Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationship between anterior chamber depth, refractive state, corneal diameter, and axial length.

PURPOSE Phakic intraocular lenses are being used increasingly to correct refractive errors. We studied the relationship between anterior chamber depth, refractive state of the eye, spherical equivalent refraction, axial length of the globe, corneal diameter, and keratometry. METHODS Two hundred eleven eyes of 211 patients were enrolled. All eyes underwent the same protocol with a complete ocular examination that included slit-lamp microscopy, intraocular pressure, objective and subjective refraction, calculation of the spherical equivalent refraction, corneal pachymetry, anterior chamber depth, axial length of the globe, and keratometry. All results were analyzed statistically using SPSS statistics software. Correlations between different parameters were studied using the Pearson correlation test. RESULTS The anterior chamber depth was found to correlate significantly with both the average corneal diameter and the axial length of the globe (0.744, 0.531, P < .01) and was also found to correlate through an inverse relation with both age and spherical equivalent refraction (-0.391, -0.623, P < .01). Corneal thickness and keratometric power did not correlate with the anterior chamber depth. CONCLUSION Most parameters (axial length, corneal diameter, spherical equivalent refraction, patient age) affected anterior chamber depth and should be considered carefully when planning refractive procedures that employ phakic intraocular lenses.
Continuous learning of compiler heuristics

Optimizing programs to exploit the underlying hardware architecture is an important task. Much research has been done on enabling compilers to find the best set of code optimizations that can build the fastest and less resource-hungry executable for a given program. A common approach is iterative compilation, sometimes enriched by machine learning techniques. This provides good results, but requires extremely long compilation times and an initial training phase lasting even for days or weeks. We present long-term learning, a new algorithm that allows the compiler user to improve the performance of compiled programs with reduced compilation times with respect to iterative compilation, and without an initial training phase. Our algorithm does not just build good programs: it acquires knowledge every time a program is compiled and it uses such knowledge to learn compiler heuristics, without the need for an expert to manually define them. The heuristics are evolved during every compilation, by evaluating their effect on the generated programs. We present implementations of long-term learning on top of two different compilers, and experimental data gathered on multiple hardware configurations showing its effectiveness.
Empirical Statistics: IV. Illustrating Meehl's Sixth Law of Soft Psychology: Everything Correlates with Everything

A 135 × 135 matrix of correlations was computed, using educational/biographical data on 2,058 subjects, to find the background level of statistically significant correlations, or Meehl's ‘crud factor. ’ Every one of the 135 variables, save ID number, displayed more statistically significant correlations with the other variables than could be predicted from chance. With alpha set at . 05 (two-tailed), a given variable correlated significantly on average with 41% of the other variables, although the absolute magrutude of the correlations averaged only . 07. The results reinforce Meehl's 1990 criticisms of over-reliance on significance levels for correlational data.
Acceleration technique for volume rendering using 2D texture based ray plane casting on GPU

In this paper, we present a very fast new GPU-based algorithm for volume rendering using the ray plane casting technique. It consists of preprocessing and main processing. In preprocessing, we reduce the waste of memory and produce the texture data which can be efficiently traversed concurrently in main processing by converting the volume data into a 2D texture of square shape in the frame buffer. In main processing, the ray plane casting and resampling are implemented by fragment programming which makes the efficient use of GPUs high performance. Early termination and space leaping have been used as acceleration techniques during the calculation of color and opacity in the fragment program on GPU using stencil and depth tests on GPU. We shall show that our GPU-based algorithm is much faster than CPU-based by the efficient fragment programming techniques used for ray plane interpolation, resampling and acceleration techniques
The Extracellular Matrix Molecule Tenascin: Expression in the Developing Chick Retinotectal System and Substrate Properties for Retinal Ganglion Cell Neurites In vitro

To investigate the molecular mechanisms involved in the outgrowth of retinal ganglion cell axons in the tectum, the expression of the extracellular matrix molecule tenascin was analysed in the tectum and retina of chickens by immunocytochemistry and in situ hybridization. Tissue was analysed between embryonic days 4 and 12, just before and during the period when retinal ganglion cell axons innervate their target region, the optic tectum. In the tectum, tenascin immunoreactivity becomes detectable at the anterior pole at embryonic day 4, 2 days before retinal ganglion cell axons arrive, and spreads caudally with increasing age. At early stages, tenascin is predominantly accumulated in the stratum opticum, the zone of ingrowing retinal ganglion cell axons, and along their prospective pathway. In the stratum opticum, the molecule is associated with radial glial fibres, glial endfeet and retinal ganglion cell axons located in the immediate neighbourhood of radial glial fibres. At all ages investigated, tenascin mRNA is mainly restricted to cells located in the periventricular region, suggesting that the molecule is synthesized by radial glial cells. In the retina, tenascin is expressed by amacrine, displaced amacrine and horizontal cells but not by retinal ganglion cells. To investigate whether the accumulation of tenascin in the developing and prospective pathway of retinal ganglion cell axons may affect their rate of growth we assayed the substrate properties of tenascin for retinal ganglion cell neurites in vitro. When retinal ganglion cell suspensions from 6–day‐old chick embryos were maintained on homogeneous mouse or chick tenascin/ polyornithine substrates, neurite length was significantly increased when compared to polyornithine substrates at coating concentrations of 10 or 20 μg/ml. Higher coating concentrations (35 or 70 μg/ml) resulted in neurite lengths comparable to control values. Together, these observations suggest that tenascin in the developing and prospective stratum opticum might serve as a preformed pathway to support growth of retinal ganglion cell axons in the tectum.
High-Frequency Gap Losses in Nanocrystalline Cores

Finite element analysis is used to examine the gap losses that occur in finely laminated nanocrystalline inductor cores under high-frequency operation. The losses are seen to be concentrated in the region of the air gap and the dependence of the losses on key design parameters and operating conditions is explored. The results show that gap losses can be significant in this type of core, creating hot spots around the gap, and the losses are not accurately predicted by established design equations for low-frequency laminated cores. A modified loss equation is proposed. Validation is provided by measurements on a 300-A, 60 kHz inductor.
The Rate of Morphological Evolution in Mammals from the Standpoint of the Neutral Expectation

A comparison of the evolutionary rates of cranial morphology in mammals with the neutral expectation suggests that stabilizing selection is a predominant evolutionary force keeping the long-term diversification of lineages well below its potential. The rate of morphological divergence of almost all lineages, including the great apes, is substantially below the minimum neutral expectation. The divergence of the modern races of man is slightly above the minimum neutral rate but well below the maximum rate. Therefore, there is no need to invoke extraordinary mutational mechanisms, such as regulatory gene evolution, to explain what has been perceived as rapid morphological evolution in mammals. Nor does it appear that behavioral drive needs to be invoked to explain rapid morphological evolution in hominoids. Outside of man, the long-term rate of phenotypic evolution in the great apes is actually lower than that for other mammals. The data suggest that, immediately after reproductive isolation, most lineages diverge morphologically at approximately the neutral rate and that this rate declines over evolutionary time. Such a pattern is consistent with a broad class of phenotypic evolutionary models that invoke an interaction between the forces of random genetic drift, polygenic mutation, and stabilizing selection. This pattern also suggests that the apparently rapid rates of morphological evolution in modern man relative to other mammals and in mammals relative to other vertebrates are artifacts of temporal scaling.
The parkinsonian toxin 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP): a technical review of its utility and safety

Parkinson's disease (PD) is a common disabling neurodegenerative disorder the cardinal clinical features of which include tremor, rigidity and slowness of movement (Fahn and Przedborski 2000). These symptoms are attributed mainly to a profound reduction of dopamine in the striatum due to a dramatic loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) (Fahn and Przedborski 2000). Thus far, both the cause and the mechanisms of PD remain unknown. Over the years, investigators have used experimental models of PD produced by several compounds such as reserpine, 6-hydroxydopamine, methamphetamine, and 1-methyl-4phenyl-1,2,3,6-tetrahydropyridine (MPTP) to provide insights into the mechanisms responsible for the demise of dopaminergic neurons in PD. To this end, MPTP has emerged unquestionably as a popular tool for inducing a model of PD in a variety of animal species including monkeys, rodents, cats, and pigs (Kopin and Markey 1988). The sensitivity to MPTP and therefore its ability to induce parkinsonism closely follows the phylogenetic tree where the species most closely related to humans are the most vulnerable to this neurotoxin. Due to the signi®cant neurotoxicity of MPTP, it is important that researchers appreciate the potential hazards of this toxin. Given this, the purpose of this review is to inform the researcher of the hazardous nature of MPTP and to provide guidance for its safe handling and use.
A novel conceptual approach to read-filtering in high-throughput amplicon sequencing studies

Adequate read filtering is critical when processing high-throughput data in marker-gene-based studies. Sequencing errors can cause the mis-clustering of otherwise similar reads, artificially increasing the number of retrieved Operational Taxonomic Units (OTUs) and therefore leading to the overestimation of microbial diversity. Sequencing errors will also result in OTUs that are not accurate reconstructions of the original biological sequences. Herein we present the Poisson binomial filtering algorithm (PBF), which minimizes both problems by calculating the error-probability distribution of a sequence from its quality scores. In order to validate our method, we quality-filtered 37 publicly available datasets obtained by sequencing mock and environmental microbial communities with the Roche 454, Illumina MiSeq and IonTorrent PGM platforms, and compared our results to those obtained with previous approaches such as the ones included in mothur, QIIME and USEARCH. Our algorithm retained substantially more reads than its predecessors, while resulting in fewer and more accurate OTUs. This improved sensitiveness produced more faithful representations, both quantitatively and qualitatively, of the true microbial diversity present in the studied samples. Furthermore, the method introduced in this work is computationally inexpensive and can be readily applied in conjunction with any existent analysis pipeline.
Using Data To Differentiate Instruction.

Because the group of students who are as “clear as glass” understands and can apply greatest common factor at both the conceptual and skill levels, she has these students use a Euclidean algorithm to find the greatest common factor in a series of exercises. A group of “buggy” students—who understand the basic concept of greatest common factor, but still need to build their confidence through application—play a greatest common factor game that Ms. Martez has created. And she sends the “muddy” group to sort factors in a giant Venn diagram constructed of two hula-hoops. This oversized graphic organizer provides a kinesthetic and interpersonal learning experience for those who need additional practice to master the basic concept and skills.
An Effective BCI Speller Based on Semi-supervised Learning

Brain-computer interfaces (BCIs) aim to provide an alternative channel for paralyzed patients to communicate with external world. Reducing the time needed for the initial calibration is one important objective in P300 based BCI research. In this paper, the training time is reduced by a semi-supervised learning approach. A model is trained by small training set first. The on-line test data with predicted labels are then added to the initial training data to extend the training data. And the model is updated online using the extended training set. The method is tested by a data set of P300 based word speller. The experimental results show that 93.4% of the training time for this data set can be reduced by the proposed method while keeping satisfactory accuracy rate. This semi-supervised learning approach is applied on-line to obtain robust and adaptive model for P300 based speller with small training set, which is believed to be very essential to improve the feasibility of the P300 based BCI
Activation of satellite cells and the regeneration of human skeletal muscle are expedited by ingestion of nonsteroidal anti‐inflammatory medication

With this study we investigated the role of nonsteroidal anti‐inflammatory drugs (NSAIDs) in human skeletal muscle regeneration. Young men ingested NSAID [1200 mg/d ibuprofen (IBU)] or placebo (PLA) daily for 2 wk before and 4 wk after an electrical stimulation‐induced injury to the leg extensor muscles of one leg. Muscle biopsies were collected from the vastus lateralis muscles before and after stimulation (2.5 h and 2,7, and 30 d) and were assessed for satellite cells and regeneration by immunohistochemistry and real‐time RT‐PCR, and we also measured telomere length. After injury, and compared with PLA, IBU was found to augment the proportion of ActiveNotch1+ satellite cells at 2 d [IBU, 29 ± 3% vs. PLA, 19 ± 2% (means ± sem)], satellite cell content at 7 d [IBU, 0.16 ± 0.01 vs. PLA, 0.12 ± 0.01 (Pax7+ cells/fiber)], and to expedite muscle repair at 30 d. The PLA group displayed a greater proportion of embryonic myosin+ fibers and a residual ~2‐fold increase in mRNA levels of matrix proteins (all P< 0.05). Endomysial collagen was also elevated with PLA at 30 d. Minimum telomere length shortening was not observed. In conclusion, ingestion of NSAID has a potentiating effect on Notch activation of satellite cells and muscle remodeling during large‐scale regeneration of injured human skeletal muscle. —Mackey, A. L. , Rasmussen, L. K. , Kadi, F. , Schjerling, P., Helmark, I. C. , Ponsot, E. , Aagaard, P., Durigan, J. L. Q. , Kjaer, M. Activation of satellite cells and the regeneration of human skeletal muscle are expedited by ingestion of nonsteroidal anti‐inflammatory medication. FASEB J. 30, 2266–2281 (2016). www.fasebj. org
Determination of the multi-slot transmission in Bluetooth systems with the estimation of the channel error probability

Bluetooth is an open specification for a technology to enable short-range wireless communications that operate in an ad hoc fashion. Bluetooth uses frequency hopping with a slot length of 625 μs. Each slot corresponds to a packet and multi-slot packets of three or five slots can be transmitted to enhance the transmission efficiency. However, the use of multi-slot packet may degrade the transmission performance under high channel error probability. Thus, the length of multi-slot should be adjusted according to the current channel condition. Segmentation and reassembly (SAR) operation of Bluetooth enables the adjustment of the length of multi-slot. In this paper, we propose an efficient multi-slot transmission scheme that adaptively determines the optimal length of slots of a packet according to the channel error probability. We first discuss the throughput of a Bluetooth connection as a function of the length of a multi-slot and the channel error probability. A decision criteria which gives the optimal length of the multi-slot is presented under the assumption that the channel error probability is known. For the implementation in the real Bluetooth system, the channel error probability is estimated with the maximum likelihood estimator (MLE). A simple decision rule for the optimal multi-slot length is developed to maximize the throughput. Simulation experiment shows that the proposed decision rule for the multi-slot transmission effectively provides the maximum throughput under any type of channel error correlation. Copyright © 2005 John Wiley & Sons, Ltd.
Machine learning-based VLSI cells shape function estimation

We describe in this paper a novel approach based upon machine learning for estimating layout shape functions of full-custom integrated circuit cells. A neural network is trained to estimate one dimension of cell layout from circuit netlist, a desired packing density, and prescribed values of the complementary dimension. The neural network is then combined with a linear function generator and a neural network that predicts the number of contacts (vias) to produce estimates of cell layout shape functions. We have experimented with this approach on an independent test set of circuits and the results are very encouraging. The resulting estimation system is very fast and can be easily incorporated into exiting floorplanning systems. An additional benefit of the the machine learning aspect is the simplicity and systematicity in incorporating into the estimation system new circuits and technology information as they become available.
A Compact Representation of Drawing Movements with Sequences of Parabolic Primitives

Some studies suggest that complex arm movements in humans and monkeys may optimize several objective functions, while others claim that arm movements satisfy geometric constraints and are composed of elementary components. However, the ability to unify different constraints has remained an open question. The criterion for a maximally smooth (minimizing jerk) motion is satisfied for parabolic trajectories having constant equi-affine speed, which thus comply with the geometric constraint known as the two-thirds power law. Here we empirically test the hypothesis that parabolic segments provide a compact representation of spontaneous drawing movements. Monkey scribblings performed during a period of practice were recorded. Practiced hand paths could be approximated well by relatively long parabolic segments. Following practice, the orientations and spatial locations of the fitted parabolic segments could be drawn from only 2–4 clusters, and there was less discrepancy between the fitted parabolic segments and the executed paths. This enabled us to show that well-practiced spontaneous scribbling movements can be represented as sequences (“words”) of a small number of elementary parabolic primitives (“letters”). A movement primitive can be defined as a movement entity that cannot be intentionally stopped before its completion. We found that in a well-trained monkey a movement was usually decelerated after receiving a reward, but it stopped only after the completion of a sequence composed of several parabolic segments. Piece-wise parabolic segments can be generated by applying affine geometric transformations to a single parabolic template. Thus, complex movements might be constructed by applying sequences of suitable geometric transformations to a few templates. Our findings therefore suggest that the motor system aims at achieving more parsimonious internal representations through practice, that parabolas serve as geometric primitives and that non-Euclidean variables are employed in internal movement representations (due to the special role of parabolas in equi-affine geometry).
A Gradient Learning Rule for the Tempotron

We introduce a new supervised learning rule for the tempotron task: the binary classification of input spike trains by an integrate-and-fire neuron that encodes its decision by firing or not firing. The rule is based on the gradient of a cost function, is found to have enhanced performance, and does not rely on a specific reset mechanism in the integrate-and-fire neuron.
Short video metadata acquisition game

Gathering proper descriptive metadata for multimedia resources is nowadays essential for effective information processing, recommendation and personalization. And, we still need to employ human workforce in crowdsourcing scenarios for solving particular metadata acquisition tasks. In this paper we present a human computation game, which acquires metadata for short videos found in the Vine social media service. Player's task is to watch a given short video (without any further description) and formulate a search query, which will make that video appear in top results of the search. The player queries are then processed for keywords characterizing the videos. Our experiments show, that these keywords are both correct and from the great part, represent new information atop existing video descriptions.
Cleaning Tweets Tokenize and basic cleaning Twitter lingo cleaning Camel case Cleaning Spell Corrections Clean Tweets LIWC 2007 Categorizing LIWC 2007 Dictionary Based Features Other Tweet based Features

In this paper we try to classify a user into three categories: “Gender”, “Age” and “Political Affiliation” with an application to Indian Twitter users. Our approach automatically predicts these attributes by leveraging observable information such as the tweet behavior, linguistic content of the user’s Twitter feed and the celebrities followed by the user. This paper would also use a novel feature that we would define in this paper as “class influencers”. Class influencers are the twitter users which influence a particular class so much that, they themselves can be used as a discriminative feature. Our approach first extracts the linguistic content based features using LIWC dictionary. Then we derive features like smiley types, smiley count, tweet frequency, night-time tweet frequency , etc. We have also derived celebrity based feature, like age, genre, gender (using Wikipedia and Freebase) of the celebrities a user is following. Finally, we refine the results using class influencers. Results show that rich linguistic features combined with popular neighborhood and influencers prove valuables and promising for additional user classification needs.