Miracle-dz/UniFAR-FTUs huggingface dataset:
Application in Tumor Classification Based on Target Morphological Consistency Patches Adaptively Extracted and Priori Guided Feature Extraction Method

PET/CT images have the characteristics of accurate location and high sensitivity for tumor lesions, so the classification on PET/CT images is of great significance in clinical practice. In terms of visual tasks such as image classification, models such as vision transformer based on attention mechanism has been proved to be effective. However, medical images are different from natural images, and only using image information as model input can not fully and effectively express target characteristics. In this paper, we propose a method of adaptive extraction of the patch to maintain the morphological characteristics of the target, and add the radiomics features to the attention mechanism as a priori guidance knowledge for feature extraction, which is applied to the classification of PET/CT tumors. Firstly, for the original PET/CT image, the patch sequence is obtained by the adaptive patch extraction method based on overlapping region and sliding stride, which adapts to the input of the model while maintaining the morphological characteristics of the target; Secondly, the corresponding image token and radiomics feature vector of patches are obtained through linear projection layer and radiomics feature extractor respectively; Finally, the two are input into the multi-head attention module of the encoder to build a multi-feature attention mechanism, and complete the classification decision after the feature extraction. To verify the effectiveness of this method, we conducted experiments on the whole-body public dataset FDG-PET-CT-Lesions, and classified PET/CT images into negative, melanoma, lymphoma and non-small cell lung cancer, and the classification accuracy reached 0.8652. The experimental results show that the proposed method has a high performance on tumor classification in PET/CT images, and can be applied to classification of various tumors.
Modification of Characteristics of Bragg Structure Based on Chebyshev Approach

Bragg-type layered dielectric structure, which provides the Chebyshev character of the behavior of the reflection frequency response, was considered. To obtain a fractional-rational representation of the structure frequency response, method of synthesis of the type I Chebyshev filter was used. An approach for mapping the entire equiripple domain of Chebyshev polynomial onto the specified reflectionless band and determining scale parameter are proposed. A modification of the periodic Bragg-type layered structure is demonstrated, which provides a reflection frequency response with minimum ripple level in the passband while preserving the location of the zeros that delimit the reflection band of the structure.
Integrated Metal Shunt with Matched Sensing Resistor for High-Side Current Sensing

This article describes the design and implementation of an integrated metal shunt resistor matched with a sense resistor for a wireless charging system. The goal of the work was to create a $ 5m\Omega$ shunt resistor coupled to a 1k$\Omega$ sense resistor with a constant ratio of 1/200k over process and temperature variations. The article explains the challenges in designing the shunt and sense resistor using only metal layers and how the metal resistors were implemented.
Identifying Abnormal Sessions via Adversarial Learning on Heterogeneous Information Network

Existing anomaly detection is mostly based on abnormal traffic and statistical analysis, but the structural information of the attacker’s network is also of great significance to anomaly detection. We convert the problem of identifying abnormal sessions in the network into a problem of link classification on a heterogeneous graph. However, the number of sessions in the real network is extremely large, forming a heterogeneous network with complex structural information, and it is difficult to extract its effective features. Therefore, we use the idea of Hin2Vec to extract features from heterogeneous graphs, and use the generative adversarial network (GAN) to improve. The negative samples is needed in the model training process of feature extraction. Through the traditional negative sampling method, the samples are often too trivial to effectively fit the model, and it is difficult to sample appropriate negative samples. Therefore, we use the generator of GAN to generate high-quality negative samples. On this basis, an anomaly detection model is constructed to identify abnormal sessions. We named our model HinDet. In this paper, heterogeneous graph embedding is applied to the field of anomaly detection. We have improved Hin2Vec and the negative sampling method. It solves the problems of difficult feature extraction and excessive noise of negative samples, and constructs an anomaly detection model to identify abnormal sessions. We experiment on two security domain datasets. Experimental results show that the use of GAN to generate negative samples can enhance the detection ability of the anomaly detection model. HinDet has good abnormal session recognition ability.
Molecular Involvement of Cannabinoid Receptors in the Regulation of Neurotransmitter Release in the Rodent Striatum : A Combined Immunochemical and Pharmacological Analysis

Attila Köfalvi,1,2 Ricardo J. Rodrigues,2 Catherine Ledent,3 Ken Mackie,4 E. Sylvester Vizi,1 Rodrigo A. Cunha,2 and Beáta Sperlágh1 1Laboratory of Molecular Pharmacology, Institute of Experimental Medicine, Hungarian Academy of Sciences, Budapest H-1450, Hungary, 2Center for Neuroscience of Coimbra, Institute of Biochemistry, Faculty of Medicine, University of Coimbra, 3004-504 Coimbra, Portugal, 3Institut de Recherche Interdisciplinaire en Biologie Humaine et Moléculaire, Université Libre de Bruxelles, Brussels B-1070, Belgium, and 4Department of Anesthesiology and Department of Physiology and Biophysics, University of Washington, Seattle, Washington 98195
A 0.4V 12b Comparator Offset Injection Assisted SAR ADC achieving 0.425 fJ/conv-step

A 12-bit hybrid SAR ADC with SAR search assisted by comparator offset injection is presented. The proposed ADC architecture reuses offset calibration circuitry for conversion of the last two LSBs, reducing the required capacitive DAC resolution and pushing its total capacitance down to its thermal noise limit. The proposed ADC can be calibrated without requiring any accurate input generation. The prototype ADC, fabricated in 40nm CMOS, occupying an active core area of 0.0315m$\mathrm{m}^{2}$, and operating at 0.35-0.45V for sampling rates ranging from 0.4 to 80 kS/s respectively, achieves the lowest Walden-FOM between 0.425-0.947fJ/conv-step, with an SNDR >64.7dB and SFDR>74.3dB.
On the reliability of spatially disaggregated global ensemble rainfall forecasts

Ensemble rainfall forecasts are of high interest for decision making, as they provide an explicit and dynamic assessment of the uncertainty in the forecast. However, for hydrological forecasting, their low resolution currently limits their use to large watersheds. To bridge this gap, various implementations of a spatial statistical downscaling method were compared, bringing Environment Canada's global ensemble rainfall forecasts from a 100 × 70‐km resolution down to 6 × 4‐km while increasing each pixel's rainfall variance and preserving its original mean. This was applied for nine consecutive days of summer 2009 with strong rain events over Quebec City, Canada. For comparison purposes, simpler methods were also implemented such as the bilinear interpolation, which disaggregates global forecasts without modifying their variance.
A 37-to-41.8 GHz Double-Gm-Boosting LNA with 2.9-dB NFmin Using Quadruple-Coupling Transformer for Phased-Array Transceivers

This paper presents a 37-to-41.8 GHz low-noise amplifier (LNA) with $\mathrm{d}\mathrm{o}\mathrm{u}\mathrm{b}\mathrm{l}\mathrm{e}-\mathrm{g}_{\mathrm{m}}$-boosting technique using quadruple-coupling transformer (QCT) to enhance performance in terms of noise figure (NF) and linearity while reducing power consumption and chip area. The proposed twostage LNA consists a common-gate (CG) single-end cascode input stage for high gain and a common-source (CS) crosscoupled differential amplifier as output stage to improve the overall linearity. The chip is fabricated in 65nm CMOS process, exhibiting a2.9 dB minimum NF, 19.3dB peak gain and 4.8 GHz bandwidth (BW) from 37 to 41.8 GHz. The LNA consumes only 6 mW with chip area of 0.11 $\mathrm{m}\mathrm{m}^{2}$. To the best knowledge of the authors, the work achieves the lowest $\mathrm{N}\mathrm{F}_{\min}$ among LNAs at similar frequency band in bulk CMOS technology so far.
A 128-channel neural stimulation and recording ASIC for scalable cortical visual prosthesis

Blindness affects millions of people around the world, being triggered by various defects within the human visual system. Different kinds of prostheses have been developed, which can stimulate the retina, the optical nerve or even the visual cortex, creating a basic form of vision. Here, we present a scalable ASIC and data-acquisition system that enables neural stimulation and recording in the visual cortex. The ASIC includes 128 area-efficient fully-programmable stimulators and 64 low-noise artifact-tolerant recording channels. The chip has been implemented in a 55nm CMOS technology, and our measurement results demonstrate its ability to stimulate and record simultaneously from the same electrode or from neighboring electrodes, which is important to enable the implementation of visual cortex prostheses.
Prediction of Regional Scenarios and Uncertainties for Defining EuropeaN Climate Change Risks and Effects -- PRUDENCE

Projections of future climate change already exist, but are deficient both in terms of the characterisation of their uncertainties and in terms of their regional detail. To date, the assessment of potential impacts of climate change has generally relied on projections from simple climate models or coarse resolution Atmospheric-Ocean General Circulation Models. Coarse resolution precludes the simulation of realistic extreme events and the detailed spatial structure of variables like temperature and precipitation over heterogeneous surfaces e.g. the Alps, the Mediterranean or Scandinavia. Simple models include, at best, a limited physical representation of the climate system. PRUDENCE is a new European-scale investigation funded by the European Commission with the following objectives: 1. to address and reduce the above-mentioned deficiencies in projections; 2. to quantify our confidence and the uncertainties in predictions of future climate and its impacts, using an array of climate models and impact models and expert judgement on their performance; 3. to interpret these results in relation to European policies for adapting to or mitigating climate change. Climate change is expected to affect the frequency and magnitude of extreme weather events, due to higher temperatures, an intensified hydrological cycle or more vigorous atmospheric motions. A major limitation in previous studies of extremes has been the lack of: appropriate computational resolution obscures or precludes analysis of the events; long-term climate model integrations drastically reduces their statistical significance; co-ordination between modelling groups limits the ability to compare different studies. These three issues are all thoroughly addressed in PRUDENCE, by using state-of-the-art high resolution climate models, by co-ordinating the project goals to address critical aspects of uncertainty, and by applying impact models and impact assessment methodologies to provide the link between the provision of climate information and its likely application to serve the needs of European society and economy. PRUDENCE will provide a series of high-resolution climate change scenarios for 2071-2100 for Europe, characterising the variability and level of confidence in these scenarios as a function of uncertainties in model formulation, natural/internal climate variability, and alternative scenarios of future atmospheric composition.
MetaLung: Towards a Secure Architecture for Lung Cancer Patient Care on the Metaverse

The interest in metaverse applications by existing industries has seen massive growth thanks to the accelerated pace of research in key technological fields and the shift towards virtual interactions fueled by the Covid-19 pandemic. One key industry that can benefit from the integration into the metaverse is healthcare. The potential to provide enhanced care for patients affected by multiple health issues, from standard afflictions to more specialized pathologies, is being explored through the fabrication of architectures that can support metaverse applications. In this paper, we focus on the persistent issues of lung cancer detection, monitoring, and treatment, to propose MetaLung, a privacy and integrity-preserving architecture on the metaverse. We discuss the use cases to enable remote patient-doctor interactions, patient constant monitoring, and remote care. By leveraging technologies such as digital twins, edge computing, explainable AI, IoT, and virtual/augmented reality, we propose how the system could provide better assistance to lung cancer patients and suggest individualized treatment plans to the doctors based on their information. In addition, we describe the current implementation state of the AI-based Decision Support System for treatment selection, I3LUNG, and the current state of patient data collection.
A 0.0106 mm2 8nW Resistor-Less BJT Bandgap Reference in 65nm

A Resistor-Less BJT based Bandgap Reference circuit is presented in 65nm achieving a power and area of SnW and 0.0106 $\mathrm{m}\mathrm{m}^{2}$ respectively. This is achieved by replacing the resistors in the current mode BGREF architecture with switched-capacitor based resistors which can reach GOhms of resistance to reduce power and area significantly. After a two-step trimming process, a measurement of 31 units yielded a mean temperature coefficient of Ill $\mathrm{p}\mathrm{p}\mathrm{m}/{}^{\circ}\mathrm{C}$, a PSRR of -38dB and the accuracy at $30{}^{\circ}\mathrm{C}$ is 0.59%.
A Chopped 6-bit 1.6 GS/s SAR ADC Utilizing Slow Decision Information in 22 nm FDSOI

Successive-approximation register (SAR) analog-to-digital converters (ADCs) have become ubiquitous in modern ADC systems due to their high power efficiency and excellent scalability. Single-loop, single-comparator (CMP) SAR ADCs struggle to achieve high conversion speeds due to loop delays and also impose a non-negligible load on their driving circuitry due to large capacitance of the capacitive digital-to-analog converter (CDAC). State of the art (SoA) solutions often require sacrificing CMP accuracy, power or area for speed and rarely achieve a sampling capacitance smaller than 1fF per quantization level. This work presents a chopped 6-bit asynchronous SAR (ASAR) ADC fabricated in 22nm FDSOI operating at 1.6GSps, which is achieved thanks to the use of slow decision information. With a total switched input capacitance of only 36.1fF(0.56fF/level) including parasitics, the ADC is a minimal load to its driver. The prototype consumes 1.89mW from a 850mV supply and achieves an SNDR of 35. 27dB near Nyquist, leading to a Walden FoM of 24.93 fJ/conv-step in an active area of only 724 $\mu \mathrm{m}^{2}$. Its suitability for use as a sub-ADC is verified in a 2x time-interleaved (TI) ADC.
To Improve Efficiency of Intrusion Detection System by Using Improved Multilayer Perceptron Algorithm

— In last few decades the use of internet has increased rapidly. Simultaneously the growing area of business, research, education has also increased use of computer network. Because of all these, it is necessary to keep computer network very safe and secure. For this purpose intrusion detection system are used, which task is to filter attacks, intrusions which occur in network. Intrusion detection system is a very popular tool to detect attacks. Intrusion Detection Systems monitor computer system to find out sign of security violations over network. When IDSs detects such sign triggers it has to report them to generate the alerts. These alerts tell the user about intruders. The alerts are presented to a human analyst then human analyst evaluates those alerts and initiates an adequate response. In Practice, IDS observe numbers of attacks per day. It also has to deal with different types of attacks. When IDS deals with network intrusions one of the important concerns is to generate true alarms, it means sometime it mistakenly generate an alarm for a legitimate user. Various soft computing techniques are used in Intrusion Detection System. A neural network Technique Multilayer Perceptron algorithm has gained importance in addressing network security issues, these works to classify and identify attacks in network. In this paper we proposed a technique called Improved Multilayer Perceptron which aims to identify attacks with a high detection rate, better time efficiency. We present Improved MLP Technique and compare with Traditional MLP Technique for intrusion detection. These techniques are applied to the KDD Cup99 data set . In addition; a Comparative analysis shows the advantage of Improved MLP Technique over Traditional MLP Technique over detection rate and time efficiency. Our main aim is to improving efficiency of network intrusion detection system by using improved Multilayer Perceptron Algorithm.
Empirical relations for the sediment transport capacity of interrill flow

Experiments were carried out in order to measure the sediment transport capacity of interrill flow with and without rainfall and to relate the transport capacity to selected hydraulic parameters, such as effective stream power and shear velocity. Different sediments were used in order to study the effect of grain size. The proposed relationships show considerable variations with grain size and there is only a minor effect of rainfall on the transport capacity which also seems to be grain size dependent. The proposed relationships can be used to predict sediment transport capacity of interrill flow and can therefore contribute to the development of physically based erosion models.
The vertical and horizontal distribution of CO2 densities in the upper mesosphere and lower thermosphere as measured by CRISTA

[1] The Cryogenic Infrared Spectrometers and Telescopes for the Atmosphere (CRISTA) experiment measured the global distribution of CO2 4.3 μm infrared emissions in the mesosphere and lower thermosphere during two Space Shuttle missions in November 1994 and August 1997. The daytime radiances have been inverted to CO2 number densities in the 60–130 km range by using a nonlocal thermodynamic equilibrium model. A detailed sensitivity study of retrieved CO2 number densities was carried out. The O(1D) excitation mechanism and model parameters constitute the most important uncertainties of retrieved CO2, typically 10–20%. The inaccuracy due to uncertainties in other atmospheric parameters is usually less than 10%. The CO2 volume mixing ratio (VMR) deviates from being well mixed between 70 and 80 km, which is significantly lower than indicated by previous rocket-borne mass spectrometer data and model calculations but is in good agreement with the data obtained by other 4.3 μm emission and absorption experiments. The global distribution of CRISTA-2 CO2 density shows significant longitudinal and latitudinal structures. The zonal mean CO2 densities are increasing toward polar summer latitudes below 90 km and above 115 km. Between 90 and 115 km, the latitudinal gradient is reversed. At 100 km, the gradient is mostly pronounced, reaching up to 50% difference between low and high latitudes. These variations are compared with results obtained by the Thermosphere/Ionosphere/Mesosphere Electrodynamics General Circulation Model (TIME-GCM), showing very good agreement for the latitudinal distribution. Below 110 km, this variation is mostly due to the change in total density rather than to the CO2 VMR.
Weak Solvability Theorem for Forward-Backward SDEs

We aim to establish the existence and uniqueness of weak solutions to a suitable class of non-degenerate deterministic FBSDEs with a one-dimensional backward component. The classical Lipschitz framework is partially weakened: the di(cid:11)usion matrix and the (cid:12)nal condition are assumed to be space H(cid:127)older continuous whereas the drift and the backward driver may be discontinuous in x . The growth of the backward driver is allowed to be at most quadratic with respect to the gradient term. The strategy holds in three di(cid:11)erent steps. We (cid:12)rst build a well controlled solution to the associated PDE and as a bypass product a weak solution to the forward-backward system. We then adapt the \decoupling strategy" introduced in the four step scheme of Ma, Protter and Yong [30] to prove uniqueness.
GIB: Imperfect Information in a Computationally Challenging Game

This paper investigates the problems arising in the construction of a program to play the game of contract bridge. These problems include both the difficulty of solving the game's perfect information variant, and techniques needed to address the fact that bridge is not, in fact, a perfect information game. GIB, the program being described, involves five separate technical advances: partition search, the practical application of Monte Carlo techniques to realistic problems, a focus on achievable sets to solve problems inherent in the Monte Carlo approach, an extension of alpha-beta pruning from total orders to arbitrary distributive lattices, and the use of squeaky wheel optimization to find approximately optimal solutions to cardplay problems. GIB is currently believed to be of approximately expert caliber, and is currently the strongest computer bridge program in the world.
Calculation of reflection and transmission coefficients for qP waves incident on a planar interface between isotropic and triclinic media

In the paper by Chattopadhyay and Rajneesh (2006, “Reflection and refraction of waves at the interface of an isotropic medium over a highly anisotropic medium’, Acta Geophysica, vol. 54, no. 3, pp. 239–249), the authors proposed a process to calculate R/T (reflection and transmission) coefficients at the interface between isotropic and triclinic half-spaces, with incident qP waves in triclinic media. Unfortunately, besides several misprints, the authors made a fatal assumption that there is no transmitted SH wave generated in isotropic media, which led the successive analytical derivations and numerical calculations thoroughly wrong. In this paper, the errors are analyzed at length and corrections are given. Then an alternative approach to solve the problem is proposed and numerical results are shown and discussed.