Miracle-dz/UniFAR-FTUs huggingface dataset:
Intelligent Healthcare: Integration of Emerging Technologies and Internet of Things for Humanity

Health is gold, and good health is a matter of survival for humanity. The development of the healthcare industry aligns with the development of humans throughout history. Nowadays, along with the strong growth of science and technology, the medical domain in general and the healthcare industry have achieved many breakthroughs, such as remote medical examination and treatment applications, pandemic prediction, and remote patient health monitoring. The advent of 5th generation communication networks in the early 2020s led to the Internet of Things concept. Moreover, the 6th generation communication networks (so-called 6G) expected to launch in 2030 will be the next revolution of the IoT era, and will include autonomous IoT systems and form a series of endogenous intelligent applications that serve humanity. One of the domains that receives the most attention is smart healthcare. In this study, we conduct a comprehensive survey of IoT-based technologies and solutions in the medical field. Then, we propose an all-in-one computing architecture for real-time IoHT applications and present possible solutions to achieving the proposed architecture. Finally, we discuss challenges, open issues, and future research directions. We hope that the results of this study will serve as essential guidelines for further research in the human healthcare domain.
Automatic Bangla License Plate Recognition System for Low-Resolution Images

Automatic License Plate Recognition (ALPR) System is a crucial task that is used in numerous critical situations. Although there are several ways to accomplish LP recognition, our method is intended to be effective not just on LP with high resolution, but even when the LP is of very low resolution (LR). Previous works on ALPR systems emphasized achieving recognition benchmarks on LP images that are close to the sensor. However, if the camera is far from the vehicle, the generated detected frame yields an LP image of LR, which is hard for the recognition model to classify. Our method employed Enhanced Super Resolution Generative Adversarial Networks (ESRGANs) to upscale the [32 × 24] LR image to the high resolution of dimension [256 × 192] with a scale factor ratio of 8. For training purposes, we also collected and trained the models on a dataset of 2211 images. The Peak signal-to-noise ratio (PSNR) for the reconstruction on 200 testing samples is 12.587. The optical character recognition accuracy for the reconstructed and ground truth images are 78% and 91% respectively.
Excitation of the radiationless anapole mode

The existence of non-radiating sources is of fundamental importance for inverse scattering problems and the design of invisible objects. However, the excitation of such radiationless sources is quite challenging. We present a method based on which the anapole mode of a high-index isotropic dielectric nanosphere can be excited but radiationless. We show that this radiationless anapole is attributed to the destructive interference of the Cartesian dipole and toroidal moment of the induced current by our proposed focused radially polarized beam illumination. Further, with a standing-wave illumination formed by two counter-propagating focused radially polarized beams under 4π configuration, the ideal radiationless anapole can be excited. This result illustrates a case where the reciprocity condition is not violated, and yet, a radiationless mode can be excited by external illumination.
A MEMS microphone for aeroacoustics measurements

This paper presents the development of a siliconmicromachined, piezoresistive~ microphone for aeroacaustics measurements. The microphone consists of four dielectrically-isolated, single-crystal silicon piezoresistors on top of a 1500 A-thick, 210 pm-diameter silicon-nitride membrane. The microphone was designed by employing a fundamental structural model coupled with a lumped-element energy model. Preliminary measurements indicate a sensitivity of &V/V/Pa and a linear response up to 155 dB. The measured and predicted sensitivity agree to within 3 dB.
A Novel Collision Avoidance Strategy with D2D Communications for UAV Systems

In recent years, safety operation issues related to the autonomous flight of unmanned aerial vehicles (UAVs) have become popular research and development topics worldwide. Among all UAV applications, multiple UAV-related applications are emerging due to the integration of UAVs into 6G networks, which is an important topic for next-generation wireless communication systems. For multiple UAV applications, flight safety among UAVs is the most significant issue. Therefore, collision avoidance for UAVs has become an emerging topic in UAV-related research. In the past, although many UAV collision avoidance methods have been proposed, there is still a probability of other problems, such as no possible avoidance route and unmanaged UAVs that are without centralized control, which both result in an unpredictable risk of collisions. In this study, we investigate the current existing methods and propose novel collision avoidance methods based on the elastic collision principle. To verify the performance of the proposed methods, we also conduct simulations in this paper to demonstrate their effectiveness. From the simulation results, it can be seen that the proposed methods can effectively perform collision avoidance for multiple UAVs. Specifically, using the proposed methods, all UAVs can reach their destination points within reasonable time resources without any collision, validating the effectiveness of the proposed methods.
Mesalazine–PAMAM Nanoparticles for Transporter-Independent Intracellular Drug Delivery: Cellular Uptake and Anti-Inflammatory Activity

Background Mesalazine is one of the main drugs used to treat inflammatory bowel diseases. However, its applicability is limited by its rapid inactivation and removal from the organism, as well as the need for its membrane transporter-dependent cellular uptake to exert therapeutic effect. The present study involved the development of an innovative nanocarrier, based on poly(amidoamine) (PAMAM) dendrimer of the 4th generation, to obtain higher concentrations of the drug in the intestinal epithelial cells, thus increasing its anti-inflammatory potential. The work involved synthesis and in vitro characterization of covalent PAMAM-mesalazine conjugate with succinic linker. Results PAMAM-mesalazine conjugate was synthesized and characterized by 1H NMR, 13C NMR, FTIR and MALDI-TOF MS. This allowed to confirm the purity of the obtained compound and intermediates. Based on the analyses, it was found that ~45 drug molecules were successfully attached to one molecule of PAMAM dendrimer. The conjugate was then characterized in terms of hydrodynamic diameter, zeta potential, spectral properties, drug release from the carrier, as well as cellular uptake and cytotoxicity in two in vitro models of gastrointestinal epithelium (CaCo-2 and HT-29 human cell lines). Analyzing cellular parameters related to the specific mechanism of action of mesalazine (inhibition of NF-κB signaling, decrease in interleukin and prostaglandin synthesis, and ROS scavenging), we showed that such a dendrimer-based carrier may enhance cellular uptake of the drug, which translated into its improved anti-inflammatory efficacy. Conclusion The use of PAMAM macromolecule as a carrier for mesalazine increases the bioavailability of the drug, ensuring enhanced cellular uptake and bypassing the need to utilize mesalazine-specific membrane transporters. All these characteristics translate into an improved anti-inflammatory activity of mesalazine in vitro. In conjunction with appropriately designed in vivo studies, such a compound may prove to be a promising alternative to the therapeutics currently used in inflammatory bowel diseases.
High Quality Triangulation of Dynamic Implicit Surfaces

We present a new method for rendering high quality dynamic implicit surfaces. It first samples the implicit surface uniformly using particle fission and floating, then reconstructs a triangular mesh from the sample points using ball pivoting algorithm, and finally subdivides the reconstructed surface using 1 to 4 subdivision scheme to obtain the high quality implicit surface tessellation. For dynamic implicit surfaces, we make full use of the shape coherence to achieve fast rendering.
Battery Pack and Underbody: Integration in the Structure Design for Battery Electric Vehicles—Challenges and Solutions

The evolution toward electric vehicle nowadays appears to be the main stream in the automotive and transportation industry. In this paper, our attention is focused on the architectural modifications that should be introduced into the car body to give a proper location to the battery pack. The required battery pack is a big, heavy, and expensive component to be located, managed, climatized, maintained, and protected. This paper develops some engineering analyses and shows sketches of some possible solutions that could be adopted. The possible consequences on the position of the vehicle center of gravity, which in turn could affect the vehicle drivability, lead to locate the battery housing below the passenger compartment floor. This solution is also one of the most interesting from the point of view of the battery pack protection in case of a lateral impact and for easy serviceability and maintenance. The integration of the battery pack’s housing structure and the vehicle floor leads to a sort of sandwich structure that could have beneficial effects on the body’s stiffness (both torsional and bending). This paper also proposes some considerations that are related to the impact protection of the battery pack, with particular reference to the side impacts against a fixed obstacle, such as a pole, which are demonstrated to be the most critical. By means of some FE simulation results, the relevance of the interplay among the different parts of the vehicle side structure and battery case structure is pointed out.
The ACE rs1799752 Variant Is Associated with COVID-19 Severity but Is Independent of Serum ACE Activity in Hospitalized and Recovered Patients

This paper assesses the association of the insertion/deletion ACE (angiotensin-converting enzyme) variant (rs1799752 I/D) and the serum ACE activity with the severity of COVID-19 as well as its impact on post-COVID-19, and we compare these associations with those for patients with non-COVID-19 respiratory disorders. We studied 1252 patients with COVID-19, 104 subjects recovered from COVID-19, and 74 patients hospitalized with a respiratory disease different from COVID-19. The rs1799752 ACE variant was assessed using TaqMan® Assays. The serum ACE activity was determined using a colorimetric assay. The DD genotype was related to risk for invasive mechanical ventilation (IMV) requirement as an indicator of COVID-19 severity when compared to the frequencies of II + ID genotypes (p = 0.025, OR = 1.428, 95% CI = 1.046–1.949). In addition, this genotype was significantly higher in COVID-19 and post-COVID-19 groups than in the non-COVID-19 subjects. The serum ACE activity levels were lower in the COVID-19 group (22.30 U/L (13.84–32.23 U/L)), which was followed by the non-COVID-19 (27.94 U/L (20.32–53.36 U/L)) and post-COVID-19 subjects (50.00 U/L (42.16–62.25 U/L)). The DD genotype of the rs1799752 ACE variant was associated with the IMV requirement in patients with COVID-19, and low serum ACE activity levels could be related to patients with severe disease.
Electro-Absorption Modulator Thermo-Optical Self-Heating Analysis

In this work a novel methodology is presented for coupled thermo-optical modelling of an electro-absorption modulator (EAM). First, an optical FDTD simulation results in the light absorption map in the EAM waveguide. This absorption is used as a heat source boundary condition in a thermal finite element (FE) simulation in order to calculate the waveguide temperature. The FE model is validated with experimental data. The temperature is averaged over the device length and used as input in a compact, fully coupled thermo-optical model. The model reveals a thermal instability of the device characteristic, which limits the maximum amount of optical power the device can handle. Finally, using the thermal FE model, a self-heating mitigation strategy is proposed. Using process compatible design changes, self-heating can be reduced by up to 40%, greatly increasing the EAM optical power handling capabilities.
Text-Guided Image Manipulation via Generative Adversarial Network With Referring Image Segmentation-Based Guidance

This study proposes a novel text-guided image manipulation method that introduces referring image segmentation into a generative adversarial network. The proposed text-guided image manipulation method aims to manipulate images containing multiple objects while preserving text-unrelated regions. The proposed method assigns the task of distinguishing between text-related and unrelated regions in an image to segmentation guidance based on referring image segmentation. With this architecture, the adversarial generative network can focus on generating new attributes according to the text description and reconstructing text-unrelated regions. For the challenging input images with multiple objects, the experimental results demonstrate that the proposed method outperforms conventional methods in terms of image manipulation precision.
The Effect of Cutting Fluid on Machined Surface Integrity of Ultra-High-Strength Steel 45CrNiMoVA

The surface integrity of ultra-high-strength steel has a significant influence on service performance, and cutting fluid plays an important role in maintaining surface integrity in production. In this paper, the surface integrity of ultra-high-strength steel 45CrNiMoVA was investigated under three cutting fluids: HY-103 (micro-emulsion), TRIM E709 (emulsion), and Vasco 7000 (micro-emulsion) from the aspects of cutting force, surface morphology, residual stress, micro hardness, microstructure, etc. The results showed that the changing trend of the cutting forces in three directions is HY-103 > Vasco 7000 > TRIM E709. The TRIM E709 contains the maximum lubricants, which reduce cutting force and Sa roughness, while the Vasco 7000 contains the minimum corrosive elements, which results in the least pitting. Both tangential and axial stresses under cutting fluid are tensile stresses. TRIM E709 and Vasco 7000 are reduced axially by 4.45% and 7.60% relative to HY-103, respectively. The grain refinement layer depths of HY-103, TRIM E709, and Vasco 7000 are 9 μm, 4 μm, and 8 μm, respectively, and TRIM E709 can induce recrystallized grains to grow along {001} of the sample cross section, which results from the lowest cooling rate. This work may provide an innovative control strategy for cutting fluid to improve surface integrity and service performance.
Investigation of the Effects of Some Cardiovascular Drugs on Angiogenesis by Transgenic Zebrafish

Introduction Angiogenesis contributes to the pathophysiology of cardiovascular disease (CVD). Some cardiovascular drugs used in the treatment of CVD have an effect on the process of angiogenesis. Methods Transgenic Tg (flk1: EGFP) zebrafish embryos were used to identify the effects of some cardiovascular drugs on angiogenesis during vertebral development in vivo. Zebrafish embryos at a one-cell stage or two-cell stage were cultured with embryo medium containing cardiovascular drugs at a final solvent concentration of 0.5% (V/V) dimethyl sulfoxide (DMSO) for 24 hours in 24-well plates. Results We found that 6 drugs including isosorbide mononitrate, amlodipine, bisoprolol fumarate, carvedilol, irbesartan, and rosuvastatin calcium may affect angiogenesis by vascular endothelial growth factor (VEGF) signaling pathway. Conclusion These new findings of some cardiovascular drugs should improve the treatment of cardiovascular diseases.
Terahertz generation and detection using femtosecond mode-locked Yb-doped fiber laser

We successfully demonstrate a THz generation using an ytterbium (Yb)-doped mode-locked femtosecond fiber laser and a home-made low-temperature grown (LTG) InGaAs Photoconductive antenna (PCA) module for THz Time-domain spectroscopy (TDS) systems. The Yb-doped fiber ring laser consists of a pump laser diode (PLD), a wavelength division multiplexer (WDM) coupler, a single-mode fiber (SMF), a 25 cm-long highly Yb-doped fiber, two collimators, two quarter wave plates (QWPs), a half-wave plate (HWP), a 10 nm broadband band pass filter, an isolator, and a polarizing beam splitter (PBS). In order to achieve the passively mode-locked optical short pulse, the nonlinear polarization rotation (NPR) effect is used. The achieved center wavelength and the 3 dB bandwidth of the modelocked fiber laser are 1.03 μm and ~ 15.6 nm, respectively. It has 175 fs duration after pulse compression with 66.2 MHz repetition rate. The average output power of mode-locked laser has more than 275 mW. The LTG-InGaAs PCA modules are used as the emitter and receiver in order to achieve the THz radiation. The PCA modules comprise a hyper-hemispherical Si lens and a log-spiral antenna-integrated LTG-InGaAs PCA chip electronically contacted on a printed circuit board (PCB). An excitation optical average pumping and probing power were ~ 6.3 mW and 5 mW, respectively. The free-space distance between the emitter and the receiver in the THz-TDS system was 70 mm. The spectrum of the THz radiation is achieved higher than 1.5 THz.
Stability estimates for some parameters of a reaction-diffusion equation coupled with an ODE

In this work, we are interested by the monodomain equation which describes the evolution of the cardiac electrical potential and which corresponds to a coupled system involving a reaction–diffusion equation and an ordinary differential equation. We show Lipschitz stability inequalities for the identification of some parameters of the model from measurements on the cardiac potential and the ionic variable.
Radar fall detection using principal component analysis

Falls are a major cause of fatal and nonfatal injuries in people aged 65 years and older. Radar has the potential to become one of the leading technologies for fall detection, thereby enabling the elderly to live independently. Existing techniques for fall detection using radar are based on manual feature extraction and require significant parameter tuning in order to provide successful detections. In this paper, we employ principal component analysis for fall detection, wherein eigen images of observed motions are employed for classification. Using real data, we demonstrate that the PCA based technique provides performance improvement over the conventional feature extraction methods.
Wafer Surface Defect Detection Based on Background Subtraction and Faster R-CNN

Concerning the problem that wafer surface defects are easily confused with the background and are difficult to detect, a new detection method for wafer surface defects based on background subtraction and Faster R-CNN is proposed. First, an improved spectral analysis method is proposed to measure the period of the image, and the substructure image can then be obtained on the basis of the period. Then, a local template matching method is adopted to position the substructure image, thereby reconstructing the background image. Then, the interference of the background can be eliminated by an image difference operation. Finally, the difference image is input into an improved Faster R-CNN network for detection. The proposed method has been validated on a self-developed wafer dataset and compared with other detectors. The experimental results show that compared with the original Faster R-CNN, the proposed method increases the mAP effectively by 5.2%, which can meet the requirements of intelligent manufacturing and high detection accuracy.
The Oligostilbene Gnetin H Is a Novel Glycolysis Inhibitor That Regulates Thioredoxin Interacting Protein Expression and Synergizes with OXPHOS Inhibitor in Cancer Cells

Since aerobic glycolysis was first observed in tumors almost a century ago by Otto Warburg, the field of cancer cell metabolism has sparked the interest of scientists around the world as it might offer new avenues of treatment for malignant cells. Our current study claims the discovery of gnetin H (GH) as a novel glycolysis inhibitor that can decrease metabolic activity and lactic acid synthesis and displays a strong cytostatic effect in melanoma and glioblastoma cells. Compared to most of the other glycolysis inhibitors used in combination with the complex-1 mitochondrial inhibitor phenformin (Phen), GH more potently inhibited cell growth. RNA-Seq with the T98G glioblastoma cell line treated with GH showed more than an 80-fold reduction in thioredoxin interacting protein (TXNIP) expression, indicating that GH has a direct effect on regulating a key gene involved in the homeostasis of cellular glucose. GH in combination with phenformin also substantially enhances the levels of p-AMPK, a marker of metabolic catastrophe. These findings suggest that the concurrent use of the glycolytic inhibitor GH with a complex-1 mitochondrial inhibitor could be used as a powerful tool for inducing metabolic catastrophe in cancer cells and reducing their growth.
Generating quantum-measurement probabilities from an optimality principle

An alternative formulation to the (generalized) Born rule is presented. It involves estimating an unknown model from a finite set of measurement operators on the state. An optimality principle is given that relates to achieving bounded solutions by regularizing the unknown parameters in the model. The objective function maximizes a lower bound on the quadratic Renyi classical entropy. The unknowns of the model in the primal are interpreted as transition witnesses. An interpretation of the Born rule in terms of fidelity is given with respect to transition witnesses for the pure state and the case of positive operator-valued measures (POVMs). The models for generating quantum-measurement probabilities apply to orthogonal projective measurements and POVM measurements, and to isolated and open systems with Kraus maps. A straightforward and constructive method is proposed for deriving the probability rule, which is based on Lagrange duality. An analogy is made with a kernel-based method for probability mass function estimation, for which similarities and differences are discussed. These combined insights from quantum mechanics, statistical modeling, and machine learning provide an alternative way of generating quantum-measurement probabilities.
NGLSFusion: Non-Use GPU Lightweight Indoor Semantic SLAM

Perception of the indoor environment is the basis of mobile robot localization, navigation, and path planning, and it is particularly important to construct semantic maps in real time using minimal resources. The existing methods are too dependent on the graphics processing unit (GPU) for acquiring semantic information about the indoor environment, and cannot build the semantic map in real time on the central processing unit (CPU). To address the above problems, this paper proposes a non-use GPU for lightweight indoor semantic map construction algorithm, named NGLSFusion. In the VO method, ORB features are used for the initialization of the first frame, new keyframes are created by optical flow method, and feature points are extracted by direct method, which speeds up the tracking speed. In the semantic map construction method, a pretrained model of the lightweight network LinkNet is optimized to provide semantic information in real time on devices with limited computing power, and a semantic point cloud is fused using OctoMap and Voxblox. Experimental results show that the algorithm in this paper ensures the accuracy of camera pose while speeding up the tracking speed, and obtains a reconstructed semantic map with complete structure without using GPU.