Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermal Sensitivity of Lateral Inhibition in Limulus Eye

The effectiveness of lateral inhibition, measured as spike response decrement in a test ommatidium, produced by activity in a group of neighboring ommatidia, decreases as temperature decreases (Q10 of 2.6). The corresponding sensory transducer-spike encoding processes have a weaker temperature dependence (Q10 of 1.6). Relative synaptic delay, the time difference between the latency of inhibition onset and the latency of test receptor excitation, has a strong temperature dependence (Q10 of 5), while receptor potential onset latency (Q10 of 1.4) and optic nerve spike conduction velocity (Q10 of 1.7), two factors inherent in relative synaptic delay, are less temperature sensitive. Oscillations of optic nerve spike response ("bursting") may be produced by thermal adjustment of temperature-sensitive parameters of the lateral inhibitory network in the retina. Burst interval has a strong temperature dependence (Q10 of 2.4) and broad interspike interval distribution compared to the thermal sensitivity (Q10 of 1.4) and narrow spike interval spectrum of the response of a single unit within the bursting group.
Multi-frequency GMRT observations of the HII regions S 201, S 206, and S 209 - Galactic temperature gradient

We present radio continuum images of three Galactic H II regions, S 201, S 206, and S 209 near 232, 327, and 610 MHz using the Giant Meterwave Radio Telescope (GMRT). The GMRT has a mix of short and long baselines, therefore, even though the data have high spatial resolution, the maps are still sensitive to diffuse extended emission. We find that all three H II regions have bright cores surrounded by diffuse envelopes. We use the high resolution afforded by the data to estimate the electron temperatures and emission measures of the compact cores of these H II regions. Our estimates of electron temperatures are consistent with a linear increase of electron temperature with Galacto-centric distance for distances up to ~ 18 kpc (the distance to the most distant H II region in our sample).
A Formal Model for Information Selection in Multi-Sentence Text Extraction

Selecting important information while accounting for repetitions is a hard task for both summarization and question answering. We propose a formal model that represents a collection of documents in a two-dimensional space of textual and conceptual units with an associated mapping between these two dimensions. This representation is then used to describe the task of selecting textual units for a summary or answer as a formal optimization task. We provide approximation algorithms and empirically validate the performance of the proposed model when used with two very different sets of features, words and atomic events.
Citalopram intravenous infusion in resistant obsessive-compulsive disorder: an open trial.

BACKGROUND Treatment with intravenous clomipramine is rapidly effective in some obsessive-compulsive disorder (OCD) patients unresponsive to orally administered serotonin reuptake inhibitors (SRIs). The selective serotonin reuptake inhibitor citalopram is effective for OCD when administered orally. We investigated whether intravenous citalopram would rapidly benefit OCD patients unresponsive to orally administered SRIs. METHOD Thirty-nine adult outpatients participated in a 3-week open-label trial of intravenous citalopram. Eligible patients had moderate-to-severe DSM-IV OCD of > or = 1 year's duration, a baseline Yale-Brown Obsessive Compulsive Scale (YBOCS) score > or = 25, and no other active Axis I diagnosis and had failed at least 2 adequate oral SRI trials, excluding citalopram. Intravenous citalopram was administered daily for 21 days, followed by oral citalopram until treatment day 84. Intravenous citalopram was started at 20 mg/day and was increased to 40 to 80 mg/day as tolerated. RESULTS Intravenous citalopram was well tolerated even at higher doses (dropout rate = 2.6%). At day 21, 23 (59%) of the 39 patients had YBOCS score decreases of > or = 25%, of whom 4 had decreases of > or = 35%. Twenty-seven patients with YBOCS score decreases of > or = 20% were allowed to continue on treatment with oral citalopram, and by day 84, all had substantial further improvement. All 27 patients also showed significant improvement in several dimensions of quality of life. CONCLUSION Intravenous citalopram was safe and rapidly effective in a group of treatment-resistant OCD patients. The early onset of response suggests a means of accelerating OCD symptom relief and predicting response to oral citalopram treatment. Double-blind, double-dummy, placebo-controlled trials of intravenous versus oral citalopram in patients with treatment-resistant OCD are indicated.
In Vivo Phosphoantigen Levels in Bisphosphonate-Treated Human Breast Tumors Trigger Vγ9Vδ2 T-cell Antitumor Cytotoxicity through ICAM-1 Engagement

Purpose: Nitrogen-containing bisphosphonates (N-BP) such as zoledronate and risedronate exhibit antitumor effects. They block the activity of farnesyl pyrophosphate synthase (FPPS) in the mevalonate pathway, leading to intracellular accumulation of mevalonate metabolites (IPP/ApppI), which are recognized as tumor phosphoantigens by Vγ9Vδ2 T cells. However, mechanisms responsible for Vγ9Vδ2 T-cell recognition of N-BP–treated tumors producing IPP/ApppI remain unclear. Experimental Design: The effects of N-BPs on Vγ9Vδ2 T-cell expansion and anticancer activity were evaluated in vitro and in animal models of human breast cancers. The modalities of recognition of breast tumors by Vγ9Vδ2 T cells in N-BP–treated animals were also examined. Results: We found a strong correlation between Vγ9Vδ2 T-cell anticancer activity and intracellular accumulation of IPP/ApppI in risedronate-treated breast cancer cells in vitro. In addition, following risedronate treatment of immunodeficient mice bearing human breast tumors, human Vγ9Vδ2 T cells infiltrated and inhibited growth of tumors that produced high IPP/ApppI levels but not those expressing low IPP/ApppI levels. The combination of doxorubicin with a N-BP improved, however, Vγ9Vδ2 T-cell cytotoxicity against breast tumors expressing low IPP/ApppI levels. Moreover, Vγ9Vδ2 T-cell cytotoxicity in mice treated with risedronate or zoledronate did not only depend on IPP/ApppI accumulation in tumors but also on expression of tumor cell surface receptor intercellular adhesion molecule-1 (ICAM-1), which triggered the recognition of N-BP–treated breast cancer cells by Vγ9Vδ2 T cells in vivo. Conclusion: These findings suggest that N-BPs can have an adjuvant role in cancer therapy by activating Vγ9Vδ2 T-cell cytotoxicity in patients with breast cancer that produces high IPP/ApppI levels after N-BP treatment. Clin Cancer Res; 18(22); 6249–59. ©2012 AACR.
Real-time pattern matching using projection kernels

A novel approach to pattern matching is presented in which time complexity is reduced by two orders of magnitude compared to traditional approaches. The suggested approach uses an efficient projection scheme which bounds the distance between a pattern and an image window using very few operations on average. The projection framework is combined with a rejection scheme which allows rapid rejection of image windows that are distant from the pattern. Experiments show that the approach is effective even under very noisy conditions. The approach described here can also be used in classification schemes where the projection values serve as input features that are informative and fast to extract.
Toward Selectivity-Based Keyword Extraction for Croatian News

Preliminary report on network based keyword extraction for Croatian is an unsupervised method for keyword extraction from the complex network. We build our approach with a new network measure the node selectivity, motivated by the research of the graph based centrality approaches. The node selectivity is defined as the average weight distribution on the links of the single node. We extract nodes (keyword candidates) based on the selectivity value. Furthermore, we expand extracted nodes to word-tuples ranked with the highest in/out selectivity values. Selectivity based extraction does not require linguistic knowledge while it is purely derived from statistical and structural information en-compassed in the source text which is reflected into the structure of the network. Obtained sets are evaluated on a manually annotated keywords: for the set of extracted keyword candidates average F1 score is 24,63%, and average F2 score is 21,19%; for the exacted words-tuples candidates average F1 score is 25,9% and average F2 score is 24,47%.
Development of PVDF micro and nanostructures for cell culture studies

Tissue engineering aims at repairing damaged tissues and recovering the lost or degraded biological functions with artificial scaffolds. In order to meet the requirement for more complex functionality such as peripheral nerve reconstruction, new types of scaffold materials are needed. In this work, we developed several micro- and nanofabrication techniques to pattern polyvinylidene fluoride (PVDF), a highly non-reactive, piezoelectric, thermoplastic fluoropolymer, which can serve as new constituents for advanced tissue engineering. We first studied the feasibility of PVDF patterning using conventional photolithography, soft lithography and microcontact printing. The fabricated patterns were systematically characterized by surface analysis techniques (FTIR, XRD) and used for cell culture studies. Then, we developed a study on electrospinning of PVDF nanofibers. Our results showed that the fabricated PVDF nanofibers were compatible with cell-based assays. Finally, we doped electrospun PVDF nanofibers with magnetic nanoparticles, which should make them excitable with a remote magnetic field
Content-Aware Web Browsing and Visualization Tools for Cantillation and Chant Research

Chant and cantillation research is particularly interesting as it explores the transition from oral to written transmission of music. The goal of this work to create web-based computational tools that can assist the study of how diverse recitation traditions, having their origin in primarily non-notated melodies, later became codified. One of the authors is a musicologist and music theorist who has guided the system design and development by providing manual annotations and participating in the design process. We describe novel content-based visualization and analysis algorithms that can be used for problem-seeking exploration of audio recordings of chant and recitations.
Epigenetic Natural Variation in Arabidopsis thaliana

Cytosine methylation of repetitive sequences is widespread in plant genomes, occurring in both symmetric (CpG and CpNpG) as well as asymmetric sequence contexts. We used the methylation-dependent restriction enzyme McrBC to profile methylated DNA using tiling microarrays of Arabidopsis Chromosome 4 in two distinct ecotypes, Columbia and Landsberg erecta. We also used comparative genome hybridization to profile copy number polymorphisms. Repeated sequences and transposable elements (TEs), especially long terminal repeat retrotransposons, are densely methylated, but one third of genes also have low but detectable methylation in their transcribed regions. While TEs are almost always methylated, genic methylation is highly polymorphic, with half of all methylated genes being methylated in only one of the two ecotypes. A survey of loci in 96 Arabidopsis accessions revealed a similar degree of methylation polymorphism. Within-gene methylation is heritable, but is lost at a high frequency in segregating F 2 families. Promoter methylation is rare, and gene expression is not generally affected by differences in DNA methylation. Small interfering RNA are preferentially associated with methylated TEs, but not with methylated genes, indicating that most genic methylation is not guided by small interfering RNA. This may account for the instability of gene methylation, if occasional failure of maintenance methylation cannot be restored by other means.
Word Translation Disambiguation Using Bilingual Bootstrapping

This article proposes a new method for word translation disambiguation, one that uses a machine-learning technique called bilingual bootstrapping. In learning to disambiguate words to be translated, bilingual bootstrapping makes use of a small amount of classified data and a large amount of unclassified data in both the source and the target languages. It repeatedly constructs classifiers in the two languages in parallel and boosts the performance of the classifiers by classifying unclassified data in the two languages and by exchanging information regarding classified data between the two languages. Experimental results indicate that word translation disambiguation based on bilingual bootstrapping consistently and significantly outperforms existing methods that are based on monolingual bootstrapping.
Affinity learning via self-diffusion for image segmentation and clustering

Computing a faithful affinity map is essential to the clustering and segmentation tasks. In this paper, we propose a graph-based affinity (metric) learning method and show its application to image clustering and segmentation. Our method, self-diffusion (SD), performs a diffusion process by propagating the similarity mass along the intrinsic manifold of data points. Theoretical analysis is given to the SD algorithm and we provide a way of deriving the critical time stamp t. Our method therefore has nearly no parameter tuning and leads to significantly improved affinity maps, which help to greatly enhance the quality of clustering. In addition, we show that much improved image segmentation results can be obtained by combining SD with e.g. the normalized cuts algorithm. The proposed method can be used to deliver robust affinity maps for a range of problems.
Efficient data harvesting in mobile sensor networks

Sensors are now attached to a lot of mobile objects such as animals and vehicles to collect data. This forms intermittently connected mobile sensor network due to weak communication power and nodal mobility, in which conventional routing protocols in wireless sensor network don't work. In this paper, we propose a data harvesting scheme for intermittently connected mobile sensor network. This approach takes fully advantage of storage resource and mobility pattern knowledge to improve the delivery ratio while minimizing the transmission overhead. We evaluate the performance of the approach through the OMNet++ simulator with the realistic mobility traces. The simulation results show that the proposed scheme achieves high delivery ratio while controlling the transmission overhead. Furthermore, the robust approach can be adaptive to the dynamic topology of network.
Benzodiazepine prescribing patterns and deaths from drug overdose among US veterans receiving opioid analgesics: case-cohort study

Objective To study the association between benzodiazepine prescribing patterns including dose, type, and dosing schedule and the risk of death from drug overdose among US veterans receiving opioid analgesics. Design Case-cohort study. Setting Veterans Health Administration (VHA), 2004-09. Participants US veterans, primarily male, who received opioid analgesics in 2004-09. All veterans who died from a drug overdose (n=2400) while receiving opioid analgesics and a random sample of veterans (n=420 386) who received VHA medical services and opioid analgesics. Main outcome measure Death from drug overdose, defined as any intentional, unintentional, or indeterminate death from poisoning caused by any drug, determined by information on cause of death from the National Death Index. Results During the study period 27% (n=112 069) of veterans who received opioid analgesics also received benzodiazepines. About half of the deaths from drug overdose (n=1185) occurred when veterans were concurrently prescribed benzodiazepines and opioids. Risk of death from drug overdose increased with history of benzodiazepine prescription: adjusted hazard ratios were 2.33 (95% confidence interval 2.05 to 2.64) for former prescriptions versus no prescription and 3.86 (3.49 to 4.26) for current prescriptions versus no prescription. Risk of death from drug overdose increased as daily benzodiazepine dose increased. Compared with clonazepam, temazepam was associated with a decreased risk of death from drug overdose (0.63, 0.48 to 0.82). Benzodiazepine dosing schedule was not associated with risk of death from drug overdose. Conclusions Among veterans receiving opioid analgesics, receipt of benzodiazepines was associated with an increased risk of death from drug overdose in a dose-response fashion.
A unified approach to identifying and healing vulnerabilities in x86 machine code

The security of software systems is threatened by a wide range of attack vectors, such as buffer overflows, insecure information flow, and side channels, which can leak private information, e.g., by monitoring a program's execution time. Even if programmers manage to avoid such vulnerabilities in a program's source code or bytecode, new vulnerabilities can arise as compilers generate machine code from those representations. We propose a virtual execution environment for x86 machine code that combines information from compositional, static, and dynamic program analysis to identify vulnerabilities and timing channels, and uses code transformations to prevent those from being exploited. To achieve an appropriate level of performance as well as combine analysis results, our approach stores summary information in the form of conditional rules that can be shared among analyses.
Poplar FT2 Shortens the Juvenile Phase and Promotes Seasonal Flowering[W]

Many woody perennials, such as poplar (Populus deltoides), are not able to form flower buds during the first several years of their life cycle. They must undergo a transition from the juvenile phase to the reproductive phase to be competent to produce flower buds. After this transition, trees begin to form flower buds in the spring of each growing season. The genetic factors that control flower initiation, ending the juvenile phase, are unknown in poplar. The factors that regulate seasonal flower bud formation are also unknown. Here, we report that poplar FLOWERING LOCUS T2 (FT2), a relative of the Arabidopsis thaliana flowering-time gene FT, controls first-time and seasonal flowering in poplar. The FT2 transcript is rare during the juvenile phase of poplar. When juvenile poplar is transformed with FT2 and transcript levels are increased, flowering is induced within 1 year. During the transition between vegetative and reproductive growth in mature trees, FT2 transcripts are abundant during reproductive growth under long days. Subsequently, floral meristems emerge on flanks of the axillary inflorescence shoots. These findings suggest that FT2 is part of the flower initiation pathway in poplar and plays an additional role in regulating seasonal flower initiation that is integrated with the poplar perennial growth habit.
Rapport technique # INRS-EMT-012-1004 Calculation of Raw BER / SER over AWGN Channel for Arbitrary Two-Dimensional Constellation and Non-Uniform Signaling

Rapport technique #INRS-EMT-012-1004 Calculation of Raw BER/SER over AWGN Channel for Arbitrary Two-Dimensional Constellation and Non-Uniform Signaling Leszek Szczecinski, Cristian Gonzalez†, Marcos Bacic†, Sonia Aissa Institut National de la Recherche ScientifiqueEnergy, Materials & Telecommunications Montreal, Canada †Universidad Técnica Federico Santa Marı́a Department of Electronics Engineering Valparaı́so, Chile {leszek,gonzalez,bacic,aissa}@inrs-emt.uquebec. ca
Medoids in almost linear time via multi-armed bandits

Computing the medoid of a large number of points in high-dimensional space is an increasingly common operation in many data science problems. We present an algorithm Med-dit which uses O(n log n) distance evaluations to compute the medoid with high probability. Med-dit is based on a connection with the multi-armed bandit problem. We evaluate the performance of Med-dit empirically on the Netflix-prize and the single-cell RNA-Seq datasets, containing hundreds of thousands of points living in tens of thousands of dimensions, and observe a 5-10x improvement in performance over the current state of the art. Med-dit is available at this https URL
Interruptibility Estimation Based on Head Motion and PC Operation

Frequent and uncontrolled interruptions by information systems that do not reflect the user’s state can result in fragmented working times and decreased intellectual productivity. To avoid adverse interruptions, interruptibility estimation methods based on PC operation information have been proposed. However, workers who use PCs to accomplish their primary tasks occasionally engage in paperwork. Occasional paperwork activities, which are not reflected in the PC’s operation information, can cause estimation errors. This study focuses on using the position of the head, posture, temporal motion, and continuity of the head position and posture while a worker is at his or her desk as indices to reflect engagement in the task at hand. Based on an analysis of the relationship between the head-related parameters and interruptibility, an interruptibility estimation algorithm is proposed using four head-related indices that reflect interruptibility during PC and non-PC work. Experiments indicate that estimation accuracy improves as a result of incorporating these indices in the algorithm.
Support Vector Machines for 3D Shape Processing

We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which are state of the art in machine learning. It is straightforward to implement and computationally competitive; its parameters can be automatically set using standard machine learning methods. The surface approximation is based on a modified Support Vector regression. We present applications to 3D head reconstruction, including automatic removal of outliers and hole filling. In a second step, we build on our SV representation to compute dense 3D deformation fields between two objects. The fields are computed using a generalized SV Machine enforcing correspondence between the previously learned implicit SV object representations, as well as correspondences between feature points if such points are available. We apply the method to the morphing of 3D heads and other objects.
Routing XML queries

In file-sharing P2P networks, a fundamental problem is that of identifying databases that are relevant to user queries. This problem is referred to as the location problem in P2P literature. We propose a scalable solution to the location problem in a data-sharing P2P network, consisting of a network of XML database nodes and XML router nodes, and make the following contributions. We develop the internal organization and routing protocols for the XML router nodes, to enable scalable XPath query and update processing, under the open and the agreement cooperation models between nodes. Since router nodes tend to be memory constrained, we facilitate a space/performance tradeoff by permitting aggregated routing states, and developing algorithms for generating and using such aggregated information. We experimentally demonstrate the scalability of our approach, and the performance of our query and update protocols, using a detailed simulation model, varying key design parameters.