Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and analysis of 0.9 and 2.3‐GHz concurrent dual‐band CMOS LNA for mobile communication

A complementary metal‐oxide‐semiconductor (CMOS) dual‐band low‐noise amplifier (LNA) for 2G/3G/4G mobile communications is presented. It operates at 0.9 and 2.3 GHz of frequencies. The dual‐band operation is achieved by adding a modified notch‐filtering path in the wideband LNA. The modified notch‐filtering path does not require additional power to cancel the signals of the stop band frequency. The impact of the filtering path in the proposed LNA is analyzed. Improved results are observed in dual bands of frequency. Sustainability of the LNA under process corner variation and temperature variation are examined, and it is found to be suitable for the application. The proposed LNA is designed at 90‐nm technology in Cadence Virtuoso with 0.5 and 0.6‐V supply. The post‐layout simulation shows 22 dB of gain (S21), 2 dB of Noise Figure (NF), and −5.5 dBm of IIP3 at the high band. In the low band, 24 dB of S21, 2.7 dB of NF, and −6.65 dBm of IIP3 are reached. The circuit consumes 5.2 mW of power and 0.0918 mm2 of area. The efficiency of the LNA is estimated by the figure of merit, and comparable results are secured in the proposed work.
Design of Collectors for High Average/Continuous-Wave Power Gyro-Devices

In this paper, techniques to improve the collector’s dissipated power density threshold are discussed first. Then, theories of electron collection are presented, aiming at improving the effective electron-collecting area and collecting uniformity. Specifically, the layered electron beam collection in linear-taper collector, respectively, with constant and gradually varying magnetic field is modeled and discussed. Results indicate that a quasi-rectangular shape collection can be realized as the tangential collection dominates. Finally, the using of a compensation coil is analyzed and the corresponding collector is designed.
A Coherent Homodyne TO-Can Transceiver as Simple as an EML

The introduction of low-cost coherent signal reception is one of the great challenges in optical telecommunications since its opto-electronic sub-systems are associated with a high degree of complexity. In this work, we propose a disruptive approach: the re-use of widely deployed direct-detection technology for simultaneous coherent homodyne reception and transmission. We first show that an externally modulated laser (EML) is sufficient to perform both, coherent reception and transmission functionality. Second, we prove that homodyne detection applies to the EML-based scheme in virtue of an injection-locked local oscillator, which for low input power levels is pulled to the optical carrier frequency of the incident data signal. The proposed methodology for coherent reception enables a greatly simplified transceiver as optical layer hardware. As we will demonstrate, it just requires single fiber access, a single radio frequency port, and can be implemented in a transistor-outline package. Full-duplex transmission with coherent homodyne reception is experimentally validated, showing 2.5 Gb/s transmission over 27.5 km reach and a loss budget of 28 dB, and coherent Gigabit Ethernet connectivity—without the use of optical layer digital signal processing functions.
Software 2.0 for Scrap Metal Classification

Software 2.0 and its approach to the processing of multi-spectral images helping to perform an automatic classification of metal scrap is the subject of this research. The use of Machine Learning and Deep Learning tools contribute to the development of intelligent systems, allowing to achieve relevant results in the classification of images, particularly of metal scrap. In this research, tests will be performed with a multi-spectral chamber to obtain images of aluminum, iron, copper, brass, stainless steel, simulating an environment of metal scrap. The aim is to obtain the classification of these metals through the development of software and to perform a multi-spectral analysis of the obtained images. Preliminary tests were made in a controlled environment, with a small sample of these materials. Studies to implement a prototype in a Brazilian steel industry will follow.
Analysis Framework of RSA Algorithms in Elastic Optical Rings

With flexibility in optical layer, elastic optical network (EON) has been considered as a competitive candidate to architect next-generation backbone networks. Routing and spectrum assignment (RSA) is a key problem for the service provisioning in EONs. The RSA problem is $\mathcal {NP}$-hard even in elastic optical rings. Numerous heuristics have been proposed, and they can generally be categorized into two types: Route-First (RF) and Spectrum-First (SF). Although most previous work demonstrated by numerical simulations that the SF algorithms always outperform the RF ones, there is a lack of theoretical analysis on the reasons causing the performance difference between the two types of RSA algorithms. In this paper, we aim at proposing a unified theoretical framework for the performance analysis of RSA algorithms by leveraging conflict graphs, which offers a new perception on the optimality of RSA algorithms. To validate the proposed framework, we apply it in elastic optical rings (with cycle topology), and theoretically analyze the number of edges of the conflict graphs for RF and SF algorithms. Different from the literature, we obtain an interesting observation that neither the RF nor the SF can surpass the other in elastic optical rings under different traffic distributions, and their performances have a strong correlation to the edge count of their conflict graph. This observation provides a new perspective, i.e., conflict graph, to explore the property of RSA algorithms.
A Novel Greedy Algorithm for Joint Sparse Recovery Through Information Transfer

In multiple measurement vectors (MMV) problems, L measurement vectors of length M are available for recovering jointly sparse signals that have a common support set of size K. This paper proposes a novel greedy algorithm for joint sparse recovery in MMV problems, by exploiting a posteriori probability ratios for every index of sparse input signals. The essence of the algorithm is to transfer the information through iterations, which improves the recovery performance of support indices. Simulation results demonstrate that if M is not too small in K < M regime, the proposed algorithm can be more reliable and noise-robust than conventional ones, such as simultaneous orthogonal matching pursuit (SOMP), subspace augmented MUSIC (SA-MUSIC), and rank-aware order recursive matching pursuit (RA-ORMP).
Leader-Following Output Consensus for High-Order Nonlinear Multiagent Systems

This technical note focuses on the leader-following output consensus problem for a class of high-order nonlinear multiagent systems under a fixed directed graph. To obtain the global result of output feedback control for the system with the less conservative condition on nonlinear terms than traditional Lipschitz one, the novel reduced-order dynamic compensator is constructed. By introducing an appropriate state transformation, a new fully distributed output feedback control method is proposed, which greatly simplifies the design procedure compared with the backstepping method. The distributed linear-like controller with a dynamic gain is designed for each agent based only on the relative output measurements of neighboring agents. The condition that the orders of all agents should be the same is not needed anymore with the proposed method; thus, the novel result will have extensive applications. Finally, the theoretical results are supported by a numerical simulation.
Joint Household Characteristic Prediction via Smart Meter Data

Predicting specific household characteristics (e.g., age of person, household income, cooking style, etc.) from their everyday electricity consumption (i.e., smart meter data) enables energy provider to develop many intelligent business applications or help consumers to reduce their energy consumption. However, most existing works intend to predict single household characteristic via smart meter data independently, and ignore the joint analysis of different characteristics. In this paper, we consider each characteristic as an independent task and intend to predict multiple household characteristics simultaneously by designing a new multi-task learning formulation: discriminative multi-task relationship learning (DisMTRL). Specifically, two main challenges need to be handled: 1) task relationship, that is the embedded structure of relationships among different characteristics and 2) feature learning, there exist redundant features in original training data. To achieve these, our DisMTRL model aims to obtain a simple but robust weight matrix through capturing the intrinsic relatedness among different characteristics by task covariance matrix (MTRL) and incorporating the discriminative features via feature covariance matrix (Dis). For model optimization, we employ an alternating minimization strategy to learn the optimal weight matrix as well as the relationship between tasks by converting feature learning regularization as trace minimization problem. For evaluation, we adopt a smart meter dataset collected from 4232 households in Ireland at a 30 min granularity over an interval of 1.5 years. The experimental results justify the effectiveness of our proposed model.
On Network Systems Design: Pushing the Performance Envelope via FPGA Prototyping

Performance studies of computer network systems traditionally relied on mathematical modelling. Then, to deal with the increasingly complex systems in a meaningful manner, simulation and emulation tools have been developed to circumvent the intractability or the oversimplification that comes with mathematical methods. However, such emulation methods still make many simplifying assumptions as they are incapable of capturing the real system in its totality. Recently, Field Programmable Gate Array (FPGA) based prototyping systems have become an affordable option for researchers as an easy and quick tool for network system prototyping. In this paper, we motivate system prototyping based research via FPGA in conducting research experiments as well as facilitating new system designs where some traditional software functions are offloaded to the FPGA. We present a new switch prototype and preliminary results from its deployment in a real testbed.
Experimental Comparison of Visual-Aided Odometry Methods for Rail Vehicles

Today, rail vehicle localization is based on infrastructure-side Balises (beacons) together with on-board odometry to determine whether a rail segment is occupied. Such a coarse locking leads to a sub-optimal usage of the rail networks. New railway standards propose the use of moving blocks centred around the rail vehicles to increase the capacity of the network. However, this approach requires accurate and robust position and velocity estimation of all vehicles. In this work, we investigate the applicability, challenges, and limitations of current visual and visual-inertial motion estimation frameworks for rail applications. An evaluation against real time kinematic-global position system ground truth is performed on multiple datasets recorded in industrial, sub-urban, and forest environments. Our results show that stereo visual-inertial odometry has a great potential to provide a precise motion estimation because of its complementing sensor modalities and shows superior performance in challenging situations compared to other frameworks.
An Online Power System Stability Monitoring System Using Convolutional Neural Networks

A continuous Online Monitoring System (OMS) for power system stability based on Phasor Measurements (PMU measurements) at all the generator buses is proposed in this paper. Unlike the state-of-the-art methods, the proposed OMS does not require information about fault clearance. This paper proposes a convolutional neural network, whose input is the heatmap representation of the measurements, for instability prediction. Through extensive simulations on standard IEEE 118-bus and IEEE 145-bus systems, the effectiveness of the proposed OMS is demonstrated under varying loading conditions, fault scenarios, topology changes, and generator parameter variations. Two different methods are also proposed to identify the set of critical generators that are most impacted in the unstable cases.
Versal: The Xilinx Adaptive Compute Acceleration Platform (ACAP)

In this presentation I will present the new Adaptive Compute Acceleration Platform. I will show the overall system architecture of the family of devices including the Arm cores (scalar engines), the programmable logic (Adaptable Engines) and the new vector processor cores (AI engines). I will focus on the new AI engines in more detail and show the architecture, the integration in the total device, the programming environment and some applications, including Machine Learning and 5G wireless applications.
Trimetazidine Attenuates Exhaustive Exercise-Induced Myocardial Injury in Rats via Regulation of the Nrf2/NF-κB Signaling Pathway

Exhausted exercise has been reported to cause the damage of myocardial structure and function in terms of cardiomyocyte apoptosis, oxidative stress, and energy metabolism disturbance. Trimetazidine (TMZ), as an anti-ischemic agent, has been approved to be effective in promoting myocardial energy metabolism, anti-inflammatory, and anti-oxidation. However, few studies examined the effects of TMZ on myocardial injury induced by exhausted exercise. To investigate whether TMZ could ameliorate the exhaustive exercise-induced myocardial injury and explore the underlying mechanisms, here the rat model of exhaustive exercise was induced by prolonged swimming exercise and TMZ was administrated to rats before exhaustive exercise. According to the results, we demonstrated that exhaustive exercise led to cardiomyocyte damage in rats as evidenced by elevations in cTnI and NT-proBNP levels, and decrease in CX43 expression, which was attenuated by TMZ treatment. Moreover, the administration of TMZ was found to restrain exhaustive exercise-induced oxidative stress damage by increasing GSH level, SOD and GSH-Px activities, and decreasing MDA level. Additionally, TMZ ameliorated myocardial injury by inhibiting apoptosis via reducing Bax/Bcl-2 ratio and down-regulating cleaved caspase-3, cleaved PARP, and cytochrome c levels in the myocardium of rats. Furthermore, we found that TMZ suppressed oxidative stress and cardiomyocyte apoptosis via activation of Nrf2/HO-1 and inactivation of NF-κB signaling pathways. Therefore, our study suggested that TMZ provided cardioprotection in rats after exhaustive exercise, indicating TMZ might served as a potential therapeutic drug for exhaustive exercise-induced myocardial injury.
Does Gender Leave an Epigenetic Imprint on the Brain?

The words “sex” and “gender” are often used interchangeably in common usage. In fact, the Merriam-Webster dictionary offers “sex” as the definition of gender. The authors of this review are neuroscientists, and the words “sex” and “gender” mean very different things to us: sex is based on biological factors such as sex chromosomes and gonads, whereas gender has a social component and involves differential expectations or treatment by conspecifics, based on an individual’s perceived sex. While we are accustomed to thinking about “sex” and differences between males and females in epigenetic marks in the brain, we are much less used to thinking about the biological implications of gender. Nonetheless, careful consideration of the field of epigenetics leads us to conclude that gender must also leave an epigenetic imprint on the brain. Indeed, it would be strange if this were not the case, because all environmental influences of any import can epigenetically change the brain. In the following pages, we explain why there is now sufficient evidence to suggest that an epigenetic imprint for gender is a logical conclusion. We define our terms for sex, gender, and epigenetics, and describe research demonstrating sex differences in epigenetic mechanisms in the brain which, to date, is mainly based on work in non-human animals. We then give several examples of how gender, rather than sex, may cause the brain epigenome to differ in males and females, and finally consider the myriad of ways that sex and gender interact to shape gene expression in the brain.
An Analytical Model for the Electrical Characteristics of Passivated Carrier- Selective Contact (CSC) Solar Cell

In this paper, we have developed a physics-based analytical model for the electrical characteristics of passivated silicon carrier-selective contact (CSC) solar cells and validated it with numerical simulations. The model comprises analytical solutions of: 1) the Poisson equation, accurately capturing the level of inversion and accumulation at the crystalline silicon (c-Si) layer interfaces, and 2) the recombination current capturing the various recombination mechanisms at work in the solar cell. The calculations establish that CSC solar cells have the potential to achieve an efficiency greater than 26% even when both c-Si interfaces have realistic SRV values of 100 cm/s. The model helps illustrate the physics underlying the performance of CSC solar cells for variation in key device parameters such as surface recombination velocities, bulk lifetime, contact layer doping, and amorphous silicon (a-Si) thickness amongst others. By circumventing the need for resource-intensive numerical simulations, the analytical model described in this paper can assist in the design and development of high-performance CSC solar cells.
Optics in Computing: From Photonic Network-on-Chip to Chip-to-Chip Interconnects and Disintegrated Architectures

Following a decade of radical advances in the areas of integrated photonics and computing architectures, we discuss the use of optics in the current computing landscape attempting to redefine and refine their role based on the progress in both research fields. We present the current set of critical challenges faced by the computing industry and provide a thorough review of photonic Network-on-Chip (pNoC) architectures and experimental demonstrations, concluding to the main obstacles that still impede the materialization of these concepts. We propose the employment of optics in chip-to-chip (C2C) computing architectures rather than on-chip layouts toward reaping their benefits while avoiding technology limitations on the way to manycore set-ups. We identify multisocket boards as the most prominent application area and present recent advances in optically enabled multisocket boards, revealing successful 40 Gb/s transceiver and routing capabilities via integrated photonics. These results indicate the potential to bring energy consumption down by more than 60% compared to current QuickPath Interconnect (QPI) protocol, while turning multisocket architectures into a single-hop low-latency setup for even more than four interconnected sockets, which form currently the electronic baseline. We go one step further and demonstrate how optically-enabled eight-socket boards can be combined via a 256 × 256 Hipoλaos Optical Packet Switch into a powerful 256-node disaggregated system with less than 335 ns latency, forming a highly promising solution for the latency-critical rack-scale memory disaggregation era. Finally, we discuss the perspective for disintegrated computing via optical technologies as a mean to increase the number of synergized high-performance cores overcoming die area constraints, introducing also the concept of cache disintegration via the use of future off-die ultrafast optical cache memory chiplets.
A Noise Circulating Oscillator

This paper presents a noise circulating cross-coupled voltage-controlled oscillator (VCO) topology with a transformer-based tank. The introduced noise circulating active core greatly suppresses the effective noise power from the active devices while offering the same amount of negative resistance compared to conventional cross-coupled VCO topologies. The mechanism of noise circulation is investigated with theoretical analysis and further verified by simulation. Due to the broadband nature of the noise circulating technique, the resulting VCO phase noise in both 1/<inline-formula> <tex-math notation="LaTeX">$f^{2}$ </tex-math></inline-formula> and 1/<inline-formula> <tex-math notation="LaTeX">$f^{3}$ </tex-math></inline-formula> regions is greatly improved over a wide frequency tuning range. A prototype VCO at 2.35 GHz is implemented in a standard 130-nm bulk CMOS process with 0.36-mm<sup>2</sup> core area. It draws 2.15 mA from a 1.2-V supply. The measured figure-of-merit (FoM) is 193.1/195.0/195.6 dBc/Hz at 100k/1M/10MHz offsets with a 1/<inline-formula> <tex-math notation="LaTeX">$f^{3}$ </tex-math></inline-formula> phase noise corner of only 50 kHz. The VCO design consistently achieves >192.8 dBc/Hz FoM at 100k/1M/10MHz offsets and <60 kHz 1/<inline-formula> <tex-math notation="LaTeX">$f^{3}$ </tex-math></inline-formula> phase noise corner over its entire 18.6% frequency tuning range (2.05 − 2.47 GHz). It also exhibits low supply frequency pushing of −25 and −13 MHz/V at the highest and lowest frequencies, respectively.
Everolimus in Anaplastic Thyroid Cancer: A Case Series

Background: Anaplastic thyroid cancer (ATC) is a very aggressive disease and accounts for over 50% of thyroid-cancer related deaths. mTOR inhibition has shown anti-tumor activity in ATC. We report our experience treating patients with ATC with everolimus off-protocol. Methods: Patients with confirmed ATC and treated with everolimus at DFCI were identified and reviewed retrospectively. NexGen sequencing was performed, and radiologic responses were correlated with mutational profile. Results: Five patients were treated from 2013 to 2016. Three patients had a response, which included one patient who achieved a partial response for 27.9 months, and two patients who had stable disease for 3.7 and 5.9 months, respectively. Genomic analysis was available in two patients and revealed that the partial responder had mutations involving the PI3K/mTOR pathway. Conclusion: Everolimus has anti-tumor activity in ATC, and responses may correlate with mutations involving the PI3K/mTOR pathway. Further studies are warranted.
Impurity Analysis and Microstructure Along the Climatic Transition From MIS 6 Into 5e in the EDML Ice Core Using Cryo-Raman Microscopy

Impurities in polar ice cores have been studied so far mainly for the purpose of reconstructions of past atmospheric aerosol concentrations. However, impurities also critically influence physical properties of the ice matrix itself. To improve the data basis regarding the in-situ form of incorporation and spatial distribution of impurities in ice we used micro-cryo-Raman spectroscopy to identify the location, phase and composition of micrometer-sized inclusions in natural ice samples around the transition from marine isotope stage (MIS) 6 into 5e in the EDML ice core. The combination of Raman results with ice-microsctructure measurements and complementary impurity data provided by the standard analytical methods (IC, CFA and DEP) allows for a more interdisciplinary approach interconnecting ice core chemistry and ice core physics. While the interglacial samples were dominated by sulfate salts - mainly gypsum, sodium sulfate (possibly thenardite) and iron-potassium sulfate (likely jarosite) - the glacial ice contained high numbers of mineral dust particles - in particular quartz, mica, feldspar, anatase, hematite and carbonaceous particles (black carbon). We cannot confirm cumulation of impurities in the grain boundary network as reported by other studies, neither micro-particles being dragged by migrating grain boundaries nor in form of liquid veins in triple junctions. We argue that mixing of impurities on millimeter scale and chemical reactions are facilitated by the deforming ice matrix. We review possible effects of impurities on physical properties of ice, however the ultimate identification of the deformation agent and the mechanism behind remains challenging.