Miracle-dz/UniFAR-FTUs huggingface dataset:
A 28–34-GHz Stacked-FET Power Amplifier in 28-nm FD-SOI With Adaptive Back-Gate Control for Improving Linearity

Adaptive back-gate control of a stacked-FET power amplifier (PA) in 28-nm fully depleted silicon-on-insulator (FD-SOI) CMOS is demonstrated for the 64-QAM signal at 28 and 31 GHz. Adaptive bias control (ABC) is applied to the back gate to effectively enhance the linearity of PAs for wideband waveforms with up to an 800-MHz envelope frequency. Third-order intermodulation distortion (IMD3), which degrades the linearity of a PA, is improved by adjusting back-gate biases of the stacked-FET PA according to the input power level without any concerns about wideband operation. From 28 to 34 GHz, the presented PA provides <inline-formula> <tex-math notation="LaTeX">$\text{P}_{\mathrm{ 1dB}}$ </tex-math></inline-formula> and PAE<sub>P1dB</sub> of >16.4-dBm and >37.3%, respectively. At 28 and 31 GHz, the measured <inline-formula> <tex-math notation="LaTeX">$\text{P}_{\mathrm{ 1dB}}$ </tex-math></inline-formula> and PAE<sub>P1dB</sub> are 17.4 and 16.9 dBm, 37.7% and 38.8%, respectively, with a compact core area of 0.088 mm<sup>2</sup>. The rms EVM improvement due to the linearity enhancement with the adaptive back-gate control is experimentally demonstrated to be around 2.6 and 1.8 dB for 8.65-dB PAPR single-carrier 64QAM signals with 8-dB back-off at 28 and 31 GHz, respectively.
The Origin of Pressure Waves in High Load HCCI Combustion: A High-Speed Video Analysis

Homogeneous charge compression ignition is an alternative combustion strategy for spark-ignited gasoline engines that improves engine efficiency and thus reduces CO2 emissions, which is crucial to meet targets set by legislation. However, this combustion strategy is limited to low loads, mainly due to pressure oscillations that arise if combustion is too rapid. The aim of the work described in this article was to record and identify these pressure oscillations and correlate them with the preceding combustion. This was performed using an image-intensified high-speed video camera with a sampling rate of 111 kHz filming inside the combustion chamber of an engine with optical access through a quartz piston. A strategy is described whereby video analysis is used to extract the acoustic modes resulting from combustion. In this work it was possible to detect four different acoustic modes. It is shown that the type and magnitude of these modes can be correlated to the size and position of combustion chamber zones with rapid combustion and the light intensity development (combustion speed) in these zones. It is also shown that the highest combustion rates occur in regions where combustion starts late.
Chemistry, mineralogy and radioactivity in posidonia oceanica meadows from North-Western Sicily

This paper presents measurements of major, minor, metal trace elements and radionuclides in sediments and in Posidonia oceanica samples from north-western Sicily (Italy). The mineralogical and chemical composition of sediments were determined by X-ray diffraction and X-ray fluorescence techniques, respectively. A flame atomic absorption spectrophotometry was used to measure concentrations of Cu, Zn, Cd and Pb in P. oceanica samples and in sediments. Specific activities of selected radionuclides have been determined by high-resolution gamma spectrometry. Standard statistical analysis was used to assess correlations between different elements and different sample types.
Electronic Excitations in Some Transition Metals and Their Oxides. Characteristic Energy Loss Measurements up to 50 eV

The characteristic energy losses suffered by a 20 keV electron beam through thin films of some transition metals (Sc, Y, Zr, Hf) and of their oxides are measured using a magnetic spectrograph up to 50 eV. The energy loss function — Im 1/e and the complex dielectric constant are calculated. It is shown that the electron excitation spectra of metals contain two main contributions in this energy range: one due to collective excitations of the conduction electrons, the other to the excitation of inner p-electrons. In the case of oxides the spectra display three strong structures: there are probably two collective excitations of valence electrons followed by the excitation of inner p-electrons of the metal. Les pertes caracteristiques d'energie subies par un faisceau d'electrons de 20 keV a la traversee de films minces de quelques metaux de transitions places en debut de serie (Sc, Y, Zr, Hf) et de leurs oxydes ont ete mesurees avec un spectrographe magnetique jusqu'a 50 eV. La fonction —Im 1/e et la constante dielectrique complexe sont calculees. On montre que le spectre des excitations electroniques des metaux contient deux contributions principales dans le domaine d'energie considere: l'une due a l'excitation collective du gaz d'electrons de conduction, l'autre a l'excitation des electrons p. Dans le cas des oxydes, les spectres mettent en evidence trois structures importantes: deux excitations collectives des electrons de valence et l'excitation des electrons p du metal.
Molybdenum–tin and molybdenum–copper complexes derived from the molybdenum tricarbonyl anions, LMo(CO)3− (where L = HBpz3 or HBpz″3; pz = pyrazolyl, N2C3H3; and pz″ = 3,5-dimethylpyrazolyl, N2C5H7)

The pyrazolylborate molybdenum tricarbonyl anions, (HBpz3)Mo(CO)3− and (HBpz″3)Mo(CO)3−, have been utilized to prepare a number of heteronuclear bimetallic species containing Mo—Sn and Mo—Cu bonds.
Channel Estimation and Robust Detection for IQ Imbalanced Uplink Massive MIMO-OFDM With Adjustable Phase Shift Pilots

In this paper, we investigate channel estimation and robust detection for uplink massive multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems with in-phase and quadrature-phase imbalances (IQI). We represent the received signal with a real-valued model, where the combination of the IQI and the wireless channel is treated as the effective channel. Based on the real-valued model, we then perform the minimum mean square error (MMSE) criterion based estimation for the effective channel. We use adjustable phase shift pilots (APSPs) to reduce the pilot overhead and verify that the MSE of the effective channel estimation can be minimized by scheduling the pilot phase shifts properly. We propose a pilot phase shift scheduling algorithm based on the covariance matrices of the effective channels. Since the channel estimation performance might be degraded due to using APSPs, we develop an MMSE criterion based data detection scheme which is robust to the channel estimation error. Using operator-valued free probability theory, we derive an asymptotic deterministic equivalent for the ergodic achievable sum rate of the proposed detection scheme. The performance of the channel estimation with APSPs and the robust data detection is demonstrated via extensive numerical results.
Non-Destructive Label-Free Biomaterials Detection Using Tunneling Carbon Nanotube-Based Biosensor

Label-free monitoring of biomaterials has become spotlight topic for the advanced nano-biosensing fields. In this regard, a non-destructive doping-less tunneling carbon nanotube field effect transistor (DL-TCNTFET) -based biosensor using the charge plasma concept is introduced. In doping-less structures, source and drain are created using the concept of charge plasma and by selecting appropriate work function of source and drain metals. The sensitivity of DL-TCNTFET is investigated in terms of dielectric constant variations at different bias conditions. The simulation is carried out in the ballistic regime by simultaneously solving the Poisson and Schrodinger equations in a self-consistent way using the non-equilibrium Green’s function in the form of state space approach. Simulations show that the DL-TCNTFET has better ambipolar behavior and also lower OFF current by reducing the dielectric constant of biomolecules. In addition, the ON current and biosensor sensitivity are significantly improved by increasing the dielectric constant.
Branch Profiles for Shape Analysis

Ahstract- The necessity for characterising highly irregularly shaped objects appears in many circumstances, most prominently in biology and medicine, but also in physical sciences and elsewhere. Here, a multi-scale method for quantifying the level of branching in irregular structures is presented to extend the repertoire descriptors of shape. The method was used to classify strains of yeast colonies and to demonstrate differences in structure of newly formed cancellous bone in rats under various experimental conditions. Yeast colonies were classified with an accuracy of 1.000 (n = 10) and classification of newly formed cancellous bone into three classes achieved mean accuracy of 0.853 ±. 088 over 10 runs with data randomly sampled from the same 15 rats each run.
Effects of Wastewater Irrigation on Physicochemical Properties of Soil and Availability of Heavy Metals in Soil and Vegetables

The present study investigated the impact of irrigation with wastewater on nutritional property and heavy‐metal concentrations in the soil and consequent accumulation in vegetables at sites having long‐term uses of wastewater for irrigation. Samples of irrigation water, soil, and root and shoot parts of palak plants were analyzed to determine the concentration of heavy metals. Wastewater irrigation led to increases in the total and phytoavailable heavy‐metal concentrations in the soil at all the sites. Heavy‐metal concentrations in soil under wastewater irrigation were negatively and positively correlated with soil hydrogen potential (pH) and organic carbon (OC), respectively. The enrichment factor and metal pollution index were higher at wastewater‐irrigated sites as compared to the clean water–irrigated ones. The study concludes that wastewater irrigation modified the physicochemical properties of the soil, leading to more availability of heavy metals in the soil and consequently to the plant.
A Highly Digital 2210μm2 Resistor-Based Temperature Sensor with a 1-Point Trimmed Inaccuracy of ± 1.3 ° C (3 σ) from -55 ° C to 125 ° C in 65nm CMOS

Microprocessors and SoCs employ multiple temperature sensors to prevent overheating and ensure reliable operation. Such sensors should be small (<10,000μm2) to monitor local hot-spots in dense layouts. They should also be moderately accurate (~1°C) up to high temperatures (≥125°C), so that the system throttling temperature can be set as close as possible to the maximum allowable die temperature. Furthermore, they should be fast (~1kS/s) and consume low power (tens of μW).
An Experimental Design and Data Collection of EEG during Kriya Yoga-An Ancient Indic Meditation Technique

The prime objective of the study is to investigate the effect (effects in the sense of an increase in psychological well-being and decrease in stress & mood disturbances) of specific relaxation technique popularly named as Kriya Yoga (KY) meditation on long-term and short-term practitioners. For comparison, the EEG data for non-meditators or control group has also been recorded. To the best of our knowledge, no such standard EEG datasets are available elsewhere on Kriya practitioners. In this study, two experimental datasets created by us, have been described. The experiments have been carried out at two places, i.e., Hariharananda Gurukulam, Balighai, Puri, Odisha and Hariharananda Balashram, Arua, Kendrapara, India. The detailed protocol and experimental methodology are described. This paper briefly introduces two EEG databases acquired during short Kriya Yoga meditation.
An Asynchronous Game-based algorithm to the Weighted Vertex Cover of Networks

Minimum weighted vertex cover (MWVC) problem of weighted networks is one of the most important combinatorial optimization problems in network optimization. This paper models the MWVC problem as an asymmetric game on weighted networks. Then, an asynchronous game-based algorithm (AGB) is proposed to solve the MWVC problem, which can guarantee to obtain a vertex cover (VC). Numerical illustrations verify the performance of the proposed game solution on the representative weighted networks.
A Perturbed Hard-Sphere-Chain Equation of State for Normal Fluids and Polymers

A perturbed hard-sphere-chain (PHSC) equation of state is presented which uses the modified Chiew equation of state for hard-sphere chains as the reference term, a van der Waals type perturbation term, and the Song-Mason method to relate equation-of-state parameters to the intermolecular potential. The PHSC equation requires three parameters to describe a pure fluid: the number of effective hard spheres per molecule, the segmental diameter, and the intermolecular potential-well depth between a nonbonded pair of segments. The PHSC equation reproduces the thermodynamic properties of a wide variety of normal fluids including polymers. Regressed parameters are related to characteristic molecular properties calculated from group contributions based on chemical structure.
Comparison of Passive Damping based LCL Filter Design Methods for Grid-connected Voltage Source Converters

Distributed generators are typically interfaced to the grid via power electronic converters that are usually operated in pulse width modulation mode. This results in undesirable higher-order harmonics in currents and voltages that deteriorate the power quality. In order to mitigate these harmonics, a filter is usually connected at the output of the converter before it is interfaced to the grid. The most commonly adopted filter is the LCL filter. This paper analyses the performance of different methods proposed in the literature to design passive LCL filters for a 3− ϕ grid-connected voltage source converter. Various filter design techniques are tested for their compliance with the standards IEEE 519-2014 and IEEE 1547-2018. Further, comparison is carried out in terms of essential system metrics such as reactive power requirement, power factor, and the voltage drop across the filter. The performance of various filter design approaches is analyzed using simulation studies on different distributed generator configurations.
Preparation of ultraviolet‐cured bisphenol A epoxy diacrylate/montmorillonite nanocomposites with a bifunctional, reactive, organically modified montmorillonite as the only initiator via in situ polymerization

A bifunctional reactive surfactant containing a polymerizable methacrylate group and a benzophenone group, [2-(methacryloyloxy)ethyl](4-benzoylbenzyl)dimethylammonium bromide (MDAB), was synthesized to modify montmorillonite (MMT) for the preparation of nanocomposites via photoinduced polymerization. Fourier transform infrared, thermogravimetric analysis, and X-ray diffraction results indicated that MDAB-modified MMT was obtained and had intercalated structures. The morphology of the ultraviolet-cured bisphenol A epoxy diacrylate/MMT nanocomposites prepared from the organically modified MMTs was studied with X-ray diffraction and transmission electron microscopy, and the results showed an intercalated structure with partial exfoliation for all the samples. Experimental results from thermogravimetric analysis, differential scanning calorimetry, and mechanical property testing also indicated that the thermal and mechanical properties of the ultraviolet-cured nanocomposites were significantly enhanced by the presence of this bifunctional, reactive, organically modified MMT. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2009
A Spatio-Temporal Co-Clustering Framework for Discovering Mobility Patterns: A Study of Manhattan Taxi Data

Research on clustering spatio-temporal data to extract mobility patterns requires further development, as most existing studies do not simultaneously integrate data along both spatial dimensions and temporal dimensions but instead focus on only one dimension or separate the dimensions in analyses and applications, which could lead to discoveries that are not representative of the overall data or are dificult to interpret. To simultaneously reveal the spatial and temporal patterns of urban mobility datasets, we propose an analytical framework that is based on co-clustering and enables mobility behaviors to be distinguished in spatial and temporal dimensions. We use one month of taxi GPS data from the Manhattan area to explore spatio-temporal co-occurrence patterns. The spatial and temporal dimensions of taxi trip data were co-clustered by using the Bregman Block Average co-clustering algorithm with I-divergence (BBAC_I). We performed this process on weekdays and holidays and compared the mobility differences between these two periods. The experimental results demonstrated the effectiveness of this analytical framework, with which we can reveal the spatial patterns and their temporal dynamics as well as temporal patterns and their spatial dynamics in mobility data.
CAPABILITY PATERNALISM

A capability approach prescribes paternalist government actions to the extent that it requires the promotion of specific functionings, instead of the corresponding capabilities. Capability theorists have argued that their theories do not have much of these paternalist implications, since promoting capabilities will be the rule, promoting functionings the exception. This paper critically surveys that claim. From a close investigation of Nussbaum's statements about these exceptions, it derives a framework of five categories of functionings promotion that are more or less unavoidable in a capability theory. It argues that some of these categories may have an expansionary dynamic; they may give rise to widespread functionings promotion, which would defeat the capabilitarian promise that paternalist interventions will be exceptions to the rule of a focus on capabilities. Finally, the paper discusses three further theoretical issues that will be decisive in holding this paternalist tendency in check: how high one sets threshold levels of capability protection, how lengthy one's list of basic capabilities is, and how one deals with individual responsibility for choices resulting in a loss of one's capabilities.
Applications of Reinforcement Learning to Image Enhancement: A Survey

In recent years, we have seen rapid development in Reinforcement Learning. Reinforcement learning, combined with deep learning has proven to be a powerful tool that has been able to make substantial breakthroughs in many complex decision-making systems. Popular examples include Google’s AlphaGo and its successor AlphaZero. In this paper, we take a look at some reinforcement learning techniques and major advancements made in the application of reinforcement learning to image enhancement tasks such as denoising, color enhancement and image restoration. We also present comparisons between existing deep learning techniques and reinforcement learning.
Image-Based Force Estimation in Medical Applications: A Review

Minimally invasive robotic interventions have highlighted the need to develop efficient techniques to measure forces applied to the soft tissues. Since the last decade, many scholars have focused on micro-scale and macro-scale robotic manipulations. Early articles used the model of soft tissue mathematically and tracked the displacement of the contour of the object in the vision system to provide the corresponding force to the user. Lack of knowledge of different materials and the computational complexity led to a transition from model-based to learning-based approaches to interpret the relation between object deformations, extracted from the vision system, and the real forces applied to the object. The dramatic growth of machine learning techniques and its integration with computer vision has brought novel learning-based visual data processing methods to the area. The application of the image-based force estimation methods in a controlled medical intervention has also received significant attention in the last five years. A decent number of surveys have been published on micromanipulation in recent years, especially for cell microinjection. However, the state of the art in meso- and macro-scale medical robotic interventions has not been reviewed. The aim and contribution of this paper are to fill the stated gap by reviewing the recent advances in image-based force estimation in robotic interventions. The survey shows that learning-based force estimation methods are growing significantly by using deep learning-based methods. The survey will encourage researchers and surgeons to apply learning-based algorithms to real-time medical and health-related operations.
Near-Field Single-Frequency Millimeter-Wave 3-D Imaging via Multifocus Image Fusion

The wideband radar system is usually exploited to obtain the 3-D image of the target under test. However, the wide bandwidth increases the system complexity and cost. Emerging techniques, such as the reconfigurable reflectarrays, reconstruct a near 3-D image via using single-frequency millimeter-wave (MMW) and near-field focusing of the beam, which greatly simplifies the system design, whereas the near-field focusing can only achieve a poor range resolution and a limited depth of focus. In this letter, we propose a multifocus image fusion method based on the criterion of minimum entropy, which can further be utilized for any kind of the MMW imaging system working at a single frequency. Simulations and experiments are presented to verify the effectiveness of the proposed method.
The Fibroblast Growth Factor Receptor Is at the Site of Convergence between μ-Opioid Receptor and Growth Factor Signaling Pathways in Rat C6 Glioma Cells

Mitogenic signaling of G protein-coupled receptors (GPCRs) can proceed via sequential epidermal growth factor receptor (EGFR) transactivation and extracellular signal-regulated kinase (ERK) phosphorylation. Although the μ-opioid receptor (MOR) mediates stimulation of ERK via EGFR transactivation in human embryonic kidney 293 cells, the mechanism of acute MOR signaling to ERK has not been characterized in rat C6 glioma cells that seem to contain little EGFR. Herein, we describe experiments that implicate fibroblast growth factor (FGF) receptor (FGFR) transactivation in the convergence of MOR and growth factor signaling pathways in C6 cells. MOR agonists, endomorphin-1 and morphine, induced a rapid (3-min) increase of ERK phosphorylation that was abolished by MOR antagonistd-Phe-Cys-Tyr-d-Trp-Arg-Thr-Pen-Thr-NH2. By using selective inhibitors and overexpression of dominant negative mutants, data were obtained to suggest that MOR signaling to ERK is transduced by Gβγ and entails Ca2+- and protein kinase C-mediated steps, whereas the FGFR branch of the pathway is Ras-dependent. An intermediary role of FGFR1 transactivation was suggested by MOR- but not κ-opioid receptor (KOR)-induced FGFR1 tyrosine phosphorylation. A dominant negative mutant of FGFR1 attenuated MOR- but not KOR-induced ERK phosphorylation. Thus, a novel transactivation mechanism entailing secreted endogenous FGF may link the GPCR and growth factor pathways involved in MOR activation of ERK in C6 cells.