Miracle-dz/UniFAR-FTUs huggingface dataset:
Tim3 and PD-1 as a therapeutic and prognostic targets in colorectal cancer: Relationship with sidedness, clinicopathological parameters, and survival

Background Colorectal cancer (CRC) is a heterogeneous disease that complicates predicting patients’ prognosis and their response to treatment. CRC prognosis is influenced by the tumor microenvironment (TME). The immune system is a critical component of the TME. Programmed cell death receptor 1 (PD-1) and T-cell immunoglobulin and mucin-domain containing-3 (Tim3) are inhibitory immune checkpoints that regulate immune response and may provide prognostic power. However, the effect of their expressions and co-expressions on the CRC prognosis remains unclear. Accordingly, this study aimed to investigate the prognostic value of the CD8, CD3, PD-1, Tim3 expression, and PD-1/Tim3 co-expression in patients with CRC. Materials and Methods One hundred and thirty six patients with CRC who underwent curative surgery were enrolled in the study. Immunohistochemical staining was performed for PD-1, Tim3, CD8, and CD3, and the expression of each marker was evaluated in the center of the tumor (CT), invasive margin (IM), and adjacent normal-like tissue. Result Our results indicated that high expression of PD-1 in IM was significantly associated with lower TNM stage, T-stage, M-stage, lack of metastasis, the presence of tertiary lymphoid structure (TLS), lack of recurrence (in the left-sided tumors), and larger tumor size (in right-sided tumors) (P<0.05). High expression of PD-1 in IM was also associated with improved overall survival (OS) in a subgroup of patients with high CD8 expression. High Tim3 expression in CT was associated with higher M-stage (M1) (in left-sided CRCs) (P<0.05). It was also associated with decreased OS in total cohort and left-sided CRCs and represented an independent prognostic factor for CRC patients in multivariate analysis. PD-1 and Tim3 co-expression had no synergistic effects on predicting OS. Conclusion Our findings suggest that the clinicopathological and prognostic significance of immune system-related markers such as CD8, PD-1, and Tim3 depends on the primary tumor sides. We also showed that Tim3 could act as a prognostic factor and therapeutic target in CRC. This marker is probably a more preferred target for immunotherapy than PD-1, especially in left-sided CRCs.
Polymer-Based 3-D Printed 140 to 220 GHz Metal Waveguide Thru Lines, Twist and Filters

This paper demonstrates the current state-of-the-art in low-cost, low loss ruggedized polymer-based 3-D printed G-band (140 to 220 GHz) metal-pipe rectangular waveguide (MPRWG) components. From a unique and exhaustive up-to-date literature review, the main limitations for G-band split-block MPRWGs are identified as electromagnetic (EM) radiation leakage, assembly part alignment and manufacturing accuracy. To mitigate against leakage and misalignment, we investigate a ‘trough-and-lid’ split-block solution. This approach is successfully employed in proof-of-concept thru lines, and in the first polymer-based 3-D printed 90° twist and symmetrical diaphragm inductive iris-coupled bandpass filters (BPFs) operating above 110 GHz. An inexpensive desktop masked stereolithography apparatus 3-D printer and a commercial copper electroplating service are used. Surface roughness losses are calculated and applied to EM (re-)simulations, using two modifications of the Hemispherical model. The 7.4 mm thru line exhibits a measured average dissipative attenuation of only 12.7 dB/m, with rectangular-to-trapezoidal cross-sectional distortion being the main contributor to loss. The 90° twist exhibits commensurate measured performance to its commercial counterpart, despite the much lower manufacturing costs. A detailed time-domain reflectometry analysis of flange quality for the thru lines and 90° twists has also been included. Finally, a new systematic iris corner rounding compensation technique, to correct passband frequency down-shifting is applied to two BPFs. Here, the 175 GHz exemplar exhibits only 0.5% center frequency up-shifting. The trough-and-lid assembly is now a viable solution for new upper-mm-wave MPRWG components. With this technology becoming less expensive and more accurate, higher frequencies and/or more demanding specifications can be implemented.
Novel electrotactile brain-computer interface with somatosensory event-related potential based control

Objective A brain computer interface (BCI) allows users to control external devices using non-invasive brain recordings, such as electroencephalography (EEG). We developed and tested a novel electrotactile BCI prototype based on somatosensory event-related potentials (sERP) as control signals, paired with a tactile attention task as a control paradigm. Approach A novel electrotactile BCI comprises commercial EEG device, an electrical stimulator and custom software for EEG recordings, electrical stimulation control, synchronization between devices, signal processing, feature extraction, selection, and classification. We tested a novel BCI control paradigm based on tactile attention on a sensation at a target stimulation location on the forearm. Tactile stimuli were electrical pulses delivered at two proximal locations on the user’s forearm for stimulating branches of radial and median nerves, with equal probability of the target and distractor stimuli occurrence, unlike in any other ERP-based BCI design. We proposed a compact electrical stimulation electrodes configuration for delivering electrotactile stimuli (target and distractor) using 2 stimulation channels and 3 stimulation electrodes. We tested the feasibility of a single EEG channel BCI control, to determine pseudo-online BCI performance, in ten healthy subjects. For optimizing the BCI performance we compared the results for two classifiers, sERP averaging approaches, and novel dedicated feature extraction/selection methods via cross-validation procedures. Main results We achieved a single EEG channel BCI classification accuracy in the range of 75.1 to 88.1% for all subjects. We have established an optimal combination of: single trial averaging to obtain sERP, feature extraction/selection methods and classification approach. Significance The obtained results demonstrate that a novel electrotactile BCI paradigm with equal probability of attended (target) and unattended (distractor) stimuli and proximal stimulation sites is feasible. This method may be used to drive restorative BCIs for sensory retraining in stroke or brain injury, or assistive BCIs for communication in severely disabled users.
The Microwave Radiative Properties of Falling Snow Derived from Nonspherical Ice Particle Models. Part I: An Extensive Database of Simulated Pristine Crystals and Aggregate Particles, and Their Scattering Properties

AbstractA 3D growth model is used to simulate pristine ice crystals, which are aggregated using a collection algorithm to create larger, multicrystal particles. The simulated crystals and aggregates have mass-versus-size and fractal properties that are consistent with field observations. The growth/collection model is used to generate a large database of snow particles, and the single-scattering properties of each particle are computed using the discrete dipole approximation to account for the nonspherical geometries of the particles. At 13.6 and 35.5 GHz, the bulk radar reflectivities of nonspherical snow particle polydispersions differ from those of more approximate spherical, homogeneous, ice–air particle polydispersions that have the same particle size distributions, although the reflectivities of the nonspherical particles are roughly approximated by polydispersions of spheres of 0.1–0.2 g cm−3 density. At higher microwave frequencies, such as 165.5 GHz, the bulk extinction (and scattering) coefficie.
Performance Analysis and System Implementation for Energy-Efficient Passive UAV Radar Imaging System

Due to the superior flexibility and cost-efficiency, unmanned aerial vehicle (UAV) is becoming an indispensable platform for advanced remote sensing applications. In this paper, the performance and implementation of the energy-efficient passive UAV radar imaging system is investigated. Equipped with a synthetic aperture radar (SAR) receiver, the UAV platform passively reuses the backscattered signal of an external illuminator, and achieves SAR imaging and data communication. Firstly, we present the system concept and block diagram. Then, the imaging performance and feasibility are analyzed for the typical illuminators. It is found that the system can achieve distinct mission performance with different kinds of illuminators, which offers more alternatives for various mission requirements. A set of mission performance evaluators is established to comprehensively assess the capability of the system, including UAV navigation, passive SAR imaging and communication. An energy-efficient path planning method is then presented to generate a UAV path with optimized mission performance. Numerical simulations are conducted to verify the effectiveness of the performance evaluators and path planning method. Finally, a real implementation of the system is given. The imaging results of an airborne passive SAR experiment using external illuminator further validates the imaging capability and performance analysis of the system.
The perturbation method and the extended finite element method. An application to fracture mechanics problems

The extended finite element method has been successful in the numerical simulation of fracture mechanics problems. With this methodology, different to the conventional finite element method, discretization of the domain with a mesh adapted to the geometry of the discontinuity is not required. On the other hand, in traditional fracture mechanics all variables have been considered to be deterministic (uniquely defined by a given numerical value). However, the uncertainty associated with these variables (external loads, geometry and material properties, among others) it is well known. This paper presents a novel application of the perturbation method along with the extended finite element method to treat these uncertainties. The methodology has been implemented in a commercial software and results are compared with those obtained by means of a Monte Carlo simulation.
Hybrid Vehicle-to-X Communication Network by Using ITS-G5 and LTE-V2X

Vehicle-to-X communication enables vehicles and other road users to exchange information in order to increase traffic efficiency and safety. All participants build a decentralized ad hoc network that can operate without the need for additional communication infrastructure. Two competing transmission technologies are available for this purpose. The WLAN-based approach ITS-G5 and the cellular-mobile-based LTE-V2X both enable the direct exchange of information between participants. Each of these technologies has individual advantages and disadvantages that recommend a specific technology for specific use cases. The hybrid usage of the two technologies in a common network can help to improve the reliability of transmissions for safety-critical applications by providing suitable transmission features for every use case, including dissemination range, latency, and channel throughput. The proposed hybrid V2X network approach provides participants with various options for selecting the transmission path to better adapt to the requirements of the specific use cases. The investigation is based on measurements of the transmission properties of ITS-G5 and LTE-V2X in real traffic environments as well as on simulations of hybrid V2X networks in a combined simulation environment for traffic and communication behavior. An important part of this investigation is the development of suitable dissemination models that describe the transmission behavior of both technologies. Initial results show that both technologies can be constructively combined to improve the reliability of communication for safety-critical applications in decentralized V2X networks.
Forecasting Drought Using the Agricultural Reference Index for Drought (ARID): A Case Study

AbstractDrought forecasting can aid in developing mitigation strategies and minimizing economic losses. Drought may be forecast using a drought index, which is an indicator of drought. The agricultural reference index for drought (ARID) was used as a tool to investigate the possibility of using climate indices (CIs) as predictors to improve the current level of forecasting, which is El Nino–Southern Oscillation (ENSO) based. The performances of models that are based on linear regression (LR), artificial neural networks (ANN), adaptive neuron-fuzzy inference systems (ANFIS), and autoregressive moving averages (ARMA) models were compared with that of the ENSO approach. Monthly values of ARID spanning 56 yr were computed for five locations in the southeastern United States, and monthly values of the CIs having significant connections with weather in this region were obtained. For the ENSO approach, the ARID values were separated into three ENSO phases and averaged by phase. For the ARMA models, monthly time .
High-Resolution Submillimeter-Wave Fourier-Transform Spectrometry of Gases

Modem interferometric techniques now permit the measurement of broad-band absorption spectra of gases at submillimetric wavelengths to high resolution with comparative ease. This paper describes briefly some new spectra of H/sub 2/O, N/sub2/O, and SO/sub 2/ in the 10-40 cm/sup -1/ (0.33 to 1.4 THz) region, at a resolution of 0.05 cm/sup-1/.
Robust steering control for a steer-by-wire automated guided vehicle via fixed-time adaptive recursive sliding mode

In this paper, a fixed-time adaptive recursive sliding mode (FTARSM) control scheme is addressed for a steer-by-wire (SbW) automated guided vehicle against model uncertainties and disturbances. First, based on a newly constructed faster fixed-time stable system, a fixed-time recursive sliding structure is developed to guarantee the SbW system fixed-time convergence, where the setting time is independent of initial conditions. By making appropriate initialization settings for the recursive structure, the sliding reaching phase is removed and the control robustness is improved. Then, the extreme learning machine (ELM) is incorporated into the FTARSM controller to estimate the lumped uncertainties upper bound, thus not only the requirement for prior bounds information in controller design is eliminated but also the control chattering is suppressed effectively. Rigorous Lyapunov analyses are further employed to ensure fixed-time closed-loop stability. Finally, the superior performance of the derived control law is verified by experimental results.
Radiation statistics in homogeneous isotropic turbulence

An analysis of turbulence–radiation interaction (TRI) in statistically stationary (forced) homogeneous and isotropic turbulence is presented. A direct numerical simulation code was used to generate instantaneous turbulent scalar fields, and the radiative transfer equation (RTE) was solved to provide statistical data relevant in TRI. The radiation intensity is non-Gaussian and is not spatially correlated with any of the other turbulence or radiation quantities. Its power spectrum exhibits a power-law region with a slope steeper than the classical −5/3 law. The moments of the radiation intensity, Planck-mean and incident-mean absorption coefficients, and emission and absorption TRI correlations are calculated. The influence of the optical thickness of the medium, mean and variance of the temperature and variance of the molar fraction of the absorbing species is studied. Predictions obtained from the time-averaged RTE are also included. It was found that while turbulence yields an increase of the mean blackbody radiation intensity, it causes a decrease of the time-averaged Planck-mean absorption coefficient. The absorption coefficient self-correlation is small in comparison with the temperature self-correlation, and the role of TRI in radiative emission is more important than in radiative absorption. The absorption coefficient–radiation intensity correlation is small, which supports the optically thin fluctuation approximation, and justifies the good predictions often achieved using the time-averaged RTE.
The boron atom and boron positive ion in strong magnetic fields

The ground and a few excited states of the boron atom in external uniform magnetic fields are calculated by means of a 2D mesh Hartree-Fock method for field strengths ranging from zero up to 2.35×109 T. With increasing field strength the ground state of the B atom undergoes five crossovers involving six different electronic configurations which belong to three groups with different spin projections Sz = -1/2,-3/2,-5/2. For weak fields the ground state configuration arises from the field-free 1s22s22p-1, Sz = -1/2 configuration. With increasing field strength the ground state involves the four Sz = -3/2 configurations 1s22s2p02p-1, 1s22s2p-13d-2, 1s22p02p-13d-2 and 1s22p-13d-24f-3, followed by the fully spin-polarized Sz = -5/2 configuration 1s2p-13d-24f-35g-4. The latter configuration forms the ground state of the boron atom in the high-field regime γ>8.0251. Analogous calculations for the B+ give a sequence of the four following ground state configurations: 1s22s2 (Sz = 0), 1s22s2p-1 (Sz = -1), 1s22p-13d-2 (Sz = -1) and 1s2p-13d-24f-3 (Sz = -2). The above series of ground state configurations are extracted from the results of numerical calculations for a number of electronic configurations selected according to general energetical arguments.
Numerical flow computation around aeroelastic 3D square cylinder using inflow turbulence

Numerical flow computations around an aeroelastic 3D square cylinder immersed in the turbulent boundary layer are shown. Present computational code can be characterized by three numerical aspects which are 1) the method of artificial compressibility is adopted for the incompressible flow computations, 2) the domain decomposition technique is used to get better grid point distributions, and 3) to achieve the conservation law both in time and space when the flow is computed a with moving and transformed grid, the time derivatives of metrics are evaluated using the time-and-space volume. To provide time-dependant inflow boundary conditions satisfying prescribed time-averaged velocity profiles, a convenient way for generating inflow turbulence is proposed. The square cylinder is modeled as a 4-lumped-mass system and it vibrates with two-degree of freedom of heaving motion. Those blocks which surround the cylinder are deformed according to the cylinder`s motion. Vigorous oscillations occur as the vortex shedding frequency approaches cylinder`s natural frequencies.
A systematic review: Virtual-reality-based techniques for human exercises and health improvement

Virtual Reality (VR) has emerged as a new safe and efficient tool for the rehabilitation of many childhood and adulthood illnesses. VR-based therapies have the potential to improve both motor and functional skills in a wide range of age groups through cortical reorganization and the activation of various neuronal connections. Recently, the potential for using serious VR-based games that combine perceptual learning and dichoptic stimulation has been explored for the rehabilitation of ophthalmological and neurological disorders. In ophthalmology, several clinical studies have demonstrated the ability to use VR training to enhance stereopsis, contrast sensitivity, and visual acuity. The use of VR technology provides a significant advantage in training each eye individually without requiring occlusion or penalty. In neurological disorders, the majority of patients undergo recurrent episodes (relapses) of neurological impairment, however, in a few cases (60–80%), the illness progresses over time and becomes chronic, consequential in cumulated motor disability and cognitive deficits. Current research on memory restoration has been spurred by theories about brain plasticity and findings concerning the nervous system's capacity to reconstruct cellular synapses as a result of interaction with enriched environments. Therefore, the use of VR training can play an important role in the improvement of cognitive function and motor disability. Although there are several reviews in the community employing relevant Artificial Intelligence in healthcare, VR has not yet been thoroughly examined in this regard. In this systematic review, we examine the key ideas of VR-based training for prevention and control measurements in ocular diseases such as Myopia, Amblyopia, Presbyopia, and Age-related Macular Degeneration (AMD), and neurological disorders such as Alzheimer, Multiple Sclerosis (MS) Epilepsy and Autism spectrum disorder. This review highlights the fundamentals of VR technologies regarding their clinical research in healthcare. Moreover, these findings will raise community awareness of using VR training and help researchers to learn new techniques to prevent and cure different diseases. We further discuss the current challenges of using VR devices, as well as the future prospects of human training.
In-situ production of ozone and ultraviolet light using a barrier discharge reactor for wastewater treatment

A dielectric barrier discharge (DBD) reactor consisting of water-filled dielectric tube electrodes was used for the treatment of wastewater. The inner dielectric tube, which acted as the discharging electrode, was filled with an aqueous electrolyte solution. The outer dielectric tube, which served as the other electrode, was in contact with the wastewater, which was grounded. The present reactor system was energy-efficient for the production of ozone, not only because the perfect contact between the aqueous electrode and the dielectric surface minimized the loss of the electrical energy, but also because the DBD reactor was cooled by the wastewater. In addition, the ultraviolet (UV) light produced in the DBD reactor was able to assist in the wastewater treatment since the quartz tube used as the dielectric material was UV-transparent. The performance of the present DBD system was evaluated using a synthetic wastewater formed from distilled water and an azo dye, amaranth. The experimental parameters were the concentration of the electrolyte in the aqueous electrode, the discharge power, the initial pH of the wastewater and the concentration of hydrogen peroxide added to the wastewater. The wastewater treatment system was found to be effective for achieving decomposition of the dye.
A Generic Cryptographic Deep-Learning Inference Platform for Remote Sensing Scenes

Deep learning plays an essential role in multidisciplinary research of remote sensing. We will encounter security problems during the data acquisition, processing, and result generation stages. Therefore, secure deep-learning inference services are one of the most important links. Some theoretical progress has been made in cryptographic deep-learning inference, but it lacks a general platform that can be realized in reality. Constantly modifying the corresponding models to approximate the plaintext results reveal the model information to a certain extent. This article proposes a generic post-quantum platform named the PyHENet, which perfectly combines cryptography with plaintext deep learning libraries. Second, we optimize the convolution, activation, and pooling functions and complete the ciphertext operation under floating point numbers for the first time. Moreover, the computation process is accelerated by single instruction multiple data streams and GPU parallel computing. The experimental results show that the PyHENet is closer to the plaintext inference platform than any other cryptographic model and has satisfactory robustness. The optimized PyHENet obtained a better accuracy of 95.05% in the high-resolution NaSC-TG2 database, which the Tiangong-2 space station received.