Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Resiliency of NCFET Circuits Against Voltage Over-Scaling

Approximate computing is established as a design alternative to improve the energy requirements of a vast number of applications, leveraging their intrinsic error tolerance. Voltage over-scaling (VOS) is one of the most energy-efficient approximation techniques, but its exploitation is still limited due to the large errors it induces. In this work, we investigate, for the first time, the resiliency of negative capacitance transistor (NCFET) technology to VOS in comparison to conventional CMOS technology. Our work reveals that circuits implemented using the NCFET technology exhibit much less timing errors under VOS due to the inherent voltage amplification provided by the ferroelectric layer. NCFET is one of the very promising emerging technologies that is rapidly evolving for low-power circuit as it enables the transistors to switch faster without the need to increase the voltage. We demonstrate how NCFET technology allows circuit designers to effectively employ VOS to boost the efficiency of their approximate circuits, while still keeping the induced errors marginal. Our analysis shows that the VOS-resilience of NCFET circuits enables maximizing the voltage decrease and thus, NCFET based VOS approximate circuits achieve from $1.83\times$ up to $2.78\times$ higher energy reduction compared to the corresponding FinFET circuits for the same error bounds.
Instructor Presence in Video Lectures: Preliminary Findings From an Online Experiment

Motivation. Despite the widespread use of video lectures in online and blended learning environments, there is still debate whether the presence of an instructor in the video helps or hinders learning. According to social agency theory, seeing the instructor makes learners believe that s/he is personally teaching them, which leads to deeper cognitive processing and, in turn, better learning outcomes. Conversely, according to cognitive load theory, adding an image of the instructor may hinder attention engagement with lecture content due to split-attention effect. Not only are theoretical propositions conflicting, but so is the empirical evidence as well. Objective. This study investigates the effects of the presence of the instructor’s face in the corner of an educational video on learning outcomes, perceived cognitive load, and perceived social presence in the context of foreign language vocabulary learning. Method. In an online quasi-controlled experiment with between-subject design, 112 participants were randomly assigned to view a 10-min-long educational video in one of two conditions: instructor-present or instructor-absent. As for the latter condition, the face was shown only at the introduction of the presentation. Afterwards, participants completed a retention test as well as a cognitive load and social presence questionnaire. Results. No significant differences were found for any dependent variable. Conclusion. Individuals differ so much in their language aptitude as well as motivation to perform well that random assignment is probably not enough to ensure balanced groups in this particular study context. Besides, the approach that we used to measure cognitive load as well as social presence is not suited for between-subject design, even though it was previously used in such settings.
Permittivity Measurement of the Dielectric Material at the Off-Axis Position in a Cylindrical Cavity

In most measurement models of the cylindrical cavity, concentricity between the rod-like sample and cylindrical cavity is a basic premise of an accurate calculation model. Once a sample is randomly placed in the off-axis position in the sample hole of the cavity, the real will not conform to the established calculation model and the off-axis position should be taken into account to the measurement error. In this article, a measurement method to calculate permittivity of the sample placed at the off-axis position in the sample hole is presented. The actual location of the sample in a cylindrical cavity is first obtained in the application of vision measurement. Field distribution in the cavity is calculated by using the mode-matching method. The measured sample in the cavity is divided into finite small elements with arc shapes, and permittivity calculation expression is established by using the perturbation theory. A TM-mode cylindrical cavity that installed two miniature camera probes around the cavity wall is designed and used to measure permittivity of the material. Teflon and fused silica with different off-axis positions are measured and compared with the published results at several resonance frequencies. The maximum permittivity errors of Teflon and fused silica are 1.6% (at around 2 GHz) and 0.68% (at around 10.8 GHz), respectively. The maximum loss tan $\delta $ errors are 5.8e−5 (at around 12.5 GHz) and 1.44e−4 (at around 9.9 GHz), respectively.
The management of the effects of navigation on the marine environment: the case of tributyltin (TBT)

The aim of this study is to review the fact-finding and decision-making process of the international community which, via the International Maritime Organization, has led to a ban on the use of antifouling paints containing organotin compounds. This review focuses on the importance of scientific knowledge supporting the sustainable management of the environment and on the centrality of ecotoxicological studies on the effects of human activities on the enviroment. The Italian Coast Guard Corps guarantees compliance with the regulations, through the action of Port State Control carried out in ports and onboard vessels.
A Fully-Integrated 40-nm 5-6.5 GHz Cryo-CMOS System-on-Chip with I/Q Receiver and Frequency Synthesizer for Scalable Multiplexed Readout of Quantum Dots

Quantum computing holds the promise to solve many of today’s intractable problems. A solid-state quantum computer (QC) is generally made of an array of qubits implemented in one of many solid-state technologies and operating at deep-cryogenic temperatures (10-to-20mK). Silicon spin qubits are a promising candidate for scalable QCs, due to their size, long coherence times and potential for co-integration with the required classical control and readout electronics. Recently, semiconductor spin qubits have been demonstrated to operate at $\sim 1\mathrm{K}$, thus accelerating the achievement of a compact QC [1]. Classical qubit control electronics has also progressed, with the demonstration of fully-integrated control of spin qubits [2] and transmons [3] implemented in a cryo-CMOS technology. While a cryo-CMOS integrated circuit has been co-integrated with quantum dots [4], fully-integrated readout electronics has not yet been addressed in the literature.
On Partial Orders in Complex Fuzzy Logic

A partial ordering <inline-formula><tex-math notation="LaTeX">$\preceq$</tex-math></inline-formula> on the unit circle of the complex plane <inline-formula><tex-math notation="LaTeX">${\bf D}$</tex-math></inline-formula>induced by the algebraic product was introduced and it was proved that <inline-formula><tex-math notation="LaTeX">$({\bf D},\preceq)$</tex-math></inline-formula> is a complete lattice (Dick, 2005). In this letter, it is pointed out that the relation <inline-formula><tex-math notation="LaTeX">$\preceq$</tex-math></inline-formula> is not a partial order on <inline-formula><tex-math notation="LaTeX">${\bf D}$</tex-math></inline-formula> and that <inline-formula><tex-math notation="LaTeX">$({\bf D},\preceq)$</tex-math></inline-formula> is not a lattice. It is shown that the relation <inline-formula><tex-math notation="LaTeX">$\preceq$</tex-math></inline-formula> is a partial order over <inline-formula><tex-math notation="LaTeX">${\bf D}^{\circ }\cup \lbrace 1\rbrace$</tex-math></inline-formula> and a strict partial order over <inline-formula><tex-math notation="LaTeX">${\bf D}^{\circ }-\lbrace 0\rbrace$</tex-math></inline-formula>, where <inline-formula><tex-math notation="LaTeX">${\bf D}^{\circ }$</tex-math></inline-formula> is the interior of <inline-formula><tex-math notation="LaTeX">${\bf D}$</tex-math></inline-formula>.
False-Alarm-Controllable Radar Detection for Marine Target Based on Multi Features Fusion via CNNs

Due to the influence of the complex marine environment, the marine target detection based on statistical theory is difficult to achieve high-performance. Moreover, due to various targets’ motion characteristics, only using a single feature for detection is unreliable. In this paper, from the perspective of feature extraction and classification, marine target and sea clutter are classified by deep learning methods. To achieve the required false alarm rate, the dual-channel convolutional neural networks (DCCNN) and false-alarm-controllable classifier (FACC)-based marine target detection method is proposed. Firstly, the measured sea clutter and the target signal are preprocessed to obtain the time-Doppler spectrum and amplitude information. The Marine-DCCNN (MDCCNN) is then constructed for features extraction and fusion, and the feature vectors of the signals are obtained. The performance of different feature extraction models is tested and compared. Finally, the FACC is used as a detector to classify the feature vectors into two categories and the control of the false alarm rate is realized. The detection performances were verified by two popular public radar datasets, i.e., IPIX radar dataset (floating target) and CSIR dataset (maneuvering marine target). The results show that compared with single-channel CNN and histogram of oriented gradient support vector machine (Hog-SVM) classification, a combination of MDCCNN feature extraction model and softmax classifier can achieve higher performance and controllable false alarm rate. Moreover, HH polarization and mixed training datasets under different sea states can help improve detection performance.
Arsenate and Chromate Removal with Cationic Surfactant-Loaded and Cation-Exchanged Clinoptilolite-Rich Tuff vs Montmorillonite

Using a laboratory set-up, sorption of chromate and arsenate from aqueous solutions with the octadecylammonium acetate (ODA)-modified clinoptilolite was examined. In the experiments, a natural montmorillonite was compared with organically, i.e . surfactant-loaded clinoptilolite and with some inorganically substituted (Ag, Pb)-monoforms. The arrangements of the surface-attached ODA chains have been an important factor for the difference in the adsorption states of the guest species (oxyanions). A novel nanostructure inorganic-organic composite prepared has been investigated using SEM, thermogravimetry, UV-VIS diffuse reflectance and powder XRD spectral analytical methods. Finally, adsorption isotherms for the system studied have been measured. An approach for regeneration of exhausted surfactant-immobilized clinoptilolite with inorganic salt solutions under dynamic regime has been proposed.
15.3 A 65nm 3T Dynamic Analog RAM-Based Computing-in-Memory Macro and CNN Accelerator with Retention Enhancement, Adaptive Analog Sparsity and 44TOPS/W System Energy Efficiency

Computing-In-Memory (CIM) techniques which incorporate analog computing inside memory macros have shown significant advantages in computing efficiency for deep learning applications. While earlier CIM macros were limited by lower bit precision, e.g. binary weights in [1], recent works have shown 4-to-8b precision for the weights/inputs and up to 20b for the output values [2], [3]. Sparsity and application features have also been exploited at the system level to further improve the computation efficiency [4], [5]. To enable higher precision, bit-wise operations were commonly utilized [3], [4]. However, there are limitations in existing solutions using the bit-wise operations with SRAM cells. Fig. 15.3. 1 shows the summary of challenges and solutions in this work. First, all existing solutions utilize 6T/8T/10T SRAM as a CIM cell, which fundamentally limits the size of the CIM array. In this work, we replace the commonly used SRAM cell with a 3-transistor (3T) analog memory cell, referred as dynamic-analog-RAM (DARAM) which represents a 4b weight value as an analog voltage. This leads to $\sim 10 \times$ reduction in transistor count and achieves an effective CIM single-bit area smaller than the foundry-supplied 6T SRAM cell. Secondly, as no bit-wise calculation is needed in this work, only single-phase MAC operations are performed, removing the throughput degradation associated with previous multi-phase approaches and digital accumulation in [3], [4]. Furthermore, analog linearity issues are mitigated by highly linear time-based activation, removal of matching requirements for critical multi-bit caps [4], [6], and a special read current compensation technique. Thirdly, to mitigate the power bottleneck of ADC or SA, this work applies analog sparsity-based low-power methods, which include a compute-adaptive ADC skipping operation when the analog MAC value is small (or “sparse”) and a special weight-shifting technique, leading to an additional $\sim 2 \times$ reduction in CIM-macro power. We demonstrate the proposed techniques using a 65nm CIM-based CNN accelerator showing state-of-art energy efficiency.
7.8 A 1-inch 17Mpixel 1000fps Block-Controlled Coded-Exposure Back-Illuminated Stacked CMOS Image Sensor for Computational Imaging and Adaptive Dynamic Range Control

In recent developments, image sensors are no longer simply a means for collecting optical signals, but rather, are increasingly expected to serve as intelligent systems with surrounding configurations. Coded exposure (CE) is one of the methods applied in intelligent systems approaches, and various functions can be realized by the selection of the integration variable in the plenoptic function. High DR can be realized if the integration variable is time. A variety of means to achieve high DR have been proposed in the literature, for example, a method that provides a plurality of detection capacitors (LOFIC, [1]) or a method of preventing saturation by adding low-sensitivity pixels [2]. These methods often require an enlarged pixel size. Alternatively, high-speed readout like an array parallel stacked structure [3] is useful for integrating multiple frames to realize high DR. However, this leads to an increase in noise and needs faster readout to reduce motion artifacts. In order to mitigate the adverse effects, a method has been proposed in which a pixel array is divided into a plurality of blocks and the signal integration time of each block is individually controlled [4]. Another method was described in which CE was demonstrated by using pixel level control of the exposure time [5]. However, in these methods, it was necessary to arrange the readout path and control circuitry within the same plane because these are non-stacked sensors, so the pixel size was relatively large and high resolution was difficult to realize. To overcome the above problems, we report a sensor that can simultaneously achieve 4K×4K resolution and 1000fps high-speed readout. Using a stacked structure, we demonstrate coded exposure capability by individually controlling exposure time for each block of pixels.
A Robotic Companion for Children Diagnosed with Autism Spectrum Disorder

The objective of this research is to develop a social robotic companion for children diagnosed with autism spectrum disorder to distract the child when they are engaged in repetitive behaviour and to improve their motor skills. The robot was designed to be of spherical shape with the appearance of a common playground object to make it easier to introduce this to the children. The experiment to test this study was designed to include parallel play as well as collaborative play. A mobile application was used to remotely control the robot as to make the introduction and interaction with a foreign object easier for the children. The child's acceptance of the robot, their reaction to its movements, the robot's ability to attract the child when they are distracted, and improvement of their motor skills were measured as well as the child's engagement with the robot. The results of this study showed that the children diagnosed with ASD are open to interact with social robots and that through continuous exposure, the motor skills and social interaction of these children can be improved. This study further demonstrates the need for and benefits of future studies in order to observe the full potential of robots in the therapy for children with autism.
Reduced Pressure CVD Growth of Ge and Ge1−xSnx Alloys

precursors. All Ge and GeSn layers exhibit high crystalline quality as revealed by X-ray reciprocal space mapping and are nearlyfully strain relaxed. © 2013 The Electrochemical Society. [DOI: 10.1149/2.006305jss] All rights reserved.Manuscript submitted January 15, 2013; revised manuscript received February 20, 2013. Published March 5, 2013. This was Paper3214 presented at the Honolulu, Hawaii, Meeting of the Society, October 7–12, 2012.
BIAS REDUCTION AND LIKELIHOOD-BASED ALMOST EXACTLY SIZED HYPOTHESIS TESTING IN PREDICTIVE REGRESSIONS USING THE RESTRICTED LIKELIHOOD

Difficulties with inference in predictive regressions are generally attributed to strong persistence in the predictor series. We show that the major source of the problem is actually the nuisance intercept parameter, and we propose basing inference on the restricted likelihood, which is free of such nuisance location parameters and also possesses small curvature, making it suitable for inference. The bias of the restricted maximum likelihood (REML) estimates is shown to be approximately 50% less than that of the ordinary least squares (OLS) estimates near the unit root, without loss of efficiency. The error in the chi-square approximation to the distribution of the REML-based likelihood ratio test (RLRT) for no predictability is shown to be $({\textstyle{3 \over 4}} - \rho ^2)n^{ - 1} (G_3 (\cdot) - G_1 (\cdot)) + O(n^{ - 2}),$ where |ρ| < 1 is the correlation of the innovation series and Gs(·) is the cumulative distribution function (c.d.f.) of a $\chi _s^2 $ random variable. This very small error, free of the autoregressive (AR) parameter, suggests that the RLRT for predictability has very good size properties even when the regressor has strong persistence. The Bartlett-corrected RLRT achieves an O(n−2) error. Power under local alternatives is obtained, and extensions to more general univariate regressors and vector AR(1) regressors, where OLS may no longer be asymptotically efficient, are provided. In simulations the RLRT maintains size well, is robust to nonnormal errors, and has uniformly higher power than the Jansson and Moreira (2006, Econometrica 74, 681–714) test with gains that can be substantial. The Campbell and Yogo (2006, Journal of Financial Econometrics 81, 27–60) Bonferroni Q test is found to have size distortions and can be significantly oversized.
Studies on the dehydrogenative polymerization of monolignol β-glycosides. Part 6: Monitoring of horseradish peroxidase-catalyzed polymerization of monolignol glycosides by GPC-PDA

Abstract Horseradish peroxidase (HRP)-catalyzed dehydrogenative polymerization of guaiacyl (G) and syringyl (S)-type monolignol γ-O-glucosides, isoconiferin (iso-G) and isosyringin (iso-S), which contain a hydrophilic glucosyl unit on γ-position of coniferyl alcohol and sinapyl alcohol, respectively, was monitored by gel permeation chromatography coupled with photodiode array detection (GPC-PDA). Contrary to the conventional dehydrogenative polymerization of monolignols, the polymerization of the glycosides produces water-soluble synthetic lignins (DHPs) in a homogeneous aqueous phase. Taking advantage of this unique reaction system, the method was developed to follow the changes of molecular weights in the course of DHP formations. Moreover, PDA detection permits determination of oligomeric S-type quinone methide intermediates (QMs) formed as stable transient compounds during polymerization of iso-S. A detailed comparison of the polymerization profiles revealed entirely different behaviors of G- and S-type monomers. The data strongly support the view that the low reactivity of oligomeric S-type QMs impedes the formation of DHPs from S-type monomers. In copolymerization of G- and S-type monomers, it is conceivable that G-type phenolic hydroxyl groups serve as good nucleophilic reactants to scavenge S-type QMs resulting in efficient production of DHPs. As a consequence, the present approach can be a powerful tool to study the in vitro dehydrogenative polymerization providing further mechanistic insights into lignin polymerization in vivo.
Particle dispersion induced by vortical interactions in a particle-laden upward jet with a partial crossflow

Abstract In the present study particle dispersions (concentrations) through vortical interactions are experimentally investigated for a particle-laden upward jet, with a horizontal crossflow covering a vertical range partially near the jet exit (Reynolds numbers of 1170–5200). We focus on the influences of the dynamics of counter-rotating vortex pairs existing in the flow on changes in the particle dispersion patterns, depending on the velocity (jet/crossflow) ratio and particle Stokes number ($St = 0.01\text {--}27.42$). Without crossflow, there is no dominant vortical structure along the horizontal direction; thus, the particles are not dispersed significantly out of the jet core in most cases, except for the case with the highest particle inertia (i.e. $St$). With crossflow, on the other hand, counter-rotating vortex pairs appear above the jet exit and become stronger as the velocity ratio decreases. With a lower velocity ratio, the vortices are tilted more toward the leeward side and dissipate faster. Driven by the vortex pairs, the drag force acting on the particles becomes stronger and, thus, particles with $St < 1.0$ are dragged out of the jet core following the rotation of the vortices. Those with $St \simeq 1.0$ are concentrated between the vortex pairs before the vortices collapse. When $St \gg 1.0$, particles are simply transported by the inertial effect. Finally, we suggest different regimes for particle dispersion (concentration) as classified by the Stokes number and velocity ratio, and elucidate their mechanisms, which are further extended to empirical particle dispersion models.