Miracle-dz/UniFAR-FTUs huggingface dataset:
3.3 A 0.51nW 32kHz Crystal Oscillator Achieving 2ppb Allan Deviation Floor Using High-Energy-to-Noise-Ratio Pulse Injection

In ultra-low-power crystal oscillators (XOs), the ideal circuit consumes minimum power while disturbing the oscillation as little as possible. In order to achieve sub-nW power consumption, there are three fundamental considerations: the loss in the crystal, the efficiency of energy injection, and the power required to extract oscillation frequency and phase as well as drive the injection. Crystal loss is a quadratic function of oscillation amplitude (Vasc) in series resonance, and it is a quadratic function of both Vasc and load capacitance (CL) in parallel resonance. Recent nW XOs use an amplitude control circuit [1] or lower voltage supply [2]–[5] to reduce Vasc, while [5] has no explicit capacitance on the crystal nodes to reduce CL. These techniques greatly reduce the crystal loss such that it no longer dominates total power [1]. However, lower oscillation amplitude makes the oscillation more prone to noise injected by the driving circuit (Fig. 3.3.1). As a result, nW XOs typically exhibit sacrificed Allan deviation floor, which indicates degraded long-term frequency stability.
Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey

Domain-specific hardware is becoming a promising topic in the backdrop of improvement slow down for general-purpose processors due to the foreseeable end of Moore’s Law. Machine learning, especially deep neural networks (DNNs), has become the most dazzling domain witnessing successful applications in a wide spectrum of artificial intelligence (AI) tasks. The incomparable accuracy of DNNs is achieved by paying the cost of hungry memory consumption and high computational complexity, which greatly impedes their deployment in embedded systems. Therefore, the DNN compression concept was naturally proposed and widely used for memory saving and compute acceleration. In the past few years, a tremendous number of compression techniques have sprung up to pursue a satisfactory tradeoff between processing efficiency and application accuracy. Recently, this wave has spread to the design of neural network accelerators for gaining extremely high performance. However, the amount of related works is incredibly huge and the reported approaches are quite divergent. This research chaos motivates us to provide a comprehensive survey on the recent advances toward the goal of efficient compression and execution of DNNs without significantly compromising accuracy, involving both the high-level algorithms and their applications in hardware design. In this article, we review the mainstream compression approaches such as compact model, tensor decomposition, data quantization, and network sparsification. We explain their compression principles, evaluation metrics, sensitivity analysis, and joint-way use. Then, we answer the question of how to leverage these methods in the design of neural network accelerators and present the state-of-the-art hardware architectures. In the end, we discuss several existing issues such as fair comparison, testing workloads, automatic compression, influence on security, and framework/hardware-level support, and give promising topics in this field and the possible challenges as well. This article attempts to enable readers to quickly build up a big picture of neural network compression and acceleration, clearly evaluate various methods, and confidently get started in the right way.
Diffuse Astrocytoma and Oligodendroglioma: An Integrated Diagnosis and Management

For the first time, the WHO classification of brain tumors has introduced molecular parameters in the diagnosis of brain tumors. Together with embryonal tumors, the diffuse gliomas have suffered significant changes in diagnosis, prognosis, and response to treatment. A new concept of “integrated diagnosis” comes to combine the classical diagnosis with the molecular one. While it is still impossible to disregard the histopathological component, according to the new rule (“molecular beats histology”) makes molecular parameters dominant in the final diagnosis. Currently, the diffuse gliomas (oligodendroglial or astrocytic) are nosologically closer than the astrocytomas with a diffuse growth pattern, and the astrocytomas with a more circumscribed growth pattern defined by the presence of the IDH mutation. The family tree was redefined by the presence of the IDH mutation and of the 1p/19q codeletion. The implementation of this new concept in clinical practice will improve patient management, as well as the design of clinical trials and experimental studies. This must also be seen as a model for diagnosis setting in the new molecular era.
Exploration of the Theory of Electric Shock Drowning

Drowning due to electric shock is theorized to occur when a current that is greater than the “let go” current passes through a body of water and conducts with the human body. Drowning would occur when the skeletal muscles contract and the victim can no longer swim. It is theorized that the likelihood of receiving a deadly shock in a freshwater environment (such as a lake) is higher than the likelihood in a saltwater environment (such as a marina). It is possible that due to the high conductivity of salt water, the current shunts around the individual, while in freshwater, where the conductivity of the water is lower than that of the human; a majority of the current will travel through the individual. The purpose of this research is to either validate or disprove these claims. To address this, we used Finite Element analysis in order to simulate a human swimming in a large body of water in which electric current has leaked from a 120V source. The conductivity of the water was varied from . 005 S/m (pure water) up to 4.8 S/m (salt water) and the current density through a cross sectional area of the human was measured. With this research, we hope to educate swimmers on the best action to take if caught in such a situation.
Selection of Appliance Using Skeletal Tracking and 3D Face Tracking for Gesture Control Home Automation

This study implements 3d face tracking and skeletal tracking in Microsoft Kinect Xbox One. Once the user is detected by the sensor head point from skeletal tracking, and a computed point D from chin point and eyebrow midpoint from 3d face tracking will be used to create the Line of Sight vector. Also, appliance points are always specified by the location of the appliance in the room with respect to the Kinect. Different appliance vectors will be created through vector subtraction. Angles between the Line of Sight vector and each of the appliance vector were computed through scalar product and compared to obtain the smallest angle. Once the smallest angle was obtained it was compared to a 15-degree threshold. If it’s within the threshold, then the appliance is selected.
Energy Spectrum of Electrons in the Plasma Bullet and Its Applied Voltage Effect in Atmospheric-Pressure Argon Plasma Jets

This article presents a numerical investigation on the energy spectrum of electrons (ESE) in an atmospheric-pressure argon plasma jet, based on a typical needle-plate discharge system with a positive applied voltage and a 1-D particle-in-cell Monte Carlo collision model. The spatiotemporal evolution characteristics of the ESEs in the three characteristic areas have been revealed. The three characteristic areas refer to the plasma bullet (the bullet), the dark channel behind the bullet, and the dim area in front of the bullet. The effects of the applied voltage amplitude on the ESEs have also been shown. As the bullet propagates, the ESEs in the bullet and the dark channel present an increasingly high peak and a gradually narrowing distribution, showing a decrease in average energy <inline-formula> <tex-math notation="LaTeX">$E_{\mathrm {ave}}$ </tex-math></inline-formula> of electrons, and in the dim area, the evolution of the ESE is opposite to that in the bullet. In contrast, the bullet has a substantial contribution to energetic electrons above the excitation threshold of argon, which shows that in applications of the plasma jet in biomedicine, the particles transporting into the aqueous solutions on the surface of living tissues may contain substantial non-subionization electrons. In the three characteristic areas, ESEs present an increasingly low peak and an increasingly wide distribution with the increase in the applied voltage amplitude, meaning an increasing <inline-formula> <tex-math notation="LaTeX">$E_{\mathrm {ave}}$ </tex-math></inline-formula>. Compared to the other two areas, <inline-formula> <tex-math notation="LaTeX">$E_{\mathrm {ave}}$ </tex-math></inline-formula> in the bullet is evidently high. In particular, a high applied voltage can induce a remarkable increase of high-energy electrons in the bullet, reaching a ratio of about 26% much higher than that in the other areas, under the applied voltage of 7 kV. This is of significance for plasma medicine.
Secondary and Backscattered Electron Current Induced Differential Charging on a Triple Junction of Spacecraft

This article discusses and analyzes the quantification of differential potential developed due to the effect of secondary electron yield (SEY) and backscattered electron yield (BEY) at adjacent dissimilar material surfaces present in a spacecraft. Subsequently, the differential potential creates electrostatic discharge (ESD). The threshold potential for generating the ESD is captured for the generalized case of differential charging on metallic patches embedded over a thin layer of the dielectric surface with the help of Spacecraft Plasma Interaction Experiments-II (SPIX-II) facilities. In view of the limitations of the experimental setup, numerical modeling is implemented to compute the differential charging for the recommended cases of plasma environment. The threat of an ESD event is indicated when the computed differential charging exceeds the ESD inception threshold voltage obtained from the experiments. Evaluation of the capacitance between material surfaces, which governs the timescale of differential charging, is carried out using the method of moments (MoM). The impact of diverse SEY and BEY of different materials on steady-state body potential is investigated. The validity of the analysis is also established with the results available in the open literature.
Effect of Temperature on Insulation Properties of SF₆/N₂ Mixed Gas Under AC Voltage

The insulation properties of SF6/N2 mixed gas are important for the insulation design of high-voltage equipment such as gas-insulated switchgear (GIS) and gas-insulated transmission line (GIL). However, the influence of temperature on insulation performance of SF6/N2 under alternating current (ac) voltage is rarely studied. In this article, we did gas breakdown experiments with SF6/N2 mixed gas at temperatures changing from −50 °C to 100 °C. The experimental results indicate that the breakdown voltages of SF6/N2 mixed gas increase with the increase in temperature. In order to explain the phenomenon, the three-body attachment process in compressed SF6 is introduced to analyze the electron avalanche process affected by temperature. The streamer and leader discharge criteria are introduced to qualitatively explain the influence of temperature on the breakdown voltages. It is found that the streamer channel radius becomes larger at elevated temperatures, which causes the increase in breakdown voltage.
Power Quality Issues Due to High Penetration of Rooftop Solar PV in Low Voltage Distribution Networks: A Case Study

Increased penetration of rooftop solar PV is causing undesirable technical impacts on the distribution networks. Several urban distribution transformers in Sri Lanka are exceeding fifty percent of the solar PV over the transformer capacity, which shed a green light to assess the cumulative effect of the rooftop solar PVs. In this study, a distribution feeder with high solar PV penetration has been selected and power quality issues such as harmonics, over voltage and DC injection are analyzed under various conditions. Effects of non-linear loads were also assessed to create an accurate representation of the existing network. The simulation results identify whether the selected system satisfies the statutory limits imposed by various global regulations concerned with power quality.
Germanium Photodetector With Alleviated Space-Charge Effect

The high-speed and high-power germanium photodetector (Ge PD) is highly desired for integrated microwave photonics systems. However, the space-charge effect has impeded the improvement of the performance. Here, we propose and demonstrate a high-speed and high-power Ge PD with alleviated space-charge effect, namely carrier-accelerated PD (CA PD). An additional electrical field is introduced to equalize the spatial distribution of photo-generated carriers, and thus the space-charge effect can be alleviated compared with conventional schemes. The CA PD is fabricated in the standard silicon photonics platform and has a small-signal bandwidth of 25 GHz. The carrier dynamics influenced by the additional electrical field is investigated using the impulse photocurrent measurement. In high-power condition, a 1-dB compression current of 1.7 mA can be observed.
Machine Learning Approach to Improve Flower Classification Using Multiple Feature Set

Image based classification systems are achieving best performance using large image datasets and advanced classification techniques. Most of the flower classes have same shape, appearance or background information such as plant leaves and grass. So, flower image classification is still challenging task. The goal of this paper is to analyse the effect of multiple local features for flower image classification. Shape, texture and color features are extracted from the flower images in order to describing different aspects of flowers. The classification performance of the proposed method is also compared with state-of-the-art flower classification performances. Performance of the local feature descriptors such as SIFT, SURF, HSV, RGB and CTM in flower classification is also analysed. According to the performance of the local descriptors, the combined SURF + CTM gives better performance than other combination of features in the context of flower image classification.
17.4 A 18.6-to-40.1GHz 201.7dBc/Hz FoMT Multi-Core Oscillator Using E-M Mixed-Coupling Resonance Boosting

The development of millimeter-wave (mmW) multiple-band systems for the 5G wireless and point-to-point backhaul communication requires ultra-wideband signal sources with low phase noise. However, with increasing parasitics and the limited quality factor of passive components at mmW bands, it is significantly challenging for an oscillator in a signal source to meet such performance. Recently, oscillator designs have evolved from the conventional single-core to multi-core types [1], [2]. With the parallel cross-coupled pairs and LCtanks, a multicore oscillator can efficiently reduce the phase noise level, while increasing the chip size and limiting frequency tuning range. To extend the operation bandwidth, mode-switching multi-core oscillators [3], [7] are developed and enable phase-noise reduction and tuning-range extension simultaneously. Nevertheless, most of the reported mode-switching oscillators are dual-mode and are still not easily able to cover the multiple bands for mmW 5G radio. A series resonator mode switching oscillator [4] achieves triple modes using four resonators, which greatly increase the chip area. Moreover, the cross-coupled pairs in [4] are switched OFF in different modes, thus the multi-core phase noise reduction cannot be achieved in each mode. This paper proposes a mmW multi-core oscillator using electric-magnetic (E-M) mixed-coupling resonance boosting to achieve a quad-mode operation bandwidth from 18.6 to 40.1GHz, which can fully cover the 5G bands around 24, 28, 37, and 39GHz. The mmW tuning range is as wide as 73%. With the wideband flicker noise suppression, the 1/f3 phase-noise corner is far below 1MHz over the operation frequency. An FoMT @1MHz of 201.7dBc/Hz is achieved at mmW bands by the proposed oscillator.
6.8 A 100Gb/s NRZ Transmitter with 8-Tap FFE Using a 7b DAC in 40nm CMOS

Recently, PAM-4 transmitters have been realized at 112Gb/s or even faster to satisfy the continuously growing demands for wireline communications [1]–[5]. Although PAM-4 signaling performs two-fold bandwidth efficiency compared with the NRZ counterpart, the NRZ signal still has the advantage in low-loss scenarios like ultra-short-reach (USR) interconnection for optical engines due to its high output swing and better SNR. This paper presents a 100Gb/s NRZ transmitter fabricated in 40nm CMOS by incorporating a 7b DAC with an 8-tap FFE implemented in DSP. The DAC-based architecture demonstrates high resolution for FFE coefficients, achieving an output eye diagram with 73mV eye height and 760fsrms jitter under 7.1dB loss at 50GHz while consuming 619mW of power from 1.1V/1.2V/1.5V supplies.
Quantitatively Improved Treatment Outcomes for Combat-Associated PTSD With Adjunctive Art Therapy: Randomized Controlled Trial

Abstract This article describes a randomized, controlled trial (N = 38) that compared art therapy in conjunction with cognitive processing therapy (CPT) to CPT alone for veterans with combat-related posttraumatic stress disorder. Participants were randomized to either the experimental condition of 8 sessions of CPT and 8 sessions of individual art therapy or to the control condition of 8 sessions of CPT and 8 individual sessions of supportive psychotherapy. Outcome measures included the Beck Depression Inventory–II (BDI–II), PTSD Checklist–Military (PCL–M), and self-ratings of perceived treatment benefits. Experimental group participants had statistically significantly greater reduction in PCL–M and BDI–II scores compared to the control group and the perceived benefit of treatment was greater for art therapy as compared to CPT.
Weighted Based Trustworthiness Ranking in Social Internet of Things by using Soft Set Theory

Internet of Things (IoT) is an evolving research area for the last two decades. The integration of the IoT and social networking concept results in developing an interdisciplinary research area called the Social Internet of Things (SIoT). The SIoT is dominant over the traditional IoT because of its structure, implementation, and operational manageability. In the SIoT, devices interact with each other independently to establish a social relationship for collective goals. To establish trustworthy relationships among the devices significantly improves the interaction in the SIoT and mitigates the phenomenon of risk. The problem is to choose a trustworthy node who is most suitable according to the choice parameters of the node. The best-selected node by one node is not necessarily the most suitable node for other nodes, as the trustworthiness of the node is independent for everyone. We employ some theoretical characterization of the soft-set theory to deal with this kind of decision-making problem. In this paper, we developed a weighted based trustworthiness ranking model by using soft set theory to evaluate the trustworthiness in the SIoT. The purpose of the proposed research is to reduce the risk of fraudulent transactions by identifying the most trusted nodes.
ECG Heartbeat Classification: A Comparative Performance Analysis between One and Two Dimensional Convolutional Neural Network

Recently automatic categorization of Electrocardiogram (ECG) has garnered great attention as it is the most reliable measure for monitoring cardiovascular system functionality. Deep learning has been proven to be a very efficient and accurate approach in this field. A deep learning method based on two-dimensional deep convolutional neural network is proposed in this paper for classifying heartbeats in order to accurately detect five different arrhythmias in accordance with the AAMI EC57 standard. Its performance is compared with another method based on one-dimensional deep convolutional neural network by using PhysioNet's MIT-BIH dataset for evaluation. Both of these CNN methods proved to be better than some state of the art methods when implemented on the same dataset. The 2D CNN method outperformed all the other implemented methods with an average accuracy of 94.37%.
Left split grafts in pediatric liver transplantation: an unexploited resource open to a multiple scenario evolution

We read with particular interest the article by Angelico and colleagues entitled “Outcomes of left split graft transplantation in Europe: report from the European Liver Transplant Registry” (1), published recently in Transplant International . The manuscript, reporting the outcome of 1,500 pediatrics transplantation performed in different European transplant centers using left split grafts (LSG) from deceased donors, makes an updated continental point on one of the most complex activities in the liver transplant (LT) area. Importantly enough, the study represents the widest LSG transplantation series ever reported.
Early CTC decline as a biomarker of response to treatment in castration-resistant prostate cancer (CRPC): Analysis of the COU-AA-301 and IMMC38 trials.

5014 Background: Circulating tumor cell counts (CTC) are prognostic in CRPC. Baseline (BL) CTC ≥ 5 CTCs/7.5mL are associated with worse prognosis. A post-treatment 30% decline in CTC has been associated with improved survival (OS) (Olmos et al, 2009). We investigated the value of 30% declines in CTC after 4 and 12 weeks (wks) of treatment in the COU-AA-301 (abiraterone) and IMMC-38 (chemotherapy) trial datasets. This is the first time %CTC decline has been evaluated in phase III CRPC clinical trials. Methods: CTC of patients (pts) were determined (CellSearch). Pts with BL CTCs ≥5 and valid counts at Wk 4/Wk 12 (IMMC38) or Cycle 2/Cycle 4 Day 1 (COU-AA-301) were evaluated. CTC response was defined as a ≥30% decline in CTC relative to BL (30%CTCresp). Association of 30%CTCresp with OS was evaluated with Cox regression in uni- and multivariable (MV) analysis with ECOG, LDH, ALP, Alb, Hb, BL CTC and PSA as covariates (continuous). C-index was calculated to determine the performance of the MV model with and wi.
Correlation of enhancement Platelet Distribution Width (PDW) with severity of dengue infection

Dengue infections are currently one of the most rapidly emerging arboviral infections in the world. During this time the emphasis of platelets only limited about number of platelets and very rarely discuss about the quality of platelets (activation and dysfunction). Changes in PDW reflects the activation of platelets. Aim of this study is to analyze the prevalence ratio of PDW enhancement in dengue hemorrhagic fever (DHF) compared to dengue fever (DF). This was a cross-sectional study to analyze the prevalence ratio of enhancement PDW in DHF compared to DF. The subjects were dengue suspected patients who meet the inclusion and exclusion criteria. Venous blood were collected for automatical hematology analysis (include PDW). Different proportions of PDW enhancement between DHF and DF groups was analyzed by Chi-square. One hundred subjects were participated in this study and classified into DF and DHF. Prevalence ratio of PDW enhancement (>64.8%) was 3.1 (95% CI 1.5 – 20.7), p 0.006. The result indicates that PDW enhancement was a risk factor of worsening dengue infection.