Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of Low Power BioSensor Read-Out Circuit Schemes for Implantable Systems

This paper presents two low-power sensor read-out circuit schemes for implantable biosensor applications. The proposed work presents the design of ASK and FSK schemes in bulk CMOS technology. Either scheme consists of a data generator block and modulator block. The first version of the circuit is designed in a 0. 35μm CMOS process and it can generate an amplitude-shift-keying (ASK) signal while consuming 400 μW of power with a 1.5-V power supply. The second version of the readout circuit is designed in a 0. 5μm CMOS process and produces a frequencyshift-keying (FSK) signal while consuming 1.675 mW of power with a 2.5-V power supply. The prototype circuitries has potential applications in the monitoring of blood glucose level, lactate in the bloodstream, and pH or oxygen in a physiological system/ environment.
Two Word Reordering Strategies in English-to-Chinese Translation

In English-to-Chinese machine translation, reordering mistakes are frequently caused by miss-located prepositional phrases(PP). In English, a PP is often located after its attached host, while in Chinese things are the opposite. Recent phrase-based MT approaches tend to ignore such syntax information. In our work, we propose two strategies to resolve the above problem: first, for MT that adopts the lexical reordering model, we modify the reordering orientations from Monotone-Swap-Discontinuous (MSD) to MonotoneLeftDiscontinuous-RightDiscontinuous (MLR), which is more efficient in guiding the reordering direction of PP; second, for MT using the pre-reordering approach, we apply PP attachment disambiguation to find the host of each PP and then pre-reorder them precisely. The superiority of the two approaches is verified in our empirical studies. Our work has already been applied in Youdao online translation system (http://fanyi.youdao.com).
Clickable and interactive video system using HTML5

Interactive video aims to make users feel more involved in an information search, so that they will try to obtain deeper information without feeling forced. Therefore, interactive video is one of the appropriate approaches that can be used in information dissemination process. In this research, we have successfully made an interactive video system in the form of clickable video where user can click some parts of the video while the video is playing. This event links user to deeper information in a pop up area. Video streaming is conducted using HTTP streaming mechanism through a web browser that supports HTML5 without additional plug-in or video player. The clickable interactive video system was made using HTML5 and JavaScript. Canvas element in HTML5 is the main component used to make the video streaming clickable and interactive. The experiment demonstrates that the clickable video streaming in MP4 format can be successfully played on Chrome, Safari and Internet Explorer Web browser and it also shown that Google Chrome has the fastest video loading time.
Combination of morphological, Local Binary Pattern Variance and color moments features for Indonesian medicinal plants identification

We propose a new method for Indonesian medicinal plants identification using combination of some leaf features, i.e. texture, shape, and color. Local Binary Pattern Variance (LBPV) is used to extract leaf texture, morphological feature is used to extract leaf shape, and color moment is used to extract leaf color distribution. In the experiment we used 51 species of Indonesian medicinal plants and each species consists of 48 images, so the total images used in this research are 2,448 images. Combination of leaf feature is done using Product Decision Rule (PDR) and classification of medicinal plants is done using Probabilistic Neural Network (PNN). The experimental results show that the combination of the morphological, LBPV, and color moments features can improve the accuracy of medicinal plants identification. This research is important to enhance utilization of Indonesian medicinal plants.
FAULT DETECTION AND DIAGNOSIS IN TURBINE ENGINES USING HIDDEN MARKOV MODELS

Accurate fault detection and diagnosis in turbine engines is key to effective maintenance and improved availability of systems dependent on these engines. In this paper, we present a novel method for accurate fault detection and diagnosis using Hidden Markov Models (HMMs). In particular, we focus on engine faults that are manifest in transient operating conditions such as engine startup and acceleration. HMMs are stochastic signal models that are effective in modeling transient signals. They are developed with engine data collected under nominal operating conditions. Engine data representing different fault conditions are used to develop the fault HMMs; a separate model is developed for each of the faults. Once the nominal and fault HMMs are developed, new engine data collected from the engine are evaluated against the HMMs and a determination is made whether a fault is indicated. Here, we demonstrate our HMM-based fault detection and diagnosis approach on engine speed profiles taken from a real engine. Further, the effectiveness of the HMM-based approach is compared with a neural-network-based approach and a method based on using principal component analysis in conjunction with a neural network approach.
Putting Simple Hierarchy into Ant Foraging: Cluster-Based Soft-Bots

This paper revisits a traditional Ant Foraging algorithm and proposes a Cluster-based Softbots algorithm to address the performance issues caused by constraints of random autonomous search featured in most swarm intelligence-based algorithms. A simple hierarchy is introduced to regulate the unfolding of dynamically changing swarm-like behaviors. Comparative experiments for Ant Foraging and the proposed Cluster-based Softbots are described. The results demonstrate that Softbots have significant comparative advantages over a traditional Ant Foraging algorithm on the benchmark criteria in the presented experimental settings. It is shown that Softbots are more suitable for resource-lean search circumstances whereas not many individual agents can be allocated.
SURVEy : Techniques for Aging Problems in Face Recognition

Aashmi Scholar, Computer Science Engg. Dept. Moradabad Institute of Technology Moradabad, U.P., INDIA E-mail: aashmichaudhary@gmail.com Sakshi Sahni Scholar, Computer Science Engg. Dept. Moradabad Institute of Technology Moradabad, U.P., INDIA E-mail: sakshisahni92@gmail.com Sakshi Saxena Scholar, Computer Science Engg. Dept. Moradabad Institute of Technology Moradabad, U.P., INDIA E-mail: saxena.sakshi2511992@gmail.com
Infant Sleep Disorders and Attachment: Sleep Problems in Infants with Insecure-Resistant Versus Insecure-Avoidant Attachments to Mother

Investigations of the development of infant sleep patterns often rely on maternal reports concerning the frequency and pattern of infant night wakings as an indicator of the underlying quality and organization of infant sleep (1-7). These studies suggest that infants usually arouse one or more times for varying periods of time each night. During the first few months of life 95% of infants signal or cry after a nighttime awakening and will not return to sleep without a maternal interaction. By age 15 months, however, approximately 70% of infants are able to self-soothe and return to sleep without maternal contact. This still leaves about 30% of infants with frequent problematic night wakings during the second year of life. Despite its prevalence in infancy, clinical correlates of night wakings are not well Infant Sleep Disorders and Attachment: Sleep Problems in Infants with InsecureResistant Versus Insecure-avoidant Attachments to Mother
Does a programmer's activity indicate knowledge of code?

The practice of software development can likely be improved if an externalized model of each programmer's knowledge of a particular code base is available. Some tools already assume a useful form of such a model can be created from data collected during development, such as expertise recommenders that use information about who has changed each file to suggest who might answer questions about particular parts of a system. In this paper, we report on an empirical study that investigates whether a programmer's activity can be used to build a model of what a programmer knows about a code base. In this study, nineteen professional Java programmers completed a series of questionnaires about the code on which they were working. These questionnaires were generated automatically and asked about program elements a programmer had worked with frequently and recently and ones that he had not. We found that a degree of interest model based on this frequency and recency of interaction can often indicate the parts of the code base for which the programmer has knowledge. We also determined a number of factors that may be used to improve the model, such as authorship of program elements, the role of elements, and the task being performed.
Source separation contrasts using a reference signal

In this letter, we consider contrast functions, which are useful tools for the sources separation problem. We present new generalized contrasts by considering a so-called reference signal. In particular, this allows us to show that a criterion recently proposed in the literature is a contrast. Furthermore, a link with a joint-diagonalization criterion is also emphasized. Finally, we show that another classical contrast can also be extended by considering a reference signal.
Open innovation: current status and research opportunities

Interest in open innovation (OI) as a field of research has grown exponentially since the phrase was coined by Chesbrough in his 2003 book, with numerous articles, special issues, books, and conference sessions. Various reviews of the literature have summarized prior work, offered new frameworks, and identified opportunities for future research. Here we summarize these opportunities, which include more research on outbound OI, the role of open innovation in services, and network forms of collaboration such as consortia, communities, ecosystems, and platforms. Research should also examine the use of OI by small, new, and not-for-profit organizations, as well as the linkage of individual actions and motivations to open innovation. Other opportunities include better measuring the costs, benefits, antecedents, mediators and moderators of the effects of OI on performance, and understanding why and how OI is rejected, abandoned, or fails. Finally, we consider how OI can be better linked to prior theoretical research, including topics such as absorptive capacity, user innovation, resources, dynamic capabilities, business models, and the definition of the firm.
Using a neural network and genetic algorithm to extract decision rules

Rule extraction from neural networks often focusses on exact equivalence and is often tested on relatively small canonical examples. We apply genetic algorithms to the extract approximate rules from neural networks. The method is robust and works with large networks. We compare the results with rules obtained using state of the art decision tree methods and achieve superior performance to straight forward application of the WEKA implementation of the C5 algorithm, J48.PART.
A stochastic model for tumor heterogeneity

Phenotype variations define heterogeneity of biological and molecular systems, which play a crucial role in several mechanisms. Heterogeneity has been demonstrated in tumor cells. Here, samples from blood of patients affected from colon tumor were analyzed and fished with a microfluidic assay based on galactose active moieties, and incubated, for culturing, in SCID mice. Following the experimental investigation, a model based on Markov theory was implemented and discussed to explain the equilibrium existing between phenotypes of subpopulations of cells sorted using the microfluidic assay. The model in combination with the experimental results had many implications for tumor heterogeneity. It displayed interconversion of phenotypes, as observed after experiments. The interconversion generates of metastatic cells and implies that targeting the CTCs will be not an efficient method to prevent tumor recurrence. Most importantly, understanding the transitions between cell phenotypes in cell population can boost the understanding of tumor generation and growth.
2016 Ieee International Conference on Big Data (big Data) Evaluating the Impacts of Code-level Performance Tunings on Power Efficiency

—As the power consumption of HPC systems will be a primary constraint for exascale computing, a main objective in HPC communities is recently becoming to maximize power efficiency (i.e., performance per watt) rather than performance. Although programmers have spent a considerable effort to improve performance by tuning HPC programs at a code level, tunings for improving power efficiency is now required. In this work, we select two representative HPC programs (Graph500 and SDPARA) and evaluate how traditional code-level performance tunings applied to these programs affect power efficiency. We also investigate the impacts of the tunings on power efficiency at various operating frequencies of CPUs and/or GPUs. The results show that the tunings significantly improve power efficiency, and different types of tunings exhibit different trends in power efficiency by varying CPU frequency. Finally, the scalability and power efficiency of state-of-the-art Graph500 implementations are explored on both a single-node platform and a 960-node supercomputer. With their high scalability, they achieve 27.43 MTEPS/Watt with 129.76 GTEPS on the single-node system and 4.39 MTEPS/Watt with 1,085.24 GTEPS on the supercomputer.
Sa-am Five-element Acupuncture and Hwangyeon- haedoktang Pharmacopuncture Treatment for an Essential Tremor: Three Case Reports

The purpose of this study was to report the effect of a combination of Sa-am five-element acupuncture and eight-principle pharmacopuncture (EPP) for the treatment of an essential tremor (ET). This study reviewed the medical records treated at OO Korean medical hospital for ET by using diverse types of acupuncture without herbal medicine, other types of physical therapy, and western medication related ET or Parkinson’s disease and was performed after the approval of the institutional review board (IRB). The three cases that were finally selected were then extracted and reviewed. The three cases that were finally selected involved three women in their 70s to 80s. The evaluation of the progress was made by using the numeric rating scale. A combined treatment, the method of liver excess (肝乘格), from amongSa-am five-element acupuncture, and Hwangyeonhaedoktang ePP at CV23 and CV17, was applied to all cases. In all three cases, the ET was improved, and recurred ETs improved with the same treatment. The results suggest that the combined treatment of Sa-am five-element acupuncture and Hwangyeonhaedoktang ePP may be effective for treating an ET, even though this conclusion is based on only three cases.
In Vitro Screening for Abiotic Stress Tolerance in Potent Biocontrol and Plant Growth Promoting Strains of Pseudomonas and Bacillus spp.

Plant growth promoting rhizobacteria (PGPR) has been identified as a group of microbes that are used for plant growth enhancement and biocontrol for management of plant diseases. The inconsistency in performance of these bacteria from laboratory to field conditions is compounded due to the prevailing abiotic stresses in the field. Therefore, selection of bacterial strains with tolerance to abiotic stresses would benefit the end-user by successful establishment of the strain for showing desired effects. In this study we attempted to isolate and identify strains of Bacillus and Pseudomonas spp. with stress tolerance and proven ability to inhibit the growth of potential phytopathogenic fungi. Screening of bacterial strains for high temperature (50°C), salinity (7% NaCl), and drought (−1.2 MPa) showed that stress tolerance was pronounced less in Pseudomonas isolates than in Bacillus strains. The reason behind this could be the formation of endospores by Bacillus isolates. Tolerance to drought was high in Pseudomonas strains than the other two stresses. Three strains, P8, P20 and P21 showed both salinity and temperature tolerance. P59 strain possessed promising antagonistic activity and drought tolerance. The magnitude of antagonism shown by Bacillus isolates was also higher when compared to Pseudomonas strains. To conclude, identification of microbial candidate strains with stress tolerance and other added characteristic features would help the end-user obtain the desired beneficial effects.
Parasitic tracking: Enabling ubiquitous tracking through existing infrastructure

For a mixed reality user the available tracking quality usually is a balance between technical requirements, user needs and economic factors, as most tracking methodologies require setup of dedicated infrastructure. As pervasive and ubiquitous computing grow in importance, so does the associated information infrastructure. Combining these two facts we present strategies to leverage existing information infrastructure and exploit its characteristics to empower users with services to determine their position, without the need for dedicated infrastructure.
Can Eye Help You?: Effects of Visualizing Eye Fixations on Remote Collaboration Scenarios for Physical Tasks

In this work, we investigate how remote collaboration between a local worker and a remote collaborator will change if eye fixations of the collaborator are presented to the worker. We track the collaborator's points of gaze on a monitor screen displaying a physical workspace and visualize them onto the space by a projector or through an optical see-through head-mounted display. Through a series of user studies, we have found the followings: 1) Eye fixations can serve as a fast and precise pointer to objects of the collaborator's interest. 2) Eyes and other modalities, such as hand gestures and speech, are used differently for object identification and manipulation. 3) Eyes are used for explicit instructions only when they are combined with speech. 4) The worker can predict some intentions of the collaborator such as his/her current interest and next instruction.
English prepositional passives in HPSG

This paper provides a detailed syntactic description of English prepositional passives (also known as " pseudopassives ") and discusses their formal treatment in HPSG. The empirical overview includes a discussion of the familiar (but unformalizable) notion of semantic cohesiveness, as well as new observations about the possibility of elements intervening between V and P. Two formal approaches to the syntactic aspects of the problem are then outlined and compared—one relying on lexical rules, the other taking advantage of HPSG's capacity to express constraints on constructions. English has an exceptionally rich variety of preposition stranding phenomena, perhaps the most striking of which is the prepositional passive—the possibility of passivizing the object of a preposition instead of the direct object of a verb. (24) a. You can rely [on David] to do get the job done. b. David i can be relied on t i to get the job done. Here the NP David, initially the complement of on, is realized as the subject of the passive verb relied, leaving the preposition behind. 1 It is often suggested that the underlined verb and preposition in this construction form a kind of " compound " , an intuitive notion that is open to many 1 I will occasionally use the symbol " t " to mark the " deep " position of the passive subject, in cases where there might be ambiguity. This is deliberately reminiscent of NP-trace in transforma-tional analyses, but here it should be understood only as a expository device with no theoretical strings attached.
Transforming RNA-Seq Data to Improve the Performance of Prognostic Gene Signatures

Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques.
Evidence in Favor of a Calcium-Sensing Receptor in Arterial Endothelial Cells: Studies With Calindol and Calhex 231

Small increases in extracellular Ca2+ dilate isolated blood vessels. In the present study, the possibility that a vascular, extracellular Ca2+-sensing receptor (CaSR) could mediate these vasodilator actions was investigated. Novel ligands that interact with the CaSR were used in microelectrode recordings from rat isolated mesenteric and porcine coronary arteries. The major findings were that (1) raising extracellular Ca2+ or adding calindol, a CaSR agonist, produced concentration-dependent hyperpolarizations of vascular myocytes, actions attenuated by Calhex 231, a negative allosteric modulator of CaSR. (2) Calindol-induced hyperpolarizations were inhibited by the intermediate conductance, Ca2+-sensitive K+ (IKCa) channel inhibitors, TRAM-34, and TRAM-39. (3) The effects of calindol were not observed in the absence of endothelium. (4) CaSR mRNA and protein were present in rat mesenteric arteries and in porcine coronary artery endothelial cells. (5) CaSR and IKCa proteins were restricted to caveolin-poor membrane fractions. We conclude that activation of vascular endothelial CaSRs opens endothelial cell IKCa channels with subsequent myocyte hyperpolarization. The endothelial cell CaSR may have a physiological role in the control of arterial blood pressure.
Detection and analysis of breast masses from MRIs and dual energy contrast enhanced mammography

This paper focuses on breast masses analysis from two different modalities: Magnetic Resonance Imaging (MRI) and Dual-Energy Contrast Enhanced Digital Mammography (DECEDM). After the segmentation step, a set of texture and shape features are extracted from both MRI and DECEDM. Then textural and morphological information extracted from the two modalities are combined in order to improve breast cancer detection. Achieved results show that features combination extracted from two different breast images modalities can give a better characterization of breast cancer with a CCR of 96%.