Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study of the Behavioral Effects of Prenatal Ethanol Exposure in Mice Fed a diet Marginally Deficient in Essential Fatty Acids for Two Generations

This study investigated the effects of prenatal ethanol exposure on measures of fecundity, growth, behavioral development and learning in mice that had been fed a diet, marginal in essential fatty acid (EFA) content for two generations. The first generation of mice were fed one of two diets (adequate or marginal EFA) from conception. They were mated at 10 weeks, and from days 5 to 17 of gestation dams on each diet were fed equivalent daily amounts of a liquid diet containing either 22.5% of the calories as ethanol or with maltose-dextrin substituted isocalorically for ethanol. An additional control group was fed lab chow ad libitum. Offspring were maintained on their respective diets after weaning. The marginal-EFA diet led to a large increase in perinatal mortality; it also decreased body and brain weight in the surviving pups, and retarded behavioural development. Ethanol retarded behavioral development in females, and delayed the acquisition of learning the position of an escape platform in a T water-maze in the mice fed the adequate-EFA diet. The effects of ethanol did not appear to be worse in the mice fed the marginal-EFA diet, but these data must be considered in light of the high mortality on this diet, where only the healthiest pups may have survived.
Differential contribution of ACh‐muscarinic and β‐adrenergic receptors to vasodilatation in noncontracting muscle during voluntary one‐legged exercise

We have demonstrated the centrally induced cholinergic vasodilatation in skeletal muscle at the early period of voluntary one‐legged exercise and during motor imagery in humans. The purpose of this study was to examine whether central command may also cause β‐adrenergic vasodilatation during the exercise and motor imagery. Relative changes in oxygenated hemoglobin concentration (Oxy‐Hb) of bilateral vastus lateralis (VL) muscles, as index of tissue blood flow, and femoral blood flow to nonexercising limb were measured during one‐legged cycling and mental imagery of the exercise for 1 min before and after propranolol (0.1 mg/kg iv). The Oxy‐Hb of noncontracting muscle increased (P < 0.05) at the early period of exercise and the increase was sustained throughout exercise, whereas the Oxy‐Hb of contracting muscle increased at the early period but thereafter decreased. We subtracted the Oxy‐Hb response with propranolol from the control response in individual subjects to identify the propranolol‐sensitive component of the Oxy‐Hb response during exercise. In both noncontracting and contracting VL muscles, the increase in Oxy‐Hb at the early period of one‐legged exercise did not involve a significant propranolol‐sensitive component. However, as the exercise proceeded, the propranolol‐sensitive component of the Oxy‐Hb response was developed during the later period of exercise. Propranolol also failed to affect the initial increases in femoral blood flow and vascular conductance of nonexercising leg but significantly attenuated (P < 0.05) their later increases during exercise. Subsequent atropine (10–15 μg/kg iv) abolished the initial increases in Oxy‐Hb of both VL muscles. Mental imagery of the one‐legged exercise caused the bilateral increases in Oxy‐Hb, which were not altered by propranolol but abolished by subsequent atropine. It is likely that the rapid cholinergic and delayed β‐adrenergic vasodilator mechanisms cooperate to increase muscle blood flow during exercise.
Generating test cases for specification mining

Dynamic specification mining observes program executions to infer models of normal program behavior. What makes us believe that we have seen sufficiently many executions? The typestate miner generates test cases that cover previously unobserved behavior, systematically extending the execution space and enriching the specification. To our knowledge, this is the first combination of systematic test case generation and typestate mining--a combination with clear benefits: On a sample of 800 defects seeded into six Java subjects, a static typestate verifier fed with enriched models would report significantly more true positives, and significantly fewer false positives than the initial models.
THE ISOLATED PERFUSED BOVINE LIVER

1. A procedure is described for surgically isolating and artificially perfusing the liver of the young bovine. Heparinized autogenous blood from the hepatectomized animal diluted with Krebs-Ringer-bicarbonate solution is employed as the perfusate. 2. This preparation has been satisfactorily reproducible in this laboratory in more than 90 separate sequential perfusions. Absence of a sensitive hepatic venous smooth musculature contributes to the ability to maintain satisfactory perfusion for as long as 24 hours. 3. The perfusate was usually maintained bacterially free for at least the first 12 hours of perfusion without the use of antibiotics. The perfusate was maintained at normal body temperature and, by varying the CO2 content of the oxygenating gas, within a physiological pH range. The importance of these features when studying problems of intermediary biochemistry and ultrastructure is emphasized. 4. The liver of the bovine calf is sufficiently large to permit (a) simultaneous and independent perfusion through the hepatic artery and portal vein, and (b) repeated sampling of hepatic tissue without interruption of the circulation. 5. Excellent, viable condition of the isolated liver, throughout many hours of perfusion, was demonstrated by steady state of oxygen consumption, efficient clearance of bromsulphalein dye, continuous secretion of bile, constancy of blood flows and pressures, and very minimal alterations from normal in histologic and ultrastructural detail.
An open graph visualization system and its applications to software engineering

We describe a package of practical tools and libraries for manipulating graphs and their drawings. Our design, which is aimed at facilitating the combination of the package components with other tools, includes stream and event interfaces for graph operations, high‐quality static and dynamic layout algorithms, and the ability to handle sizeable graphs. We conclude with a description of the applications of this package to a variety of software engineering tools. Copyright © 2000 John Wiley & Sons, Ltd.
Lack of Effect of Methylprednisolone on Lysosomal and Microsomal Enzymes after Two Hours of Weil‐DefinedCanine Myocardial Ischemia

Myocardial ischemia was produced for 2 hours by coronary ligation in 11 dogs pretreated with methylprednisolone (MP, 30 mg/kg). microspheres (IS fun) in each tissue sample used for enzymatic analysis. Homogenates of these tissue samples were separated by ultracentrifugation into lysosome-rich and microsomal fractions and were analyzed for N-acetyl-β-glusosaminidase (NAGA), β-glucuronidase (β-gluc), rotenone-insensitive-NADH-cytochrome c reductase (RINCR), and cytochrome oxidase. The enzymatic data from centrifugal fractions were grouped according to MBF values for statistical analysis of inter-group effects of ischemia. Significant losses (P <0.001) of NAGA and β-gluc were seen in all MP-treated lysosome-rich particulate fractions that were isolated from zones demonstrating MBF values less than 25% of control (L-ischemia). Similar significant losses (P< 0.001) of RINCR were seen in microsomal fractions from L-ischemia zones. Samples with MBF values greater than 25% but less than 75% of control (M-ischemia) also demonstrated significant decreases of lysosomal and microsomal enzymatic activity in specific fractions. When the data of the above MP-treated group were compared with the untreated control group, no significant intergroup effects of treatment with MP were observed. In addition, enzymatic data (NAGA, RINCR) were normalized prior to performing linear regression analyses; percent loss of particulate enzymatic activity was plotted against percent decrease in MBF. The effects of 2 hours of ischemia on the above biochemical parameters were comparable between untreated and MP-treated groups. Finally, when myocardial samples were grouped according to similar levels of MBF, statistical analysis using the general linear models procedure revealed no beneficial effect of MP treatment on changes in lysosomal hydrolases, microsomal RINCR, or latency of lysosomes.
Controlling the density evolution of classical, thermodynamic and quantum systems

We present perturbation formulas for the (Markovian) density evolution of physical systems. Examples are provided from classical mechanics, thermodynamics and quantum mechanics. In all situations, formulas concern the relative entropy (Kullback-Leibler) distance between densities corresponding to unperturbed (uncontrolled) and perturbed (controlled) evolutions.
Wisteria Floribunda Agglutinin-Labeled Perineuronal Nets in the Mouse Inferior Colliculus, Thalamic Reticular Nucleus and Auditory Cortex

Perineuronal nets (PNNs) are specialized extracellular matrix molecules that are associated with the closing of the critical period, among other functions. In the adult brain, PNNs surround specific types of neurons, however the expression of PNNs in the auditory system of the mouse, particularly at the level of the midbrain and forebrain, has not been fully described. In addition, the association of PNNs with excitatory and inhibitory cell types in these structures remains unknown. Therefore, we sought to investigate the expression of PNNs in the inferior colliculus (IC), thalamic reticular nucleus (TRN) and primary auditory cortex (A1) of the mouse brain by labeling with wisteria floribunda agglutinin (WFA). To aid in the identification of inhibitory neurons in these structures, we employed the vesicular GABA transporter (VGAT)-Venus transgenic mouse strain, which robustly expresses an enhanced yellow-fluorescent protein (Venus) natively in nearly all gamma-amino butyric acid (GABA)-ergic inhibitory neurons, thus enabling a rapid and unambiguous assessment of inhibitory neurons throughout the nervous system. Our results demonstrate that PNNs are expressed throughout the auditory midbrain and forebrain, but vary in their local distribution. PNNs are most dense in the TRN and least dense in A1. Furthermore, PNNs are preferentially associated with inhibitory neurons in A1 and the TRN, but not in the IC of the mouse. These data suggest regionally specific roles for PNNs in auditory information processing.
A non-iterative registration method based on image transformation descriptors

In this article we present a novel method of the image registration based on the image transformation descriptors which are also introduced in this paper. The algorithm computes the registration parameters directly, on the contrary to the most known, iterative methods. It is fast and robust and therefore can be used as an initialization for the more accurate (but slower) algorithms. Our registration technique relies on the values obtained from appropriate transformation descriptions (image transformation descriptors, ITDs), computed from the geometric properties present on the images. It is also possible to adapt the process to a specific registration problem by providing custom descriptors, specific for a particular case. To prove the usability of the method, we have successfully tested it for registering 3D CT images with the angiography of thoracic aortas.
Prediction of air pollution based on FCM-HMM Multi-model

Air pollution is a growing problem arising from various activities and events. Monitoring and prediction of air pollution index remains an important public health concern. In this paper, FCM-HMM Multi-model is proposed to model the air pollution atmosphere system. First, FCM-HMM clustering is developed to mine the inherent states behind the meteorological observation sequence. Second, TS fuzzy inference multi-model is constructed for each state to predict the air pollution index. The experiment results proved the feasibility of the model on air pollution data in Beijing.
Clustering Appearance for Scene Analysis

We propose a new approach called "appearance clustering" for scene analysis. The key idea in this approach is that the scene points can be clustered according to their surface normals, even when the geometry, material and lighting are all unknown. We achieve this by analyzing an image sequence of a scene as it is illuminated by a smoothly moving distant source. Each pixel thus gives rise to a "continuous appearance profile" that yields information about derivatives of the BRDF w.r. t source direction. This information is directly related to the surface normal of the scene point when the source path follows an unstructured trajectory (obtained, say, by "hand-waving"). Based on this observation, we transform the appearance profiles and propose a metric that can be used with any unsupervised clustering algorithm to obtain iso-normal clusters. We successfully demonstrate appearance clustering for complex indoor and outdoor scenes. In addition, iso-normal clusters serve as excellent priors for scene geometry and can strongly impact any vision algorithm that attempts to estimate material, geometry and/or lighting properties in a scene from images. We demonstrate this impact for applications such as diffuse and specular separation, both calibrated and uncalibrated photometric stereo of non-lambertian scenes, light source estimation and texture transfer.
LSV-Based Tail Inequalities for Sums of Random Matrices

The techniques of random matrices have played an important role in many machine learning models. In this letter, we present a new method to study the tail inequalities for sums of random matrices. Different from other work (Ahlswede & Winter, 2002; Tropp, 2012; Hsu, Kakade, & Zhang, 2012), our tail results are based on the largest singular value (LSV) and independent of the matrix dimension. Since the LSV operation and the expectation are noncommutative, we introduce a diagonalization method to convert the LSV operation into the trace operation of an infinitely dimensional diagonal matrix. In this way, we obtain another version of Laplace-transform bounds and then achieve the LSV-based tail inequalities for sums of random matrices.
A methodology for designing accurate anomaly detection systems

Anomaly detection systems have the potential to detect zero-day attacks. However, these systems can suffer from high rates of false positives and can be evaded through through mimicry attacks. The key to addressing both problems is careful control of model generalization. An anomaly detection system that undergeneralizes generates too many false positives, while one that overgeneralizes misses attacks. In this paper, we present a methodology for creating anomaly detection systems that make appropriate trade-offs regarding model precision and generalization. Specifically, we propose that systems be created by taking an appropriate, undergeneralizing data modeling method and extending it using data pre-processing generalization heuristics. To show the utility of our methodology, we show how it has been applied to the problem of detecting malicious web requests.
The C‐terminal domain of Armadillo binds to hypophosphorylated Teashirt to modulate Wingless signalling in Drosophila

Wnt signalling is a key pathway for tissue patterning during animal development. In Drosophila, the Wnt protein Wingless acts to stabilize Armadillo inside cells where it binds to at least two DNA‐binding factors which regulate specific target genes. One Armadillo‐binding protein in Drosophila is the zinc finger protein Teashirt. Here we show that Wingless signalling promotes the phosphorylation and the nuclear accumulation of Teashirt. This process requires the binding of Teashirt to the C‐terminal end of Armadillo. Finally, we present evidence that the serine/threonine kinase Shaggy is associated with Teashirt in a complex. We discuss these results with respect to current models of Armadillo/β‐catenin action for the transmission of the Wingless/Wnt pathway.
An approach to multibeam covariance matrices for adaptive beamforming in ultrasonography

Medical ultrasound imaging systems are often based on transmitting, and recording the backscatter from, a series of focused broadband beams with overlapping coverage areas. When applying adaptive beamforming, a separate array covariance matrix for each image sample is usually formed. The data used to estimate any one of these covariance matrices is often limited to the recorded backscatter from a single transmitted beam, or that of some adjacent beams through additional focusing at reception. We propose to form, for each radial distance, a single covariance matrix covering all of the beams. The covariance matrix is estimated by combining the array samples after a sequenced time delay and phase shift. The time delay is identical to that performed in conventional delay-and-sum beamforming. The performance of the proposed approach in conjunction with the Capon beamformer is studied on both simulated data of scenes consisting of point targets and recorded ultrasound phantom data from a specially adapted commercial scanner. The results show that the proposed approach is more capable of resolving point targets and gives better defined cyst-like structures in speckle images compared with the conventional delay-and-sum approach. Furthermore, it shows both an increased robustness to noise and an increased ability to resolve point-like targets compared with the more traditional per-beam Capon beamformer.
ToPIN: A Visual Analysis Tool for Time-anchored Comments in Online Educational Videos

Online videos are widely used to share content for a variety of entertainment, educational and other purposes. To support social interaction, several video-sharing websites Including Ustream, niconico, and Twitch - allow users to post messages while they are watching videos. As users' comments can be sorted according to the timecode of each video, this is known as time-anchored commenting. We propose a novel visualization method, ToPIN, which is able to analyze and categorize the topics and content types of users' time-anchored comments. We have also developed a visualization interface that combines the visualization techniques of ToPIN and ThemeRiver to generate additional valuable insights for analysts seeking to make sense of time-anchored comments. To test the utility of our approach, we visualized time-anchored commenting data from two online course videos and invited the course instructors to evaluate our system.
The Impact Analysis of Stamping Process Factors Based on Dynaform

Combining with practical needs in production, it carried out the numerical simulation analysis of automobile beam stamping forming process based on Dynaform in this paper. According to quality evaluation index of forming parts, it analyzed the effect of variation of blank holder force, the stamping speed, the coefficient of friction and draw bead on stamping quality. It forecast the quality problems happened in forming process, which provides the theoretical basis for design of stamping process and mold.
Photometric stereo under perspective projection

Photometric stereo is a fundamental approach in computer vision. At its core lies a set of image irradiance equations each taken with a different illumination. The vast majority of studies in this field have assumed orthography as the projection model. This paper re-examines the basic set of equations of photometric stereo, under an assumption of perspective projection. We show that the resulting system is linear (as is the case under the orthographic model; Nevertheless, the unknowns are different in the perspective case). We then suggest a simple reconstruction algorithm based on the perspective formulae, and compare it to its orthographic counterpart on synthetic as well as real images. This algorithm obtained lower error rates than the orthographic one in all of the error measures. These findings strengthen the hypothesis that a more realistic set of assumptions, the perspective one, improves reconstruction significantly.
Working with Clinicians to Improve a Patient-Information NLG System

NLG developers must work closely with domain experts in order to build good NLG systems, but relatively little has been published about this process. In this paper, we describe how NLG developers worked with clinicians (nurses) to improve an NLG system which generates information for parents of babies in a neonatal intensive care unit, using a structured revision process. We believe that such a process can significantly enhance the quality of many NLG systems, in medicine and elsewhere.
Incentivizing the Use of Bike Trailers for Dynamic Repositioning in Bike Sharing Systems

Bike Sharing System (BSS) is a green mode of transportation that is employed extensively for short distance travels in major cities of the world. Unfortunately, the users behaviour driven by their personal needs can often result in empty or full base stations, thereby resulting in loss of customer demand. To counter this loss in customer demand, BSS operators typically utilize a fleet of carrier vehicles for repositioning the bikes between stations. However, this fuel burning mode of repositioning incurs a significant amount of routing, labor cost and further increases carbon emissions. Therefore, we propose a potentially self-sustaining and environment friendly system of dynamic repositioning, that moves idle bikes during the day with the help of bike trailers. A bike trailer is an add-on to a bike that can help with carrying 3-5 bikes at once. Specifically, we make the following key contributions: (i) We provide an optimization formulation that generates “repositioning” tasks so as to minimize the expected lost demand over past demand scenarios; (ii) Within the budget constraints of the operator, we then design a mechanism to crowdsource the tasks among potential users who intend to execute repositioning tasks; (iii) Finally, we provide extensive results on a wide range of demand scenarios from a real-world data set to demonstrate that our approach is highly competitive to the existing fuel burning mode of repositioning while being green.
Aerosol optical depth retrieval over land using Meteosat-8 SEVIRI data

Geostationary sensors bear the potential to derive and analyze daily and seasonal trends of aerosol optical depth (AOD) from spatially homogeneous data. However, to date most AOD retrieval algorithms from geostationary sensors are limited to sea surfaces. In this study, a multi-temporal technique to retrieve AOD over land from the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on-board the geostationary Meteosat-8 satellite is presented. The proposed method takes advantage of SEVIRI's high temporal resolution of 15 minutes and improved spatial and spectral resolution in comparison to its predecessors Meteosat-1 to 7. The crucial issue is the decomposition of the measured signal into its surface and atmospheric contributing parts. Assumed that surface characteristics remain constant during a certain time period, changes in observed reflectance can be assigned to varying atmospheric constituents and varying sun zenith and azimuth angles. Surface reflectance is estimated by the determination of the lowest reflectance within the observed time period for each satellite observation time of the day. Since clouds seriously affect the retrieval of AOD, clouds and cloud shadows are masked out and the data set is corrected for atmospheric gases prior to the AOD retrieval. Finally, AOD is calculated by means of the radiative transfer code SMAC. The study area covers Switzerland and its neighboring areas (45.0N-48.5N, 5.0E-12.0E). SEVIRI data for the entire month of August, 2004, acquired daily between 6:12 and 17:12 UTC are used in order to test the method. In comparison to sun-photometer measurements from the Aerosol Robotic Network (AERONET), first results show promising AOD values.