Miracle-dz/UniFAR-FTUs huggingface dataset:
Adopting Deep Learning for Chest X-ray Analysis: An Extensive Survey

Chest X-ray (CXR) investigations are commonly carried out at healthcare centres. These analyses may identify critical medical illnesses such pneumonia, idiopathic pulmonary fibrosis, cardiac disease, and breaking bones, and pneumothorax. Unfortunately, radiologists frequently perform these diagnoses manually, which makes it time-consuming and prone to mistakes and misinterpretation. Researchers have been investigating various algorithms and models to build machine learning that might aid radiologists in their assessment and lower the likelihood of misinterpretation in recent years due to the growing processing capacity of hardware and developments in deep learning. To increase the precision and accuracy of the assessment, researchers have developed single- and multi-level localization and segmentation approaches. This study reviews the advancements achieved in deep learning in the context of CXR.
IN SINCE ITS

26 During the first months of SARS-CoV-2 evolution in a new host, contrasting hypotheses 27 have been proposed about the way the virus has evolved and diversified worldwide. The aim 28 of this study was to perform a comprehensive evolutionary analysis to describe the human 29 outbreak and the evolutionary rate of different genomic regions of SARS-CoV-2. 30 The molecular evolution in nine genomic regions of SARS-CoV-2 was analyzed using three 31 different approaches: phylogenetic signal assessment, emergence of amino acid 32 substitutions, and Bayesian evolutionary rate estimation in eight successive fortnights since 33 the virus emergence. 34 All observed phylogenetic signals were very low and trees topologies were in agreement 35 with those signals. However, after four months of evolution, it was possible to identify 36 regions revealing an incipient viral lineages formation despite the low phylogenetic signal, 37 since fortnight 3. Finally, the SARS-CoV-2 evolutionary rate for regions nsp3 and S, the ones 38 presenting greater variability, was estimated to values of 1.37 x 10 -3 and 2.19 x 10 -3 39 substitution/site/year, respectively. 40 In conclusion, results obtained in this work about the variable diversity of crucial viral regions 41 and the determination of the evolutionary rate are consequently decisive to understand 42 essential feature of viral emergence. In turn, findings may allow characterizing for the first 43 time, the evolutionary rate of S protein that is crucial for vaccines development.
A Comprehensive Review on Partial Power Processing-based Voltage Regulator Modules for 48-V Bus-based Data Centers

Nowadays, the data center is becoming a large consumer in the electricity market with the blooming of information and communication technologies. To ensure the chip-level power supply, the electric power from the utility must step down to the desired very-low voltage domains, leading to considerable losses in cascaded power conversions. As the interface between the bus bar and load elements, high-performance voltage regulation modules (VRMs) are the cornerstone of greener data centers. Hence, along with the development of power electronics technologies, various converters have been presented in the literature. One of the key issues for data centers is to maintain the voltage balance with high efficiency. In this paper, state-of-the-art partial power processing (PPP)-based VRMs are systematically analyzed and reviewed. Then, a comparative simulation between different control objectives is carried out with four series-connected loads. The results showed that the difference in control objectives will influence both the total and the unit-maximum processing power of the PPP-based system. Additionally, the challenges for future data centers are briefly discussed.
Controlling Flow Instabilities in Direct-to-Chip Two-Phase Cooling for High Heat Flux Processors

As thermal dissipation from high-power density chips is anticipated to exceed the limits of single-phase cooling, two-phase cooling is being investigated as an alternative solution in the thermal management of data centers. However, it is necessary to recognize two-phase cooling issues and provide solutions to them before they can be widely implemented in data centers. The nonuniform distribution of flow in parallel pathways under the nonuniform heat load is one of the main problems two-phase systems encounters. This is explained by the fact that the pressure drop in the path increases with increasing power owing to evaporation, forcing the flow through parallel paths with less resistance. In this work, two effective solutions to eliminate flow nonuniformity namely constant flow regulators and flow restrictors were introduced. These two solutions were investigated experimentally using proof-of-concept cooling loops that have four parallel cold plates. At the entrance of each cold plate, an ultrasonic flow sensor was installed to measure the flowrate in this branch. These solutions were tested under extremely nonuniform heat loads using high-power-density Thermal Testing Vehicles (TTVs) with 2.5 kW rated heaters. Results proved that flow nonuniformity can be eliminated by using either one of these two flow stability solutions with maximum variation as low as 0.15 LPM. R134a refrigerant was used in this experiment to establish a baseline. Testing these solutions while considering a green refrigerant substitute for R134a would be the next step.
Sub-THz Ray Tracing Simulation and Experimental Validation for Indoor Scenarios

Sub-terahertz (THz) communication is envisioned as one of the key components for 6G because of the abundantly available spectrum resource. Accurate and efficient channel models are prerequisites for developing sub-THz communication systems. Due to the sparsity and more ray optics propagation characteristics of the sub-THz channel, deterministic Ray-Tracing (RT) has attracted much attention for sub-THz channel modeling, which shows the potential of reducing the simulation complexity yet maintaining the accuracy. This paper presents an implementation of RT for sub-THz channel modeling and demonstrates its performance based on sub-THz channel measurements. A virtual massive multiple-input-multiple-output (MIMO) channel operating at 100 GHz and a double-directional 300 GHz channel are considered in the RT implementation, where the RT achieves a high similarity compared to the channel measurements in terms of channel impulse response and power angular spectrum. Besides, the near-field and spatial non-stationary properties of the sub-THz massive MIMO channel and the dominant multipaths of the 300 GHz channel are accurately reconstructed in the RT simulation. This work can provide insights into deterministic sub-THz channel modeling research from the implementation, evaluation, and challenges perspectives.
Conversion of Pixel to Millimeter in Ultrasound Images: A Methodological Approach and Dataset

Ultrasound imaging is integral to prenatal care, facilitating the identification of fetal landmarks. However, the accuracy of fetal structure measurements largely hinges on the precise conversion of pixel values to millimeters (mm), an essential step in developing artificial intelligence (AI) applications capable of automating fetal measurements. This paper presents a novel pixel intensity-based technique for converting pixel values to millimeters in fetal ultrasound images. Utilizing a publicly available dataset, we have enhanced its value by adding new labels that provide pixel size in millimeters, thereby creating an augmented resource. Our augmented dataset, comprising 2835 fetal head images, represents the largest and most diverse collection of its kind in the literature. The mean pixel size label is 0.144 mm, ranging from a minimum of 0.06 mm to a maximum of 0.33 mm. The proposed technique proves to be accurate and efficient, thus serving as a substantial resource for future AI-based fetal measurement applications in clinical settings.
Glacial geomorphic evidence for a late climatic change on Mars

In a series of preliminary reports, we documented evidence of former glacial epochs on Mars. Apparent glacial landforms seemed to be concentrated primarily at middle to high southern latitudes. We now have additional evidence supporting the view that Martian glaciation appears to have been more extensive than previously recognized. The growth and collapse of ice sheets on Mars seems closely analogous to the growth and decline of Earth's great Pleistocene ice sheets. This implies that climate change was probably somewhat comparable on the two planets, although in the case of Mars the entire planet seems to have changed rapidly to a cold, dry present-day environment after the collapse of the ice sheets.
Aktywność innowacyjna przedsiębiorstw zagranicznych i krajowych

Przedmiotem rozwazan w artykule jest kwestia wplywu wlasności przedsiebiorstw na aktywnośc innowacyjną przemyslu zlokalizowanego w Polsce. Autor stara sie odpowiedziec na trzy zasadnicze pytania- po pierwsze, czy podmioty o odmiennej strukturze kapitalu w zroznicowany sposob realizują dzialalnośc innowacyjną, po drugie, jezeli tak, to czy takie roznice powinny wplywac na korekte realizowanej w Polsce polityki innowacyjnej i po trzecie, czy zachowania przedsiebiorstw przemyslowych zlokalizowanych w naszym kraju znacząco odbiegają od tych obserwowanych dla krajow wysokorozwinietych? Kraje przechodzące transformacje systemową cechują sie niedoborami kapitalowymi uniemozliwiającymi akceleracje rozwoju gospodarczego w dlugim okresie. Przedsiebiorstwa zagraniczne, przez bezpośrednie inwestycje zagraniczne, oddzialują na przyśpieszenie realnych procesow ekonomicznych w gospodarce, w tym rowniez na aktywnośc innowacyjną w przemyśle. Glownym celem badania byla proba poszukiwania kierunkow wplywu struktury wlasności przedsiebiorstw przemyslowych na ich systemową aktywnośc innowacyjną uwzgledniającą specyfike polskiej gospodarki. Cześc metodyczna opracowania zostala przygotowana na podstawie modelowania probitowego bazującego na rachunku prawdopodobienstwa. Prowadzone badania wskazują, ze kluczem do akceleracji rozwoju innowacji w Polsce jest stymulowanie tej aktywności glownie w podmiotach posiadających w swojej strukturze kapital zagraniczny. Nie mniej przedsiebiorstwa krajowe, mimo mniejszego zainteresowania prowadzeniem dzialalności innowacyjnej, charakteryzują sie wysoką sklonnością asymilacji nowych technologii przez kanaly pasywnego transfery wiedzy. Na tym etapie rozwoju, aktywnośc innowacyjna ewoluuje z podmiotow zagranicznych w kierunku tych o mieszanej strukturze wlasności.
Internet of Medical Things: Current Applications, Challenges and Future

The Internet of Things (IoT) is a field which is revolutionizing today's world. From turning on the lights to air quality control, IoT is everywhere. An IoT ecosystem combines hardware, software, and computer devices to enable automated internet communication between them. IoT is being used more and more in every business, and it has the potential to revolutionize the health care sector by offering creative solutions that enhance patient outcomes while lowering costs and manual involvement. The IoT helps connect doctors and patients in a completely new way. The paper highlights the applications of Internet of Things (loT) in healthcare sector with the focus to understand the major challenges and future scope. A bibliometric analysis of the open access web of science articles published on IoMT is also presented.
Key Technologies of 5G Wireless Communication Network Physical Layer Based on Information Security Early Warning Model

With the continuous development of the fifth generation (5G) technology, the physical layer of the wireless communication network is facing new challenges. How to effectively prevent and protect these key technologies in the physical layer has a great impact on the entire network and even the entire society. Information security early warning model is a state evaluation model of important security control points in the physical layer of communication network. Security is an important indicator of communication system. Whether its security protection is effective is the basis of its survival and use. Aiming at the situation that the receiver is monitored in the transmission system, this paper has studied the safe transmission method assisted by artificial noise (AN). After the simulation experiment of the physical layer security transmission algorithm, this paper discussed the performance of different algorithms in three scenarios: transmission under non ideal channel information, one-way relay eavesdropping system, and multiple input multiple output (MIMO) untrusted relay eavesdropping system. When analyzing the relationship between the safe transmission rate of different MIMO untrusted relay antennas and the target power constraint $A_{T}, M_{y}=5, M_{d}3, M_{t}=4, A_{t}=\{5,35\}$ dB. On this basis, the optimal power distribution was realized. In the six schemes, when the power constraint $A_{T}$ increased, the security transmission rate of each scheme was improved.
Deep Learning and Latent Variables in Nonuniform Antenna Array Processing for Direction of Arrival

The problem of Direction of Arrival (DOA) in Antenna Array processing has been widely studied. Nonuniform spacing between consecutive elements of linear arrays gives particular advantages but is also challenging. Precedent solutions aimed to deal with it using standard and complex Deep Learning architectures. Given the simplicity of the complex DOA basic equations, we hypothesized that the intrinsic structure of DOA problems should correspond to well-defined manifolds in low-dimensional latent spaces and that this should also hold in nonuniform spatially distributed arrays. We benchmarked a variety of manifold learning estimators for DOA problems, namely, Principal Component Analysis, t-Distributed Stochastic Neighbor Embedding (tSNE), shallow and deep autoencoders (AE), and Uniform Manifold Active Projection (UMAP). The generated latent spaces exhibited intrinsic geometrical structures in one-dimensional manifolds with four branches. On the other hand, DOA recovery built upon fine-tuning these latent spaces exhibited better performance for nonuniform arrays using shallow AE architectures. Our results pave the way for using low-dimensional latent variable spaces in various electromagnetic problems based on the simplicity of the physical equations describing these technologies.
IGBT and Free-Wheeling Diode Behavior during the Short Circuit Type III with varied Operation Conditions

In this paper, the interaction between the Insulated Gate Bipolar Transistor (IGBT) and the Free-Wheeling Diode (FWD) in the short circuit type III (SC III) failure has been studied. The influence of the different operation conditions, like the load current and temperature, are investigated. Furthermore, external factors such as gate impedance, packaging style, and the different diode technologies are discussed. Since the paralleled diode is in the conducting mode before the short circuit, the plasma inside the bipolar silicon (Si) diode and the reverse recovery behavior play essential roles in the short circuit behavior of the IGBT. Under certain conditions, the short circuit stress of the IGBT can be minor and the diode enters the regime of the dynamic avalanche. Moreover, TCAD simulations have been carried out to analyze the internal behavior of IGBT and diode during the SC type III event.
A Spectrum Interference Prediction Method for Multiple Transmitters and Receivers

In the electromagnetic compatibility (EMC) design stage of large electronic platforms, it is required to predict the emission spectrum of transmitters and the reception spectrum of receivers as a way to discover possible spectral compatibility problems within the system. To solve this problem, we provide a method for predicting spectrum interference between multiple transmitters and receivers, which is studied in defining the type of interference and identifying the potential spectrum interference. The prediction results reveal possible spectral compatibility problems within the system at the EMC design stage of parameter allocation, and thus provide a basis for automated evaluation and verification of the reasonableness of design parameters within the system.
Clothing Style Diagram Retrieval Technology Based on VGG

Aiming at the application of deep learning model in sketch retrieval, this paper uses transfer learning method combined with deep learning method to transfer the image feature extraction method of VGG pretrained model to the feature retrieval of hand-drawn sketches of clothing style drawings. Select VGG's latest deep learning models VGG16 and VGG19 to conduct clothing style image retrieval experiments, and compare the retrieval performance of two different deep models. The experiment first uses the depth model to extract image features from the style map dataset and hand-drawn sketches. Secondly, the Euclidean distance is used to calculate the distance between the feature value of the retrieval sketch and the feature value of the image in the existing style atlas, and compare and match the most similar image. Finally, the image similarity is calculated, and the corresponding image is retrieved and output. The experimental results show that the retrieval effect of VGG19 is better than that of VGG16. The retrieval accuracy rate of VGG16 is 28%, and the return rate is 50%, while the retrieval accuracy rate of VGG19 can reach 43%, and the return rate can reach 70%.
Design of an Integrated Rectenna on Multi-layer High-Resistivity Silicon Substrate

This paper presents the design of a rectenna integrated on silicon, using a multilayer substrate composed of silicon and air. The rectenna is designed to harvest microwave energy at2.45 GHz. The substrate structure is composed of three layers of high-resistivity silicon (HRSi, $\varepsilon_{\mathrm{r}}=11.7$) where the central layer presents an air cavity obtained through etching process. The chosen feeding structure for the antenna is based on a planar microstrip feeding line while for the rectifier a planar matching network is adopted to allow the maximum power transfer. The adopted rectifier topology is a voltage doubler, consisting of a pair of Skyworks SMS7630-079LF Schottky diodes. The synthetized low-permittivity substrate is compatible with on-chip systems silicon and assure a 84 % radiation efficiency with a maximum gain of 7.76 dBi, for the patch antenna. The overall efficiency of the rectenna is 45% for a received power level of 7 dBm.
Fast Collision Detection Technology of Group Animation

Presents a collision detection algorithm which can quickly determine the location of primitives in group animation. The convex hull algorithm of space geometry is established by using the sphere mixture hulling technique based on spatial geometry model in complex scenes, and the sphere mixture reconstruction is transformed into line body mixture reconstruction to deal with non-convex process. The reality of virtual object is enhanced and the distortion of virtual object surface is avoided. The experimental results show that it has some advantages compared with the classical algorithm.
A Robust and Effective Control Method for the Cascaded Buck-Boost Converter Using a Single Controller

This paper proposes a simple but robust control method for the effective operation of the cascaded buck-boost converter using only one output voltage controller in combination with logic circuits. The converter has an input voltage range from 450V to 750V, providing an output voltage of 600V and up to 15A RMS output current. An analytical single-controller design approach shows stable and robust behavior throughout the whole input voltage range in both continuous conduction mode (CCM) and discontinuous conduction mode (DCM).
Infinite slope stability under steady unsaturated seepage conditions

We present a generalized framework for the stability of infinite slopes under steady unsaturated seepage conditions. The analytical framework allows the water table to be located at any depth below the ground surface and variation of soil suction and moisture content above the water table under steady infiltration conditions. The framework also explicitly considers the effect of weathering and porosity increase near the ground surface on changes in the friction angle of the soil. The factor of safety is conceptualized as a function of the depth within the vadose zone and can be reduced to the classical analytical solution for subaerial infinite slopes in the saturated zone. Slope stability analyses with hypothetical sandy and silty soils are conducted to illustrate the effectiveness of the framework. These analyses indicate that for hillslopes of both sandy and silty soils, failure can occur above the water table under steady infiltration conditions, which is consistent with some field observations that cannot be predicted by the classical infinite slope theory. A case study of shallow slope failures of sandy colluvium on steep coastal hillslopes near Seattle, Washington, is presented to examine the predictive utility of the proposed framework.
Sensorless State of Temperature Estimation for Smart Battery based on Electrochemical Impedance

Temperature plays a significant role in the safety, performance, and lifetime of lithium-ion batteries (LIBs). Therefore, monitoring battery temperature becomes one of the fundamental tasks for the safe and efficient operation of LIBs. Given the limited onboard temperature sensors, this paper proposes a sensorless temperature estimation method suitable for the smart battery system by obtaining the electrochemical impedance of batteries online via bypass actions. A suitable frequency is selected from the battery electrochemical impedance spectroscopy (EIS) to achieve an accurate and robust estimation of the battery temperature through online impedance measurement. Using the battery impedance with this selected frequency, the battery temperature can be estimated under different scenarios, with RMSE less than 1.5 ℃.