Miracle-dz/UniFAR-FTUs huggingface dataset:
Preserved Excitatory-Inhibitory Balance of Cortical Synaptic Inputs following Deprived Eye Stimulation after a Saturating Period of Monocular Deprivation in Rats

Monocular deprivation (MD) during development leads to a dramatic loss of responsiveness through the deprived eye in primary visual cortical neurons, and to degraded spatial vision (amblyopia) in all species tested so far, including rodents. Such loss of responsiveness is accompanied since the beginning by a decreased excitatory drive from the thalamo-cortical inputs. However, in the thalamorecipient layer 4, inhibitory interneurons are initially unaffected by MD and their synapses onto pyramidal cells potentiate. It remains controversial whether ocular dominance plasticity similarly or differentially affects the excitatory and inhibitory synaptic conductances driven by visual stimulation of the deprived eye and impinging onto visual cortical pyramids, after a saturating period of MD. To address this issue, we isolated visually-driven excitatory and inhibitory conductances by in vivo whole-cell recordings from layer 4 regular-spiking neurons in the primary visual cortex (V1) of juvenile rats. We found that a saturating period of MD comparably reduced visually–driven excitatory and inhibitory conductances driven by visual stimulation of the deprived eye. Also, the excitatory and inhibitory conductances underlying the synaptic responses driven by the ipsilateral, left open eye were similarly potentiated compared to controls. Multiunit recordings in layer 4 followed by spike sorting indicated that the suprathreshold loss of responsiveness and the MD-driven ocular preference shifts were similar for narrow spiking, putative inhibitory neurons and broad spiking, putative excitatory neurons. Thus, by the time the plastic response has reached a plateau, inhibitory circuits adjust to preserve the normal balance between excitation and inhibition in the cortical network of the main thalamorecipient layer.
A Memetic Algorithm for the Weight Setting Problem in Deft

To use interior gateway protocols like OSPF (Open Shortest Path First, [6]), IS-IS (Intermediate System-Intermediate System), and DEFT (Distributed Exponentially-weighted Flow Splitting, [7]) it is necessary to set the link weights to allow data routing. The problem of finding suitable weights for these protocols is known as the weight setting problem. Examples of objective functions are network congestion, link utilization, and latency. In the literature we can find a few papers describing methods to set the link weights according to some protocol. In this paper we present a new memetic algorithm which can be applied to both the OSPF and DEFT protocols, study its performance, and discuss future directions of this work.
Erythromycin, roxithromycin, and clarithromycin: use of slow-binding kinetics to compare their in vitro interaction with a bacterial ribosomal complex active in peptide bond formation.

In a cell-free system derived from Escherichia coli, it is shown that clarithromycin and roxithromycin, like their parent compound erythromycin, do not inhibit the puromycin reaction (i.e., the peptide bond formation between puromycin and AcPhe-tRNA bound at the P-site of 70S ribosomes programmed with heteropolymeric mRNA). Nevertheless, all three antibiotics compete for binding on the ribosome with tylosin, a 16-membered ring macrolide that behaves as a slow-binding, slowly reversible inhibitor of peptidyltransferase. The mutually exclusive binding of these macrolides to ribosomes is also corroborated by the fact that they protect overlapping sites in domain V of 23S rRNA from chemical modification by dimethyl sulfate. From this competition effect, detailed kinetic analysis revealed that roxithromycin or clarithromycin (A), like erythromycin, reacts rapidly with AcPhe-tRNA.MF-mRNA x 70S ribosomal complex (C) to form the encounter complex CA which is then slowly isomerized to a more tight complex, termed C*A. The value of the overall dissociation constant, K, encompassing both steps of macrolide interaction with complex C, is 36 nM for erythromycin, 20 nM for roxithromycin, and 8 nM for clarithromycin. Because the off-rate constant of C*A complex does not significantly differ among the three macrolides, the superiority of clarithromycin as an inhibitor of translation in E. coli cells and many Gram-positive bacteria may be correlated with its greater rate of association with ribosomes.
Speeding Up the Douglas-Peucker Line-Simplification Algorithm

We analyze the line simplification algorithm reported by Douglas and Peucker and show that its worst case is quadratic in n, the number of input points. Then we give a algorithm, based on path hulls, that uses the geometric structure of the problem to attain a worst-case running time proportional to n log_2(n), which is the best case of the Douglas algorithm. We give complete C code and compare the two algorithms theoretically, by operation counts, and practically, by machine timings.
Nonlinear indirect adaptive decoupling control based on neural networks and multiple models

In this paper, an indirect adaptive decoupling controller is presented for a class of uncertain nonlinear multivariable discrete time dynamical systems. The indirect adaptive decoupling controller is composed of a linear robust indirect adaptive decoupling controller, a neural network nonlinear indirect adaptive decoupling controller and a switching mechanism. The linear decoupling controller can provide boundedness of the input and output signals, and the nonlinear decoupling controller can improve performance of the system. The purpose of using the switching mechanism is to obtain the improved system performance and stability simultaneously. Theory analysis and simulation results are presented to show the effectiveness of the proposed method
Explicit Non-Malleable Codes Resistant to Permutations

A non-malleable code protects messages against various classes of tampering. Informally, a code is non-malleable if the message contained in a tampered codeword is either the original message, or a completely unrelated one. Although existence of such codes for various rich classes of tampering functions is known, explicit constructions exist only for “compartmentalized” tampering functions: i.e. the codeword is partitioned into a priori fixed blocks and each block can only be tampered independently. The prominent examples of this model are the family of bit-wise independent tampering functions and the split-state model. In this paper, for the first time we construct explicit non-malleable codes against a natural class of non-compartmentalized tampering functions. We allow the tampering functions to permute the bits of the codeword and (optionally) perturb them by flipping or setting them to 0 or 1. We construct an explicit, efficient non-malleable code for arbitrarily long messages in this model (unconditionally). We give an application of our construction to non-malleable commitments, as one of the first direct applications of non-malleable codes to computational cryptography. We show that nonmalleable string commitments can be “entirely based on” non-malleable bit commitments. More precisely, we show that simply encoding a string using our code, and then committing to each bit of the encoding using a CCA-secure bit commitment scheme results in a non-malleable string commitment scheme. This reduction is unconditional, does not require any extra properties from the bit-commitment such as “tag-based” non-malleability, and works even with physical implementations (which may not imply standard one-way functions). Further, even given a partially malleable bit commitment scheme which allows toggling the committed bit (instantiated, for illustration, using a variant of the Naor commitment scheme under a non-standard assumption on the PRG involved), this transformation gives a fully non-malleable string commitment scheme. This application relies on the non-malleable code being explicit.
Global Shutter CMOS Image Sensor With Wide Dynamic Range

A novel concept for global shutter CMOS image sensors with Wide Dynamic Range (WDR) implementation is presented. The proposed imager is based on the multi sampling WDR approach and it allows an efficient global shutter pixel implementation achieving small pixel size and high fill factor. The proposed imager provides wide DR by applying adaptive exposure time to each pixel, according to the local illumination intensity level. Two pixel configurations, employing different kinds of 1-bit in-pixel memory were implemented. An imager, including all proposed pixels was designed and simulated in a mixed-signal 0.18 mum CMOS technology. While operating at 1.8 V voltage supply the proposed sensors achieve the DR up to 120 dB. System architecture and operation are discussed and simulation results are presented.
Planning and provisioning of Virtual Content Aware Networks over IP infrastructures

Virtual Content Aware Networks (VCAN) constructed as overlays over IP network substrate is considered an efficient solution to incrementally introduce content awareness at network level. Planning, mapping on top of multiple domains IP network and optimizing these VCANs is still an open research issue. This paper is focused on intradomain planning and VCAN mapping, with QoS guarantees, thus continuing previous studies dedicated to the general architectures of the same system. A combined algorithm is proposed to perform jointly QoS routing, admission control, VCAN mapping and resource reservation. Several case studies and simulation results are presented in comparative way.
Clinical Utility of Quantitative Cerebral Blood Flow Measurements during Internal Carotid Artery Test Occlusions

OBJECTIVE Internal carotid artery (ICA) balloon test occlusions (BTOs) are performed in the angiography suite to predict whether the patient has adequate collateral circulation to prevent stroke when permanent ICA occlusion (PCO) is required for treatment. Although many criteria have been proposed to facilitate predictions of stroke risk after PCO, no BTO techniques have been subjected to predictive validity testing in outcome studies. We describe a prospective case series study that tests the predictive validity of quantitative cerebral blood flow (CBF) measurements during ICA BTO. METHODS Thirty-three patients with clinical indications for PCO underwent ICA BTO and then PCO. During BTO, standard neurological examinations, sustained-attention testing, and quantitative CBF measurements were performed. Two scalp scintillation detectors recorded washout data after ipsilateral intracarotid injection of xenon-133 through a port at the tip of the ICA-occluding balloon. Patients were monitored for the outcome measure of ipsilateral stroke for a mean of 34 months. The variables of quantitative CBF values, neurological examination results, sustained-attention test results, age, sex, and side of occlusion were examined with Kaplan-Meier log-rank tests, predictive validity analyses, and logistic regression analyses. RESULTS CBF of less than 30 ml/100 g/min during BTO was the only variable that predicted stroke after PCO (log rank = 5.87, P = 0.015). The negative and positive predictive values for CBF findings were superior to those for standard neurological examination findings and sustained-attention test results. Age, sex, and side of occlusion did not predict stroke. CONCLUSION Quantitative CBF testing, via the intracarotid injection technique, during BTO seems to be an important predictor of stroke after PCO.
An Electrophysiological Measure of Priming of Visual Word-Form

Priming and recollection are expressions of human memory mediated by different brain events. These brain events were monitored while people discriminated words from nonwords. Mean response latencies were shorter for words that appeared in an earlier study phase than for new words. This priming effect was reduced when the letters of words in study-phase presentations were presented individually in succession as opposed to together as complete words. Based on this outcome, visual word-form priming was linked to a brain potential recorded from the scalp over the occipital lobe about 450 ms after word onset. This potential differed from another potential previously associated with recollection, suggesting that distinct operations associated with these two types of memory can be monitored at the precise time that they occur in the human brain.
Lack of Association of Factor V Leiden and Coronary Heart Disease in Individuals With and Without Diabetes

Odawara and Yamashita (1) recently reported that there was no association of factor V Leiden with coronary heart disease (CHD) in 60 Japanese patients with type 2 diabetes. Factor V Leiden is a single-point mutation in the coagulation factor V gene associated with resistance to degradation by activated protein C (2). This abnormality of the coagulation system predisposes individuals to the development of a hypercoagulable state. Heterozygosity for this mutation increases risk of venous thrombosis fivefold (3), but its association with arterial thrombosis and diabetes has produced conflicting results (1,4). Patients with diabetes have an increased risk of CHD as evidenced by a 1.5to threefold increase in CHD mortality (5). This increased risk may result from a high incidence of arterial thrombosis (4) and changes in hemostatic factors (4,5) in these patients. Thus, we investigated the prevalence of factor V Leiden in 200 patients with known CHD undergoing nonemergency coronary artery bypass graft (CABG) surgery at the Medical Center of Delaware, Newark, Delaware. Previous studies done at this institution have shown that 30% of patients undergoing CABG surgery have a diagnosis of diabetes. After informed consent was obtained, DNA was isolated from the patients whole blood (collected with other routine preoperative blood studies) and analyzed for factor V Leiden using polymerase chain reaction (2). Demographic and clinical data were extracted by retrospective chart review, and the results of the comparisons of these data for those with (32%) and without diabetes are shown in Table 1. The prevalence of this mutation was 7.4% for those without diabetes and 3.1% for those with diabetes (P = 0.34, Fishers exact test). The overall prevalence of the point mutation in these patients with CHD (i.e., 6.0%) appears to be no higher than the reported prevalence of this mutation in healthy white Americans (i.e., 5.27%) (6). Although other investigators (4) showed a higher prevalence (i.e., 8.2%) of factor V Leiden in 147 consecutively hospitalized diabetic patients and concluded that this mutation was associated with diabetes, our results do not indicate any higher prevalence of this mutation in diabetic patients with CHD than in CHD patients without diabetes. The lack of an association of factor
Probing photoionization : simulations of positive streamers in varying N 2 : O 2-mixtures

Photo-ionization is the accepted mechanism for the propagation of positive streamers in air though the parameters are not very well known; the efficiency of this mechanism largely depends on the presence of both nitrogen and oxygen. But experiments show that streamer propagation is amazingly robust against changes of the gas composition; even for pure nitrogen with impurity levels below 1 ppm streamers propagate essentially with the same velocity as in air, but their minimal diameter is smaller, and they branch more frequently. Additionally, they move more in a zigzag fashion and sometimes exhibit a feathery structure. In our simulations, we test the relative importance of photo-ionization and of the background ionization from pulsed repetitive discharges, in air as well as in nitrogen with 1 ppm O2. We also test reasonable parameter changes of the photo-ionization model. We find that photo-ionization dominates streamer propagation in air for repetition frequencies of at least 1 kHz, while in nitrogen with 1 ppm O2 the effect of the repetition frequency has to be included above 1 Hz. Finally, we explain the feather-like structures around streamer channels that are observed in experiments in high purity nitrogen, but not in air. (Some figures in this article are in colour only in the electronic version)
Indomethacin inhibits the natriuretic effects of neuropeptide Y in anesthetized rats.

Neuropeptide Y (NPY) is a unique modulator of renal function that enhances urine flow and sodium excretion despite marked reductions in renal blood flow. We investigated whether the cyclooxygenase inhibitor indomethacin alters the renal NPY effects in anesthetized rats. Treatment with 5 mg/kg indomethacin i.p. lowered urinary prostaglandin excretion by approximately 85%. Systemic infusion of NPY elevated mean arterial pressure by approximately 15 mm Hg and renovascular resistance by approximately 8.0 mm Hg/ml/min, whereas the related peptide YY3-36 (PYY3-36) did not. Nevertheless, both peptides enhanced urine flow rate by approximately 250 and approximately 100 microl/15 min, respectively, and sodium excretion by approximately 15 micromol/15 min. Treatment with indomethacin did not affect NPY- and PYY3-36-induced alterations of systemic and renovascular hemodynamics but completely abolished NPY- and PYY3-36-induced diuresis and natriuresis. Endogenous creatinine clearance was not affected by any treatment. We conclude that cyclooxygenase-derived arachidonic acid metabolites are not involved in the systemic or renal hemodynamic effects of NPY and PYY3-36 but mediate NPY- and PYY3-36-induced diuresis and natriuresis.
Block-sparsity: Coherence and efficient recovery

We consider compressed sensing of block-sparse signals, i.e., sparse signals that have nonzero coefficients occurring in clusters. Based on an uncertainty relation for block-sparse signals, we define a block-coherence measure and show that a block-version of the orthogonal matching pursuit algorithm recovers block k-sparse signals in no more than k steps if the block-coherence is sufficiently small. The same condition on block-sparsity is shown to guarantee successful recovery through a mixed ℓ2/ℓ1 optimization approach. The significance of the results lies in the fact that making explicit use of block-sparsity can yield better reconstruction properties than treating the signal as being sparse in the conventional sense, thereby ignoring the additional structure in the problem.
Cost-effective outbreak detection in networks

Given a water distribution network, where should we place sensors toquickly detect contaminants? Or, which blogs should we read to avoid missing important stories? These seemingly different problems share common structure: Outbreak detection can be modeled as selecting nodes (sensor locations, blogs) in a network, in order to detect the spreading of a virus or information asquickly as possible. We present a general methodology for near optimal sensor placement in these and related problems. We demonstrate that many realistic outbreak detection objectives (e.g., detection likelihood, population affected) exhibit the property of "submodularity". We exploit submodularity to develop an efficient algorithm that scales to large problems, achieving near optimal placements, while being 700 times faster than a simple greedy algorithm. We also derive online bounds on the quality of the placements obtained by any algorithm. Our algorithms and bounds also handle cases where nodes (sensor locations, blogs) have different costs. We evaluate our approach on several large real-world problems,including a model of a water distribution network from the EPA, andreal blog data. The obtained sensor placements are provably near optimal, providing a constant fraction of the optimal solution. We show that the approach scales, achieving speedups and savings in storage of several orders of magnitude. We also show how the approach leads to deeper insights in both applications, answering multicriteria trade-off, cost-sensitivity and generalization questions.
The practice of exclusive breastfeeding: its socio-demographic determinants in Kashmir, North India

Background: Breastfeeding is a well-established and recommended intervention for the improvement of child nutrition. Formula feeding is a major public health problem. Objective of the current study was to know the significance of demography, socioeconomic, parental education and employment and mode of delivery on exclusive breast-feeding Kashmir, North India.Methods: A prospective hospital-based study, carried out in the Department of Pediatrics, G.B Pant Hospital Srinagar Kashmir India over the period from 2014 July to June 2015. A teaching, research and tertiary care hospital at Srinagar Kashmir North India. All the mothers who were having infants in the age group 0 to 6 months were included in study. Procedure of this variables recorded were modes of feeding, demographics, socioeconomic status, literacy level, mode of delivery, place of delivery etc.Results: A total of 600 mothers were included in study. Less than 35% of mothers were exclusively breast feeding their infants. Exclusive breast feeding was significantly high in babies born by normal vaginal delivery, more than 3 antenatal visits, mother knowing advantages of breast feeding and higher parental education.Conclusions: Exclusive breast feeding is very low (less than 35%) in this part of world and formula feeding is a major public health problem.
Distance Metric Learning: A Comprehensive Survey

Many machine learning algorithms, such as K Nearest Neighbor (KNN), heavily rely on the distance metric for the input data patterns. Distance Metric learning is to learn a distance metric for the input space of data from a given collection of pair of similar/dissimilar points that preserves the distance relation among the training data. In recent years, many studies have demonstrated, both empirically and theoretically, that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. This paper surveys the field of distance metric learning from a principle perspective, and includes a broad selection of recent work. In particular, distance metric learning is reviewed under different learning conditions: supervised learning versus unsupervised learning, learning in a global sense versus in a local sense; and the distance matrix based on linear kernel versus nonlinear kernel. In addition, this paper discusses a number of techniques that is central to distance metric learning, including convex programming, positive semi-definite programming, kernel learning, dimension reduction, K Nearest Neighbor, large margin classification, and graph-based approaches.
Windsurf: region-based image retrieval using wavelets

In this paper we present WINDSURF (Wavelet-Based Indexing of Images Using Region Fragmentation), a new approach to content-based image retrieval. The method uses the wavelet transform to extract color and texture features from an image and applies a clustering technique to partition the image into a set of "homogeneous" regions. Similarity between images is assessed by using the Bhattacharyya distance to compare region descriptors, and then combining the results at image level. Experimental results on a testbed of 10000 general-purpose images show that our approach is very effective in retrieving images that are "semantically" similar to the query image. In particular, we compared results of WINDSURF with the approach by Stricker and Orengo, showing that that a significant improvement is obtained in the quality of the result.