Miracle-dz/UniFAR-FTUs huggingface dataset:
Capsaicin-induced pain and tourniquet constriction.

To the Editor:—Recently, Byas-Smith et al. reported that tourniquet constriction expands and exacerbates pain during intradermal injection of capsaicin in humans. The underlying mechanism was unclear. It is suggested herein that excitation of paravascular nociceptors is involved in expansion of pain. Capsaicin has been shown to evoke pain from skin, muscle, and paravascular tissue, but not from veins. In the latter study, one of the authors had a disconcerting experience. Capsaicin was perfused through a vascularly isolated hand vein segment to test capsaicin for its property to excite vascular nociceptors. It definitively did not, but strong pain occurred distant from the perfusion site and spread to the entire forearm. In fear of spreading pain to the entire body, a tourniquet was installed quickly to the upper arm, which, however, increased pain further, up to an unbearable intensity. It was determined that capsaicin solution had drained via a previously unnoticed side branch of the isolated vein segment into the venous system. From there, capsaicin apparently had gained access to the paravascular space (capsaicin does not evoke pain in veins). The substantial increase in capsaicin-induced pain during tourniquet inflation is unknown. A recruitment of myelinated fibers during ischemia has been discussed; however, fostering by venous congestion of transendothelial crossing of capsaicin to the paravascular tissue also may play a role. Thus, the spread of capsaicin from the site of application to the paravascular space may have contributed, at least in part, to the observations made by Byas-Smith et al.
Casting online votes: To predict offline results using sentiment analysis by machine learning classifiers

In today's world, Social Networking website like Twitter, Facebook, Instagram, etc. plays a very significant role. Twitter is a social networking website which provides loads of data that can be used for various purposes such as Sentiment Analysis for predictions, marketing, elections, etc. The objective of this research is to classify twitter data into sentiments (positive or negative) by using different supervised machine learning classifiers to predict the Delhi Corporation Elections results and to identify the most accurate machine learning classifier. The research highlights the performance of different classifiers on the twitter dataset related to political parties. Experiments show that Multinomial Naïve Bayes classifier is the most accurate sentiment predictors with 78%.
The first intensive care unit in the world: Copenhagen 1953

After an extensive survey of the medical literature we present compelling evidence that the first intensive care unit was established at Kommunehospitalet in Copenhagen in December 1953. The pioneer was the Danish anaesthetist Bjørn Ibsen. The many factors that interacted favourably in Copenhagen to promote the idea of intensive care therapy, half a century ago, are also described.
Mitochondrial DNA variation in wild populations of Leporinus elongatus from the Paraná River basin

Leporinus elongatus, a fish species widely distributed throughout the Parana River basin in South America, is an important fishery resource and a valuable species in aquaculture programs. Despite its great economic importance, several wild populations have been suffering a drastic reduction. The comprehension of its population structure represents an important step for the conservation of these organisms in natural environments, and also for the selection of wild stocks to be used in hatchery programs. In order to understand the genetic-population structure of L. elongatus, D-loop mitochondrial DNA analyses were applied in six wild populations of the species. The results were used to estimate the levels of within and among population genetic variability. Although the D-loop variations could not be correlated to the geographic distribution of these organisms, it was possible to detect high levels of genetic variability within each population and the occurrence of exclusive population haplotypes, which suggests a partial genetic differentiation among them. The obtained data can be useful in selecting fish stocks that preserve a better genetic diversity of L. elongatus for use in conservation and/or hatchery programs.
Low-Complexity and Energy-Efficient Algorithms on Image Compression for Wireless Sensor Networks

This paper proposes two algorithms to balance energy consumption among sensor nodes by distributing the workload of image compression tasks within a cluster on wireless sensor networks. The main point of the proposed algorithms is to adopt the energy threshold, which is used when we implement the exchange and/or assignment of tasks among sensor nodes. The threshold is well adaptive to the residual energy of sensor nodes, input image, compressed output, and network parameters. We apply the lapped transform technique, an extended version of the discrete cosine transform, and run length encoding before Lempel-Ziv-Welch coding to the proposed algorithms to improve both quality and compression rate in image compression scheme. We extensively conduct computational experiments to verify the our methods and find that the proposed algorithms achieve not only balancing the total energy consumption among sensor nodes and, thus, increasing the overall network lifetime, but also reducing block noise in image compression.
Relative importance of mothers' versus medical staffs' behavior in the prediction of infant immunization pain behavior.

OBJECTIVE To examine the relative importance of mothers' versus medical staffs' behavior in the prediction of infant pain during routine immunization. METHODS We video-recorded 60 infants' 6- or 18-month immunizations. Recordings were used to code infant pain behavior using the Neonatal Facial Action Coding System (NFCS, R. V. E. Grunau & K. D. Craig, 1987), and maternal and staff vocalizations using the Child-Adult Medical Procedure Interaction Scale-Revised (CAMPIS-R, R. L. Blount, J. W. Sturges, & S. W. Powers, 1990). RESULTS Maternal and staff vocalizations showed different patterns of relation with infant pain behavior, depending upon the type of vocalization. Mothers' distress-promoting behavior (e.g., reassurance) predicted increased infant pain behavior, while staffs' coping-promoting behavior (e.g., distraction) predicted decreased infant pain behavior.
Nano-Scale Modelling and Simulation of Metal Wiredrawing by Using Molecular Dynamics Method

In this paper, molecular dynamics (MD) simulations of nano-sized wiredrawing are performed. The wiredrawing is a traditional plastic working method, but there has not been any insight to develop it in a nano-sized scale. Therefore, to materialize the concept of the nano-sized wiredrawing, a numerical modelling is pursued at first in this paper, and the interatomic potential, a crystalline orientation, the drawing condition realized by a die geometry are thoroughly investigated. In particular, to reduce the friction between a wire and a die, a simple friction model for the MD analysis is newly proposed, where the interatomic interaction is adequately modified by a single factor ω. Then, the fruitful results are obtained by using ω = 0.1. We checked the availability of such nano-sized MD simulation by constructing a two-dimensional wiredrawing model, at first. The analysis of atomic stress during drawing is also assessed. It is useful to use invariant of the atomic stress tensor, such as hydrostatic stress (average stress, σm) or von Mises equivalent stress (σeq). The former is related to the phase transformation from the body-centered-cubic (bcc) structure to the face-centered-cubic (fcc) one, which is found in the present MD simulation. It is observed that an initial α-iron crystal with bcc structure changes partially into the fcc phase. It is recognized that the phase transformation is caused by the positive hydrostatic stress values, which is occurring especially inside the die region. We observed that a lot of dislocation core structures occur in wiredrawing process and their existence and evolution are well related to the equivalent stress values.
Osmotic regulation of gene expression

Cells react to increased osmolality with numerous changes in gene expression. The specific genes affected differ between species, but the known osmoprotective effects of the gene products are remarkably similar, particularly with regard to cellular accumulation of compatible organic os‐ molytes. Here we concentrate on the molecular basis for osmotic regulation of gene expression, emphasizing certain genes expressed in bacteria, yeast, and the mammalian renal medulla because their expression is best understood. Thus, we emphasize 1) bac‐terial and yeast two‐component histidine kinase systems, each consisting of a membrane osmolality sensor and a separate cytoplasmic response regulator that, when phosphorylated, alters transcription, 2) volume regulatory increases in cellular K+ salts that can prompt increased gene transcription in bacteria through direct effects on DNA and that in mammalian renal cells increase transcription, seemingly via Irans‐activating proteins, 3) a yeast kinase cascade that transmits an osmotic signal to the gene regulating the level of glycerol, and 4) in mammalian cells, several homologous cascades that are activated by hypertonicity, but whose osmoregulatory targets are not yet known. —Burg, M. B. , Kwon, E. D. , Kültz, D. Osmotic regulation of gene expression. FASEBJ. 10, 1598‐1606(1996)
Learning Style Estimation using Bayesian Networks

In order to improve the efficiency of Learning Style estimation, we propose an easily, applicable, Web based, expert system founded on Bayesian networks. The proposed system takes under consideration learners’ answers to a certain questionnaire, as well as classification of learners who have been examined before. As a result, factors such as cultural environment will add value to the learning style estimation. Moreover, the influence of wrong answers, caused by various reasons, is expected to be reduced.
Electronically switchable microstrip bandpass filter with good selectivity

In this work, an electronically switchable cross-coupled microstrip bandpass filter using p-i-n diodes is proposed. The basic filter structure is based on the cascade of λ/8 parallel and anti-parallel coupled-line sections. Therefore, it occupies only about half the circuit size of conventional parallel-coupled filters. The magnetic cross-coupling is also introduced to achieve two transmission zeros in the lower and upper stopbands. In addition, by employing the four-line anti-parallel coupled microstrip structure, two more transmission zeros in the upper stopband are obtained. Two p-i-n diodes along with a common bias control circuitry are then introduced to allow the bandpass filter to be switched on and off. For design purpose, suitable equivalent-circuit for the filter is also introduced. Specifically, a switchable 4th-order microstrip bandpass filter with a center frequency of 1.5 GHz, passband insertion loss less than 2 dB, 3-dB bandwidth of 19.5%, and four transmission zeros is demonstrated. The ON-OFF isolation is better than 20 dB from dc up to 4.3 GHz.
Debug methodology for the McKinley processor

The McKinley processor is the result of a joint design effort between Intel and Hewlett-Packard engineers, and is the second processor implementation of the Itanium/sup TM/ Processor Family. This paper describes in detail the processes and methodology developed for debugging a complex and challenging microprocessor design. An overview of microprocessor debug techniques utilized by HP and Intel is presented, followed by descriptions of debug techniques employed on McKinley. Two case studies of electrical bugs encountered during design debug are presented to demonstrate some of the processes and techniques described previously, and results are discussed.
Evidence-based review of diabetic macular edema management: Consensus statement on Indian treatment guidelines

The purpose of the study was to review the current evidence and design a diabetic macular edema (DME) management guideline specific for India. The published DME guidelines from different organizations and publications were weighed against the practice trends in India. This included the recently approved drugs. DME management consisted of control of diabetes and other associated systemic conditions, such as hypertension and hyperlipidemia, and specific therapy to reduce macular edema. Quantification of macular edema is precisely made with the optical coherence tomography and treatment options include retinal laser, intravitreal anti-vascular endothelial growth factors (VEGF), and implantable dexamethasone. Specific use of these modalities depends on the presenting vision and extent of macular involvement. Invariable eyes with center-involving macular edema benefit from intravitreal anti-VEGF or dexamethasone implant therapy, and eyes with macular edema not involving the macula center benefit from retinal laser. The results are illustrated with adequate case studies and frequently asked questions. This guideline prepared on the current published evidence is meant as a guideline for the treating physicians.
A REMOVAL MODEL FOR ESTIMATING DETECTION PROBABILITIES FROM POINT-COUNT SURVEYS

Abstract Use of point-count surveys is a popular method for collecting data on abundance and distribution of birds. However, analyses of such data often ignore potential differences in detection probability. We adapted a removal model to directly estimate detection probability during point-count surveys. The model assumes that singing frequency is a major factor influencing probability of detection when birds are surveyed using point counts. This may be appropriate for surveys in which most detections are by sound. The model requires counts to be divided into several time intervals. Point counts are often conducted for 10 min, where the number of birds recorded is divided into those first observed in the first 3 min, the subsequent 2 min, and the last 5 min. We developed a maximum-likelihood estimator for the detectability of birds recorded during counts divided into those intervals. This technique can easily be adapted to point counts divided into intervals of any length. We applied this method to unlimited-radius counts conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. We found differences in detection probability among species. Species that sing frequently such as Winter Wren (Troglodytes troglodytes) and Acadian Flycatcher (Empidonax virescens) had high detection probabilities (∼90%) and species that call infrequently such as Pileated Woodpecker (Dryocopus pileatus) had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. We used the same approach to estimate detection probability and density for a subset of the observations with limited-radius point counts.
Distinctiveness magnifies the impact of biological invaders in aquatic ecosystems

There exist few empirical rules for the effects of introduced species, reflecting the context-dependent nature of biological invasions. A promising approach toward developing generalizations is to explore hypotheses that incorporate characteristics of both the invader and the recipient system. We present the first general test of the hypothesis that an invader’s impact is determined by the system’s evolutionary experience with similar species. Through a meta-analysis, we compared the taxonomic distinctiveness of high- and low-impact invaders in several aquatic systems. We find that high-impact invaders (i.e. those that displace native species) are more likely to belong to genera not already present in the system.
When Novice Researchers Adopt Constructivist Grounded Theory: Navigating Less Travelled Paradigmatic and Methodological Paths in PhD Dissertation Work

Graduate students considering constructivist grounded theory as a qualitative methodological approach may benefit from recognizing the many challenges they could face when embarking in thesis work. These challenges include great diversity in approaches to grounded theory, lack of congruity in how grounded theory methodology is described and understood within the literature, and a dearth of expertise and/or support within academic committees and institutions for both grounded theory and constructivist approaches to qualitative research. In this article, we describe why we selected constructivist grounded theory for our PhD work and the common challenges we encountered. Drawing on the analogy of preparing for a journey, we offer strategies for future graduate students including locating one’s ontological and epistemological worldview, finding grounded theory mentors, and facilitating a methodological fit with academic stakeholders. Our recommendations focus on how to navigate the challenging terrain of conducting a qualitative research project within a predominantly post-positivist landscape.
Examination of enterotoxigenic Escherichia coli H10407 (colonization factor antigen I+) by scanning electron microscopy with conductive staining

We have used the scanning electron microscope to examine enterotoxigenic Escherichia coli H10407, which expresses colonization factor antigen I pili. The use of low accelerating voltages and conductive staining procedures allowed us to obtain images of colonization factor antigen I pili and other structural details which were obscured by conventional gold-coating techniques.
Reconfigurable and Adaptive Spark Applications

The contribution of this paper is two-fold. First, we propose a Domain Specific Language (DSL) to easily reconfigure and compose Spark applications. For each Spark application we define its input and output interfaces. Then, given a set of connections that map outputs of some Spark applications to free inputs of other Spark applications, we automatically embed Spark applications with the required synchronization and communication to properly run them according to the user-defined mapping. Second, we present an adaptive quality management/selection method for Spark applications. The method takes as input a pipeline of parameterized Spark applications, where the execution time of each Spark application is an unknown increasing function of quality level parameters. The method builds a controller that automatically computes adequate quality for each Spark application to meet a user-defined deadline. Consequently, users can submit a pipeline of Spark applications and a deadline, our method automatically runs all the Spark applications with the maximum quality while respecting the deadline specified by the user. We present experimental results showing the effectiveness of our method.
On minimal realization for a fuzzy language and Brzozowski's algorithm

The purpose of the present work is to provide a simpler solution of a well-known characterization of fuzzy regular languages and a minimal realization for given fuzzy language by using Brzozowski’s algorithm. In between, we associate two crisp deterministic fuzzy automata with a given crisp deterministic fuzzy automaton and show that the reachability and observability maps of the given crisp deterministic fuzzy automaton turn out to be morphisms of category of all crisp deterministic fuzzy
Mechanistic insights into cognate substrate discrimination during proofreading in translation

Editing/proofreading by aminoacyl-tRNA synthetases is an important quality control step in the accurate translation of the genetic code that removes noncognate amino acids attached to tRNA. Defects in the process of editing result in disease conditions including neurodegeneration. While proofreading, the cognate amino acids larger by a methyl group are generally thought to be sterically rejected by the editing modules as envisaged by the “Double-Sieve Model. ” Strikingly using solution based direct binding studies, NMR-heteronuclear single quantum coherence (HSQC) and isothermal titration calorimetry experiments, with an editing domain of threonyl-tRNA synthetase, we show that the cognate substrate can gain access and bind to the editing pocket. High-resolution crystal structural analyses reveal that functional positioning of substrates rather than steric exclusion is the key for the mechanism of discrimination. A strategically positioned “catalytic water” molecule is excluded to avoid hydrolysis of the cognate substrate using a “RNA mediated substrate-assisted catalysis mechanism” at the editing site. The mechanistic proof of the critical role of RNA in proofreading activity is a completely unique solution to the problem of cognate-noncognate selection mechanism.
Signal Processing Implementation and Comparison of Automotive Spatial Sound Rendering Strategies

Design and implementation strategies of spatial sound rendering are investigated in this paper for automotive scenarios. Six design methods are implemented for various rendering modes with different number of passengers. Specifically, the downmixing algorithms aimed at balancing the front and back reproductions are developed for the 5.1-channel input. Other five algorithms based on inverse filtering are implemented in two approaches. The first approach utilizes binaural (Head-Related Transfer Functions HRTFs) measured in the car interior, whereas the second approach named the point-receiver model targets a point receiver positioned at the center of the passenger's head. The proposed processing algorithms were compared via objective and subjective experiments under various listening conditions. Test data were processed by the multivariate analysis of variance (MANOVA) method and the least significant difference (Fisher's LSD) method as a post hoc test to justify the statistical significance of the experimental data. The results indicate that inverse filtering algorithms are preferred for the single passenger mode. For the multipassenger mode, however, downmixing algorithms generally outperformed the other processing techniques.
Mining E-commerce feedback comments for trust evaluation

Buyers express their opinions openly in free text feedback comments. The users are attracted to online-shopping not only due to the convenience in accessing the information of items on-sold, but also the availability of the other buyer's feedback on their purchasing experience, item-related and/or seller-related. The Mining E-Commerce feedback comments for trust evaluation System proposes a novel technique that uses a multi-dimensional trust evaluation model, for computing comprehensive trust scores for sellers in e-commerce applications. The system computes dimension trust scores and the dimension weights. It automatically extracting dimension ratings from feedback comments and by combining natural language processing with opinion mining and summarization techniques in trust evaluation to improve the accuracy for mining process.