Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing clinical competency in medical senior house officers: how and why should we do it?

Most consultants are involved in the training and assessment of several grades of doctors in training especially senior house officers (SHOs) and specialist registrars. In the medical and other specialties there is an increasing trend towards assessing junior doctors’ competency using the record of in-training assessment process for specialist registrars and using the Royal College of Physicians folder to record competences of medical SHOs. It is necessary to consider why there is a need to assess competency, how it may be done practically, and the advantages and disadvantages of this system of assessment. There are considerable hurdles to the implementation of this system in the medical specialties within today’s NHS and the organisation may need to undergo fairly radical change to facilitate this system.
Evolution of locomotion in a simulated quadruped robot and transferral to reality

In this paper, we study the suitability of using simulation in the evolution of locomotion in a quadruped robot. The goal of the evolution is to design a control system that produces fast gaits. We evolve gaits in simulation, and then the best controllers are transferred into the real custom built robot and compared with their simulated versions. The results show effective locomotion, with a 1.8 times improvement in speed over earlier results. Finally, we investigate some measures to reduce the difference between simulated and real locomotion.
Intelligent Mobile Agent Middleware for Wireless Sensor Networks: A Real Time Application Case Study

In-Motes is a mobile agent middleware that generates an intelligent framework for deploying applications in wireless sensor networks (WSNs). in- motes is based on the injection of mobile agents into the network that can migrate or clone following specific rules and performing application specific tasks. By doing so, each mote is given a certain degree of perception cognition and control, forming the basis for its intelligence. We have developed, implemented and evaluated a real time application in a dynamic environment to determine how well in-motes achieves its goals. Namely, in-motes Bins is an agent based in- motes application for environmental monitoring sensing light and temperature variations. Using in-motes we were able to create and rapidly deploy our application on a WSN consisting of 10 MICA2 motes. Our application was tested in a wine store for a period of four months. In this paper we present the in-motes bins application and provide a detailed evaluation of its implementation. We also present a detailed analysis of in-motes middleware in regards of its efficiency, adaptability and reliability inside the WSN.
Semi automated dc-squid based CCC bridge for precision resistance measurements at the Spanish TPYCEA

A semi automated Cryogenic Current Comparator (CCC) system for precision resistance measurements, RX(Omega), has been developed within a joint collaboration ICMA-TPYCEA. The system, installed at TPYCEA, has an uncertainty of plusmn8ldr10-9ldrRX (k=1) and is being used in conjunction with the previously developed Quantum Hall Resistance system.
Capacity of VoIP Services in TDD OFDMA System with Different Delay Requirements

In this paper, we evaluate the voice service capacity of the TDD OFDMA system based on IEEE 802.16d/e. Voice traffic must be transmitted in real time with very small delay when we use packet transmission networks. Voice over IP (VoIP) services can be provided in this wireless packet network as Unsolicited Granted Service (UGS) or Real Time Polling Service (rtPS) class. As UGS, a fixed amount of bandwidth can be allocated to transmit the voice traffic for the duration of a call. On the other hand, as rtPS, bandwidth is allocated variably as needed to transmit the talk spurts using polling process. In this analysis, we also take into account the delay limit as one of the main Quality of Service (QoS) requirements of the voice services. The capacities of VoIP services for the classes with different delay limits are derived and compared in this paper. Simulation results show that the voice capacity is larger when we treat the VoIP service as rtPS than that as UGS.
A Brain-Computer Interface Based Security System

Banks and ATMs often rely on alpha-numeric passwords and biometric systems for authentication and secure access. Yet, a large number of cases on the misuse of accounts by miscreants continue to be reported. In this paper, we propose a novel security system based on Brain-Computer Interfaces that have the potential of providing higher security when compared to the above two methods. This system utilizes the Steady State Visually Evoked Potentials (SSVEP) generated by flickering visual stimuli for keying in the passwords. Both the Analog Front End and Digital Filtering & Analysis have been designed and implemented successfully. The Analog Front End includes a Pre-Amplification stage comprising of Instrumentation Amplifier, a Butter worth Filter and an Isolation Amplifier. The Digital Filtering and Analysis have been carried out using the ADS1298ECGFE-PDK and the computer. The simulation and individual module tests have shown promising results. Our final aim is that the integrated modules will provide enhanced security for password authentication.
Weak " -Nets for Points on a Hypersphere

A weak " -net for a set of points M , is a set of points W (not necessarily in M ) where every convex set containing " j M j points in M must contain at least one point in W . Weak " -nets have applications in diverse areas such as computational geometry, learning theory, optimization, and statistics. Here we show that if M is a set of points quasi-uniformly distributed on a unit sphere S d ¡ 1 , then there is a weak " -net W (cid:181) R d of size O . log . 1 ="/ log . 1 ="// for M , where k d is exponential in d . A set of points M is quasi-uniformly distributed on S d ¡ 1 if, for any spherical cap C (cid:181) S d ¡ 1 with Vol . C / ‚ c 1 = j M j , we have
Design and comparison of SiGe active downconversion mixers for S-band applications

In this paper, 4 types of SiGe active downconversion mixers are designed, simulated and compared with each other for non-portable S-Band applications. All mixers have single-ended RF inputs and they are designed in the same 0. 35μm BiCMOS process with 5 V supply voltages. These mixers are compared in terms of conversion gain, IIP3, P1dB, DSB noise figure, and power dissipation at 2–4 GHz RF frequency. In addition to this, an LO amplifier and an IF buffer are designed to provide higher conversion gain, lower noise figure and output matching. These circuits are common for all mixers; thus, they have the same effect on all. Figure of merits of mixers are calculated and their pros and cons are explained.
The design and implementation of COSEN, an iterative algorithm for fully 3-D listmode data

Presents coincidence-list-ordered set expectation-maximisation (COSEM), an algorithm for iterative image reconstruction directly from list-mode coincidence acquisition data. The COSEM algorithm is based on the ordered sets EM algorithm for binned data but has several extensions that makes it suitable for rotating two planar detector tomographs. The authors develop the COSEM algorithm and extend it to include analytic calculation of detection probability, noise reducing iterative filtering schemes, and on-the-fly attenuation correction methods. The authors present an adaptation of COSEM to the VaricamVG camera and show results from clinical and phantom studies.
Leveraging Ontologies to Improve Model Generalization Automatically with Online Data Sources

This paper describes an end-to-end learning framework that allows a novice to create a model from data easily by helping structure the model building process and capturing extended aspects of domain knowledge. By treating the whole modeling process interactively and exploiting high-level knowledge in the form of an ontology, the framework is able to aid the user in a number of ways, including in helping to avoid pitfalls such as data dredging. Prudence must be exercised to avoid these hazards: certain conclusions may be supported by extra knowledge if, for example, there are reasons to trust a particular narrower set of hypotheses. This paper adopts the solution of using higher-level knowledge in order to allow this sort of domain knowledge to be inferred automatically, thereby selecting only relevant input attributes and thence constraining the hypothesis space. We describe how the framework automatically exploits structured knowledge in an ontology to identify relevant concepts, and how a data extraction component can make use of online data sources to find measurements of those concepts so that their relevance can be evaluated. To validate our approach, models of four different problem domains were built using our implementation of the framework. Prediction error on unseen examples of these models show that our framework, making use of the ontology, helps to improve model generalization.
Visual Representation in the Wild: How Rhesus Monkeys Parse Objects

Visual object representation was studied in free-ranging rhesus monkeys. To facilitate comparison with humans, and to provide a new tool for neurophysiologists, we used a looking time procedure originally developed for studies of human infants. Monkeys' looking times were measured to displays with one or two distinct objects, separated or together, stationary or moving. Results indicate that rhesus monkeys used featural information to parse the displays into distinct objects, and they found events in which distinct objects moved together more novel or unnatural than events in which distinct objects moved separately. These findings show both common-alities and contrasts with those obtained from human infants. We discuss their implications for the development and neural mechanisms of higher-level vision.
Dictionaries for Sparse Representation Modeling

Sparse and redundant representation modeling of data assumes an ability to describe signals as linear combinations of a few atoms from a pre-specified dictionary. As such, the choice of the dictionary that sparsifies the signals is crucial for the success of this model. In general, the choice of a proper dictionary can be done using one of two ways: i) building a sparsifying dictionary based on a mathematical model of the data, or ii) learning a dictionary to perform best on a training set. In this paper we describe the evolution of these two paradigms. As manifestations of the first approach, we cover topics such as wavelets, wavelet packets, contourlets, and curvelets, all aiming to exploit 1-D and 2-D mathematical models for constructing effective dictionaries for signals and images. Dictionary learning takes a different route, attaching the dictionary to a set of examples it is supposed to serve. From the seminal work of Field and Olshausen, through the MOD, the K-SVD, the Generalized PCA and others, this paper surveys the various options such training has to offer, up to the most recent contributions and structures.
A Prospective, Open-Label, 12 Week Trial of S-adenosylmethionine in the Symptomatic Treatment of Alzheimer’s Disease

Objective: To determine if treatment with S-adenosylmethionine (SAM-e) might lead to cognitive and behavioral improvement in patients with Alzheimer’s disease (AD). Interventions: We conducted a prospective, open-label study of six subjects who were given oral SAM-e over 12 weeks and measured the effects on cognition and behavior. Outcome measures: Outcome measures of cognition and behavior included the Alzheimer’s Disease Assessment Scale-Cognitive subscale (ADAS-Cog), Mini-Mental State Examination (MMSE), Behave-AD, Clinical Global Impression Scale (CGI), Hamilton Rating Scale for Depression (HAM-D), informant version, Blessed Dementia Scale to assess activities of daily living (ADL), the Physical Self-Maintainance Scale (PSMS), and the Lawton-Brody IADL Scale to measure instrumental activities of daily living. Results: At study completion, two subjects were “moderately improved” and 4 were “minimally improved” on the CGI. Five subjects improved on the ADAS-Cog by an average of 20%. No significant side effects were reported. Conclusions: In this small open label study, SAM-e appeared to have a beneficial effect in patients with AD, but the small subject number didn’t provide enough power to show statistical significance. Controlled trials with adequate statistical power to investigate its utility in AD are warranted.
Microfluidics and thin-film processes: a recipe for organic integrated photonics based on 3D microresonators

We report on the design and realization of photonic integrated devices based on 3D organic microresonators. This has been achieved by combining microfluidics techniques and thin-film processes. The microfluidic device and the control of the flow rates of the continuous and dispersed phases allow the fabrication of organic microresonators with diameter ranging from 30 to 200 μm. The resonance of the sphere in air has been first investigated by using the Raman spectroscopy set-up demonstrating the appropriate photonic properties. Then the microresonators have been integrated on an organic chip made of the photosensitive resin SU-8 and positioned at the extremity of a taper and alongside a rib waveguide. The realization of these structures by thin-film processes needs one step UV-lithography leading to 6μm width and 30μm height. Both devices have proved the efficient evanescent coupling leading to the excitation of the whispering gallery modes confined at the surface of the organic 3D microresonators. Finally, a band-stop filter has been used to detect the resonance spectra of the resonators once integrated.
Probabilistic context prediction using time-inferred multiple pattern networks

We propose a probabilistic method for context prediction of mobile users based on their historic context data. The proposed method predicts general context based on the probability theory through a novel graphical data structure, which is a kind of weighted directed multi-graphs. User context data are transformed into the new graphical structure, in which each node represents a context or a combined context and each directed edge indicates a context transfer with the time weight inferred from corresponding time data. The periodic property of context data is also considered. We bring a nice solution to context data with such property. Through simulation, we could show the merits of the proposed method.
Starch biosynthesis.

Starch is the most significant form of carbon reserve in plants in terms of the amount made, the universality of its distribution among different plant species, and its commercial importance. It consists of different glucose polymers arranged into a threedimensional, semicrystalline structure-the starch granule. The biosynthesis of starch involves not only the production of the composite glucans but also their arrangement into an organized form within the starch granule. The formation of the starch granule can be viewed as a simple model for the formation of ordered three-dimensional polysaccharide structures in plants. Understanding the biochemical basis for the assembly of the granule could provide a conceptual basis for understanding other higher order biosynthetic systems such as cellulose biosynthesis (see Delmer and Amor, 1995, this issue). For example, one emerging concept is that structure within the granule itself may determine or influence the way in which starch polymers are synthesized. Starch is synthesized in leaves during the day from photosynthetically fixed carbon and is mobilized at night. It is also synthesized transiently in other organs, such as meristems and root cap cells, but its major site of accumulation is in storage organs, including seeds, fruits, tubers, and storage roots. Almost all structural studies have used starch from storage organs because it is readily available and commercially important; we therefore focus on starch biosynthesis in storage organs. However, where aspects of transient biosynthesis are clearly different from long-term reserve synthesis, reference is made to biosynthesis in nonstorage tissues. Starch is synthesized in plastids, which in storage organs committed primarily to starch production are called amyloplasts. These develop directly from proplastids and have little interna1 lamellar structure. Starch may also be synthesized in plastids that have other specialized functions, such as chloroplasts (photosynthetic carbon fixation), plastids of oilseed (fatty acid biosynthesis), and chromoplasts of roots such as carrot (carotenoid biosynthesis). In some cases, for example, in the storage cotyledons of some legumes, amyloplasts in storage organs develop from chloroplasts. These amyloplasts may maintain considerable amounts of stacked lamellar material from the thylakoids and, in cells receiving sufficient light, may undertake some photosynthetic carbon fixation for use in starch
EPIC: Efficient prediction of IC manufacturing hotspots with a unified meta-classification formulation

In this paper we present EPIC, an efficient and effective predictor for IC manufacturing hotspots in deep sub-wavelength lithography. EPIC proposes a unified framework to combine different hotspot detection methods together, such as machine learning and pattern matching, using mathematical programming/optimization. EPIC algorithm has been tested on a number of industry benchmarks under advanced manufacturing conditions. It demonstrates so far the best capability in selectively combining the desirable features of various hotspot detection methods (3.5-8.2% accuracy improvement) as well as significant suppression of the detection noise (e.g., 80% false-alarm reduction). These characteristics make EPIC very suitable for conducting high performance physical verification and guiding efficient manufacturability friendly physical design.
DMD 28746 1 Physiologically-Based Pharmacokinetic Model of Mechanism-Based Inhibition of CYP 3 A by Clarithromycin

Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana (SKQ, JCG, LL, SDH) Division of Biostatistics, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana (SKQ, LL) Department of Pharmacy Practice, School of Pharmacy and Pharmaceutical Sciences, Purdue University, Indianapolis, Indiana (XZ, AL) DMD Fast Forward. Published on November 2, 2009 as doi:10.1124/dmd.109. 028746
Retrieval of degraded Chinese document based on fuzzy coding strategy

For the sake of the low recognition rate for degraded Chinese document, the performance of retrieval is not good if directly based on OCR result. This paper presents a new way to improve the performance of retrieval by fuzzy coding strategy. Lots of character classes with similar shapes are clustered and are indexed by pseudo code. For ease of test, this paper also presents a way to generate ground-truth of imaged document and synthesized degraded document image. A true OCR text collection and two synthesized document image collections are used for performance evaluation, and the result confirms the validation of our method.
Graphene via Molecule-Assisted Ultrasound-Induced Liquid-Phase Exfoliation: A Supramolecular Approach

Abstract Graphene is a two-dimensional (2D) material holding unique optical, mechanical, thermal and electrical properties. The combination of these exceptional characteristics makes graphene an ideal model system for fundamental physical and chemical studies as well as technologically ground breaking material for a large range of applications. Graphene can be produced either following a bottom-up or top-down method. The former is based on the formation of covalent networks suitably engineered molecular building blocks undergoing chemical reaction. The latter takes place through the exfoliation of bulk graphite into individual graphene sheets. Among them, ultrasound-induced liquid-phase exfoliation (UILPE) is an appealing method, being very versatile and applicable to different environments and on various substrate types. In this chapter, we describe the recently reported methods to produce graphene via molecule-assisted UILPE of graphite, aiming at the generation of high-quality graphene. In particular, we will focus on the supramolecular approach, which consists in the use of suitably designed organic molecules during the UILPE of graphite. These molecules act as graphene dispersion-stabilizing agents during the exfoliation. This method relying on the joint effect of a solvent and ad hoc molecules to foster the exfoliation of graphite into graphene in liquid environment represents a promising and modular method toward the improvement of the process of UILPE in terms of the concentration and quality of the exfoliated material. Furthermore, exfoliations in aqueous and organic solutions are presented and discussed separately.
Analysis of an algorithm for generating locally optimal meshes for L2 approximation by discontinuous piecewise polynomials

This paper discusses the problem of constructing a locally optimal mesh for the best L 2 approximation of a given function by discontinuous piecewise polynomials. In the one-dimensional case, it is shown that, under certain assumptions on the approximated function, Baines' algorithm [M.J. Baines, Math. Comp., 62 (1994), pp. 645-669] for piecewise linear or piecewise constant polynomials produces a mesh sequence which converges to an optimal mesh. The rate of convergence is investigated. A two-dimensional modification of this algorithm is proposed in which both the nodes and the connection between the nodes are self-adjusting. Numerical results in one and two dimensions are presented.
Investigating Polarisation and Shape of Beam Microwave Signals at the ANKA Storage Ring

At the ANKA synchrotron radiation facility measurements in the microwave range (10 to 12 GHz) employing a LNB (Low Noise Block), which is the receiving part of a Satellite-TV system, have been carried out. Experiments showed that the observed signal depends on the length of the electron bunches. Furthermore the temporal shape of the microwave signal depends on the detector’s position along the accelerator. Due the LNB antenna’s sensitivity to polarisation it was also possible to measure the polarisation along the several ns long signal, revealing polarised and non-polarised regions. This paper describes the experimental setup and summarises the observations of the systematic studies performed with the LNB system. MICROWAVE RADIATION AT ANKA Earlier experiments at ANKA, the synchrotron radiation facility of Karlsruhe Institute of Technology (Karlsruhe, Germany) showed that there is an electron beam correlated microwave signal visible at the infrared beamline IR1 [1], [2]. Further studies performed at the IR2 beamline and at the synchrotron light monitor port (SLM) confirmed these first observations. The detection of microwave radiation is an interesting fact since the coherent synchrotron radiation (CSR) suppression threshold frequency at ANKA can be calculated using [3]:
Hidden Markov model-based Assamese vowel phoneme recognition using cepstral features

We use linear prediction cepstrum coefficients LPCC-based features, namely, the weighted LPCC and delta weighted LPCC, to recognise Assamese vowel phonemes employing a discrete hidden Markov model HMM. We create a small database for the Assamese vowels, spoken in isolation by 20 speakers with equal numbers of male and female speaker. Each spoken phoneme is repeated ten times by each speaker. Thus, our database consists of 1,600 phonemes out of which 1,000 phonemes are used for the training stage and the remaining 600 phonemes are used for the recognition stage in our experiment. The overall recognition rate of our experiment is nearly about 81.5%.