Miracle-dz/UniFAR-FTUs huggingface dataset:
A Case of On-Chip Memory Subsystem Design for Low-Power CNN Accelerators

The rapid development of machine learning is enabling a plenty of novel applications, such as image and speech recognition for embedded and mobile devices. However, state-of-the-art deep learning models like convolutional neural networks (CNNs) are demanding so much on-chip storage and compute resources that they cannot be smoothly handled by low-power mobile or embedded systems. In order to fit large CNN models into mobile or more cutting-edge devices for IoT or cyberphysics applications, we proposed an efficient on-chip memory architecture for CNN inference acceleration, and showed its application to in-house single-instruction multiple-data structure machine learning processor. The redesigned on-chip memory subsystem, Memsqueezer, includes an active weight buffer and data buffer set that embraces specialized compression methods to reduce the footprint of CNN parameters (weights) and activation data, respectively. Memsqueezer buffer can compress the data and weight set according to the dataflow in computation, and it also includes a built-in redundancy detection mechanism that actively scans through the working-set of CNNs to boost their inference performance by eliminating the computation redundancy in CNN models. In our experiments, it is shown that the CNN processors with Memsqueezer buffers achieve more than $2{\times }$ performance improvement and reduces 85% energy consumption on average over the conventional buffer design with the same area budget.
Securing Cooperative Spectrum Sensing Against Collusive False Feedback Attack in Cognitive Radio Networks

Cooperative spectrum sensing (CSS) is considered as a powerful approach to improve the utilization of scarce spectrum resources. However, CSS assumes that all secondary users (SU) always are honest, thus offering opportunities for attackers to launch spectrum sensing data falsification (SSDF) attack. To combat such threat, recent efforts have been made to trust mechanism. In this paper, we argue that powering CSS with trust mechanism is not enough. A vulnerability for trust mechanism is found, that is, the feedback data from initiator SUs are generally unchecked. Such feedback data corresponding to the spectrum status of primary users can be exploited by attackers to disturb trust mechanism in a collusive manner. Especially, collusive false feedback (CFF) attackers would form a clique to help each other. One of CFF attackers can disguise as an initiator SU who sends the feedback in accordance with the sensing data of their conspirators who play the role of cooperating SUs, resulting in promoting their conspirators’ sensing trust quickly. With high sensing trust, attackers can avoid the detection of trust mechanism and, hence, launch SSDF attack (fake sensing data) more easily. We conduct an in-depth investigation on CFF attack and propose a two-level defense scheme called FeedGuard from the design ideas of feedback trust and I-C frequency correlation analysis. Simulation results show that the FeedGuard scheme can enhance the accuracy of sensing trust evaluation, thus successfully reducing the power of CFF attack against CSS.
Nitric Oxide Enhancing Resistance to PEG-Induced Water Deficiency is Associated with the Primary Photosynthesis Reaction in Triticum aestivum L.

Photosynthesis is affected by water-deficiency (WD) stress, and nitric oxide (NO) is a free radical that participates in the photosynthesis process. Previous studies have suggested that NO regulates excitation-energy distribution of photosynthesis under WD stress. Here, quantitative phosphoproteomic profiling was conducted using iTRAQ. Differentially phosphorylated protein species (DEPs) were identified in leaves of NO- or polyethylene glycol (PEG)-treated wheat seedlings (D), and in control seedlings. From 1396 unique phosphoproteins, 2257 unique phosphorylated peptides and 2416 phosphorylation sites were identified. Of these, 96 DEPs displayed significant changes (≥1.50-fold, p < 0.01). These DEPs are involved in photosynthesis, signal transduction, etc. Furthermore, phosphorylation of several DEPs was upregulated by both D and NO treatments, but downregulated only in NO treatment. These differences affected the chlorophyll A–B binding protein, chloroplast post-illumination chlorophyll-fluorescence-increase protein, and SNT7, implying that NO indirectly regulated the absorption and transport of light energy in photosynthesis in response to WD stress. The significant difference of chlorophyll (Chl) content, Chl a fluorescence-transient, photosynthesis index, and trapping and transport of light energy further indicated that exogenous NO under D stress enhanced the primary photosynthesis reaction compared to D treatment. A putative pathway is proposed to elucidate NO regulation of the primary reaction of photosynthesis under WD.
Persistent coding of outcome-predictive cue features in the rat nucleus accumbens

The nucleus accumbens (NAc) is important for learning from feedback, and for biasing and invigorating behavior in response to cues that predict motivationally relevant outcomes. NAc encodes outcome-related cue features such as the magnitude and identity of reward. However, little is known about how features of cues themselves are encoded. We designed a decision making task where rats learned multiple sets of outcome-predictive cues, and recorded single-unit activity in the NAc during performance. We found that coding of cue identity and location occurred alongside coding of expected outcome. Furthermore, this coding persisted both during a delay period, after the rat made a decision and was waiting for an outcome, and after the outcome was revealed. Encoding of cue features in the NAc may enable contextual modulation of ongoing behavior, and provide an eligibility trace of outcome-predictive stimuli for updating stimulus-outcome associations to inform future behavior.
Revisiting Neutrophil Gelatinase-Associated Lipocalin (NGAL) in Cancer: Saint or Sinner?

Human neutrophil gelatinase-associated lipocalin (NGAL) is a glycoprotein present in a wide variety of tissues and cell types. NGAL exists as a 25 kDa monomer, a 46 kDa homodimer (the most abundant form in healthy subjects) and a 130 kDa disulfide-linked heterodimer bound to latent matrix metalloproteinase-9. Dysregulated expression of NGAL in human malignancies suggests its value as a clinical marker. A growing body of evidence is highlighting NGAL’s paradoxical (i.e., both beneficial and detrimental) effects on cellular processes associated with tumor development (proliferation, survival, migration, invasion, and multidrug resistance). At least two distinct cell surface receptors are identified for NGAL. This review (i) summarizes our current knowledge of NGAL’s expression profiles in solid tumors and leukemias, and (ii) critically evaluates the beneficial and detrimental activities of NGAL having been documented in a diverse range of cancer-derived cell lines. A better understanding of the causal relationships between NGAL dysregulation and tumor development will require a fine analysis of the molecular aspects and biological role(s) of NGAL both in primary tumors and at different stages of disease. Having an accurate picture of NGAL’s contribution to tumor progression is a prerequisite for attempting to modulate this protein as a putative therapeutic target.
Evaluation and Improvement of Indonesian Massive Open Online Course (MOOC) Interaction Design of MOOC X

Massive Open Online Course (MOOC) is one of interactive learning media providing online courses which enable learners to access learning resources anytime and anywhere. One of the leading MOOCs in Indonesia is MOOC X. However, there has not been any research conducted to investigate whether the interaction design of MOOC X is easy to use or not. The objective of this study is to make recommendations to improve the interaction design on the course pages of MOOC X. The evaluation was done by using an online questionnaire, usability testing, and contextual interview. The results of this study show that MOOC X has applied interaction design principles and is easy to use, yet it still needs some improvements. Recommendations on MOOC X interaction design improvements which were acquired from the evaluation results were constructed based on the design and e- Learning principles in this study.
An Active Damping Scheme With Energy Saving Feature for Use with Regenerative Converters

Regenerative drives, also known as four-quadrant drives are an integral part of many industrial applications ranging from wind power generation, elevators, escalators, centrifuges, pump jacks in oil fields, etc. All regenerative converters need passive LCL filters to filter out pulsewidth modulation frequency components. One disadvantage of using an input LCL filter in front of regenerative converters is that they are also a major source of power loss in the power system as their configuration allows for the flow of capacitive circulating currents even when the power converter is off. The associated power loss in the power system can significantly affect the overall system efficiency when there are large numbers of large power regenerative units in the power system. The filter capacitors also interact with pre-existing voltage distortion in the power system. Multiple regenerative units of various sizes have been shown in this paper to cause undesirable voltage ripple, which in turn causes current oscillations especially in smaller sized regenerative converters. A new active damping scheme is proposed, which also includes actively opening the neutral point of the filter capacitor to eliminate standby power loss associated with regenerative converters with LCL filters. Two ideas are proposed. In the first, only one damping resistor is used, whereas in the other two, damping resistors are used in parallel, where one resistor acts as the fixed damping resistor whereas the other is modulated depending on the amount of system distortion. Test results are given to demonstrate the fundamental concept.
The Effect of Ultrasound, Oxygen and Sunlight on the Stability of (−)-Epigallocatechin Gallate

(−)-Epigallocatechin gallate (EGCG), is the main catechin found in green tea, and has several beneficial effects. This study investigated the stability of EGCG aqueous solution under different stored and ultrasonic conditions to determine whether it can be used with an ultrasonic dental scaler to treat periodontal infection. Four concentrations (0.05, 0.1, 0.15, 2 mg/mL) of EGCG aqueous solution were prepared and stored under four different conditions (A: Exposed to neither sunlight nor air, B: Exposed to sunlight, but not air, C: Not exposed to sunlight, but air, D: Exposed to sunlight and air) for two days. The degradation rate of EGCG was measured by high performance liquid chromatography (HPLC). On the other hand, an ultrasonic dental scaler was used to atomize the EGCG solution under four different conditions (a: Exposed to neither air nor sunlight, b: Not exposed to air, but sunlight, c: Not exposed to sunlight, but air, d: Exposed to air and sunlight), the degradation of EGCG was measured by HPLC. We found that the stability of EGCG was concentration-dependent in water at room temperature. Both sunlight and oxygen influenced the stability of EGCG, and oxygen had a more pronounced effect on stability of EGCG than sunlight. The most important conclusion was that the ultrasound may accelerate the degradation of EGCG due to the presence of oxygen and sunlight, but not because of the ultrasonic vibration. Thus, EGCG aqueous solution has the potential to be used through an ultrasonic dental scaler to treat periodontal infection in the future.
Fully ZVS, Minimum RMS Current Operation of the Dual-Active Half-Bridge Converter Using Closed-Loop Three-Degree-of-Freedom Control

This paper discusses how duty ratios of the primary and secondary half-bridge legs of a dual-active half-bridge converter can be used in conjunction with phase-shift control to operate the converter with the least possible transformer rms current at a given power. Following introduction of all possible operational modes arising due to such three-degree-of-freedom control, results from a numerical-optimization-based approach are used to identify the best mode. Using information gleaned from careful observation of simulation results corresponding to the minimum current trajectory in this mode, key insights regarding circuit conditions to be satisfied for optimal operation are obtained. This information is used to propose the framework of a 3-D modulation strategy, which results in globally minimum rms current operation and is remarkably also found to satisfy the necessary conditions for zero-voltage-switching operation of all devices. The proposed strategy is implemented through closed-loop control and, hence, does not have the demerits associated with a lookup-table-based approach involving offline precomputation of optimal duty ratios. Simulation and experimental results on a 625-W laboratory prototype demonstrate the significant efficiency advantages of the proposed modulation scheme compared to simple phase-shift (1-D) control or 2-D asymmetric control, particularly at light loads in applications with widely varying voltage ratios.
Breakdown Characteristics of Triggered Pseudospark Discharge-Based Multigap Plasma Cathode Electron Source

Pseudospark (PS) sourced electron beam with high energy can be produced by a multigap PS discharge-based plasma cathode electron (PD-PCE) source under high-voltage operations. The process of successive high-voltage breakdown and plasma formation inside hollow cathode (HC) and in the gaps play significant role for electron beam generation. An investigation has been carried out for the analysis of discharge processes in different multigap PS structures using the 2-D kinetic plasma simulation code. It has been observed that the distribution of equipotential contour lines in the HC cavity as well as gaps is important to investigate the occurrence of the breakdown and plasma generation in the PD-PCE source. The higher equipotential lines start penetrating through the electrode apertures only when the plasma is formed in the adjacent previous gap. The potential lines help the electrons to run out through the electrode apertures and have collision process for the ionization in the next gaps. The radial expansion of the electrons and ions has also been analyzed which depends on the profile of equipotential contour lines. The expansion of ions is relatively more compared to electrons at the time of breakdown and plasma formation in the gaps. The expansions of electrons and ions are less in the first and last gap compared to the intermediate gaps. The equipotential contour lines determine the successive breakdown and discharge processes in the multigap PD-PCE source, which are required for the generation of efficient plasma, and energetic and high-density PS discharge-based electron beams.
Adaptive Integral Terminal Sliding Mode Control for Automobile Electronic Throttle via an Uncertainty Observer and Experimental Validation

A robust adaptive integral terminal sliding mode (AITSM) control scheme with an uncertainty observer (UO) is developed for automobile electronic throttle (AET) systems. Distinguished from the ordinary sliding mode (SM)-based AET control systems, by using a novel integral terminal sliding surface (SS) to force the closed-loop system to start on the SS at the very beginning, an excellent error convergence and tracking accuracy as well as robustness of the closed-loop system against uncertainties and nonlinearities including transmission friction, return spring limp-home, and gear backlash can be assured. Also, in order to achieve a stably excellent performance for different tracking commands, the sliding parameters are updated by the designed adaptive laws in Lyapunov sense. Moreover, for reducing the control chattering caused by the large switching gain in conventional SM control, an SM-based UO is introduced to provide with the online estimation for the system lumped uncertainty and conduct the feed-forward compensation in the control design. In addition, model-free robust exact differentiators (MRED) are presented to obtain the accurate angular velocity and acceleration information from the unique angle sensors with measurement noises. Not only the comparative experimental results from a real-time digital signal processor (DSP)-based AET plant but also the quantitive root mean square (RMS) values and the maximum (MAX) values of the sampled tracking errors are demonstrated to validate the superior performance of the proposed control. In particular, in the disturbance rejection test by combining trapezium and sinusoidal reference commands, the proposed control exhibits the smallest RMS error values of 0.6832 deg (37% and 27% of the ones of the nonsingular terminal sliding mode and the proportional-integral-derivative controllers), and the smallest MAX values of 2.9352 deg (67% and 35% of the ones of the comparative controllers, respectively).
Trait Mindfulness and Wellness in Multiple Sclerosis

Abstract Multiple sclerosis (MS) is a chronic, progressive, autoimmune, neurodegenerative disorder that can interfere with physical and psychological functioning, negatively affecting health-related quality of life (HRQoL). Fostering mindfulness may mitigate the negative consequences of MS on HRQoL. The relationship between mindfulness, mood and MS-related quality of life was investigated. In total, 52 individuals with MS completed questionnaires to examine the relationship between trait mindfulness and wellness. Higher levels of trait mindfulness were associated with better HRQoL, lower depression and anxiety, lower fatigue impact and fewer perceived cognitive deficits. Mindfulness interventions have the potential to enhance wellness in those living with MS. RÉSUMÉ États de pleine conscience et de bien-être chez des patients atteints de sclérose en plaques. La sclérose en plaques (SP) est une maladie chronique, évolutive, auto-immune et neuro-dégénérative qui peut perturber le fonctionnement physique et psychologique d’une personne, affectant ainsi négativement sa qualité de vie liée à la santé (QVLS). À cet égard, il est possible que le fait de favoriser chez des patients un état de pleine conscience (mindfulness) puisse atténuer les conséquences négatives de la SP sur la QVLS. Le lien entre un état de pleine conscience, l’humeur et la qualité de vie de ceux et celles atteints de la SP a été étudié. Ainsi, cinquante-deux individus aux prises avec la SP ont répondu à des questionnaires afin qu’on puisse analyser la relation existant entre les aspects se rapportant à un état de pleine conscience et le bien-être. Des niveaux plus élevés d’état de pleine conscience ont ainsi été associés à une meilleure QVLS, à des niveaux moins élevés de dépression et d’anxiété, à un impact moins important de la fatigue et à un nombre moins important de déficits cognitifs tels que perçus par les patients. En somme, des interventions focalisant sur un état de pleine conscience ont le potentiel d’améliorer le bien-être des personnes vivant avec la SP.
Ethical Considerations in Adaptive Design Clinical Trials

Adaptive design clinical trial methodologies offer both opportunities and challenges for observing basic ethical principles in human subject research. Using both published and unpublished adaptive design clinical trials, we have selected and reviewed examples of clinical trials with different design adaptations to discuss the ethical obstacles presented and often successfully resolved by these approaches, including (1) confirmatory trials for treatments widely accepted on the basis of uncontrolled case series or open-label trials (clinical equipoise and “justice” in the sense of which trial groups will “receive the benefits of research and bear its burdens”) (infantile hemangioma/propranolol); (2) interim results analysis by unblinded data monitoring committees (“withholding information necessary to make a considered judgment” [“respect for persons”] versus compromising the trial’s scientific basis) (BIG 1-98); (3) adaptations involving sample size reassessment or dose adjustment via dropping or adding treatment arms, allowing fewer subjects to produce statistically significant results, fewer subjects treated with ineffective/toxic doses, and more subjects given doses showing tolerance and treatment activity (“beneficence” or “protecting from harm and making efforts to secure wellbeing”) (ECMO, Neuromyelitis Optica); (4) adaptive randomization inferential problems balanced against ethical benefits (trastuzumab vs taxane in advanced gastric cancer; ADVENT); (5) more efficient allocation of societal resources for research, in both public and commercial realms, versus uncertain regulatory acceptance (indicaterol; VALOR); and (6) platform, umbrella, and basket trials offering additional efficiencies (I-SPY II, BATTLE, Lung-MAP). The importance of careful design, meticulous planning, and rigorous ethical review of adaptive design trials on a case-by-case basis cannot be overemphasized.
Computational Intelligence Techniques in Smart grid planning and operation: A Survey

The Smart Grids are the future vision of the electric power system with integrated communication, protection, control and sensing technologies. With the introduction of new technologies which constitute the smart grid like demand response, demand side management, electric vehicles, energy storage systems, distributed energy resources, integration of renewable energy resources, and forecasting methods like artificial neural networks, deep learning methods etc, the scope of planning and operation of a smart grid has broadened. The new technologies bring in the need for better tools for solving the planning and operation problems. This paper aims to provide a survey of the works related to some of the smart grid components and classifies the works based on the computational intelligence tools used in solving the planning or operation problem.
Temporal Convolutional Neural Network for Gesture Recognition

Convolutional Neural Network (CNN) brings us advantages to extract image features. The Long Short Term Memory (LSTM) is a natural choice to construct time sequence models. We combine these two methods to generate an end-to-end model for gesture recognition. In this study, we propose a neural network structure, using the general CNN network to extract frame-level spatial features, and using LSTM to extract time sequence features. We name this network Temporal Convolution Neural Network (TCNN). Our experiments are performed with VIVA Gesture Dataset, and this dataset has 19 gestures, labeled by 8 people. Through 8-cross-fold validation, the network structure we propose has better performance than the state of art methods like 3DCNN. Meanwhile, we compare the results conducted with different general CNNs. That is, the network based on ReNet50 has the accuracy of 82.3% while light and shallow network MobileNet has the accuracy of 60%.
Dynamic Gallager-Humblet-Spira Algorithm for Wireless Sensor Networks

The problem of constructing and maintaining a tree topology in a distributed manner is a challenging task in WSNs. This is because the nodes have limited computational and memory resources and the network changes over time. We propose the Dynamic Gallager-Humblet-Spira (D-GHS) algorithm that builds and maintains a minimum spanning tree. To do so, we divide D-GHS into four phases, namely neighbor discovery, tree construction, data collection, and tree maintenance. In the neighbor discovery phase, the nodes collect information about their neighbors and the link quality. In the tree construction, DGHS finds the minimum spanning tree by executing the GallagerHumblet-Spira algorithm. In the data collection phase, the sink roots the minimum spanning tree at itself, and each node sends data packets. In the tree maintenance phase, the nodes repair the tree when communication failures occur. The emulation results show that D-GHS reduces the number of control messages and the energy consumption, at the cost of a slight increase in memory size and convergence time.