Miracle-dz/UniFAR-FTUs huggingface dataset:
Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex

The information processing abilities of neural circuits arise from their synaptic connection patterns. Understanding the laws governing these connectivity patterns is essential for understanding brain function. The overall distribution of synaptic strengths of local excitatory connections in cortex and hippocampus is long-tailed, exhibiting a small number of synaptic connections of very large efficacy. At the same time, new synaptic connections are constantly being created and individual synaptic connection strengths show substantial fluctuations across time. It remains unclear through what mechanisms these properties of neural circuits arise and how they contribute to learning and memory. In this study we show that fundamental characteristics of excitatory synaptic connections in cortex and hippocampus can be explained as a consequence of self-organization in a recurrent network combining spike-timing-dependent plasticity (STDP), structural plasticity and different forms of homeostatic plasticity. In the network, associative synaptic plasticity in the form of STDP induces a rich-get-richer dynamics among synapses, while homeostatic mechanisms induce competition. Under distinctly different initial conditions, the ensuing self-organization produces long-tailed synaptic strength distributions matching experimental findings. We show that this self-organization can take place with a purely additive STDP mechanism and that multiplicative weight dynamics emerge as a consequence of network interactions. The observed patterns of fluctuation of synaptic strengths, including elimination and generation of synaptic connections and long-term persistence of strong connections, are consistent with the dynamics of dendritic spines found in rat hippocampus. Beyond this, the model predicts an approximately power-law scaling of the lifetimes of newly established synaptic connection strengths during development. Our results suggest that the combined action of multiple forms of neuronal plasticity plays an essential role in the formation and maintenance of cortical circuits.
Monitoring beta-lactamase activity in vivo by 13C nuclear magnetic resonance spectroscopy

A 13C-labeled cephalothin, 7 beta-(2-thienylacetamido)-3-[acetoxy-13C1]methyl-3-cephem-4- carboxylate (compound 1), has been prepared and used to monitor beta-lactamase activities by 13C nuclear magnetic resonance spectroscopy. Time-elapsed spectral analysis of the reaction of the labeled cephalothin with the TEM-2 beta-lactamase purified from Escherichia coli revealed the progressive loss of the cephalothin acetyl resonance at 176.8 ppm and accumulation of an acetate signal at 184.3 ppm. Spectral results identical to those observed in the in vitro experiment were obtained when compound 1 was incubated with cell suspensions of E. coli JSR-O (pBR322), which contains the plasmid-encoded TEM-2 beta-lactamase, and Enterobacter cloacae strains that contain a class I chromosomal beta-lactamase. Pseudo-first-order rate constants for the lactamase-catalyzed formation of acetate from cephalothin in vivo were obtained by integration of the 13C-acetyl resonances of compound 1 during timed incubations with cell preparations. These results constitute the first demonstration of the ability to monitor beta-lactamase activity in viable cells by nuclear magnetic resonance spectroscopy.
Dynamic Searchable Encryption in Very-Large Databases: Data Structures and Implementation

We design and implement dynamic symmetric searchable encryption schemes that efficiently and privately search server-held encrypted databases with tens of billions of record-keyword pairs. Our basic theoretical construction supports single-keyword searches and offers asymptotically optimal server index size, fully parallel searching, and minimal leakage. Our implementation effort brought to the fore several factors ignored by earlier coarse-grained theoretical performance analyses, including lowlevel space utilization, I/O parallelism and goodput. We accordingly introduce several optimizations to our theoretically optimal construction that model the prototype’s characteristics designed to overcome these factors. All of our schemes and optimizations are proven secure and the information leaked to the untrusted server is precisely quantified. We evaluate the performance of our prototype using two very large datasets: a synthesized census database with 100 million records and hundreds of keywords per record and a multi-million webpage collection that includes Wikipedia as a subset. Moreover, we report on an implementation that uses the dynamic SSE schemes developed here as the basis for supporting recent SSE advances, including complex search queries (e.g., Boolean queries) and richer operational settings (e.g., query delegation), in the above terabyte-scale databases.
An Image Fusion Algorithm Based on Non-subsampled Shearlet Transform and Compressed Sensing

In order to obtain rapid fusion speed, an image fusion algorithm based on Nonsubsampled Shearlet Transform (NSST) and Compressed Sensing (CS) is presented. The source images are decomposed with NSST. Based on local area energy, the low-frequency coefficients are fused. The high-frequency coefficients are compressed, fused and reconstructed with CS. Based on global gradient, the measurements of high-frequency coefficients are fused. The inverse NSST is used to get the final fused image. During the fusion course, only the compressed data of the high-frequency coefficients are fused, so the fusion effects can’t be affected. At the same time, the running time can be reduced. In this paper, the multi-focus images are used to verify the algorithm effectiveness. The simulation results indicate that the fusion image can be achieved without prior knowledge of the original images. Although the fusion quality is sacrificed when the sampling rate becomes higher, the algorithm can significantly reduce the time cost and hardware requirements. The algorithm provides an idea on how to satisfy the real time requirements in the fusion system.
Parallel Memory Implementation for Arbitrary Stride Accesses

Parallel memory modules can be used to increase memory bandwidth and feed a processor with only necessary data. Arbitrary stride access capability with interleaved memories is described in previous research where the skewing scheme is changed at run time according to the currently used stride. This paper presents the improved schemes which are adapted to parallel memories. The proposed novel parallel memory implementation allows conflict free accesses with all the constant strides which has not been possible in prior application specific parallel memories. Moreover, the possible access locations are unrestricted and the data patterns have equal amount of accessed data elements as the number of memory modules. Timing and area estimates are given for Altera Stratix FPGA and 0.18 micrometer CMOS process with memory module count from 2 to 32. The FPGA results show 129 MHz clock frequency for a system with 16 memory modules when read and write latencies are 3 and 2 clock cycles, respectively
Measuring symptom occurrence and symptom distress: development of the symptom experience index.

AIM This paper is a report of a study to assess reliability and construct validity of revised and refined version of the Adapted Symptom Distress Scale: the Symptom Experience Index (SEI). BACKGROUND The development of the SEI, a 41-item Likert Scale assessing 20 symptoms, was based on self-regulation theory and an integrative conceptual analysis of symptom assessment and management. The model emphasizes the difference between the occurrence of a symptom (or multiple symptoms) and the distress (emotional) response to the occurrence of a symptom. It is the distress from symptom occurrence that promotes a person to take action and use known coping strategies to prevent the symptom occurrence or alleviate the distress from the symptom. METHOD A contrast-group and test-retest approach was used to assess construct validity and reliability with a convenience sample of 158 patients at United States of America in 2003-2004. RESULTS The SEI demonstrated reasonable internal consistency with a Cronbach's alpha of 0.91 for symptom experience, 0.85 for symptom occurrence and 0.84 for symptom distress. Test-retest reliability was supported by high intra-class correlation coefficients (symptom experience r = 0.93; symptom occurrence r = 0.94; symptom distress, r = 0.92). Construct validity was supported by statistically significant differences between patients and healthy adults. CONCLUSION The SEI can be used as a baseline and outcome measure to assess the impact of multiple symptoms on patients, and the effectiveness of interventions to manage these symptoms.
A neuropsychological instrument measuring age-related cerebral decline in older drivers: development, reliability, and validity of MedDrive

When facing age-related cerebral decline, older adults are unequally affected by cognitive impairment without us knowing why. To explore underlying mechanisms and find possible solutions to maintain life-space mobility, there is a need for a standardized behavioral test that relates to behaviors in natural environments. The aim of the project described in this paper was therefore to provide a free, reliable, transparent, computer-based instrument capable of detecting age-related changes on visual processing and cortical functions for the purposes of research into human behavior in computational transportation science. After obtaining content validity, exploring psychometric properties of the developed tasks, we derived (Study 1) the scoring method for measuring cerebral decline on 106 older drivers aged ≥70 years attending a driving refresher course organized by the Swiss Automobile Association to test the instrument's validity against on-road driving performance (106 older drivers). We then validated the derived method on a new sample of 182 drivers (Study 2). We then measured the instrument's reliability having 17 healthy, young volunteers repeat all tests included in the instrument five times (Study 3) and explored the instrument's psychophysical underlying functions on 47 older drivers (Study 4). Finally, we tested the instrument's responsiveness to alcohol and effects on performance on a driving simulator in a randomized, double-blinded, placebo, crossover, dose-response, validation trial including 20 healthy, young volunteers (Study 5). The developed instrument revealed good psychometric properties related to processing speed. It was reliable (ICC = 0.853) and showed reasonable association to driving performance (R2 = 0.053), and responded to blood alcohol concentrations of 0.5 g/L (p = 0.008). Our results suggest that MedDrive is capable of detecting age-related changes that affect processing speed. These changes nevertheless do not necessarily affect driving behavior.
Discovering Low-Rank Shared Concept Space for Adapting Text Mining Models

We propose a framework for adapting text mining models that discovers low-rank shared concept space. Our major characteristic of this concept space is that it explicitly minimizes the distribution gap between the source domain with sufficient labeled data and the target domain with only unlabeled data, while at the same time it minimizes the empirical loss on the labeled data in the source domain. Our method is capable of conducting the domain adaptation task both in the original feature space as well as in the transformed Reproducing Kernel Hilbert Space (RKHS) using kernel tricks. Theoretical analysis guarantees that the error of our adaptation model can be bounded with respect to the embedded distribution gap and the empirical loss in the source domain. We have conducted extensive experiments on two common text mining problems, namely, document classification and information extraction, to demonstrate the efficacy of our proposed framework.
Transgenic expression of CD95 ligand on islet beta cells induces a granulocytic infiltration but does not confer immune privilege upon islet allografts.

Binding of CD95 (Fas/APO-1) by its ligand (CD95L) commonly induces apoptosis. Apoptosis of activated T cells, induced by CD95L expressed in the rodent testis, has been proposed to be the mechanism of immune privilege [Bellgrau, D. , Gold, D. , Selawry, H. , Moore, J., Franzusoff, A. & Duke, R. C. (1995) Nature (London) 377, 630-632]. To test whether CD95L could protect pancreatic islet grafts from rejection, we made transgenic mice expressing murine CD95L on their islet beta cells and transplanted fetal pancreata under the kidney capsules of allogeneic animals. Expression of CD95L failed to protect the grafts from rejection. However, transgenic mice developed a granulocytic infiltration in their pancreata. These results demonstrate a pro-inflammatory function of CD95L and suggest that expression of CD95L may not be sufficient to protect organ allografts.
Evidence That Base-pairing Interaction between Intron and mRNA Leader Sequences Inhibits Initiation of HAC1 mRNA Translation in Yeast*

Background: Hac1 protein, encoded by a cytoplasmically spliced mRNA, activates the unfolded protein response to maintain cellular protein homeostasis and alleviate endoplasmic reticulum stress. Results: Under non-stress conditions, translation initiation on the HAC1 mRNA is repressed. Conclusion: Base-pairing interaction between the 5′ leader and intron represses translation initiation on the HAC1 mRNA. Significance: A unique mechanism of intron-mediated inhibition of ribosomal scanning. The Hac1 transcription factor in yeast up-regulates a collection of genes that control protein homeostasis. Base-pairing interactions between sequences in the intron and the 5′-untranslated region (5′ UTR) of the HAC1 mRNA represses Hac1 protein production under basal conditions, whereas cytoplasmic splicing of the intron by the Ire1 kinase-endonuclease, activated under endoplasmic reticulum stress conditions, relieves the inhibition and enables Hac1 synthesis. Using a random mutational screen as well as site-directed mutagenesis, we identify point mutations within the 5′ UTR-intron interaction site that derepress translation of the unspliced HAC1 mRNA. We also show that insertion of an in-frame AUG start codon upstream of the interaction site releases the translational block, demonstrating that an elongating ribosome can disrupt the interaction. Moreover, overexpression of translation initiation factor eIF4A, a helicase, enhances production of Hac1 from an mRNA containing an upstream AUG start codon at the beginning of the base-paired region. These results suggest that the major block of translation occurs at the initiation stage. Supporting this interpretation, the point mutations that enhanced Hac1 production resulted in an increased percentage of the HAC1 mRNA associating with polysomes versus free ribosomal subunits. Thus, our results provide evidence that the 5′ UTR-intron interaction represses translation initiation on the unspliced HAC1 mRNA.
Pharmacological intervention based on fecal calprotectin levels in patients with ulcerative colitis at high risk of a relapse: A prospective, randomized, controlled study

Background Targeted therapy, using biomarkers to assess disease activity in ulcerative colitis (UC), has been proposed. Objective The objective of this study was to evaluate whether pharmacological intervention guided by fecal calprotectin (FC) prolongs remission in patients with UC. Methods A total of 91 adults with UC in remission were randomized to an intervention group or a control group. Analysis of FC was performed monthly, during 18 months. A FC value of 300 µg/g was set as the cut-off for intervention, which was a dose escalation of the oral 5-aminosalicylate (5-ASA) agent. The primary study end-point was the number of patients to have relapsed by month 18. Results There were relapses in 18 (35.3%) and 20 (50.0%) patients in the intervention and the control groups, respectively (p = 0.23); and 28 (54.9%) patients in the intervention group and 28 (70.0%) patients in the control group had a FC > 300 µg/g, of which 8 (28.6%) and 16 (57.1%) relapsed, respectively (p < 0.05). Conclusion Active intervention significantly reduced relapse rates, although no significant difference was reached between the groups overall. Thus, FC-levels might be used to identify patients with UC at risk for a flare, and a dose escalation of their 5-ASA agent is a therapeutic option for these patients.
Simultaneous Inference of Places, Activities, and Behavioral Classes in Maritime GPS Traces

Previous work has shown that activities and places of interest can be extracted from GPS traces of human movements using behavioral models based on conditional random fields (CRFs). In this paper, we adapt and extend this work in two ways. First, we apply the framework to analysis of a vehicle-tracking maritime environment, analyzing GPS data from a 5 day surveillance of merchant marine ships conducting exercises in the English channel. Secondly, we expand the model to a perform a broader population analysis segmenting the population into several classes with distinct behavioral models. Empirical results show that our algorithm is successful in inferring locations of interest, but makes only coarse distinction in activity inference. In clustering behaviors, it successfully divides agents with highly localized activities from those servicing distant ports.
Fast dynamic programming for labeling problems with ordering constraints

Many computer vision applications can be formulated as labeling problems. However, multilabeling problems are usually very challenging to solve, especially when some ordering constraints are enforced. We solve in this paper a five-parts labeling problem proposed in [6, 7]. In this model, one wants to find an optimal labeling for an image with five possible parts: “left”, “right”, “top”, “bottom” and “center”. The geometric ordering constraints can be read naturally from the names. No previous method can solve the problem with globally optimal solutions in a linear space complexity. We propose an efficient dynamic programming based algorithm which guarantees the global optimal labeling for the five-parts model. The time complexity is O(N1.5) and the space complexity is O(N), with N being the number of pixels in the image. In practice, it runs faster than previous methods. Moreover, it works for both 4-neighborhood and 8-neighborhood settings, and can be easily parallelized for GPU.
Sentiment analysis in financial markets A framework to utilize the human ability of word association for analyzing stock market news reports

As financial markets getting faster and more complex, it is difficult for market participants to manage the information overload. Sentiment analysis is a useful text mining method to process textual content and filter the results with analysis methods to relevant and meaningful information. The paper in hand introduces a new method for sentiment analysis in financial markets which combines word associations and lexical resources. Based on stock market news from January 2000 to February 2014 we analyzed documents on different levels. The results are presented and evaluated in this paper.
Polarisation studies of the prompt gamma-ray emission from GRB 041219a using the spectrometer aboard INTEGRAL

Context. Linear polarisation in gamma-ray burst prompt emission is an important diagnostic with the potential to significantly constrain models. The spectrometer aboard INTEGRAL , SPI, has the capability to detect the signature of polarised emission from a bright γ -ray source. GRB 041219a is the most intense burst localised by INTEGRAL with a fluence of 5.7 $\times 10^{-4}$ erg cm -2 over the energy range 20 keV–8 MeV and is an ideal candidate for such a study. Aims. Polarisation can be measured using multiple events scattered into adjacent detectors because the Compton scatter angle depends on the polarisation of the incoming photon. A search for linear polarisation in the most intense pulse of duration 66 seconds and in the brightest 12 seconds of GRB 041219a was performed in the 100–350 keV, 100–500 keV and 100 keV–1 MeV energy ranges. It was possible to divide the events into six directions in the energy ranges of 100–350 keV and 100–500 keV using the kinematics of the Compton scatter interactions. Methods. The multiple event data from the spectrometer was analysed and compared with the predicted instrument response obtained from Monte-Carlo simulations using the GEANT 4 INTEGRAL mass model. The $\chi^2$ distribution between the real and simulated data as a function of the percentage polarisation and polarisation angle was calculated for all three energy ranges. The degree and angle of polarisation were obtained from the best-fit value of $\chi^2$. Results. A weak signal consistent with polarisation was found throughout the analyses. The degree of linear polarisation in the brightest pulse of duration 66 s was found to be $63^{+31}_{-30}$% at an angle of $70^{+14}_{-11}$ degrees in the 100–350 keV energy range. The degree of polarisation was also constrained in the brightest 12 s of the GRB and a polarisation fraction of $96^{+39}_{-40}$% at an angle of $60^{+12}_{-14}$ degrees was determined over the same energy range. However, despite extensive analysis and simulations, a systematic effect that could mimic the weak polarisation signal could not be definitively excluded. Conclusions. Our results over several energy ranges and time intervals are consistent with a polarisation signal of about 60% but at a low level of significance (~$2\sigma$). The polarisation results are compared with predictions from the synchrotron and Compton drag processes. The spectrum of this GRB can also be well fit by a combined black body and power law model which could arise from a combination of the Compton and synchrotron processes, with different degrees of polarisation. We therefore conclude that the procedure described here demonstrates the effectiveness of using SPI as a polarimeter, and is a viable method of measuring polarisation levels in intense gamma-ray bursts.
Design and Implementation of Navigation System for Protein Interaction Networks

Proteins may not only perform a few of molecular functions, but it may also have many interactions with other proteins to accomplish a biological process successfully in cell [1]. These interactions could be defined as PINs (Protein Interaction Network). In general, researchers may adopt the yeast two-hybrid system for identifying protein interaction and it should be managed in database systematically such as BIND, DIP, YPD, PIMdb, and etc. But it’s not easy for user to analyze and interpret complicated PINs directly. There are application system to support this problem such as Cytoscape [4], Osprey [5], Tulip, and etc. But, these systems aren’t able to retrieve PINs which include proteins that have specific function and biological process, and interact with others at particular position in cell. Also, most systems use FDP (Force-Directed Placement) [3] algorithm for visualization, but this algorithm is not suitable to layout PINs because they are consisted of many disconnected sub-networks.
Data management projects at Google

This article describes some of the ongoing research projects related to structured data management at Google today. The organization of Google encourages research scientists to work closely with engineering teams. As a result, the research projects tend to be motivated by real needs faced by Google's products and services, and solutions are put into production and tested rapidly. In addition, because of the sheer scale at which Google operates, the engineering challenges faced by Google's services often require research innovations.
Dynamic Programming Generation of Curves on Brain Surfaces

Dynamic programming algorithms are presented for automated generation of length minimizing geodesics and curves of extremal curvature on the neocortex of the macaque and the visible human. Probabilistic models of curve variation are constructed in terms of the variability in speed, curvature, and torsion in the Frenet representation.