Miracle-dz/UniFAR-FTUs huggingface dataset:
Systematic review of validated case definitions for diabetes in ICD-9-coded and ICD-10-coded data in adult populations

Objectives With steady increases in ‘big data’ and data analytics over the past two decades, administrative health databases have become more accessible and are now used regularly for diabetes surveillance. The objective of this study is to systematically review validated International Classification of Diseases (ICD)-based case definitions for diabetes in the adult population. Setting, participants and outcome measures Electronic databases, MEDLINE and Embase, were searched for validation studies where an administrative case definition (using ICD codes) for diabetes in adults was validated against a reference and statistical measures of the performance reported. Results The search yielded 2895 abstracts, and of the 193 potentially relevant studies, 16 met criteria. Diabetes definition for adults varied by data source, including physician claims (sensitivity ranged from 26.9% to 97%, specificity ranged from 94.3% to 99.4%, positive predictive value (PPV) ranged from 71.4% to 96.2%, negative predictive value (NPV) ranged from 95% to 99.6% and κ ranged from 0.8 to 0.9), hospital discharge data (sensitivity ranged from 59.1% to 92.6%, specificity ranged from 95.5% to 99%, PPV ranged from 62.5% to 96%, NPV ranged from 90.8% to 99% and κ ranged from 0.6 to 0.9) and a combination of both (sensitivity ranged from 57% to 95.6%, specificity ranged from 88% to 98.5%, PPV ranged from 54% to 80%, NPV ranged from 98% to 99.6% and κ ranged from 0.7 to 0.8). Conclusions Overall, administrative health databases are useful for undertaking diabetes surveillance, but an awareness of the variation in performance being affected by case definition is essential. The performance characteristics of these case definitions depend on the variations in the definition of primary diagnosis in ICD-coded discharge data and/or the methodology adopted by the healthcare facility to extract information from patient records.
An ILP-based Proof System for the Crossing Number Problem

Formally, approaches based on mathematical programming are able to find provably optimal solutions. However, the demands on a verifiable formal proof are typically much higher than the guarantees we can sensibly attribute to implementations of mathematical programs. We consider this in the context of the crossing number problem, one of the most prominent problems in topological graph theory. The problem asks for the minimum number of edge crossings in any drawing of a given graph. Graph-theoretic proofs for this problem are known to be notoriously hard to obtain. At the same time, proofs even for very specific graphs are often of interest in crossing number research, as they can, e.g., form the basis for inductive proofs. We propose a system to automatically generate a formal proof based on an ILP computation. Such a proof is (relatively) easily verifiable, and does not require the understanding of any complex ILP codes. As such, we hope our proof system may serve as a showcase for the necessary steps and central design goals of how to establish formal proof systems based on mathematical programming formulations.
Analysis of weight initialization techniques for Gradient Descent algorithm

Gradient Descent Backpropagation is the most commonly used training algorithm for the artificial neural networks. In this paper, we have conducted experiments to perform a detailed comparison of various well known weight initialization techniques given by Nguyen-Widrow, Drago et al, Kim and Ra, Chen and Nutter, Bottou etc and hence identify the best weight initialization method for the gradient descent approach. Six functions approximation problems were chosen for experimentation. Results of one sided tailed t-test, mean and standard deviation of test error were used for the decision making purpose. Results strongly suggest that the Nguyen and Widrow method is the best suited method for the Gradient Descent training algorithm.
GeneTrack - a genomic data processing and visualization framework

MOTIVATION High-throughput 'ChIP-chip' and 'ChIP-seq' methodologies generate sufficiently large data sets that analysis poses significant informatics challenges, particularly for research groups with modest computational support. To address this challenge, we devised a software platform for storing, analyzing and visualizing high resolution genome-wide binding data. GeneTrack automates several steps of a typical data processing pipeline, including smoothing and peak detection, and facilitates dissemination of the results via the web. Our software is freely available via the Google Project Hosting environment at http://genetrack.googlecode. com
Galvanostatic Entrapment of Penicillinase into Polytyramine Films and its Utilization for the Potentiometric Determination of Penicillin

A sensitive and reliable potentiometric biosensor for determination of penicillin has been developed by exploiting the self-limiting growth of the non-conducting polymer, polytyramine. Optimum polytyramine-penicillinase (PTy-PNCnase) films for potentiometric detection of penicillin were accomplished with monomer solutions which contained 0.03 M tyramine, 37 U/mL penicillinase, 0.01 M KNO3, and 3 mM penicillin with an applied current density of 0.8 mA/cm2 and an electropolymerisation time of 40 seconds. The potentiometric biosensor gave a linear concentration range of 3–283 μM for penicillin and achieved a minimum detectable concentration of 0.3 μM. The biosensor was successfully utilized for the detection of Amoxycillin and gave an average percentage recovery of 102 ± 6%. Satisfactory recoveries of penicillin G were also achieved in milk samples with the potentiometric biosensor when concentrations are ≥20 ppm.
A Learning Model of Information Technology Outsourcing: Normative Implications

We use an economic learning model to examine how knowledge parameters characterizing a sourcing relationship between a vendor and a client interact with production costs and coordination costs to affect the business value of alternative outsourcing strategies. This information is then used to determine a firm's optimal rate of information technology (IT) outsourcing. We find that the optimal outsourcing rate is dependent on the ability of the outsourcing client to acquire production knowledge from its outsourcing vendor and to retain its internal coordination knowledge despite losses of fundamental production skills due to outsourcing. Specifically, when the client is unable to acquire sufficient production knowledge from the external vendor, the client's optimal outsourcing decision is to engage in either one of two extreme strategies—total insourcing or total outsourcing—depending on the rate at which the client's coordination knowledge depreciates. On the other hand, when the client is able to acquire a substantial amount of production knowledge from the external vendor, the firm's optimal decision is to outsource only a portion of its IT services, where the proportion depends on the rate at which the client's coordination knowledge depreciates.
Analysis of THD and Output Voltage for Seven Level Asymmetrical Cascaded H-Bridge Multilevel Inverter using LSCPWM Technique

In this paper, a seven level asymmetrical cascaded H-Bridge multilevel inverter in three phase configuration using different level-shifted carrier-based pulse width modulation techniques is discussed. Multilevel inverters have become more popular due to high voltage and high power output applications. Comparable to traditional PWM inverters, multilevel inverters are able to reduced switching losses, low harmonic distortion and high-voltage capability with low costs. This paper presents ACMLI using fixed frequency level-shifted carrierbased PWM technique for three phase squirrel cage induction motor as a load. In this topology, two H-Bridges with 8-IGBT switches are used for getting seven level output voltage for each phase leg. Simulation using MATLAB-SIMULINK is done to verify the performance of the ACMLI using LSCPWM techniques. Simulation results for this proposed scheme are shown in this paper. General Terms Multilevel Inverter (MLI), Symmetrical Cascaded H-Bridge Multilevel Inverter (SCMLI), Asymmetrical Cascaded HBridge Multilevel Inverter (ACMLI).
On Causal Inferences in the Humanities and Social Sciences: Actual Causation

The last forty years have seen an explosion of research directed at causation and causal inference. Statisticians developed techniques for drawing inferences about the likely effects of proposed interventions: techniques that have been applied most noticeably in social and life sciences. Computer scientists, economists, and methodologists merged graph theory and structural equation modeling in order to develop a mathematical formalism that underwrites automated search for causal structure from data. Analytic metaphysicians and philosophers of science produced an array of theories about the nature of causation and its relationship to scientific theory and practice.Causal reasoning problems come in three varieties: effects-of-causes problems, causes-of-effects problems, and structure-learning or search problems. Causes-of-effects problems are the least well-understood of the three, in part because of confusion about exactly what problem is supposed to be solved. I claim that the problem everyone is implicitly trying to solve is the problem of identifying the actual cause(s) of a given effect, which I will call simply the problem of actual causation. My dissertation is a contribution to the search for a satisfying solution to the problem of actual causation.Towards a satisfying solution to the problem of actual causation, I clarify the nature of the problem. I argue that the only serious treatment of the problem of actual causation in the statistical literature fails because it confuses actual causation with simple difference-making. Current treatments of the problem of actual causation by philosophers and computer scientists are better but also ultimately unsatisfying. After pointing out that the best current theories fail to capture intuitions about some simple voting cases, I step back and ask a methodological question: how is the correct theory of actual causation to be discovered? I argue that intuition-fitting, whether by experimentation or by armchair, is misguided, and I recommend an alternative, pragmatic approach. I show by experiments that ordinary causal judgments are closely connected to broadly moral judgments, and I argue that actual causal inferences presuppose normative, not merely descriptive, information. I suggest that the way forward in solving the problem of actual causation is to focus on norms of proper functioning.
Simulation of Standard Benchmarks in Hardware Implementations of L2 Cache Models in Verilog HDL

Improving the performance of on-chip caches has been continually regarded with much effort to provide solution to the increased performance gap between microprocessor and memory. Proposed new design techniques were mostly implemented in software simply because it is easier and faster than hardware implementation. However, with the microprocessor technology advancement, this approach fails to consider other crucial matters such as power and area. To investigate and further evaluate the dynamic partitioning schemes in a shared L2 cache in Chip Multiprocessors (CMP), we have come up with a model to bring together generated traces from the M5 simulator and the hardware implementation of a shared L2 cache described using Verilog Hardware Description Language (HDL) and developed using the Synopsys EDA tools. The use of this system model offers a number of benefits such as the following: (1) L2 cache designs can now be characterized using power and area measurements and not just performance gain alone, (2) processor and L1 caches can be abstracted away from the design to provide more focus, (3) standard benchmark can still be used to evaluate the different designs being compared, and (4) a more realistic design that is closer to getting materialized can be produced.
Measurement of the $B^{\pm}$ production asymmetry and the $CP$ asymmetry in $B^{\pm} \to J/\psi K^{\pm}$ decays

The $B^{\pm}$ meson production asymmetry in pp collisions is measured using $B^+ \to \overline{D}^0\pi^+$ decays. The data were recorded by the LHCb experiment during Run 1 of the LHC at center-of-mass energies of $\sqrt{s}$ = 7 and 8 TeV. The production asymmetries, integrated over transverse momenta in the range $2 < p_T < 30 GeV/c$, and rapidities in the range $2.1 < y < 4.5$ are measured to be $\mathcal{A}_{prod}(B^+, \sqrt{s} = 7 TeV) = (−0.41 \pm 0.49 \pm 0.10) \times 10^{−2}$, $\mathcal{A}_{prod}(B^+, \sqrt{s} = 8 TeV) = (−0.53 \pm 0.31 \pm 0.10) \times 10^{−2}$, where the first uncertainties are statistical and the second are systematic. These production asymmetries are used to correct the raw asymmetries of $B^+ \to J/\psi K^{\pm}$ decays, thus allowing a measurement of the CP asymmetry, $\mathcal{A}_{CP}(B^+ \to J/\psi K^{\pm}) = (0.09 \pm 0.27 \pm 0.07) \times 10^{−2}$.
ParkSense: a smartphone based sensing system for on-street parking

Studies of automotive traffic have shown that on average 30% of traffic in congested urban areas is due to cruising drivers looking for parking. While we have witnessed a push towards sensing technologies to monitor real-time parking availability, instrumenting on-street parking throughout a city is a considerable investment. In this paper, we present ParkSense, a smartphone based sensing system that detects if a driver has vacated a parking spot. ParkSense leverages the ubiquitous Wi-Fi beacons in urban areas for sensing unparking events. It utilizes a robust Wi-Fi signature matching approach to detect driver's return to the parked vehicle. Moreover, it uses a novel approach based on the rate of change of Wi-Fi beacons to sense if the user has started driving. We show that the rate of change of the observed beacons is highly correlated with actual user speed and is a good indicator of whether a user is in a vehicle. Through empirical evaluation, we demonstrate that our approach has a significantly smaller energy footprint than traditional location sensors like GPS and Wi-Fi based positioning while still maintaining sufficient accuracy.
Continuous Monitoring of Spatial Queries in Wireless Broadcast Environments

Wireless data broadcast is a promising technique for information dissemination that leverages the computational capabilities of the mobile devices in order to enhance the scalability of the system. Under this environment, the data are continuously broadcast by the server, interleaved with some indexing information for query processing. Clients may then tune in the broadcast channel and process their queries locally without contacting the server. Previous work on spatial query processing for wireless broadcast systems has only considered snapshot queries over static data. In this paper, we propose an air indexing framework that 1) outperforms the existing (i.e., snapshot) techniques in terms of energy consumption while achieving low access latency and 2) constitutes the first method supporting efficient processing of continuous spatial queries over moving objects.
Skin fluorescence controlled photodynamic photorejuvenation (wrinkle reduction)

Identical skin fluorescence can be obtained after one hour spraying with 0.5% liposome‐encapsulated 5‐ALA and after 0.5 hour application of 20% 5‐ALA in a cream base. In this study the clinical outcome and side effects using the 0.5% 5‐ALA in Caucasian skin are investigated and compared to earlier reported non‐ablative treatments for wrinkles and improvements of skin texture using 20% ALA photodynamic photorejuvenation.
Admission Control Framework for Delay Bounded Traffic in Cellular Networks

In this paper we present an admission control framework for serving streaming connections to mobile users in wireless cellular networks. The network is assumed to allocate a fixed number of channels to streaming services, and serve each connection at a fixed data rate. In addition, it is assumed that each connection has specified bounds on the maximum tolerable start of service delay, and the total service interruption delay. The admission control problem is formalized as a discrete scheduling problem which the framework handles by utilizing a heuristic algorithm guided by a mechanism that dynamically adapts a scheduling planning interval according to the offered connection request pattern. The devised framework does not assume a priori knowledge of the distribution of the arriving requests from either the target cell, or as a consequence of handoff. Performance is compared against a scheme that assumes a priori knowledge of such traffic distribution and admits a stream only if the estimated cell overload probability, after a prescribed prediction interval, does not exceed a specified threshold value. The obtained results show improvements with regard to the achieved throughput of the connections served to completion, and forced terminations.
Solutions of certain fractional kinetic equations and a fractional diffusion equation

In view of the usefulness and importance of the kinetic equation in certain physical problems, the authors derive the explicit solution of a fractional kinetic equation of general character, that unifies and extends earlier results. Further, an alternative shorter method based on a result developed by the authors is given to derive the solution of a fractional diffusion equation.
Tailoring the temperature coefficient of capacitance (TCC), dielectric loss and capacitance density with ceramic-polymer nanocomposites for RF applications

High-K inorganic materials generally show high loss or high TCC or both, making them unsuitable for RF capacitor applications where high Q, tolerance and thermal stability are critical. Most polymers do not have the required total set of attributes, making it extremely challenging to integrate high-performance RF thin film capacitors in organic packages and boards. In this paper, we demonstrate a strategy to tailor the properties of polymeric composite materials and satisfy all the RF capacitor requirements. With this strategy, it is feasible to meet low TCC and low loss while increasing the capacitance density or permittivity to miniaturize RF components
Skeletal muscle pump versus respiratory muscle pump: modulation of venous return from the locomotor limb in humans

The vast majority of quantitative data examining the effects of breathing on venous return have been derived from anaesthetized or reduced animal preparations, making an extrapolation to an upright exercising human problematic due to the lack of a hydrostatic column and an absence of muscular contraction. Thus, this study is the first to quantitatively examine the effects of different breathing mechanics on venous return from the locomotor limbs both at rest and during calf contraction exercise in the semirecumbent human. When subjects inspired using predominantly their ribcage/accessory inspiratory muscles at rest (change in gastric pressure (ΔPGA) = <2 cmH2O, change in oesophageal pressure (ΔPES) =∼−6 cmH2O; inspiratory time/total breath time (TI/TTOT) = 0.5), a slight facilitation of femoral venous return was observed during inspiration (65% of all flow occurred during inspiration), with a slight reduction in femoral venous return during the ensuing expiratory phase of the breath. However, when subjects inspired using a predominantly diaphragmatic breath at rest (ΔPGA= > 5 cmH2O, ΔPES=∼−6 cmH2O; TI/TTOT= 0.5), femoral venous return was markedly impeded (net retrograde flow of 11%) and significantly lower than that observed during ribcage breathing conditions (P < 0.01). During the ensuing expiratory phase of a diaphragmatic breath, there was a large resurgence of femoral venous blood flow. The pattern of modulation during ribcage and diaphragmatic breathing persisted during both mild (peak calf force = 7 kg) and moderate (peak calf force = 11 kg) levels of calf contraction. Despite the significant within‐breath modulation of femoral venous return by breathing, net blood flow in the steady state was not altered by the breathing pattern followed by the subjects. Though popliteal blood flow appeared to be modulated by respiration at rest, this pattern was absent during mild calf contraction where popliteal outflow was phasic with the concentric phase of calf contraction. We conclude that respiratory muscle pressure production is the predominant factor modulating venous return from the locomotor limb both at rest and during calf contraction even when the veins of the lower limb are distended due to the presence of a physiologic hydrostatic column.
Sparse and Non-Negative BSS for Noisy Data

Non-negative blind source separation (BSS) has raised interest in various fields of research, as testified by the wide literature on the topic of non-negative matrix factorization (NMF). In this context, it is fundamental that the sources to be estimated present some diversity in order to be efficiently retrieved. Sparsity is known to enhance such contrast between the sources while producing very robust approaches, especially to noise. In this paper, we introduce a new algorithm in order to tackle the blind separation of non-negative sparse sources from noisy measurements. We first show that sparsity and non-negativity constraints have to be carefully applied on the sought-after solution. In fact, improperly constrained solutions are unlikely to be stable and are therefore sub-optimal. The proposed algorithm, named nGMCA (non-negative Generalized Morphological Component Analysis), makes use of proximal calculus techniques to provide properly constrained solutions. The performance of nGMCA compared to other state-of-the-art algorithms is demonstrated by numerical experiments encompassing a wide variety of settings, with negligible parameter tuning. In particular, nGMCA is shown to provide robustness to noise and performs well on synthetic mixtures of real NMR spectra.
Prevention of Contrast Media-Induced Renal Dysfunction With Prostaglandin E 1 : A Randomized, Double-Blind, Placebo-Controlled Study

Preexisting renal impairment is an all-encompassing risk factor for radiocontrast-associated nephrotoxicity. Renal impairment appears to be associated with the inadequate production of renal prostaglandins at the critical time of radiocontrast administration and for a variable time period afterward. We prospectively studied 130 patients with chronic renal insufficiency (serum creatinine ≥1.5 mg/dL) who were undergoing radiocontrast administration. Using a double-blind, randomized, prospective technique, patients were assigned to either placebo or one of three prostaglandin E 1 (PGE 1 ) treatment groups (10, 20, or 40 ng/kg/min). Infusion was started 60 ± 30 minutes before the administration of radiocontrast and was continued for a total of 6 hours. In the placebo group, radiocontrast administration resulted in a mean increase (± SD) in serum creatinine of 0.72 ± 1.15 mg/dL at 48 hours. This increase was less in each of the PGE 1 treatment groups after 48 hours, with a significant difference between placebo and the 20 ng/kg/min PGE 1 group (P = 0.01). Using baseline adjusted means, analysis of covariance with baseline serum creatinine as the covariable demonstrated significant differences between the placebo and 20 ng/kg/min PGE 1 group (P = 0.03) and between the placebo and 10 ng/kg/min PGE 1 group (P = 0.047). In a subgroup analysis of the diabetic patients, the increase in serum creatinine was less pronounced in the three PGE 1 groups versus the placebo group, and the 20 ng/kg/min PGE 1 group had the most favorable outcome. The parenteral administration of PGE 1 immediately before radiocontrast exposure and continued for a period of 5 to 5.5 hours significantly reduced the elevation of serum creatinine poststudy. The most effective of the three PGE 1 dosing regimens was 20 ng/kg/min.