A performance evaluation of pruning effects on hybrid neural network

In this paper, we explore the pruning effects on a hybrid mode sequential learning algorithmnamely FuzzyARTMAP-prunable Radial Basis Function (FAM-PRBF) that utilizes FuzzyARTMAP to learn a training dataset and Radial Basis Function Network (RBFN) to performregression and classification. The pruning algorithm is used to optimize the hidden layer ofthe RBFN. The experimental results show that FAM-PRBF has successfully reduced thecomplexity and computation time of the neural network.Keywords: pruning; radial basis function network; fuzzy ARTMAP

Sequential Keystroke Behavioral Biometrics for Mobile User Identification via Multi-view Deep Learning

With the rapid growth in smartphone usage, more organizations begin to focus on providing better services for mobile users. User identification can help these organizations to identify their customers and then cater services that have been customized for them. Currently, the use of cookies is the most common form to identify users. However, cookies are not easily transportable (e.g., when a user uses a different login account, cookies do not follow the user). This limitation motivates the need to use behavior biometric for user identification. In this paper, we propose DEEPSERVICE, a new technique that can identify mobile users based on user's keystroke information captured by a special keyboard or web browser. Our evaluation results indicate that DEEPSERVICE is highly accurate in identifying mobile users (over 93% accuracy). The technique is also efficient and only takes less than 1 ms to perform identification.Comment: 2017 Joint European Conference on Machine Learning and Knowledge Discovery in Database

Future Frontiers in Organic Synthesis

The role of organic synthesis to the mankind is of paramount importance since the early nineteen century [1]. In 1828, Friedrich Wöhler discovered the synthesis of urea from ammonium cyanate, marking the starting point of modern organic synthesis. Wöhler concluded to his mentor Jöns Jacob Berzelius, "I cannot, so to say, hold my chemical water and must tell you that I can make urea without thereby needing to have kidneys, or anyhow, an animal, be it human or dog". Since then, organic synthesis has become an indispensable tool in industries such as petrochemicals, pharmaceutical, flavors, fragrances, agrochemical, and others. This is evident by the number of Nobel prizes awarded to organic chemists. The Nobel Prize in Chemistry 2001 was awarded to William S. Knowles, Ryoji Noyori, and K. Barry Sharpless for their work in asymmetric synthesis. This was followed by the award of the Nobel Prize in Chemistry 2005 to Yves Chauvin, Robert H. Grubbs and Richard R. Schrock "for the development of the metathesis method in organic synthesis". And just recently, Richard F. Heck, Ei-ichi Negishi and Akira Suzuki won the Nobel Prize in Chemistry 2010 for “palladium-catalyzed cross couplings in organic synthesis”

Nano lab-on-chip systems for biomedical and environmental monitoring

In recent years, nano lab-on-chip (NLOC) has emerged as a powerful tool for biosensing and an active area of research particularly in DNA genetic and genetic related investigations. Compared with conventional sensing techniques, distinctive advantages of using NLOC for biomedicine and other related area include ultra-high sensitivity, higher throughput, in-situ monitoring and lower cost. This review aims to summarize recent  advancements in two major types of NLOC sensing approaches, label and labelled free NLOC, as well as their biomedical applications. The state-of-the-art on how these sensors interface with nano/microfluidics is then presented and the latest papers in the area summarized and also proposal to develop compact NLOC with four different sensing elements with two different mechanisms, common and separate padding is prospected.Keywords: Nano lab-on-chip, in-situ, nano/microfluidics, sensors, DNA African Journal of Biotechnology Vol. 12(36), pp. 5486-549

High frame rate contrast enhanced ultrasound imaging for slow flow: influence of ultrasound pressure and flow rate on bubble disruption and image persistence

Contrast-enhanced ultrasound (CEUS) utilising microbubbles shows great potential for visualising lymphatic vessels and identifying sentinel lymph nodes (SLNs) which are valuable for axillary staging in breast cancer patients. However, current CEUS imaging techniques have limitations that affect the accurate visualisation and tracking of lymphatic vessels and SLN. (i) Tissue artefacts and bubble disruption can reduce the image contrast. (ii) Limited spatial and temporal resolution diminishes the amount of information that can be captured by CEUS. (iii) The slow lymph flow makes Doppler-based approaches less effective. This work evaluates on a lymphatic vessel phantom the use of high frame rate (HFR) CEUS for the detection of lymphatic vessels where flow is slow. Specifically, the work particularly investigates the impact of key factors in lymphatic imaging, including ultrasound pressure and flow velocity as well as probe motion during vessel tracking, on bubble disruption and image contrast. Experiments were also conducted to apply HFR CEUS imaging on vasculature in a rabbit popliteal lymph node (LN). Our results show that (i) HFR imaging and singular value decomposition (SVD) filtering can significantly reduce tissue artefacts in the phantom at high clinical frequencies; (ii) the slow flow rate within the phantom makes image contrast and signal persistence more susceptible to changes in ultrasound amplitude or mechanical index (MI), and an MI value can be chosen to reach a compromise between images contrast and bubble disruption under slow flow condition; (iii) probe motion significantly decreases image contrast of the vessel, which can be improved by applying motion correction before SVD filtering; (iv) the optical observation of the impact of ultrasound pressure on HFR CEUS further confirms the importance of optimising ultrasound amplitude and (v) vessels inside rabbit LN with blood flow less than 3 mm/s are clearly visualised

DeepMood: Modeling Mobile Phone Typing Dynamics for Mood Detection

The increasing use of electronic forms of communication presents new opportunities in the study of mental health, including the ability to investigate the manifestations of psychiatric diseases unobtrusively and in the setting of patients' daily lives. A pilot study to explore the possible connections between bipolar affective disorder and mobile phone usage was conducted. In this study, participants were provided a mobile phone to use as their primary phone. This phone was loaded with a custom keyboard that collected metadata consisting of keypress entry time and accelerometer movement. Individual character data with the exceptions of the backspace key and space bar were not collected due to privacy concerns. We propose an end-to-end deep architecture based on late fusion, named DeepMood, to model the multi-view metadata for the prediction of mood scores. Experimental results show that 90.31% prediction accuracy on the depression score can be achieved based on session-level mobile phone typing dynamics which is typically less than one minute. It demonstrates the feasibility of using mobile phone metadata to infer mood disturbance and severity.Comment: KDD 201

Triggering Mechanisms for Motor Actions: The Effects of Expectation on Reaction Times to Intense Acoustic Stimuli

Motor actions can be released much sooner than normal when the go-signal is of very high intensity (>100 dBa). Although statistical evidence from individual studies has been mixed, it has been assumed that sternocleidomastoid (SCM) muscle activity could be used to distinguish between two neural circuits involved in movement triggering. We summarized meta-analytically the available evidence for this hypothesis, comparing the difference in premotor reaction time (RT) of actions where SCM activity was elicited (SCM+ trials) by loud acoustic stimuli against trials in which it was absent (SCM- trials). We found ten studies, all reporting comparisons between SCM+ and SCM- trials. Our mini meta-analysis showed that premotor RTs are faster in SCM+ than in SCM- trials, but the effect can be confounded by the variability of the foreperiods employed. We present experimental data showing that foreperiod predictability can induce differences in RT that would be of similar size to those attributed to the activation of different neurophysiological pathways to trigger prepared actions. We discuss plausible physiological mechanisms that would explain differences in premotor RTs between SCM+ and SCM- trials

Recurrence and progression of periodontitis and methods of management in long-term care: A systematic review and meta-analysis

Aim: To systematically review the literature to evaluate the recurrence of disease of people in long-term supportive periodontal care (SPC), previously treated for periodontitis, and determine the effect of different methods of managing recurrence. The review focused on stage IV periodontitis. Materials and methods: An electronic search was conducted (until May 2020) for prospective clinical trials. Tooth loss was the primary outcome. Results: Twenty-four publications were retrieved to address recurrence of disease in long-term SPC. Eight studies were included in the meta-analyses for tooth loss, and three studies for disease progression/recurrence (clinical attachment level [CAL] loss ≥2 mm). For patients in SPC of 5–20 years, prevalence of losing more than one tooth was 9.6% (95% confidence interval [CI] 5%–14%), while experiencing more than one site of CAL loss ≥2 mm was 24.8% (95% CI 11%–38%). Six studies informed on the effect of different methods of managing recurrence, with no clear evidence of superiority between methods. No data was found specifically for stage IV periodontitis. Conclusions: A small proportion of patients with stage III/IV periodontitis will experience tooth loss in long-term SPC (tendency for greater prevalence with time). Regular SPC appears to be important for reduction of tooth loss. No superior method to manage disease recurrence was found

Removal of chlorinated phenol from aqueous solution utilizing activated carbon derived from papaya (carica papaya) seeds

Activated carbons (ACs) were prepared from papaya seeds with different dry weight impregnation ratios of zinc chloride (ZnCl2) to papaya seeds by using a two-stage self-generated atmosphere method. The papaya seeds were first semi-carbonized in a muffle furnace at 300 oC for 1 h and then impregnated with ZnCl2 before activation at 500 oC for 2 h. Several physical and chemical characteristics such as moisture, ash, pH, functional groups, morphological structure and porosity of prepared ACs were studied and presented here. AC2, with the impregnation ration of 1 : 2 (papaya seeds: ZnCl2), yielded a product that had the highest adsorption capacity, 91.75%, achieved after 180min contact time. The maximum Brunauer, Emmett and Teller (BET) surface area of AC2 was 546m2/g. Adsorption studies indicated that AC2 complied well with the Langmuir isotherm (qm=39.683mg g-1) and the pseudo-second-order (qe=29.36mg g-1). This indicated that chemisorption was the primary adsorption method for AC2. The intraparticle diffusion model proved that the mechanism of adsorption was separated into two stages: the instantaneous stage and the gradual adsorption stage. Overall, this work demonstrated the suitability of using papaya seeds as a precursor to manufacture activated carbon

Acoustic wave sparsely activated localization microscopy (AWSALM): super-resolution ultrasound imaging using acoustic activation and deactivation of nanodroplets

Photo-activated localization microscopy (PALM) has revolutionized the field of fluorescence microscopy by breaking the diffraction limit in spatial resolution. In this study, “acoustic wave sparsely activated localization microscopy (AWSALM),” an acoustic counterpart of PALM, is developed to super-resolve structures which cannot be resolved by conventional B-mode imaging. AWSALM utilizes acoustic waves to sparsely and stochastically activate decafluorobutane nanodroplets by acoustic vaporization and to simultaneously deactivate the existing vaporized nanodroplets via acoustic destruction. In this method, activation, imaging, and deactivation are all performed using acoustic waves. Experimental results show that sub-wavelength micro-structures not resolvable by standard B-mode ultrasound images can be separated by AWSALM. This technique is flow independent and does not require a low concentration of contrast agents, as is required by current ultrasound super resolution techniques. Acoustic activation and deactivation can be controlled by adjusting the acoustic pressure, which remains well within the FDA approved safety range. In conclusion, this study shows the promise of a flow and contrast agent concentration independent super-resolution ultrasound technique which has potential to be faster and go beyond vascular imaging