Miracle-dz/UniFAR-FTUs huggingface dataset:
SWIFT—Scalable Clustering for Automated Identification of Rare Cell Populations in Large, High-Dimensional Flow Cytometry Datasets, Part 1: Algorithm Design

We present a model‐based clustering method, SWIFT (Scalable Weighted Iterative Flow‐clustering Technique), for digesting high‐dimensional large‐sized datasets obtained via modern flow cytometry into more compact representations that are well‐suited for further automated or manual analysis. Key attributes of the method include the following: (a) the analysis is conducted in the multidimensional space retaining the semantics of the data, (b) an iterative weighted sampling procedure is utilized to maintain modest computational complexity and to retain discrimination of extremely small subpopulations (hundreds of cells from datasets containing tens of millions), and (c) a splitting and merging procedure is incorporated in the algorithm to preserve distinguishability between biologically distinct populations, while still providing a significant compaction relative to the original data. This article presents a detailed algorithmic description of SWIFT, outlining the application‐driven motivations for the different design choices, a discussion of computational complexity of the different steps, and results obtained with SWIFT for synthetic data and relatively simple experimental data that allow validation of the desirable attributes. A companion paper (Part 2) highlights the use of SWIFT, in combination with additional computational tools, for more challenging biological problems. © 2014 The Authors. Published by Wiley Periodicals Inc.
Types of Supplementary Aids and Services for Students With Significant Support Needs

Supplementary aids and services (SAS) have been a provision in special education law since PL 94-142, however, almost no guidance has been provided to help teams make decisions about their appropriate selection and use. In this exploratory study, we explore the types of SAS selected for students with significant support needs using a conventional content analysis of individualized education program (IEPs) from 88 students in Grades K–12. Results illustrate the wide variation in types of SAS chosen for students overall. Curricular accommodations and personnel supports were the most commonly identified supports, while supports to assist students to communicate and make meaning of curriculum (e.g., curricular modifications) were less common, as were less intrusive supports such as peer-assisted learning. Implications for policy, practice, and research are provided.
From design experiences to generic mechanisms: Model-based learning in analogical design

Abstract Analogical reasoning plays an important role in design. In particular, cross-domain analogies appear to be important in innovative and creative design. However, making cross-domain analogies is hard and often requires abstractions common to the source and target domains. Recent work in case-based design suggests that generic mechanisms are one type of abstractions useful in adapting past designs. However, one important yet unexplored issue is where these generic mechanisms come from. We hypothesize that they are acquired incrementally from design experiences in familiar domains by abstraction over patterns of regularity. Three important issues in abstraction from experiences are what to abstract from an experience, how far to abstract, and what methods to use. In this short paper, we describe how structure-behavior-function models of designs in a familiar domain provide the content, and together with the problem-solving context in which learning occurs, also provide the constraints for learning generic mechanisms from design experiences. In particular, we describe the model-based learning method with a scenario of learning feedback mechanism.
Behavioural and Morphological Asymmetries in Vertebrates

The development of all animal embryos is accompanied by several symmetry breaks which transform a spherically symmetric oocyte into a body, characterized by polarity, dorso-ventrality, left-right and translational dissymmetry. We explore whether these symmetry breaks obey a classical Curie principle, demanding the existence of external “dissymmetrizers”, and show that in many cases the symmetry breaks occur “spontaneously”, i.e., as a result of instability of a more symmetric shape. Therefore the symmetry breaks should be considered as the consequences of morphogenetic processes rather than the elements of an externally superimposed prepattern. A model is proposed from which predictions can be made about spontaneous symmetry breaks from general morphomechanical laws. We discuss also the conditions permitting a left-right dissymmetry to emerge from a supramolecular to a morphological level.
The Speedup Test

Numerous code optimisation methods are usually experimented by doing multiple observations of the initial and the optimised executions times in order to declare a speedup. Even with fixed input and execution environment, programs executions times vary in general. So hence different kinds of speedups may be reported: the speedup of the average execution time, the speedup of the minimal execution time, the speedup of the median, etc. Many published speedups in the literature are observations of a set of experiments. In order to improve the reproducibility of the experimental results, this technical report presents a rigorous statistical methodology regarding program performance analysis. We rely on well known statistical tests (Shapiro-wilk's test, Fisher's F-test, Student's t-test, Kolmogorov-Smirnov's test, Wilcoxon-Mann-Whitney's test) to study if the observed speedups are statistically significant or not. By fixing $0 Y}>\frac{1}{2}$, the probability that an individual execution of the optimised code is faster than the individual execution of the initial code. Our methodology defines a consistent improvement compared to the usual performance analysis method in high performance computing as in \cite{Jain:1991:ACS,lilja:book}. We explain in each situation what are the hypothesis that must be checked to declare a correct risk level for the statistics. The Speedup-Test protocol certifying the observed speedups with rigorous statistics is implemented and distributed as an open source tool based on R software.
An experimental study on Performance Evaluation of Asymmetric Encryption Algorithms

This paper presents the evaluation of RSA, ElGamal & Pallier asymmetric encryption algorithms. Encryption algorithms provide a secure communication over the internet and play main role in any security system. These algorithms consume a considerable amount of time and resources such as memory, CPU time, battery power and computation time to encrypt and decrypt data. In this paper, different experiments have been conducted to compare these algorithms in term of encryption time, decryption time, memory usage and throughput over variable text file and private key sizes. Key-Words: -Asymmetric Algorithms, Encryption Time, Decryption Time, Throughput, Encrypted File Size, Decrypted Files Size
Clinical implications of the variations of sciatic nerve bifurcation on the popliteal nerve block

iii OPSOMMING. iv RESEARCH OUTPUTS . vi ACKNOWLEDGEMENTS . vii TABLE OF CONTENTS . viii LIST OF FIGURES . xii LIST OF TABLES . xiv ABBREVIATIONS . xv Chapter 1 INTRODUCTION . 1 Chapter 2 LITERATURE REVIEW . 3 . Sciatic nerve . 3 Development of the sciatic nerve . 3 Anatomy . 4 Branches of the sciatic nerve . 7 The popliteal fossa . 14 Structures innervated by SN . 15 . Popliteal block . 17 Definition . 17 Indications . 18 Technique . 18 Stellenbosch University https://scholar.sun.ac.za
Current perspectives of nanoparticles in medical and dental biomaterials

Nanotechnology is gaining tremendous impetus due to its capability of modulating metals into their nanosize, which drastically changes the chemical, physical and optical properties of metals. Nanoparticles have been introduced as materials with good potential to be extensively used in biological and medical applications. Nanoparticles are clusters of atoms in the size range of 1-100 nm. Inorganic nanoparticles and their nano-composites are applied as good antibacterial agents. Due to the outbreak of infectious diseases caused by different pathogenic bacteria and the development of antibiotic resistance, pharmaceutical companies and researchers are searching for new antibacterial agents. The metallic nanoparticles are the most promising as they show good antibacterial properties due to their large surface area to volume ratios, which draw growing interest from researchers due to increasing microbial resistance against metal ions, antibiotics and the development of resistant strains. Metallic nanoparticles can be used as effective growth inhibitors in various microorganisms and thereby are applicable to diverse medical devices. Nanotechnology discloses the use of elemental nanoparticles as active antibacterial ingredient for dental materials. In dentistry, both restorative materials and oral bacteria are believed to be responsible for restoration failure. Secondary caries is found to be the main reason to restoration failure. Secondary caries is primarily caused by invasion of plaque bacteria (acid-producing bacteria) such as Streptococcus mutans and lactobacilli in the presence of fermentable carbohydrates. To make long-lasting restorations, antibacterial materials should be made. The potential of nanoparticles to control the formation of biofilms within the oral cavity is also coming under increasing scrutiny. Possible uses of nanoparticles as topically applied agents within dental materials and the application of nanoparticles in the control of oral infections are also reviewed.
AN EMPIRICAL COMPARISON OF TECHNIQUES FOR EXTRACTING CONCEPT ABBREVIATIONS FROM IDENTIFIERS

When a programmer is faced with the task of modifying code written by others, he or she must first gain an understanding of the concepts and entities used by the program. Comments and identifiers are the two main sources of such knowledge. In the case of identifiers, the meaning can be hidden in abbreviations that make comprehension more difficult. A tool that can automatically replace abbreviations with their full word meanings would improve the comprehension ability (especially of less experienced programmers) to understand and work with the code. Such a tool first needs to isolate abbreviations within the identifiers. When identifiers are separated by division markers such as underscores or camel-casing, this isolation task is trivial. However, many identifiers lack these division markers. Therefore, the first task of automatic expansion is separation of identifiers into their constituent parts. Presented here is a comparison of three techniques that accomplish this task: a random algorithm (used as a straw man), a greedy algorithm, and a neural network based algorithm. The greedy algorithm’s performance ranges from 75 to 81 percent correct, while the neural network’s performance ranges from 71 to 95 percent correct.
Phase I and pharmacodynamic study of an orally administered novel inhibitor of histone deacetylases, SB939, in patients with refractory solid malignancies.

BACKGROUND The objective of this study was to assess the safety, maximum tolerated dose (MTD), pharmacokinetics, pharmacodynamics, and preliminary efficacy of SB939, a novel histone deacetylase (HDAC) inhibitor, in patients with advanced solid malignancies. PATIENTS AND METHODS Dose-escalating cohorts of three to six patients received SB939 orally thrice weekly for 3 weeks in a 4-week cycle. Acetylated histone H3 (acH3) was measured in peripheral blood mononuclear cells (PBMCs). RESULTS Thirty patients treated at one of five doses (10-80 mg/day) received 79 cycles of SB939 (range, 1-12 cycles). Dose-limiting toxic effects were fatigue, hypokalemia, troponin T elevation, and QTc prolongation. Peak plasma concentration (C(max)) and area under the concentration-time curve extrapolated to infinity increased dose proportionally. The MTD of SB939 was 80 mg/day. The mean elimination half-life and oral clearance of SB939 were 7.2 ± 0.6 h and 53.0 ± 8.5 l/h, respectively, with no substantial accumulation on day 15. An increase in acH3 was observed at hour 3 and correlated with dose and C(max). Stable disease was seen in several tumor types treated at ≥40 mg. HDAC inhibition was consistently observed at 60 mg, the recommended dose. CONCLUSIONS SB939 can be safely administered at the recommended dose and reaches plasma levels that strongly inhibit HDAC in PBMCs. These data support further efficacy studies of SB939.
Comparison Between Different Finite Element Methods for Foreseeing the Elastic Properties of Carbon nanotube Reinforced Epoxy Resin Composite

this paper the mechanical properties of carbon nanotube C.N. T reinforced epoxy resin composite are studied with several methods in order to determine the best finite element modeling method. Composite effective module in different aspect ratios and volume fractions have been calculated. Effective ratio which achieved by different orientations of C.N. Ts in matrix has been investigated too. Two methods have been applied. In the first method by embedding a C.N. T into representative volume element with different alignments the equivalent module were calculated . In the second method, the nanotube was modeled as a beam element in a representative surface element. In both methods by substituting the obtained equivalent module in surface element, composite effective module has been calculated. Finally, the achieved results are compared with Halpin-Tsai method and also experimental results.
Mobility Assisted Efficient Coverage Control in Cluster Based Sensor Networks

Provisioning the network with sufficient lifetime is a key requirement in many sensor network applications. In order to save energy in densely deployed sensor network often a subset of so called redundant nodes periodically kept off while the other nodes in the vicinity working on behalf of the sleeping nodes. Preserving the adequate communication and sensing coverage throughout the entire network becomes challenging in such scenario. This work considers the various issues on coverage control for conserving energy of individual nodes thus indirectly increasing the network lifetime. Based upon the analysis a mobility assisted coverage control scheme is presented. The approach utilizes the fact that mobility assisted neighborhood probing enhances the sensing capability of individual nodes without substantial synchronization overhead among its neighbors.
A Privacy-Preserving Cloud Computing System for Creating Participatory Noise Maps

Participatory sensing is a crowd-sourcing technique which relies both on active contribution of citizens and on their location and mobility patterns. As such, it is particularly vulnerable to privacy concerns, which may seriously hamper the large-scale adoption of participatory sensing applications. In this paper, we present a privacy-preserving system architecture for participatory sensing contexts which relies on cryptographic techniques and distributed computations in the cloud. Each individual is represented by a personal software agent, which is deployed on one of the popular commercial cloud computing services. The system enables individuals to aggregate and analyse sensor data by performing a collaborative distributed computation among multiple agents. No personal data is disclosed to anyone, including the cloud service providers. The distributed computation proceeds by having agents execute a cryptographic protocol based on a homomorphic encryption scheme in order to aggregate data. We show formally that our architecture is secure in the Honest-But-Curious model both for the users and the cloud providers. Our approach was implemented and validated on top of the NoiseTube system [1], [2], which enables participatory sensing of noise. In particular, we repeated several mapping experiments carried out with NoiseTube, and show that our system is able to produce identical outcomes in a privacy-preserving way. We experimented with real and simulated data, and present a live demo running on a heterogeneous set of commercial cloud providers. The results show that our approach goes beyond a proof-of-concept and can actually be deployed in a real-world setting. To the best of our knowledge this system is the first operational privacy-preserving approach for participatory sensing. While validated in terms of NoiseTube, our approach is useful in any setting where data aggregation can be performed with efficient homomorphic cryptosystems.
A Methodology for Building Regression Models using Extreme Learning Machine: OP-ELM

This paper proposes a methodology named OP-ELM, based on a recent development –the Extreme Learning Machine– decreasing drastically the training speed of networks. Variable selection is beforehand performed on the original dataset for proper results by OP-ELM: the network is first created using Extreme Learning Process, selection of the most relevant nodes is performed using Least Angle Regression (LARS) ranking of the nodes and a Leave-One-Out estimation of the performances. Results are globally equivalent to LSSVM ones with reduced computational time.
Error Detection with Real-Number Codes Based on Random Matrices

Some well-known real-number codes are DFT codes. Since these codes are cyclic, they can be used to correct erasures (errors at known positions) and detect errors, using the locator polynomial via the syndrome, with efficient algorithms. The stability of such codes are, however, very poor for burst error patterns. In such conditions, the stability of the system of equations to be solved is very poor. This amplifies the rounding errors inherent to the real number field. In order to improve the stability of real-number error-correcting codes, other types of coding matrices were considered, namely random orthogonal matrices. These type of codes have proven to be very stable, when compared to DFT codes. However, the problem of detecting errors (when the positions of these errors are not known) with random codes was not addressed. Such codes do not possess any specific structure which could be exploited to create an efficient algorithm. In this paper, we present an efficient method to locate errors with codes based on random orthogonal matrices
Detecting data races in Cilk programs that use locks

When two parallel threads holding no locks in common access the same memory location and at least one of the threads modifies the location, a “data race” occurs, which is usually a bug. This paper describes the algorithms and strategies used by a debugging tool, called the Nondeterminator-2, which checks for data races in programs coded in the Cilk multithreaded language. Like its predecessor, the Nondeterminator, which checks for simple “determinacy” races, the Nondeterminator-2 is a debugging tool, not a verifier, since it checks for data races only in the computation generated by a serial execution of the program on a given input. We give an algorithm, ALL-SETS, that determines whether the computation generated by a serial execution of a Cilk program on a given input contains a race. For a program that runs serially in time T , accesses V shared memory locations, uses a total of n locks, and holds at most k n locks simultaneously, ALL-SETS runs in O(nkT α(V;V )) time and O(nkV ) space, where α is Tarjan’s functional inverse of Ackermann’s function. Since ALL-SETS may be too inefficient in the worst case, we propose a much more efficient algorithm which can be used to detect races in programs that obey the “umbrella” locking discipline, a programming methodology that is more flexible than similar disciplines proposed in the literature. We present an algorithm, BRELLY, which detects violations of the umbrella discipline in O(kT α(V;V )) time using O(kV ) space. We also prove that any “abelian” Cilk program, one whose critical sections commute, produces a determinate final state if it is deadlock free and if it generates any computation which is datarace free. Thus, the Nondeterminator-2’s two algorithms can verify the determinacy of a deadlock-free abelian program running on a given input. Keywords
Electronic synthesis using genetic algorithms for automatic music transcription

This paper presents a novel approach to the problem of automatic music transcription using electronic synthesis with genetic algorithms. Although the problem is well known and different techniques have been applied before, evolutionary algorithms have never been considered when addressing this problem. By means of a series of steps, we show that a polyphonic MIDI file -containing instrument’s partiturescan be automatically generated from an audio recording, by extracting and separating simultaneous notes. The results obtained shows the feasibility of the approach.
Transcriptome Analyses of a Salt-Tolerant Cytokinin-Deficient Mutant Reveal Differential Regulation of Salt Stress Response by Cytokinin Deficiency

Soil destruction by abiotic environmental conditions, such as high salinity, has resulted in dramatic losses of arable land, giving rise to the need of studying mechanisms of plant adaptation to salt stress aimed at creating salt-tolerant plants. Recently, it has been reported that cytokinins (CKs) regulate plant environmental stress responses through two-component systems. A decrease in endogenous CK levels could enhance salt and drought stress tolerance. Here, we have investigated the global transcriptional change caused by a reduction in endogenous CK content under both normal and salt stress conditions. Ten-day-old Arabidopsis thaliana wild-type (WT) and CK-deficient ipt1,3,5,7 plants were transferred to agar plates containing either 0 mM (control) or 200 mM NaCl and maintained at normal growth conditions for 24 h. Our experimental design allowed us to compare transcriptome changes under four conditions: WT-200 mM vs. WT-0 mM, ipt1,3,5,7-0 mM vs. WT-0 mM, ipt1,3,5,7-200 mM vs. ipt1,3,5,7-0 mM and ipt1,3,5,7-200 mM vs. WT-200 mM NaCl. Our results indicated that the expression of more than 10% of all of the annotated Arabidopsis genes was altered by CK deficiency under either normal or salt stress conditions when compared to WT. We found that upregulated expression of many genes encoding either regulatory proteins, such as NAC, DREB and ZFHD transcription factors and the calcium sensor SOS3, or functional proteins, such as late embryogenesis-abundant proteins, xyloglucan endo-transglycosylases, glycosyltransferases, glycoside hydrolases, defensins and glyoxalase I family proteins, may contribute to improved salt tolerance of CK-deficient plants. We also demonstrated that the downregulation of photosynthesis-related genes and the upregulation of several NAC genes may cause the altered morphological phenotype of CK-deficient plants. This study highlights the impact of CK regulation on the well-known stress-responsive signaling pathways, which regulate plant adaptation to high salinity as well as other environmental stresses.