively train the network with information-rich samples. The performance of the ALT classifier is evaluated using the ADHD200 rs-fMRI benchmark dataset over a 10 fold cross-validation study.
Phase Diagram of 2 × 2 Adsorbates at Surfaces with Hexagonal Symmetry

The phase diagram of a lattice-gas model for 2 2 2 adsorbates at surfaces with hexagonal symmetry has been investigated by Monte Carlo simulations. The model relies on repulsive interactions between the particles for distances up to second nearest neighbor sites. It is shown that first- or second-order phase transitions take place depending on the strength of the interactions. Strong first- or second-neighbor interactions are responsible for a first-order transition while for intermediate interaction strength a second-order transition is possible. The critical exponent for the susceptibility shows the expected value of the four-states Potts model in case of a second-order transition. The value of the critical exponent is reduced when the transition changes from first to second order.
Feeding Aquilaria sinensis Leaves Modulates Lipid Metabolism and Improves the Meat Quality of Goats

Aquilaria (A.) sinensis is a medicinal plant widely grown in tropical South China. Given the abundant pruning waste of its leaves, the use of A. sinensis leaves is valuable. In this study, goats were fed a diet containing 20% A. sinensis leaves. Compared with the basal diet, feeding A. sinensis leaves to goats did not affect growth performance but considerably reduced the feeding cost. Strikingly, feeding A. sinensis leaves resulted in a significant decrease in the blood cholesterol levels (2.11 vs. 1.49 mmol/L, p = 0.01) along with a significant increase in the high-density lipoprotein levels (1.42 vs. 1.82 mmol/L, p = 0.01). There was also a tendency to lower the content of low-density lipoprotein levels in goats (0.78 vs. 0.45 mmol/L, p = 0.09). Furthermore, metabolomics analysis demonstrated that the reduction in cholesterol levels occurred in both the serum (0.387-fold change) and muscle (0.382-fold change) of goats during A. sinensis leaf feeding. The metabolic responses to feeding A. sinensis leaves suggest that the activation of lipolysis metabolism might happen in goats. These observed changes would be conducive to improving animal health and meat quality, ultimately benefiting human health.
Constant‐capacitance DLTS measurement of defect‐density profiles in semiconductors

An analysis is presented for obtaining spatial depth profiles of electronic defects in semiconductors from deep‐level spectroscopic measurements performed in the constant‐capacitance mode. Combined with the double‐correlation technique proposed by Lefevre and Schulz, the new method offers significant advantages for measuring defect profiles. Deep‐level transient spectroscopy (DLTS), performed in either the conventional capacitance‐transient mode or the constant‐capacitance mode, provides the energy levels of defect states in the semiconductor band gap. The double correlation DLTS technique (DDLTS) is used to define a narrow spatial observation window for defect profiling. However, in the DDLTS analysis of capacitance‐transient data, specific approximations are required to deal with the change with time of the semiconductor depletion width during the transient response to a charging pulse. In the constant‐capacitance mode, the depletion width is held constant by dynamically varying the applied voltage duri.
Incremental Neural Synthesis for Spiking Neural Networks

We present an iterative neural synthesis approach to train Convolutional Spiking Neural Networks for classification problems. Unlike previous neural synthesis methods which pri-marily compute the neuron firing rates, our method is designed to compute multiple spikes at arbitrary timings. As such, our approach is directly applicable to spatio-temporal problems using spiking network models. In our approach, each weight update is formulated as a linear Constraint Satisfaction Problem, which can then be solved using existing numerical techniques. On the MNIST, EMNIST, and ETH-80 image classification benchmarks, our approach demonstrates competitive with other models in the literature, while requiring relatively few training samples to converge to a good solution.
Difficulties in Emotion Regulation and Sexual Functioning in Sports Practitioners: A Pilot Study

Abstract Emotion regulation is a transdiagnostic process strongly related with emotional difficulties, which may interfere with sexual functioning. Little is known about this association in athletes. The current study examined differences in difficulties in emotion regulation in sports practitioners with and without sexual difficulties. A total of 174 athletes (64 women and 110 men) completed a web-survey, answering a sociodemographic information questionnaire, the Difficulties in Emotion Regulation Scale – Short Form, and the Female Sexual Functioning Index/the International Index of Erectile Function. Results suggested that 34 women (53.1%) experienced sexual difficulties and 40 men (35.1%) reported erectile difficulties. Women with sexual difficulties revealed greater difficulties in goal-directed behavior. Men with erectile difficulties revealed greater lack of emotional awareness and clarity, more difficulties in goal-directed behavior (focusing on relevant information and ignoring distractors) and impulse control, and higher nonacceptance of emotions. Overall, current findings enhance the role of difficulties in emotional regulation in sexual functioning in male and female sports practitioners.
A Compact Wideband Bandpass Filter With Tunable Notched Band

A compact wideband BPF (bandpass filter) with tunable notched band is presented in this paper. The presented filter consists of three quarter-wavelength short-circuited stubs, which are connected by half-wavelength microstrip line. To improve the selectivity of filter, the input and output microstrip lines of filter are folded to the middle of filter to realize multiple TZs (transmission zeros) at the left and right side of the passband. The H-shaped resonator loaded in the filter can generate odd-mode and even-mode resonant frequencies in the passband and upper stopband respectively. The odd-mode resonant frequency lied in the passband form a notched band and the even-mode resonant frequency lied in the upper stopband can expand bandwidth of the stopband. The tunable notched band is realized by loading a varactor diode in H-shaped resonator. The filter is optimized with HFSS, simulation results show that the IL (insertion loss) is less than 1.2 dB and RL (return loss) is greater than 10dB within 3.7-9.9 GHz band. The upper stopband frequency range is 10.4-15.9 GHz; the adjustable notch frequency range is 5.63-7.25 GHz, the tuning rate is 25.2%, and the depth of notched band is greater than 20dB in the whole tuning range.
An optical emission study of the glow-discharge deposition of hydrogenated amorphous silicon from argon-silane mixtures

Optical emission intensities from atomic silicon and argon and molecular hydrogen have been measured in silane‐argon mixture glow discharges as a function of silane percentage and rf voltage. These measurements show that the electron concentration decreases and the average electron energy increases as the silane concentration increases. This dependence explains why the deposition rate of hydrogenated amorphous silicon from silane‐noble gas mixtures is not proportional to the silane concentration.
The Role of Emotion Regulation as a Potential Mediator between Secondary Traumatic Stress, Burnout, and Compassion Satisfaction in Professionals Working in the Forced Migration Field

Background: Professionals working with refugees are vicariously exposed to complex traumatic experiences lived by forced migrants, which can lead to the risk of developing secondary traumatic stress, burnout, and a poor compassion satisfaction. The current study aimed to explore the effects of secondary traumatic stress on burnout and compassion satisfaction in 264 Italian professionals working with refugees and forced migrants. Moreover, it examined the mediating role of emotion regulation between secondary traumatic stress and both burnout and compassion satisfaction. Methods: A structural equation modeling (SEM) was performed to test the hypothesis. Results: The results showed that increased levels of secondary traumatic stress were associated with an increase of burnout both directly and indirectly through the mediation of emotion regulation. Emotion regulation also totally mediated the relationship between secondary traumatic stress and compassion satisfaction. Conclusions: The results suggested that prevention or interventions programs targeting emotion regulation might be important to improve the professional quality of life of operators working with refugees and forced migrants.
Adaptive Support With Working Examples in Serious Games About Programming

Serious games are a growing field in academic research and they are considered an effective tool for education. Game-based learning invokes motivation and engagement in students resulting in effective instructional outcomes. An essential aspect of a serious game is the method of support for presenting the teaching material and providing feedback. A support design that evaluates students’ progress and adapts accordingly, has the potential of producing better learning results. This paper presents an adaptive model based on fuzzy logic that adjusts the support acquisition according to student knowledge level. A serious game for teaching the concepts of sequence and iteration in programming to novice students was built to assess the model. It employs working examples as a support method since previous research indicated that it produced less cognitive load during problem-solving. An empirical study with 102 students has been conducted to evaluate the learning efficiency of the model. The analysis indicates positive results and a potential solution for balancing the amount of assistance in serious games.
Serial Cultivation of an MSC-Like Cell Line with Enzyme-Free Passaging Using a Microporous Titanium Scaffold

In vitro studies on adherent cells require a process of passage to dissociate the cells from the culture substrate using enzymes or other chemical agents to maintain cellular activity. However, these proteolytic enzymes have a negative influence on the viability and phenotype of cells. The mesenchymal stem cell (MSC)-like cell line, C3H10T1/2, adhered, migrated, and proliferated to the same extent on newly designed microporous titanium (Ti) membrane and conventional culture dish, and spontaneous transfer to another substrate without enzymatic or chemical dissociation was achieved. The present study pierced a 10 μm-thick pure Ti sheet with 25 μm square holes at 75 μm intervals to create a dense porous structure with biomimetic topography. The pathway of machined holes allowed the cells to access both sides of the membrane frequently. In a culture with Ti membranes stacked above- and below-seeded cells, cell migration between the neighboring membranes was confirmed using the through-holes of the membrane and contact between the membranes as migration routes. Furthermore, the cells on each membrane migrated onto the conventional culture vessel. Therefore, a cell culture system with enzyme-free passaging was developed.
Seismic fragility analysis of self-centering segmental piers with mortise-tenon shear keys

To comprehensively consider and study the seismic performance of the self-center mortise-tenon segmental pier, its vulnerability under earthquake is evaluated. The reliability of the model is verified by comparing the cyclic pseudo-static test results with the finite element models. The model is used as the basis for vulnerability analysis. Taking the maximum displacement of the pier top as a damage index. Different damage states are described. The damage index limits μcy1, μcy, μc2, and μcmax of different damage levels are determined. The time history analysis of cast-in-place pier and mortise-tenon segmental piers under different earthquake actions is carried out by using finite element software. The probabilistic seismic demand model is established through IDA curves. And the seismic vulnerability analysis is carried out. The influence of various parameters on the seismic vulnerability of mortise-tenon segmental pier is studied by changing the longitudinal reinforcement ratio, axial compression ratio, and aspect ratio. The results show that the seismic vulnerability of the two types of piers designed according to the principle of equivalence is similar under different damage states. It can be considered that it has better seismic performance. The longitudinal reinforcement ratio, axial compression ratio, and aspect ratio have a great impact on the vulnerability of piers.