Miracle-dz/UniFAR-FTUs huggingface dataset:
An Advanced Bootstrap Circuit for High Frequency, High Area-Efficiency and Low EMI Buck Converter

An advanced bootstrap control circuit with directly sensing bootstrap voltage (DSBV) for a high frequency, high area-efficiency, and low electromagnetic interference (EMI) buck converter in automotive applications is proposed in this brief. By removing the large off-chip capacitor at the output <inline-formula> <tex-math notation="LaTeX">${V} _{\text {CC}}$ </tex-math></inline-formula> of low-dropout regulator (LDO), the relevant current loop around <inline-formula> <tex-math notation="LaTeX">${V} _{\text {CC}}$ </tex-math></inline-formula> to power ground can be eliminated, which is a great contribution for EMI noise mitigation. On the other hand, the fast charging control for bootstrap capacitance has been substituted by a novel bootstrap architecture and is not dependent on the internal capless LDO, which will not degrade high-frequency behavior for the high-side gate driver. This buck converter has been implemented in a 0.35 <inline-formula> <tex-math notation="LaTeX">$ {\mu }\text{m}$ </tex-math></inline-formula> high-voltage BCD process and occupies a chip area of <inline-formula> <tex-math notation="LaTeX">$2 {\times }2.39$ </tex-math></inline-formula> mm<sup>2</sup>, where the active area of bootstrap circuit is <inline-formula> <tex-math notation="LaTeX">$320 {\times } 194\,\, {\mu }\text{m}^{{2}}$ </tex-math></inline-formula>. Experimental results show that the bootstrap capacitance can be fully charged at MHz switching frequency with a small quiescent current of 43 <inline-formula> <tex-math notation="LaTeX">$ {\mu }\text{A}$ </tex-math></inline-formula>.
A Study on the Normal Transmission of a One-Dimensional P-Wave across a Single Nonlinear Joint in a Rockmass

The presence of nonlinear discontinuities in a rockmass makes the stress wave propagation rules in a continuous medium not applicable. In an attempt to reveal the transmission laws of a one-dimensional P-wave across a single nonlinear joint in a rockmass, a recurrence equation is deduced using a semianalytical and seminumerical method from the nonlinear wave equation by introducing the static Bandis−Barton (BB) model for a single rock joint. Parametric studies are conducted to analyze the effects of the joint position and incident wave frequency. Results demonstrated that incident one-cycle sinusoidal pulse shifted into a wave that had two lobes after propagation in nonlinear rock within a certain distance. The wave then became a wave with two lobes in a different shape after normal transmission across a nonlinear single joint. The amplitude of the recorded waveform before the joint had an obvious inverse correlation with the frequency of the incident pulse. In addition, the amplitude of the transmitted waveform had a positive correlation with the incident pulse within a fixed distance from the joint. The magnitude of the transmission coefficient increased with the incident wave frequency. The conclusions drawn from this study provide a reference for the assessment of the stability of rock structures when they are subjected to dynamic disturbance.
Inside-Out Multiperson 3-D Pose Estimation Using the Panoramic Camera Capture System

Estimating the 3-D human poses of multiple individuals using multiple cameras is a significant research topic within the field of vision-based measurement. Contrary to the classical outside-in camera capture system, the inside-out panoramic camera capture system can cover larger scenes with fewer cameras for 3-D human pose estimation. This advancement extends the application of 3-D human pose measurement beyond small spaces like motion capture studios. For example, this approach can be utilized for intelligent security surveillance in broad outdoor squares or capturing athletes’ movements in large-scale sports scenes. However, existing inside-out 3-D human pose estimation methods that utilize panoramic cameras encounter challenges, particularly in multiperson occlusion scenarios. Aimed at these problems, this article presents a novel inside-out multiperson 3-D human pose estimation method using just a few calibrated panoramic cameras. Specifically, we first propose a cross-view multiperson matching algorithm based on panoramic camera epipolar geometry constraint to improve human body matching robustness across viewpoints. Then, we take advantage of multiple panoramic cameras and introduce a multiview human pose clustering and fusion algorithm to improve the average recall (AR) of 3-D human pose estimation. In addition, we propose a multiview human pose nonlinear optimization algorithm to jointly optimize the weighted reprojection errors of estimated 3-D human poses, which can further improve the average precision (AP). We have conducted extensive experiments on the public Panoptic Studio dataset and self-built real and simulated datasets to demonstrate that our method can inside-out estimate 3-D human poses using multiple panoramic cameras. Compared to state-of-the-art methods, the 3-D human pose omission is greatly reduced through the complementarity of multiple cameras, and the precision of 3-D human pose estimation is largely improved by utilizing multicamera observation information.
A study of Cell Cracks Formation During Freight Shipping : Monitoring Shock and Temperature in Real-Time & Assessing Damages With Pre and Post-Transit Characterizations of PV Modules

The solar photovoltaic (PV) industry often experiences module damage during transportation. PV modules stacked horizontally and strapped on wooden pallets may develop failures impacting their efficiency (glass shattering, cracks, frame indentation, etc.), especially when modules are not packed by professionals. The appearance of failures during the shipment from one laboratory to another can be detrimental to research studies. In this study, we tested a reusable plastic pallet designed to ship modules vertically. Five technologies of commercial PV modules were shipped together from Arizona to Florida including: glass/glass bifacial modules (framed and frameless), glass/transparent backsheet bifacial modules and glass/white backsheet modules (framed). Each module technology has a different physical size. Some modules had pre-existing cell-cracks allowing for the study of cell-crack formation and propagation during shipment. Dark current-voltage (I-V), light I-V and electroluminescence characterization were performed before and after shipment. A datalogger was used to monitor shocks and ambient temperature throughout the shipment and identify when the modules were more susceptible to damage. The modules were tilted upon receipt and the pallet were damaged but with no shattered modules. Time series shock data provided by the datalogger were used to determine potential responsible events. Our results reveal a few new post-transportation cracks for some modules. Modules parameters before and after shipment are also compared regarding the module constructions and their position in the pallet.
Dynamic Positioning of a Ship using Disturbance Observer based Sliding Mode Control

Dynamic positioning (DP) systems play a crucial role in controlling the position and heading of vessels using their own propulsion systems. These systems are extensively utilized for precise maneuvering of marine crafts and sea-going vessels during slow-speed movements and high-seas operations. However, environmental disturbances such as wind, waves, and ocean currents can cause deviations from the desired track, hindering maritime operations. To address these challenges, an effective and robust control technique is required to maintain the heading and orientation of vessels. This research focuses on the application of two different types of disturbance observer (DO) based controllers for DP systems. First, a DO is designed to estimate the external disturbance affecting the dynamics of a ship. Then a sliding mode controller (SMC) with DO is designed for the DP system. However, the classical SMC suffers from chattering, prompting the use of a higher order sliding mode (HOSM) controller with DO for the DP system. The control techniques based on DO contribute to the reduction of control effort while simultaneously improving system robustness. Both control approaches are simulated in MATLAB/Simulink® environment. Then the results of both approaches are compared both qualitatively and quantitatively. The study aims to evaluate the performance of these controllers and assess their effectiveness in maintaining precise vessel positioning and heading in the presence of environmental disturbances.
Study on Performance Bottleneck of Flow-Level Information-Centric Network Simulator

Information-Centric Networking (ICN) has gained attention as one of the next-generation internet architectures that focuses on the data being transmitted rather than the hosts transmitting it. Due to the differences between ICN and TCP/IP networks, it is not possible to evaluate the performance of ICN using network simulators designed for TCP/IP. A number of studies have been conducted to develop ICN network simulators. However, further acceleration of ICN network simulators is expected to enable large-scale ICN network performance evaluation. In this paper, we analyze the performance bottleneck of the flow-level ICN simulator called FICNSIM (Fluid-based ICNSIMulator) by profiling its performance using the Julia language source code. Specifically, we identify the processing that is causing the performance bottleneck of FICNSIM and investigate the scalability of FICNSIM with respect to network scale.
Wearable Device for Drowsy User Detection

This paper proposes a wearable acquisition device for noninvasive brain–computer interface-based drowsy driving detection, which is a major cause of automobile accidents. The device detects changes in brain activity and eye movements that indicate drowsiness by monitoring electrical signals obtained using electroencephalography, electrooculography, and muscle activity. This hardware device is intended to be low-cost and robust. The acquired signals (electroencephalography, electrooculography, and muscle activity) are accurate and noise-free, allowing the detection of electrical activity fluctuations when blinking, moving the head, or biting the teeth. This device can prevent car accidents caused by drowsy driving by providing real-time alerts to sleepy drivers. The proposed solution is low-cost. It is based on machine learning and monitors electroencephalography signals. It presents a promising approach to improving road safety. Further research and development in this area are warranted.
Implementation of deep neural networks learning on unmanned aerial vehicle based remote-sensing

Due to efficient and adaptable data collecting, unmanned aerial vehicle (UAV) has been a popular topic in computer vision (CV) and remote sensing (RS) in recent years. Inspiring by the recent success of deep learning (DL), several enhanced object identification and tracking methods have been broadly applied to a variety of UAV-related applications, including environmental monitoring, precision agriculture, and traffic management. In this research, we present efficient neural network (ENet), a unique deep neural network architecture designed exclusively for jobs demanding low latency operation. ENet is up to quicker, takes fewer floating-point operations per second (FLOPs), has fewer parameters, and offers accuracy comparable to or superior to that of previous models. We have tested it on the street and cityscapes reports on comparisons with current state-of-the-art approaches and the tradeoffs between a network's processing speed and accuracy. We give measurements of the proposed architecture's performance on embedded devices and offer software enhancements that might make ENet even quicker.
Biosynthesis, Engineering, and Delivery of Selenoproteins

Selenocysteine (Sec) was discovered as the 21st genetically encoded amino acid. In nature, site-directed incorporation of Sec into proteins requires specialized biosynthesis and recoding machinery that evolved distinctly in bacteria compared to archaea and eukaryotes. Many organisms, including higher plants and most fungi, lack the Sec-decoding trait. We review the discovery of Sec and its role in redox enzymes that are essential to human health and important targets in disease. We highlight recent genetic code expansion efforts to engineer site-directed incorporation of Sec in bacteria and yeast. We also review methods to produce selenoproteins with 21 or more amino acids and approaches to delivering recombinant selenoproteins to mammalian cells as new applications for selenoproteins in synthetic biology.
Biochemical Study of Andrographis paniculata under the stress of Cadmium

Medicinal herbs contamination due to heavy metals can be attributed to pollute environment by metal dyeing, smelter, electroplating and other industries. Herbs are subjected to a range of abiotic stresses, such as drought, heat, alkalinity, heavy metals, temperature and pathogen infection, all of which cause devastating impact on plant growth and crop production. 5th for Chordates and 4th for vascular plants Cadmium is most toxic metal.With inhibiting pollen germination and tube growth Cd may have opposite effect in the process of reproduction of plants. The toxic effects of Cd on living system and its reports have already carried out by a number of authors. The main aim of this paper is that to provide the major effects of Cd i.e. toxicity are oxidative stress mediated by increased level of reactive oxygen species (ROS) but in contrast with other heavy metals.
A coupled human‐natural systems analysis of irrigated agriculture under changing climate

Exponentially growing water demands and increasingly uncertain hydrologic regimes due to changes in climate and land use are challenging the sustainability of agricultural water systems. Farmers must adapt their management strategies in order to secure food production and avoid crop failures. Investigating the potential for adaptation policies in agricultural systems requires accounting for their natural and human components, along with their reciprocal interactions. Yet this feedback is generally overlooked in the water resources systems literature. In this work, we contribute a novel modeling approach to study the coevolution of irrigated agriculture under changing climate, advancing the representation of the human component within agricultural systems by using normative meta‐models to describe the behaviors of groups of farmers or institutional decisions. These behavioral models, validated against observational data, are then integrated into a coupled human‐natural system simulation model to better represent both systems and their coevolution under future changing climate conditions, assuming the adoption of different policy adaptation options, such as cultivating less water demanding crops. The application to the pilot study of the Adda River basin in northern Italy shows that the dynamic coadaptation of water supply and demand allows farmers to avoid estimated potential losses of more than 10 M€/yr under projected climate changes, while unilateral adaptation of either the water supply or the demand are both demonstrated to be less effective. Results also show that the impact of the different policy options varies as function of drought intensity, with water demand adaptation outperforming water supply adaptation when drought conditions become more severe.
Theoretical Performance Analysis for Thermo-Radiative Assisted Photovoltaic (TRAP™) Cell Operating in Outer Space

In the paper, we propose a thermo-radiative assisted photovoltaic (TRAPTM) cell to simultaneously harvest incoming sunlight and outgoing thermal radiation when it is operating in outer space. The TRAP™ cell device consists of three layers: a conventional space photovoltaic (PV) cell as the top layer, a mid-infrared transparent solar absorber as the middle layer, and a thermo-radiative (TR) cell as the bottom layer. When producing electrical power, the conventional photovoltaic cell needs to face the sun, while the thermo-radiative cell needs to face the ultra-cold deep space. To address the challenges when combining them together, we introduce a mid-infrared transparent solar absorber layer between the solar cell and the thermo-radiative cell. Due to the mid-infrared transparent nature of the solar cell (top layer) and solar absorber (middle layer), the bottom thermo-radiative cell layer is only radiatively coupled to the ultra-cold deep space, while the top and middle layers will utilize the entire solar spectrum by either generating electricity directly or converting unused solar radiation into heat to provide thermal energy for the bottom layer. We analyzed the theoretical performance of the TRAP™ cell using detailed balance principle when the cell is operating in the outer space from near the Mercury orbit to near Jupiter orbit, calculated the maximum achievable temperature for the TRAP™ cell under only solar illumination without any other active heating, and investigated the effect of an imperfect solar absorber on the performance of the TRAP™ cell.
A Holistic Optimisation - Success Mantra for HPC Performance

High Performance Computing (HPC) aids in solving numerous complex scientific problems such as weather forecasting, drug discovery, physical simulations, molecular modeling, nuclear research, cryptanalysis, oil and gas exploration. To scale these kinds of applications across the nodes of a cluster or supercomputer Message Passing Interface (MPI) is used. The performance of MPI is one of the key aspects to achieve the expected speedup in the application performance on a HPC cluster, which in turn depends on the architecture of the servers and hence it is important to understand the same for HPC practitioners. Application performance is dependent not only on an applications' capability to scale but also on the efficiency of application to execute on an architecture. In this paper, we compare the performance of applications using MPI on two architectures of based on Intel and ARM. This is important as the former is a predominant architecture and the latter is one of the upcoming architectures among the supercomputers. We have used benchmarks which cover a wide variety of applications belonging to the Berkley dwarfs. This will help to analyze the comprehensive behavior of HPC applications on both the architectures. Finally, we present our observations in terms of computation, communication, data size and functional behavior of the applications.
The relationship between paleo-landmass and uranium mineralization in China

The paleo-landmass and its margin are important uranium metallogenic regions.Statistics show that 47% uranium deposits are located in the paleo-landmass or its margin in China.In response to these phenomena,a series of data investigation have been carried out to preliminarily summarize the relationship between paleo-landmass and uranium mineralization.On one hand,the paleo-landmass is believed to be the oldest mature crust and has the high uranium content Which can provide the material source for uranium mineralization.On the other hand,there existed significant crust-mantle circulation and frequent magmatic-hydrothermal activities around the paleo-landmass which are favorable for uranium mineralization.These factors make the paleo-landmass and its margins become the uranium concentration area and control the space-time distribution of uranium deposits to some extent.
A 56Gb/s PAM4 Optical Receiver Integrated with Si-Ge APD

This paper presents a broadband optical PAM4 receiver (RX) integrated with a Si-Ge avalanche photodiode (APD) by wire bonding. Fabricated in 28nm CMOS, the 56Gb/s PAM4 receiver achieves an optical modulation amplitude (OMA) of -7dBm at BER of 10-4 and power efficiency of 1.61pJ/bit.
Novel Approach for Image Compression Using Curvelet Transform

This paper proposes a novel image compression algorithm using curvelet transform. The proposed research decomposed the original image into curvelet coefficients by using fast discrete curvelet transform, after that the different scales of quantized curvelet coefficients were selected for lossy compression by the help of cutoff threshold. The proposed method was compared with image compression method based on wavelet transform. Experimental results show that the compression performance of our method gains much improvement based on PSNR, MSE and memory size. Moreover, the algorithm works fairly well for declining block effect at higher compression ratios.
Co-Delivery of Novel Synthetic TLR4 and TLR7/8 Ligands Adsorbed to Aluminum Salts Promotes Th1-Mediated Immunity against Poorly Immunogenic SARS-CoV-2 RBD

Despite the availability of effective vaccines against COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to spread worldwide, pressing the need for new vaccines with improved breadth and durability. We developed an adjuvanted subunit vaccine against SARS-CoV-2 using the recombinant receptor–binding domain (RBD) of spikes with synthetic adjuvants targeting TLR7/8 (INI-4001) and TLR4 (INI-2002), co-delivered with aluminum hydroxide (AH) or aluminum phosphate (AP). The formulations were characterized for the quantities of RBD, INI-4001, and INI-2002 adsorbed onto the respective aluminum salts. Results indicated that at pH 6, the uncharged RBD (5.73 ± 4.2 mV) did not efficiently adsorb to the positively charged AH (22.68 ± 7.01 mV), whereas it adsorbed efficiently to the negatively charged AP (−31.87 ± 0.33 mV). Alternatively, pre-adsorption of the TLR ligands to AH converted it to a negatively charged particle, allowing for the efficient adsorption of RBD. RBD could also be directly adsorbed to AH at a pH of 8.1, which changed the charge of the RBD to negative. INI-4001 and INI-2002 efficiently to AH. Following vaccination in C57BL/6 mice, both aluminum salts promoted Th2-mediated immunity when used as the sole adjuvant. Co-delivery with TLR4 and/or TLR7/8 ligands efficiently promoted a switch to Th1-mediated immunity instead. Measurements of viral neutralization by serum antibodies demonstrated that the addition of TLR ligands to alum also greatly improved the neutralizing antibody response. These results indicate that the addition of a TLR7/8 and/or TLR4 agonist to a subunit vaccine containing RBD antigen and alum is a promising strategy for driving a Th1 response and neutralizing antibody titers targeting SARS-CoV-2.
A Systematic Review on Detection and Classification of Melanoma

The human skin serves as the exterior protective layer of body, shielding the interior organs beneath from damaging UV rays, dust, and pollution. Cancer is one of the main causes of mortality worldwide as per WHO. One-third of all malignancies that have been diagnosed around the world are skin cancers. Skin cancer has been more common during the last few decades. Melanoma and its global incidence rate have been quickly increasing in recent years. Identifying skin cancer in its early stages can result in a considerable drop in the fatality rate. Melanoma's complicated nature and structure make it difficult to distinguish unique aspects based on the type, shape of the cancer cells, color and texture. This literature review gives an overview of the present state of melanoma detection methods. The review discusses the numerous approaches and procedures used to diagnose melanoma, as well as their potential accuracy, limitations in accuracy, and prospects for improvement. It will concentrate on various ways of diagnosis, such as imaging techniques such as dermoscopy and various methods in artificial intelligence. The review will also look at the problems and potential breakthroughs in the field of melanoma detection.