Miracle-dz/UniFAR-FTUs huggingface dataset:
Examining the readability of patient-informed consent forms

Correspondence: Marli Terblanche Room 41, Department of Cardiology, 8th Floor, Tygerberg Hospital, Parow 7500, South Africa Tel +27 21 931 7825 Fax + 27 21 933 3597 Email marli@treadresearch.com Primary objective: To investigate the readability of informed consent forms (ICF) used at TREAD Research, a private clinical trial research unit located in Tygerberg Hospital. Secondary objective: To assess if there is a difference in readability between therapeutic areas, as well as a difference in readability over two time periods. Methods: The readability of 84 ICFs given to patients at TREAD Research between the years 2000 and 2009 was quantitatively assessed by means of the Flesch–Kincaid Reading Ease, Flesch–Kincaid Grade Level, and Gunning-Fog index. Results: The mean ± standard deviation (SD) Flesch–Kincaid Reading Ease score for the 84 ICFs was 46.60 ± 5.62 (range 33.2–65.6). The mean ± SD grade level was 12.13 ± 1.8 (range 8.3–14.9) using the Flesch–Kincaid formula and 13.96 ± 1.22 (range 10.3–16.6) using the Gunning-Fog index. Readability at grade level 8 was only found in 1.2% of all the ICFs assessed. No differences were found in readability between therapeutic areas or over the two time periods. Conclusions: The main finding is that these forms are too complex to be understood by average study participants and their families.
Optimization of model based functional test case generation for android applications

The importance of mobile applications is gaining momentum because nowadays mobile application are using more frequently for personal and business purposes. Due to this reason, the development of mobile applications is also increasing day by day, so developers of mobile applications are frequently developing and deploying the mobile applications in the short interval of time. For assuring the functionality of the mobile application, we adopt a GUI based testing technique known as model based testing. In the model based testing, the functionality of the existing applications is tested by the external behavior of the system so basically this technique comes in the area of black-box testing. By leveraging the recent research, it is identified that the model based testing in the context of mobile applications testing; are facing problems such as large number of generated test cases and inadequate testing coverage of the application. The newly proposed technique is for generating the minimal functional test cases with the maximum coverage of the application. The proposed technique facilitates the developers/testers to test the functionality of the mobile application in short interval of time by consuming less effort.
Infection and dispersal processes of Pseudomonas syringae pv. coriandricola on coriander

An Australian isolate of Pseudomonas syringae pv. c oriandricola ( Psc ) was used to study aspects of dispersal of the pathogen and infection of coriander. Needle inoculation of Psc in the stem of coriander resulted in up to 94% plant mortality. The total biomass of inoculated plants decreased significantly four weeks after inoculation as compared to the control plants. Systemic infection was rapid and one week after inoculation a bacterial population of about 104 to 108 cfu g -1 was isolated from different parts of the stems and roots. Surface contamination of coriander seed with Psc prior to planting resulted in low disease incidence (8%). However, spray inoculation of healthy coriander plants with Psc at concentrations equal to or greater than 103 CFU mL -1 caused disease on the leaves, suggesting infection was common through the stomata. Splash dispersal of Psc was demonstrated, with disease being observed on surrounding coriander seedlings. Psc bacteria were dispersed up to 70 cm from the inoculum source
EVALUATION OF ALVEOLAR OSTEOTOMY FOR CORRECTION OF VERTICAL BONE RESORPTION IN ANTERIOR MANDIBULAR RIDGE USING A MIXTURE OF TWO GRAFTED MATERIALS

INTRODUCTION: Extensive loss of alveolar bone and teeth in the anterior mandible presents a complex problem for reconstruction. Alveolar osteotomy technique with the use of mixture of hydroxy apatite and beta-tricalcium phosphate together with injectable PRF is one of the reliable methods to restore vertical ridge deficiencies. OBJECTIVES: : Evaluate vertical ridge augmentation using sandwich osteotomy technique in anterior atrophic mandible and the use of hydroxy apatite, beta-tri-calcium phosphate mixed with injectable PRF as a grafting material. MATERIALS AND METHODS: This study was conducted clinically on 8 patients indicated for vertical ridge augmentation by sandwich technique osteotomy and fixation of the osteomatized segment by micro-plates and screws, and the placement of Ha- BTCP mixed with I-PRF as interpositional graft material. Patients were evaluated clinically and radiographically by using panoramic radiograph and cone beam computed tomography (CBCT). RESULTS: In this study no severe pain was recorded postoperatively. No signs of inflammation or swelling were observed in almost all of the patients along the follow up period. Vertical bone height gain of the residual ridge was satisfactory and prepared the ridge to receive final prosthesis successfully. CONCLUSIONS Sandwich osteotomy technique with Ha- BTCP mixed with I-prf is a reliable method to restore vertical ridge deficiencies in anterior mandible.
Laplacian kernel splatting for efficient depth-of-field and motion blur synthesis or reconstruction

Simulating combinations of depth-of-field and motion blur is an important factor to cinematic quality in synthetic images but can take long to compute. Splatting the point-spread function (PSF) of every pixel is general and provides high quality, but requires prohibitive compute time. We accelerate this in two steps: In a pre-process we optimize for sparse representations of the Laplacian of all possible PSFs that we call spreadlets. At runtime, spreadlets can be splat efficiently to the Laplacian of an image. Integrating this image produces the final result. Our approach scales faithfully to strong motion and large out-of-focus areas and compares favorably in speed and quality with off-line and interactive approaches. It is applicable to both synthesizing from pinhole as well as reconstructing from stochastic images, with or without layering.
Artificial bee colony algorithm based automatic generation control in two-area non-reheat thermal power system using SMES

In modern real world power system is very complex and uncertainties of parameters are controlled is a huge task of the problem due to continuous power demand variations. The proper balance between power demand and generation is much essential of the system. Automatic generation control (AGC) is a vital role to maintain the steady state frequency and tie-line power interchange values under normal and step load perturbations in the system. In this proposed work to design a optimal controllers for AGC to improve the dynamic performance and reliability of the system. The optimum gains of the proportional-integral-derivative (PID) controller are optimized using a artificial bee colony (ABC) algorithm employing an integral time absolute error (ITAE) criterion. Superconducting magnetic energy storage system (SMES) unit is incorporated in the proposed system to further improve the dynamic performance. The superiority of this proposed approach is compared with existing published method such as Loci map based chaotic optimization algorithm (LOCA) tuned PID controller for the system of two area non-reheat thermal power system. It is observed that the ABC tuned PID controller is better performers in terms of settling time, peak overshoot, undershoot in frequency and tie line power deviation as compared to the LOCA based PID controller.
Deep Learning Method for Denial of Service Attack Detection Based on Restricted Boltzmann Machine

In this article, the application of the deep learning method based on Gaussian-Bernoulli type restricted Boltzmann machine (RBM) to the detection of denial of service (DoS) attacks is considered. To increase the DoS attack detection accuracy, seven additional layers are added between the visible and the hidden layers of the RBM. Accurate results in DoS attack detection are obtained by optimization of the hyperparameters of the proposed deep RBM model. The form of the RBM that allows application of the continuous data is used. In this type of RBM, the probability distribution of the visible layer is replaced by a Gaussian distribution. Comparative analysis of the accuracy of the proposed method with Bernoulli-Bernoulli RBM, Gaussian-Bernoulli RBM, deep belief network type deep learning methods on DoS attack detection is provided. Detection accuracy of the methods is verified on the NSL-KDD data set. Higher accuracy from the proposed multilayer deep Gaussian-Bernoulli type RBM is obtained.
Variational Mode Decomposition and Decision Tree Based Detection and Classification of Power Quality Disturbances in Grid-Connected Distributed Generation System

This paper presents a variational mode decomposition (VMD) and decision tree based detection and classification method of single and mixed power quality (PQ) disturbances in grid-connected distributed generation system. Applicability of VMD technique is investigated for discrimination of stationary PQ disturbances (such as harmonics, interharmonics, and flicker), non-stationary events (e.g., transients) and noise. Studies indicate usefulness of VMD for accurate estimation of phasor quantities such as amplitude, phase angle, and frequency and other describing features. Features namely, mode central frequencies, relative mode energy ratios, zero crossings, and instantaneous amplitude (IA) are extracted for classification of single and mixed PQ disturbances using a decision tree algorithm. A set of synthetic test signals, disturbance signals obtained from real events as well as signals generated from real time digital simulator platform are used to test effectiveness of proposed method, under various system operating scenarios and noise levels. Proposed method is found to be capable of accurate detection, estimation, localization, and classification of all kinds of PQ disturbances in both noisy and noise-free cases.
Monitoring EGFR-T790M mutation in serum/plasma for prediction of response to third-generation EGFR inhibitors in patients with lung cancer

Background Osimertinib is efficacious in lung cancer patients with epidermal growth factor receptor (EGFR) mutations and acquired resistance (AR) to EGFR tyrosine kinase inhibitors due to EGFR-T790M mutation (T790M). We sought to describe T790M changes in serum/plasma during osimertinib therapy and correlate these changes with treatment outcomes. Material and methods Serum/plasma from EGFR-mutant lung cancer patients with T790M-AR was collected before and during osimertinib treatment. Changes in T790M were evaluated using a peptide-nucleic acid-PCR assay, and correlated with clinical and radiographic response. Results Thirteen patients were included. Median time on osimertinib treatment was 10.6 months with a median progression-free survival of 13.6 months. Best response to osimertinib was partial response (PR), stable disease (SD) or progression (PD) in 46.1%, 30.8% and 23.1% of patients, respectively. Most of the patients were paucisymptomatic at baseline. Symptom improvement was reported in 66.6% of responder patients; while symptoms remained stable in 75% of patients with SD, and 66% of patients with PD had clinical deterioration. Three patterns of T790M changes during osimertinib treatment were identified. T790 remained detectable with PD or a short-lasting SD in 15.4% of the patients. T790M disappeared in 69.2% of patients with PR or SD. T790M disappeared, despite clinical and/or radiographic progression in 15.4% of the patients. Conclusion Changes of T790M in serum/plasma in EGFR-mutant lung cancer patients with T790M-AR might be a useful marker of symptomatic and radiographic outcome to osimertinib. Longer follow-up is needed to establish if subsequent emergence of T790M could be a marker of resistance.
Detection of shoreline change using geo-spatial techniques along the coast between Kanyakumari and Tuticorin

The multi-temporal Landsat 7 ETM+ images acquired from 2011 to 2015 are used to demarcate the rate of shoreline shift using GIS-based Digital Shoreline Analysis System for the study area the coast between Kanyakumari and Tuticorin of the Tamil Nadu state, East Coast of India. The statistical analysis such as Shoreline Change Envelope, Net Shoreline Movement, End Point Rate, and Linear Regression Rate are determined from the multi-temporal shoreline layers. The data is streamlined on image processing software and analyzed using GIS technology indicating the suitability of DSAS to assess the shoreline changes compared with the traditional methods. The Tuticorin coast has experienced heavy accretion from 1969 to 2004, high amount of erosion in 2004. In present study of 2011 to 2015 the shoreline change has been considerably controlled.
On the Theory of Function Placement and Chaining for Network Function Virtualization

Network function virtualization (NFV) can significantly reduce the operation cost and speed up the deployment for network services to markets. Under NFV, a network service is composed by a chain of ordered virtual functions, or we call a "network function chain. " A fundamental question is when given a number of network function chains, on which servers should we place these functions and how should we form a chain on these functions? This is challenging due to the intricate dependency relationship of functions and the intrinsic complex nature of the optimization. In this paper, we formulate the function placement and chaining problem as an integer optimization, where each variable is an indicator whether one service chain can be deployed on a configuration (or a possible function placement of a service chain). While this problem is generally NP-hard, our contribution is to show that it can be mapped to an exponential number of min-cost flow problems. Instead of solving all the min-cost problems, one can select a small number of mapped min-cost problems, which are likely to have a low cost. To achieve this, we relax the integer problem into a fractional linear problem, and theoretically prove that the fractional solutions possess some desirable properties, i.e., the number and the utilization of selected configurations can be upper and lower bounded, respectively. Based on such properties, we determine some "good" configurations selected from the fractional solution and determine the mapped min-cost flow problem, and this helps us to develop efficient algorithms for network function placement and chaining. Via extensive simulations, we show that our algorithms significantly outperform state-of-art algorithms and achieve near-optimal performance.
Hypothesis on Different Data Mining Algorithms

In this paper, different classification algorithms for data mining are discussed. Data Mining is about explaining the past & predicting the future by means of data analysis. Classification is a task of data mining, which categories data based on numerical or categorical variables. To classify the data many algorithms are proposed, out of them five algorithms are comparatively studied for data mining through classification. There are four different classification approaches namely Frequency Table, Covariance Matrix, Similarity Functions & Others. As work for research on classification methods, algorithms like Naive Bayesian, K Nearest Neighbors, Decision Tree,
Avatar Embodiment. Towards a Standardized Questionnaire

Inside virtual reality, users can embody avatars that are collocated from a first-person perspective. When doing so, participants have the feeling that the own body has been substituted by the self-avatar, and that the new body is the source of the sensations. Embodiment is complex as it includes not only body ownership over the avatar, but also agency, co-location, and external appearance. Despite the multiple variables that influence it, the illusion is quite robust, and it can be produced even if the self-avatar is of a different age, size, gender, or race from the participant's own body. Embodiment illusions are therefore the basis for many social VR experiences and a current active research area among the community. Researchers are interested both in the body manipulations that can be accepted, as well as studying how different self-avatars produce different attitudinal, social, perceptual, and behavioral effects. However, findings suggest that despite embodiment being strongly associated with the performance and reactions inside virtual reality, the extent to which the illusion is experienced varies between participants. In this paper, we review the questionnaires used in past experiments and propose a standardized embodiment questionnaire based on 25 questions that are prevalent in the literature. We encourage future virtual reality experiments that include first-person virtual avatars to administer this questionnaire in order to evaluate the degree of embodiment.
MEADOR LECTURE SERIES 2004-2005 : RISK AND THE LAW PRECAUTIONS AGAINST WHAT ? THE AVAILABILITY HEURISTIC AND CROSS-CULTURAL RISK PERCEPTION

Because risks are on all sides of social situations, it is not possible to be globally "precautionary. " Hence, the Precautionary Principle runs into serious conceptual difficulties; any precautions will themselves create hazards of one kind or another. When the principle gives guidance, it is often because of the availability heuristic, which can make some risks stand out as particularly salient, regardless of their actual magnitude. The same heuristic helps to explain differences across groups, cultures, and even nations in the perception of risks, especially when linked with such social processes as cascades and group polarization. One difficulty is that what is available is sometimes a result of predispositions, cultural and otherwise. There are complex links among availability, social processes for the spreading of information, and predispositions. Many Germans believe that drinking water after eating cherries is deadly; they also believe that putting ice in soft drinks is unhealthy. The English, however, rather enjoy a cool drink of water after some cherries, and Americans love icy refreshments. ' * Karl N. Llewellyn Distinguished Service Professor, Law School and Department of Political Science, University of Chicago. 1. Joseph Henrich et al., Group Report: What is the Role of Culture in Bounded Rationality? , in BOUNDED RATIONALITY: THE ADAPTIVE TOOLBOX 343, 353 (Gerd Gigerenzer & Reinhard Selten eds., 2001). See id. at 353-54 (providing an entertaining outline in connection with food choice decisions). HeinOnline -57 Ala. L. Rev. 75 2005-2006
3DPatch: fast 3D structure visualization with residue conservation

Summary: Amino acid residues showing above background levels of conservation are often indicative of functionally significant regions within a protein. Understanding how the sequence conservation profile relates in space requires projection onto a protein structure, a potentially time‐consuming process. 3DPatch is a web application that streamlines this task by automatically generating multiple sequence alignments (where appropriate) and finding structural homologs, presenting the user with a choice of structures matching their query, annotated with residue conservation scores in a matter of seconds. Availability and implementation: 3DPatch is written in JavaScript and is freely available at http://www.skylign. org/3DPatch/. Mozilla Firefox, Google Chrome, and Safari web browsers are supported. Source code is available under MIT license at https://github.com/davidjakubec/3DPatch. Supplementary information: Supplementary data are available at Bioinformatics online.
Improving IPv6 transition management with IPv6 network virtualization

We have entered the transitional period between IPv4 and IPv6. However, IPv6 transition management involves entirely new challenges. To tackle these management challenges, we propose a management architecture (VNET6) to improve IPv6 transition manageability. Compared with the traditional network management architecture, VNET6 presents four different aspects: network layer virtualization for IPv4/IPv6 coexistence, service abstraction for IPv6 transition technologies, dynamic and autonomic management manner and end-to-end communication guarantee over heterogeneous networks. The implementation and evaluation demonstrate that VNET6 is a distributed enabler for the dynamic and autonomic management of IPv6 transition. This enabler facilitates incremental IPv6 deployment and simplifies the management of IPv4/IPv6 coexistence. Meanwhile, this enabler can effectively ensure application's end-to-end communication across multiple heterogeneous administrative domains. Especially, VNET6 makes it easier to provide performance-assured end-to-end paths for application's communication. Hence, VNET6 can improve the manageability for IPv6 transition. The manageability can facilitate IPv6 deployment and transition in a stable and manageable manner.
Towards online spike sorting for high-density neural probes using discriminative template matching with suppression of interfering spikes

Objective. The process of grouping neuronal spikes in an extracellular recording according to their neuronal sources, is generally referred to as spike sorting. Currently, the use of spike sorting is mainly limited to an offline usage, where spikes are sorted after the data acquisition has been completed. In this paper, we propose a discriminative template matching algorithm for threshold-based spike sorting on high-density extracellular data. Such threshold-based spike sorting has a low and deterministic algorithmic delay, allowing for fast online spike sorting. Approach. At its core, threshold-based spike sorting is driven by linear filters. The proposed discriminative template matching filter design algorithm optimizes the output signal-to-peak-interference ratio in a data-driven fashion, assuming the template of the target spike is available. The latter allows the filter to suppress the spikes of interfering neurons and to resolve spike overlap. The data-driven filter design algorithm requires only templates of the target neurons of interest, which can be retrieved, e.g. through a prior clustering on an initial recording. Main results. The proposed discriminative template matching filters are validated on in vivo ground truth data and are shown to provide single-unit activity with good accuracy using a simple thresholding operation on the filter outputs. Significance. The low algorithmic complexity allows for computationally cheap and fast spike sorting. Also the proposed filters are guaranteed to be stable and have a deterministic delay. These characteristics make the proposed filter design method a valuable building block for online spike sorting, thereby enabling unit activity-based real-time and closed-loop experiments for high-density neural recordings.
Identifying What Student Affairs Professionals Value: A Mixed Methods Analysis of Professional Competencies Listed in Job Descriptions.

Volume Sevem | Summer 2012 Abstract This mixed method study explored the professional competencies that administrators expect from entry-, mid-, and senior-level professionals as reflected in 1,759 job openings posted in 2008. Knowledge, skill, and dispositional competencies were identified during the qualitative phase of the study. Statistical analysis of the prevalence of competencies revealed significant differences between major functional areas and requirements for educational and work experience. Implications for institutional leaders, graduate faculty, and professional development planning as well as for mixed methods research are discussed.