Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptation to Natural Time Series of Intensities

In natural conditions, an organism copes with the large variations of theluminance input to the eyes by means of adaptation. In order to investigatethe luminance and contrast adaptation mechanisms under naturalconditions, we used a time series of intensities representative of what aphotoreceptor would encounter while moving in a natural environment.W e measured psychophysical detection thresholds for luminanceincrements relative to the natural time series, in comparison to stimuliwith different dynamics. For the natural time series we found a thresholdthat is elevated about 20% above steady-state level. Thresholds for variousstimuli vary approximately linearly with stimulus contrast, and areconsistent with mediation by the parvocellular pathway.INTRODUCTIONWhen an organism moves around in a natural environment, the luminance input to the eyeschanges continually. The input luminance range is much larger than the (linear) dynamicrange of photoreceptors and subsequent neurons (e.g., van Hateren, 1997). The visual systemcopes with this problem by means of luminance and contrast adaptation. These adaptationmechanisms have been studied extensively, both psychophysically (e.g., Hayhoe et al., 1992;Foley & Boynton, 1993; Kortum & Geisler, 1995; Pokorny & Smith, 1997; Poot et al., 1997;Hood et al., 1997) and physiologically (e.g., Lankheet et al., 1993; Yeh et al., 1996; Wu B Victor et al., 1997; Shapley, 1997). Although these studies are giving anincreasingly detailed view of early processes of luminance and contrast adaptation, it is notclear how these processes act in concert under natural luminance conditions.In order to study how the human visual system handles natural luminance andcontrast variations through adaptation, we performed experiments using a natural time seriesof intensities (NTSI). As described by van Hateren (1997), NTSIs were measured with a lightdetector carried on the head by a freely walking person. The detector had a spectralsensitivity close to the photopic sensitivity of the human eye, and an angular resolutionsimilar to that of a human (para)foveal cone. Here, we probe the sensitivity of the visualsystem during presentation of the NTSI by measuring detection thresholds for smallluminance increments relative to the NTSI. This experiment gives information on how wellsensitivity is retained during the rapid luminance fluctuations of the NTSI, and to what extentthe early processing channels are saturated. Furthermore, detection of small luminanceincrements is a relevant task for natural vision, since detection of, for example, the shape ormotion of objects depends on the ability to discriminate small luminance differences.For the experimental paradigm we made several simplifying choices. First, the NTSIwas presented on a large, spatially homogeneous field, in order to produce a well-definedadaptation state, which is not compromised by eye movements. This stimulus probablyproduces sensitivity changes reasonably close to those in natural circumstances, since at leastluminance adaptation occurs locally in the retina, possibly at the scale of a cone's receptive
An efficient oil and gas pipeline monitoring systems based on wireless sensor networks

Wireless sensor networks (WSN) is considered an effective technique to collect oil and gas transmission pipeline information. The studies that use conventional technologies (such as GPRS, microwave, radio modem and cables etc.) to collect these pipelines state information have the disadvantages of high cost of system maintenance and long data packet delay. The usage of WSN in oil and gas pipeline monitoring system is expected to be able to overcome the above difficulties. This paper proposes an efficient pipeline state information collection algorithm based on sensor node line deployment strategy and data fusion strategy in WSN. And the analysis result of this algorithm shows that the proposed algorithm can remarkably improve the network performances on delay and energy, ensure the urgency data to be propagated effectively and prolong the network life span. It is characterized with high performance, low cost and control efficiency.
Sonographic visualization and ultrasound-guided blockade of the greater occipital nerve: a comparison of two selective techniques confirmed by anatomical dissection.

BACKGROUND Local anaesthetic blocks of the greater occipital nerve (GON) are frequently performed in different types of headache, but no selective approaches exist. Our cadaver study compares the sonographic visibility of the nerve and the accuracy and specificity of ultrasound-guided injections at two different sites. METHODS After sonographic measurements in 10 embalmed cadavers, 20 ultrasound-guided injections of the GON were performed with 0.1 ml of dye at the classical site (superior nuchal line) followed by 20 at a newly described site more proximal (C2, superficial to the obliquus capitis inferior muscle). The spread of dye and coloration of nerve were evaluated by dissection. RESULTS The median sonographic diameter of the GON was 4.2 x 1.4 mm at the classical and 4.0 x 1.8 mm at the new site. The nerves were found at a median depth of 8 and 17.5 mm, respectively. In 16 of 20 in the classical approach and 20 of 20 in the new approach, the nerve was successfully coloured with the dye. This corresponds to a block success rate of 80% (95% confidence interval: 58-93%) vs 100% (95% confidence interval: 86-100%), which is statistically significant (McNemar's test, P=0.002). CONCLUSIONS Our findings confirm that the GON can be visualized using ultrasound both at the level of the superior nuchal line and C2. This newly described approach superficial to the obliquus capitis inferior muscle has a higher success rate and should allow a more precise blockade of the nerve.
DSB-Tree: An Improved Spatial Data Index Structure Based on SS-Tree

Using approximate geometrical expression to construct spatial data index becomes to an effective method because of the complexity of spatial entity. The simple exterior approximate expression could not satisfy the multiple query requirements to the spatial dataset. Obvious distance and topology relationships can be found between spatial data, especially the two or three dimensions spatial data used in GIS. Circle shape is can be constructed and expressed with a low amount of data, and all kinds of operations on distance and topology are exceedingly simple and easy to implement. A novel index structure named double sphere balance tree and abbreviated as DSB-tree is represented with importing maximum enclosed circle (MEC) as interior approximate expression based on SS-tree. Due to the double approximate expression constructed with two circles (MBC and MEC), all the operations of DSB-tree are low cost and more effective. We implement the structure and its basal operations as spatial data index, including insertion, remove and query. Finally, the extensive experiments and their results are given to discuss the performance of the DSB-tree for the NN query.
Psychological treatments in schizophrenia: II. Meta-analyses of randomized controlled trials of social skills training and cognitive remediation

Background. Social skills training and cognitive remediation are psychological techniques with considerable face validity for the treatment of negative symptoms of schizophrenia and their consequences. This paper provides a meta-analytical review of these treatments. It includes an appreciable number of randomized controlled trials, using comparisons against both standard care and other active interventions. However, the assessment of particular outcomes sometimes had to be based on single studies. Method. A detailed search strategy was used to identify randomized controlled trials of social skills training and cognitive remediation, primarily employing electronic databases. Randomized controlled trials (RCTs) that met predefined criteria were then subjected to meta-analysis on a variety of outcome measures. Results. There was no clear evidence for any benefits of social skills training on relapse rate, global adjustment, social functioning, quality of life or treatment compliance. Cognitive remediation had no benefit on attention, verbal memory, visual memory, planning, cognitive flexibility or mental state. Conclusions. Social skills training and cognitive remediation do not appear to confer reliable benefits for patients with schizophrenia and cannot be recommended for clinical practice.
A novel market based grid resource allocation algorithm

The aim of this paper has been to introduce a novel market based algorithm for grid resource allocation and resolve some incompetence with current mechanisms. Grid resource allocation could be considered as a double auction in which grid resource manager acts as an auctioneer and jobs and resource owners act as buyers (resource consumers) and sellers. In our approach resource allocation is based on activity history of each participant in the auction. Bids (Asks) in the auctions are calculated in each round, based on proportion of former bids (asks) fluctuation and prior activity of each buyer(seller). Practical evaluation results demonstrate that market equilibrium in our mechanism is improved in comparison with other mechanisms. Also essence of learning features in proposed mechanism increases competition incentive in participants which do selfishly in every round of an auction to maximize their utility.
Bioinformatics Applications Note Structural Bioinformatics Cheshift-2: Graphic Validation of Protein Structures

The differences between observed and predicted 13 C α chemical shifts can be used as a sensitive probe with which to detect possible local flaws in protein structures. For this reason, we previously introduced CheShift, a Web server for protein structure validation. Now, we present CheShift-2 in which a graphical user interface is implemented to render such local flaws easily visible. A series of applications to 15 ensembles of conformations illustrate the ability of CheShift-2 to locate the main structural flaws rapidly and accurately on a per-residue basis. Since accuracy plays a central role in CheShift predictions, the treatment of histidine (His) is investigated here by exploring which form of His should be used in CheShift-2.
A comparison between MATLAB optimization toolbox and GA in cooperative grasp planning

In this paper, an optimal grasp planning for cooperative object manipulation, based on Genetic Algorithm (GA) and MATLAB optimization toolbox and using the MAG performance index is presented. The MAG index, which has been designed for object manipulation tasks, takes into account three major aspects of grasp planning such as, the position of grasping points, the kinematic aspects of cooperative manipulators, and the kinetic aspects of manipulators and the manipulated object. These numerical methods would be used to find the best grasping point of the symmetrical and unsymmetrical objects which are manipulated in a predefined path. Also, these methods would be compared with each other in speed. The results show that in the tasks that speed is the key factor; MATLAB optimization toolbox is preferred to GA.
ASYMPTOTICALLY UNBIASED ESTIMATION OF AUTOCOVARIANCES AND AUTOCORRELATIONS WITH LONG PANEL DATA

An important reason for analyzing panel data is to observe the dynamic nature of an economic variable separately from its time-invariant unobserved heterogeneity. This paper examines how to estimate the autocovariances of a variable separately from its time-invariant unobserved heterogeneity. When both cross-sectional and time series sample sizes tend to infinity, we show that the within-group autocovariances are consistent, although they are severely biased when the time series length is short. The biases have the leading term that converges to the long-run variance of the individual dynamics. This paper develops methods to estimate the long-run variance in panel data settings and to alleviate the biases of the within-group autocovariances based on the proposed long-run variance estimators. Monte Carlo simulations reveal that the procedures developed in this paper effectively reduce the biases of the estimators for small samples.
A universal interpretation of receive diversity gain in MIMO systems over flat channels

We present universal bit-error rate (BER) performance ordering for different receive antenna sizes in Multiple-Input Multiple-Output (MIMO) wireless systems with linear equalizations, which hold for all SNR. We show that when the number of transmit antennas is fixed, BER of each symbol degrades with a decrease in the number of receive antennas even if the received SNR is kept constant. This is due to the convexity property of the BER functions. Then for any i.i. d. channels, we show that the BER averaged over random channels also degrades with a decrease in the number of receive antennas. These highlight the advantage and the limit of MIMO with linear equalizations.
Beat your mom at solitaire — A review of reverse engineering techniques and countermeasures

As computer software systems grow ever more sophisticated, so do the mechanisms used in compromising them. Some of the most advanced cyber attacks in recent years would have required considerable preparation and research on the specific software applications and the hardware they targeted. In this paper we focus on native applications and evaluate different reverse engineering techniques with a focus on memory manipulation, used to compromise their security. Additionally we discuss different protection mechanism and their practicalities. The techniques discussed are executed against a well known application (i.e. the Microsoft Windows Solitaire game) and the results are presented.
Unsupervised pattern recognition in continuous seismic wavefield records using Self-Organizing Maps

SUMMARY Modern acquisition of seismic data on receiver networks worldwide produces an increasing amount of continuous wavefield recordings. In addition to manual data inspection, seismogram interpretation requires therefore new processing utilities for event detection, signal classification and data visualization. The use of machine learning techniques automatises decision processes and reveals the statistical properties of data. This approach is becoming more and more important and valuable for large and complex seismic records. Unsupervised learning allows the recognition of wavefield patterns, such as short-term transients and long-term variations, with a minimum of domain knowledge. This study applies an unsupervised pattern recognition approach for the discovery, imaging and interpretation of temporal patterns in seismic array recordings. For this purpose, the data is parameterized by feature vectors, which combine different real-valued wavefield attributes for short time windows. Standard seismic analysis tools are used as feature generation methods, such as frequency–wavenumber, polarization and spectral analysis. We use Self-Organizing Maps (SOMs) for a data-driven feature selection, visualization and clustering procedure. The application to continuous recordings of seismic signals from an active volcano (Mount Merapi, Java, Indonesia) shows that volcanotectonic and rockfall events can be detected and distinguished by clustering the feature vectors. Similar results are obtained in terms of correctly classifying events compared to a previously implemented supervised classification system. Furthermore, patterns in the background wavefield, that is the 24-hr cycle due to human activity, are intuitively visualized by means of the SOM representation. Finally, we apply our technique to an ambient seismic vibration record, which has been acquired for local site characterization. Disturbing wavefield patterns are identified which affect the quality of Love wave dispersion curve estimates. Particularly at night, when the overall energy of the wavefield is reduced due to the 24-hr cycle, the common assumption of stationary planar surface waves can be violated.
Fast approximate similarity search in extremely high-dimensional data sets

This paper introduces a practical index for approximate similarity queries of large multi-dimensional data sets: the spatial approximation sample hierarchy (SASH). A SASH is a multi-level structure of random samples, recursively constructed by building a SASH on a large randomly selected sample of data objects, and then connecting each remaining object to several of their approximate nearest neighbors from within the sample. Queries are processed by first locating approximate neighbors within the sample, and then using the pre-established connections to discover neighbors within the remainder of the data set. The SASH index relies on a pairwise distance measure, but otherwise makes no assumptions regarding the representation of the data. Experimental results are provided for query-by-example operations on protein sequence, image, and text data sets, including one consisting of more than 1 million vectors spanning more than 1.1 million terms - far in excess of what spatial search indices can handle efficiently. For sets of this size, the SASH can return a large proportion of the true neighbors roughly 2 orders of magnitude faster than sequential search.
A Load-Balancing and Weighted Clustering Algorithm in Mobile Ad-Hoc Network

A Mobile Ad Hoc Networks (MANET) is a collection of two or more mobile devices (e.g. PDAs, laptop, cell phones, etc .), with multi-hop wireless communication. These nodes or devices can communicate with other nodes directly within or outside their transm ission range. In previous research on mobile ad-hoc network indicated to use of clustering algorithm because it simplifies routing and can improve the p erformance of flexibility and scalability in the network. In this paper, we p ropose that the enhancement on weighted clustering algorithm (EWCA) , leads to a high degree of stability in the network and improves the load balancing. In this simulation study, a comparison was conducted to mea sur the performance of our algorithm with original WCA in terms of numb ers of clusters formed with satisfy load balancing , topology stability, a nd number of clusterhead change.
Ovarian Cancer Classification based on Mass Spectrometry Analysis of Sera

In our previous study [1], we have compared the performance of a number of widely used discrimination methods for classifying ovarian cancer using Matrix Assisted Laser Desorption Ionization (MALDI) mass spectrometry data on serum samples obtained from Reflectron mode. Our results demonstrate good performance with a random forest classifier. In this follow-up study, to improve the molecular classification power of the MALDI platform for ovarian cancer disease, we expanded the mass range of the MS data by adding data acquired in Linear mode and evaluated the resultant decrease in classification error. A general statistical framework is proposed to obtain unbiased classification error estimates and to analyze the effects of sample size and number of selected m/z features on classification errors. We also emphasize the importance of combining biological knowledge and statistical analysis to obtain both biologically and statistically sound results. Our study shows improvement in classification accuracy upon expanding the mass range of the analysis. In order to obtain the best classification accuracies possible, we found that a relatively large training sample size is needed to obviate the sample variations. For the ovarian MS dataset that is the focus of the current study, our results show that approximately 20–40 m/z features are needed to achieve the best classification accuracy from MALDI-MS analysis of sera. Supplementary information can be found at http://bioinformatics.med.yale.edu/proteomics/BioSupp2.html.
JNJ-20788560 [9-(8-Azabicyclo[3.2.1]oct-3-ylidene)-9H-xanthene-3-carboxylic Acid Diethylamide], a Selective Delta Opioid Receptor Agonist, Is a Potent and Efficacious Antihyperalgesic Agent That Does Not Produce Respiratory Depression, Pharmacologic Tolerance, or Physical Dependence

μ-Opioid analgesics are a mainstay in the treatment of acute and chronic pain of multiple origins, but their side effects, such as constipation, respiratory depression, and abuse liability, adversely affect patients. The recent demonstration of the up-regulation and membrane targeting of the δ-opioid receptor (DOR) following inflammation and the consequent enhanced therapeutic effect of δ-opioid agonists have enlivened the search for δ-opioid analgesic agents. JNJ-20788560 [9-(8-azabicyclo-[3.2.1]oct-3-ylidene)-9H-xanthene-3-carboxylic acid diethylamide] had an affinity of 2.0 nM for DOR (rat brain cortex binding assay) and a naltrindole sensitive DOR potency of 5.6 nM (5′-O-(3-[35S]thio)triphosphate assay). The compound had a potency of 7.6 mg/kg p.o. in a rat zymosan radiant heat test and of 13.5 mg/kg p.o. in a rat Complete Freund's adjuvant RH test but was virtually inactive in an uninflamed radiant heat test. In limited studies, tolerance was not observed to the antihyperalgesic or antinociceptive effects of the compound. Unlike ibuprofen, JNJ-20788560 did not produce gastrointestinal (GI) erosion. Although morphine reduced GI motility at all doses tested and reached nearly full effect at the highest dose, JNJ-20788560 did not retard transit at the lowest dose and reached only 11% reduction at the highest dose administered. Unlike morphine, JNJ-20788560 did not exhibit respiratory depression (blood gas analysis), and no withdrawal signs were precipitated by the administration of opioid (μ or δ) antagonists. Coupled with the previously published lack of self-administration behavior of the compound by alfentanil-trained primates, these findings strongly recommend δ-opioid agonists such as JNJ-20788560 for the relief of inflammatory hyperalgesia.
Practical DIFC Enforcement on Android

Smartphone users often use private and enterprise data with untrusted third party applications. The fundamental lack of secrecy guarantees in smartphone OSes, such as Android, exposes this data to the risk of unauthorized exfiltration. A natural solution is the integration of secrecy guarantees into the OS. In this paper, we describe the challenges for decentralized information flow control (DIFC) enforcement on Android. We propose contextsensitive DIFC enforcement via lazy polyinstantiation and practical and secure network export through domain declassification. Our DIFC system, Weir, is backwards compatible by design, and incurs less than 4 ms overhead for component startup. With Weir, we demonstrate practical and secure DIFC enforcement on Android.