Miracle-dz/UniFAR-FTUs huggingface dataset:
A 0.8–1.2 V 10–50 MS/s 13-bit Subranging Pipelined-SAR ADC Using a Temperature-Insensitive Time-Based Amplifier

This paper presents an energy-efficient 13-bit 10–50 MS/s subranging pipelined-successive approximation register (SAR) analog-to-digital converter (ADC) with power supply scaling. In the presented ADC, an SAR-assisted subranging floating capacitive DAC switching algorithm reduces switching energy along with enhanced linearity and speed in the first-stage SAR ADC. A following temperature-insensitive time-based residue amplifier realizes open-loop residual amplification without background calibration, while maintaining the benefits of dynamic operation and noise filtering. Furthermore, asynchronous SAR control logic employs a pre-window technique to accelerate SAR logic operations. The prototype ADC was fabricated in a 130-nm CMOS process with an active area of 0.22 mm2. With a 1.2-V power supply and a Nyquist frequency input, the ADC consumes 1.32 mW at 50 MS/s and achieves signal-to-noise and distortion ratio and spurious-free dynamic range of 69.1 and 80.7 dB, respectively. The operating speed is scalable from 10 to 50 MS/s with a scalable power supply range of 0.8–1.2 V. Walden FoMs of 4–11.3 fJ/conversion-step are achieved.
GHFHC: Generalized Hesitant Fuzzy Hierarchical Clustering Algorithm

Dealing with uncertainty is an undeniable challenge in the real‐world problems. In this paper, we focus on hesitant environment such as generalized hesitant fuzzy sets introduced by Qian et al. So we propose a new generalized hesitant fuzzy hierarchical clustering (GHFHC) algorithm based on Atanassov's intuitionistic fuzzy set theory. We extend conventional hierarchical clustering, which just works on the crisp data, and introduce a clustering algorithm, which can be applied on large data set with generalized hesitant fuzzy data. The run time of the GHFHC algorithm shows that its computational complexity will be low. Also, the GHFHC algorithm produces the clusters with arbitrary shapes by using the various distance measures. Finally, an example is provided to illustrate the practicality of the proposed algorithm.
Terminal base pairs of oligodeoxynucleotides: imino proton exchange and fraying.

We have estimated the dissociation constant of the terminal base pairs of the B-DNA duplexes formed by 5'-d(CGCGATCGCG) and 5'-d(TAGCGCTA) by two methods, one based on the change in imino proton chemical shift with temperature and the other on the apparent pK shift of the imino proton, as monitored by the change in chemical shift of aromatic protons. These methods do not rely on imino proton exchange, whose rate was also measured. (1) The effect of ammonia on the imino proton exchange rate of the terminal pair of the 5'-d(CGCGATCGCG) duplex is 67 times less than on the isolated nucleoside. This provides an upper limit on the exchange rate from the closed pair. In fact, the effect is just as predicted from the dissociation constant, assuming that there is no exchange at all from the closed pair and that, as has been argued previously, external catalysts act on the open state as they do on the isolated nucleoside. The inhibition of catalyzed proton exchange in the closed pair, despite exposure of one face of the pair to solvent, is a new feature of the exchange process. It will allow determination of the dissociation constant of terminal pairs from the exchange rate. (2) Intrinsic catalysis of proton exchange is less efficient for the terminal pair than for an internal one. A possible explanation is that proton transfer across the water bridge responsible for intrinsic catalysis is slower, as expected if the open-state separation of the bases is larger in a terminal pair. This observation may lead to a direct method for the study of fraying. (3) At 0 degrees C, the dissociation constant of the second pair of the 5'-d(CGCGATCGCG) duplex is close to the square of the constant for the terminal pair, as predicted from a simple model of fraying. The enthalpy and entropy of opening of the terminal pairs may be compared with those of nearest neighbor interactions derived from calorimetry [Breslauer, K. J., et al. (1986) Proc. Natl. Acad. Sci. U.S.A. 83, 3746-3750].
Term Identification Methods for Consumer Health Vocabulary Development

Background The development of consumer health information applications such as health education websites has motivated the research on consumer health vocabulary (CHV). Term identification is a critical task in vocabulary development. Because of the heterogeneity and ambiguity of consumer expressions, term identification for CHV is more challenging than for professional health vocabularies. Objective For the development of a CHV, we explored several term identification methods, including collaborative human review and automated term recognition methods. Methods A set of criteria was established to ensure consistency in the collaborative review, which analyzed 1893 strings. Using the results from the human review, we tested two automated methods—C-value formula and a logistic regression model. Results The study identified 753 consumer terms and found the logistic regression model to be highly effective for CHV term identification (area under the receiver operating characteristic curve = 95.5%). Conclusions The collaborative human review and logistic regression methods were effective for identifying terms for CHV development.
A note on tailbiting codes and their feedback encoders

Tailbiting codes encoded by feedback convolutional encoders are studied. A condition for when tailbiting will work is given and it is described how the encoder starting state can be obtained for feedback encoders in both controller and observer canonical forms. Finally, results from a search for systematic feedback encoders that encode tailbiting codes with good decoding bit error probabilities are presented.
A low ripple on-chip charge pump for bootstrapping of the noise-sensitive nodes

Charge pump with less than 1 mV ripple of the output voltage employs on-chip capacitors with large parasitic capacitance between bottom plate and substrate and does not generate pulsed supply current or noticeable substrate noise during switching. It operates in current mode and is developed with structural approach to analog design that uses dedicated feedback loop for every important parameter
Associative Training of Hermissenda

Reflex behavior of Hermissenda in response to visual and rotational stimuli is described. It is shown that repeated association of light with rotation modifies the subsequent responses of the animals to light. This modification does not occur after the same period of light or rotation alone. The effect of the associative training is strongly dependent on the amount of daily light with which the animals are maintained.
Sequence‐based analysis of protein degradation rates

Protein turnover is a key aspect of cellular homeostasis and proteome dynamics. However, there is little consensus on which properties of a protein determine its lifetime in the cell. In this work, we exploit two reliable datasets of experimental protein degradation rates to learn models and uncover determinants of protein degradation, with particular focus on properties that can be derived from the sequence. Our work shows that simple sequence features suffice to obtain predictive models of which the output correlates reasonably well with the experimentally measured values. We also show that intrinsic disorder may have a larger effect than previously reported, and that the effect of PEST regions, long thought to act as specific degradation signals, can be better explained by their disorder. We also find that determinants of protein degradation depend on the cell types or experimental conditions studied. This analysis serves as a first step towards the development of more complex, mature computational models of degradation of proteins and eventually of their full life cycle. Proteins 2017; 85:1593–1601. © 2017 Wiley Periodicals, Inc.
Survival in sarcoidosis-associated pulmonary hypertension: the importance of hemodynamic evaluation.

OBJECTIVE Pulmonary hypertension (PH) has been associated with increased mortality in patients with advanced pulmonary sarcoidosis. Sarcoidosis-associated PH may be the result of left ventricular dysfunction (LVD) or isolated pulmonary vasculature abnormality. Our objective was to determine if the cause of PH affects survival in patients with sarcoidosis with persistent dyspnea. METHODS Patients with sarcoidosis with persistent dyspnea despite immunosuppressive therapy underwent right-sided heart catheterization. Patients with a pulmonary artery occluding pressure (PAO) ≥ 15 mm Hg were defined as having LVD. Patients were classified based on hemodynamics as no PH (pulmonary artery mean pressure [PAmean] < 25 mm Hg), PH without LVD (PAmean ≥ 25 mm Hg and PAO < 15 mm Hg), and PH with LVD (PH/LVD) (PAmean ≥ 25 mm Hg and PAO ≥ 15 mm Hg). RESULTS One hundred thirty patients were studied at one institution: 50 (38.5%) patients had PH without LVD, whereas 20 (15.4%) had PH/LVD. All patients had their diagnostic procedure at least 18 months prior to analysis. The hazard ratio (HR) for death in PH without LVD vs no PH was 10.39 (95% CI, 2.99-13.78; P < .0001). The HR for dying for PH without LVD vs PH/LVD was 3.14 (95% CI, 1.01-5.62; P < .05). The presence of stage 4 chest roentgenograms and the need for supplemental oxygen were different between the groups. In a Cox proportional hazards model, independent predictors for survival were stage 4 chest roentgenogram (P < .005) and hemodynamic group (P < .02). CONCLUSION PH without LVD was associated with increased mortality. Proper characterization of patients required hemodynamic evaluation, as 29% of sarcoidosis-associated PH was due to LVD.
On Applying Matching Tools to Large-scale Ontologies

Many existing ontology matching tools are not well scalable. In this paper, we present the Malasco system, which serves as a framework for reusing existing, non-scalable matching systems on large-scale ontologies. The results achieved with different combinations of partitioning and matching tools are discussed, and optimization techniques are examined. It is shown that the loss of result quality when matching with partitioned data can be reduced to less than 5% compared to matching with unpartitioned data.
Machine Learning based Traffic Classification using Low Level Features and Statistical Analysis

In this paper, Data mining technique is used to present the concept of attack data analysis and traffic classification. Here the system is completely a automated system that contains packet capturing, processing of multiple attack logs, labeling of network traffic based on low level features and applying the classification algorithm to build a traffic classifier which will classify the normal and malicious traffic. In this paper mixing of machine learning approach and behavior based analysis is done to valid the analysis results in a better way. Previously lot‟s of work has been done in this field to classify the network logs but all of the existing techniques such as payload based, port based classifications have their own advantages and disadvantages but classification using Machine Learning techniques is still an open field to explore and has provided an excellent results up till now. The main aim of the proposed work is to perform the passive traffic monitoring based on honeypot technology and then analyze the network attack logs to determine the intruders. We collect attack data throw honeypot system and normal user browser than we combined that attack data and develop an automated traffic classification system based on the low level features of the network traffic. This type of classification will help the IT administrators to determine the unknown attacks spreading in the IT industry.
Electrocorticography reveals the temporal dynamics of posterior parietal cortical activity during recognition memory decisions

Significance Over the past decade, human posterior parietal cortex (PPC) has been unexpectedly implicated in remembering and memory-related decision making. Functional neuroimaging indicates that memory-related responses differ across PPC, and patients with PPC lesions show subtle to significant changes in memory behavior. These surprising observations have motivated novel theorizing, yet current understanding of PPC contributions to memory is limited by the absence of temporal information about activity in PPC subregions as retrieval decisions unfold. In this study, recordings from the human brain show for the first time that distinct temporal and functional profiles of activity are present in PPC subregions as participants make recognition memory decisions. These new findings inform theories of parietal functional contributions to memory, decision making, and attention. Theories of the neurobiology of episodic memory predominantly focus on the contributions of medial temporal lobe structures, based on extensive lesion, electrophysiological, and imaging evidence. Against this backdrop, functional neuroimaging data have unexpectedly implicated left posterior parietal cortex (PPC) in episodic retrieval, revealing distinct activation patterns in PPC subregions as humans make memory-related decisions. To date, theorizing about the functional contributions of PPC has been hampered by the absence of information about the temporal dynamics of PPC activity as retrieval unfolds. Here, we leveraged electrocorticography to examine the temporal profile of high gamma power (HGP) in dorsal PPC subregions as participants made old/new recognition memory decisions. A double dissociation in memory-related HGP was observed, with activity in left intraparietal sulcus (IPS) and left superior parietal lobule (SPL) differing in time and sign for recognized old items (Hits) and correctly rejected novel items (CRs). Specifically, HGP in left IPS increased for Hits 300–700 ms poststimulus onset, and decayed to baseline ∼200 ms preresponse. By contrast, HGP in left SPL increased for CRs early after stimulus onset (200−300 ms) and late in the memory decision (from 700 ms to response). These memory-related effects were unique to left PPC, as they were not observed in right PPC. Finally, memory-related HGP in left IPS and SPL was sufficiently reliable to enable brain-based decoding of the participant’s memory state at the single-trial level, using multivariate pattern classification. Collectively, these data provide insights into left PPC temporal dynamics as humans make recognition memory decisions.
Integrating Language and Motor Function on a Humanoid Robot

In order to design an artificial entity that is able to use language naturally, a computer program that simply manipulates lexical symbols is not good enough. Using these symbols without understanding the meaning attached to them is pointless. Not only does use of natural language require a framework for computational function (the brain), but it re quires a physical embodiment. Our lab’s focus is therefore to creat e such a framework using mathematical approaches in statistical pattern recognition, as well as dynamical systems models. While the s aim to emulate the brain, the iCub humanoid robot serves as our embodied platform. Through the fusion of a rich sensorimotor periphery, we have begun to develop a cognitive architectur e capable of autonomous language acquisition.
Effect of a robotic rehabilitation device on upper limb function in a sub-acute cervical spinal cord injury population

Robotic rehabilitation devices have been suggested as a tool to increase the amount of rehabilitation delivered after a neurological injury. Clinical robotic rehabilitation studies of the upper extremity have generally focused on stroke survivors. We present the results of a multi-center pilot study where an upper-limb robotic rehabilitation device (Armeo Spring®, Hocoma AG) was incorporated into the rehabilitation program of 12 subjects with sub-acute cervical spinal cord injury (motor level C4-C6, AIS A-D). Outcomes were measured using two tests of upper extremity function: ARAT and GRASSP. The change in scores for the arm receiving the Armeo training were not statistically significant when compared to the arm not receiving the Armeo training at discharge from therapy and over follow up assessments (8.7 +/− 2.9 compared to 7.4 +/− 2.5 for ARAT at discharge, p = 0.98, and 13.0 +/− 3.2 compared to 13.3 +/− 3.3 for GRASSP at discharge, p = 0.69). Nevertheless, subjects with some minimal (partial) hand function at baseline had a significantly larger increase in GRASSP scores than subjects with no minimal hand function preserved at baseline (19.3 +/− 2.4 compared to 6.6 +/− 4.7, p = 0.02). This suggests that the initial functional capabilities of patients can influence the benefits measured after robotic rehabilitation training and heterogeneous subject populations should be avoided in early phase studies.
An ontological approach for strategic alignment: a supply chain operations reference case study

Firms cannot be competitive if their business and information technology strategies are not aligned. Yet achieving strategic alignment continues to be a major concern for business executives. A number of alignment models have been proposed in the literature. Enterprise modelling (EM) can deliver models that are understandable by all participants and formalised enough to map the Enterprise Engineering and Reengineering activities directly onto the business process execution. However, models need terms (names, verbs, etc.) to identify and describe the constructs modelled in the EM language used. To share business knowledge, a common modelling language is not sufficient. A common business language is required to share the understanding of any constructs used in the modelling language at a semantic level. The aim of this article is to present the importance of knowledge formalisation for strategic alignment. Our work is based on knowledge contained in a well-known reference model for supply chain: Supply Chain Operations Reference (SCOR) model. To analyse this knowledge, we transform this model into ontology. Finally, we will explore the respective advantages of the different representations of SCOR model (original text, using a business modelling language, ontology), and more generally, the contribution of ontologies as they are becoming a major issue in business modelling.
Natural History of Unruptured Intracranial Aneurysms: A Long-term Follow-up Study

Background and Purpose— Unruptured intracranial aneurysms are increasingly being detected and are a notable healthcare burden. We investigated the long-term natural history of unruptured intracranial aneurysms and risk factors predictive of subsequent rupture. Methods— A total of 142 patients with 181 unruptured intracranial aneurysms diagnosed between 1956 and 1978, when these were not treated, were followed up until death or subarachnoid hemorrhage, or until 2011 to 2012. Annual and cumulative incidences of aneurysm rupture and risk factors for rupture were studied using Kaplan–Meier survival analysis and Cox proportional hazards regression models. Results— The median follow-up time was 21.0 (range, 0.8–52.3) years. During 3064 person-years, there were 34 first episodes of aneurysm rupture, giving an average annual incidence of 1.1%. Eighteen patients died on account of an initial or recurrent aneurysm rupture. The cumulative rate of bleeding was 10.5% (95% confidence interval [CI], 5.2–15.8) at 10 years, 23.0% (95% CI, 15.4–30.6) at 20 years, and 30.1% (95% CI, 21.3–38.9) at 30 years. None of the index aneurysms bled after a follow-up of 25 years. Cigarette smoking (adjusted hazard ratio, 2.44; 95% CI, 1.02–5.88), location of the aneurysm in the anterior communicating artery (adjusted hazard ratio, 3.73; 95% CI, 1.23–11.36), patient age inversely (0.96 per year, 95% CI, 0.92–1.00) and aneurysm diameter ≥7 mm (adjusted hazard ratio, 2.60; 95% CI, 1.13–5.98) independently predicted subsequent aneurysm rupture, as did alcohol consumption (1.27 per 100 g/week; 95% CI, 1.05–1.53; P<0.05), but only in univariable analysis. Conclusions— Cigarette smoking, patient age inversely, and the size and location of the unruptured intracranial aneurysm seem to be risk factors for aneurysm rupture. The risk of bleeding decreases with a very long-term follow-up.
Cooperative QoS Beamforming for Multicast Transmission in Terrestrial-Satellite Networks

Terrestrial-satellite networks (TSNs) play a significant role in achieving 100\% geographic coverage in the next generation of wireless networks. In TSNs, multimedia transmission is an important application scenario, where efficient content delivery solutions are required for effectively alleviating network congestion. In this paper, we study multicast beamforming problems in TSNs by reusing the entire bandwidth for providing efficient solutions for content delivery. In order to mitigate the interference imposed by multicast transmission of the satellite, we formulate the cooperative multicast beamforming problems for the TSN under the quality of service (QoS) constraints. Then, according to different considerations, the semidefinite relaxation (SDR) method is applied for the beamforming design of the satellite, whilst the recently developed feasible point pursuit successive convex approximation (FPP-SCA) approach is adopted for tackling the beamforming design problem of the base station. The system performance is studied by simulation results. Our investigations show that our TSN is capable of attaining a sufficient high rate for supporting multimedia transmission.
Online Detection of P300 and Error Potentials in a BCI Speller

Error potentials (ErrPs), that is, alterations of the EEG traces related to the subject perception of erroneous responses, have been suggested to be an elegant way to recognize misinterpreted commands in brain-computer interface (BCI) systems. We implemented a P300-based BCI speller that uses a genetic algorithm (GA) to detect P300s, and added an automatic error-correction system (ECS) based on the single-sweep detection of ErrPs. The developed system was tested on-line on three subjects and here we report preliminary results. In two out of three subjects, the GA provided a good performance in detecting P300 (90% and 60% accuracy with 5 repetitions), and it was possible to detect ErrP with an accuracy (roughly 60%) well above the chance level. In our knowledge, this is the first time that ErrP detection is performed on-line in a P300-based BCI. Preliminary results are encouraging, but further refinements are needed to improve performances.
Total arrest of spontaneous and evoked synaptic transmission but normal synaptogenesis in the absence of Munc13-mediated vesicle priming

Synaptic vesicles must be primed to fusion competence before they can fuse with the plasma membrane in response to increased intracellular Ca2+ levels. The presynaptic active zone protein Munc13-1 is essential for priming of glutamatergic synaptic vesicles in hippocampal neurons. However, a small subpopulation of synapses in any given glutamatergic nerve cell as well as all γ-aminobutyratergic (GABAergic) synapses are largely independent of Munc13-1. We show here that Munc13-2, the only Munc13 isoform coexpressed with Munc13-1 in hippocampus, is responsible for vesicle priming in Munc13-1 independent hippocampal synapses. Neurons lacking both Munc13-1 and Munc13-2 show neither evoked nor spontaneous release events, yet form normal numbers of synapses with typical ultrastructural features. Thus, the two Munc13 isoforms are completely redundant in GABAergic cells whereas glutamatergic neurons form two types of synapses, one of which is solely Munc13-1 dependent and lacks Munc13-2 whereas the other type employs Munc13-2 as priming factor. We conclude that Munc13-mediated vesicle priming is not a transmitter specific phenomenon but rather a general and essential feature of multiple fast neurotransmitter systems, and that synaptogenesis during development is not dependent on synaptic secretory activity.