Miracle-dz/UniFAR-FTUs huggingface dataset:
Biased Agonism of Three Different Cannabinoid Receptor Agonists in Mouse Brain Cortex

Cannabinoid receptors are able to couple to different families of G proteins when activated by an agonist drug. It has been suggested that different intracellular responses may be activated depending on the ligand. The goal of the present study was to characterize the pattern of G protein subunit stimulation triggered by three different cannabinoid ligands, Δ9-THC, WIN55212-2, and ACEA in mouse brain cortex. Stimulation of the [35S]GTPγS binding coupled to specific immunoprecipitation with antibodies against different subtypes of G proteins (Gαi1, Gαi2, Gαi3, Gαo, Gαz, Gαs, Gαq/11, and Gα12/13), in the presence of Δ9-THC, WIN55212-2 and ACEA (submaximal concentration 10 μM) was determined by scintillation proximity assay (SPA) technique in mouse cortex of wild type, CB1 knock-out, CB2 knock-out and CB1/CB2 double knock-out mice. Results show that, in mouse brain cortex, cannabinoid agonists are able to significantly stimulate not only the classical inhibitory Gαi/o subunits but also other G subunits like Gαz, Gαq/11, and Gα12/13. Moreover, the specific pattern of G protein subunit activation is different depending on the ligand. In conclusion, our results demonstrate that, in mice brain native tissue, different exogenous cannabinoid ligands are able to selectively activate different inhibitory and non-inhibitory Gα protein subtypes, through the activation of CB1 and/or CB2 receptors. Results of the present study may help to understand the specific molecular pathways involved in the pharmacological effects of cannabinoid-derived drugs.
Large-scale maximum likelihood-based phylogenetic analysis on the IBM BlueGene/L

Phylogenetic inference is a grand challenge in Bioinformatics due to immense computational requirements. The increasing popularity of multi-gene alignments in biological studies, which typically provide a stable topological signal due to a more favorable ratio of the number of base pairs to the number of sequences, coupled with rapid accumulation of sequence data in general, poses new challenges for high performance computing. In this paper, we demonstrate how state-of-the-art Maximum Likelihood (ML) programs can be efficiently scaled to the IBM BlueGene/L (BG/L) architecture, by porting RAxML, which is currently among the fastest and most accurate programs for phylogenetic inference under the ML criterion. We simultaneously exploit coarse-grained and fine-grained parallelism that is inherent in every ML-based biological analysis. Performance is assessed using datasets consisting of 212 sequences and 566,470 base pairs, and 2,182 sequences and 51,089 base pairs, respectively. To the best of our knowledge, these are the largest datasets analyzed under ML to date. The capability to analyze such datasets will help to address novel biological questions via phylogenetic analyses. Our experimental results indicate that the fine-grained parallelization scales well up to 1, 024 processors. Moreover, a larger number of processors can be efficiently exploited by a combination of coarse-grained and fine-grained parallelism. Finally, we demonstrate that our parallelization scales equally well on an AMD Opteron cluster with a less favorable network latency to processor speed ratio. We recorded super-linear speedups in several cases due to increased cache efficiency.
Detect Key Gene Information in Classification of Microarray Data

We detect key information of high-dimensional microarray profiles based on wavelet analysis and genetic algorithm. Firstly, wavelet transform is employed to extract approximation coefficients at 2nd level, which remove noise and reduce dimensionality. Genetic algorithm (GA) is performed to select the optimized features. Experiments are performed on four datasets, and experimental results prove that approximation coefficients are efficient way to characterize the microarray data. Furthermore, in order to detect the key genes in the classification of cancer tissue, we reconstruct the approximation part of gene profiles based on orthogonal approximation coefficients. The significant genes are selected based on reconstructed approximation information using genetic algorithm. Experiments prove that good performance of classification is achieved based on the selected key genes.
On the Chromatic Roots of Generalized Theta Graphs

The generalized theta graph ? s1, ? , sk consists of a pair of endvertices joined by k internally disjoint paths of lengths s1, ? , sk? 1. We prove that the roots of the chromatic polynomial ? (? s1, ? , sk, z) of a k-ary generalized theta graph all lie in the disc|z? 1|? 1+o(1)]k/logk, uniformly in the path lengths si. Moreover, we prove that ? 2, ? , 2? K2, k indeed has a chromatic root of modulus 1+o(1)]k/logk. Finally, for k? 8 we prove that the generalized theta graph with a chromatic root that maximizes |z? 1| is the one with all path lengths equal to 2; we conjecture that this holds for all k.
Refolding of a Thermostable Glyceraldehyde Dehydrogenase for Application in Synthetic Cascade Biomanufacturing

The production of chemicals from renewable resources is gaining importance in the light of limited fossil resources. One promising alternative to widespread fermentation based methods used here is Synthetic Cascade Biomanufacturing, the application of minimized biocatalytic reaction cascades in cell free processes. One recent example is the development of the phosphorylation independent conversion of glucose to ethanol and isobutanol using only 6 and 8 enzymes, respectively. A key enzyme for this pathway is aldehyde dehydrogenase from Thermoplasma acidophilum, which catalyzes the highly substrate specific oxidation of d-glyceraldehyde to d-glycerate. In this work the enzyme was recombinantly expressed in Escherichia coli. Using matrix-assisted refolding of inclusion bodies the yield of enzyme production was enhanced 43-fold and thus for the first time the enzyme was provided in substantial amounts. Characterization of structural stability verified correct refolding of the protein. The stability of the enzyme was determined by guanidinium chloride as well as isobutanol induced denaturation to be ca. −8 kJ/mol both at 25°C and 40°C. The aldehyde dehydrogenase is active at high temperatures and in the presence of small amounts of organic solvents. In contrast to previous publications, the enzyme was found to accept NAD+ as cofactor making it suitable for application in the artificial glycolysis.
PACKARD Architectures for Efficient Scribble Matching

handwriting, matching, recognition, scribble Scribble matching is a form of partial handwriting recognition that allows like scribbles to be identified. In a companion paper [1] we describe a set of three algorithms which achieve high accuracy on this task. In this paper we address the issue of increasing the computational efficiency of these algorithms by over an order of magnitude to the point where interactive use on a modest platform such as Intel 80386 is possible.
SVM based approach for opinion classification in Arabic written tweets

We propose a machine learning approach for automatically classifying opinions of Twitter texts written in Modern Standard Arabic (MSA). Tweets are classified as either positive, negative, neutral or non-opinion. Various features for opinion classification have been used which are mainly linguistic and numeric. Our in-house collected and developed training data consists of tweets preserving their specifications such as @usermentions, #hashtags which are used as tweet-particular features. Four machine learning algorithms were applied on our dataset: Support Vector Machine (SVM), Naive Bayes (NB), J48 decision tree and Random forest. The experiments results show that SVM gives the highest F measure (72%), while the j48 classifier gives the highest precision (70,97%). Our experimental results demonstrate that tweet's specific features can significantly improve classification performance in comparison to other features combination.
Algorithms for Filling Obstacle Pockets with Hexagonal Metamorphic Robots

The problem addressed is the distributed reconfiguration of a metamorphic robotic system composed of any number of identical hexagonal modules. A metamorphic robotic system is a collection of independently controlled, smaller robots that can move around adjacent robots to change the shape of the overall system. The shape-changing ability of these systems makes them more versatile than conventional mobile robots. Because the modules are homogeneous, the systems are also capable of self-repair. As part of our research, we developed deterministic, distributed reconfiguration algorithms for planning the reconfiguration when a single obstacle with an irregular surface (e.g., containing pockets) is embedded in the goal. Current reconfiguration algorithms find a bisecting path of goal cells spanning the goal, called the substrate path. Modules fill in this substrate path and then move along the path to fill in the remainder of the goal. We present algorithms to 1) determine if an obstacle fulfills a simple admissibility requirement based on contact patterns, 2) include an admissible obstacle in a substrate path, and 3) determine the order to fill the pocket cells.
The functional curcumin liposomes induce apoptosis in C6 glioblastoma cells and C6 glioblastoma stem cells in vitro and in animals

Glioblastoma is a kind of malignant gliomas that is almost impossible to cure due to the poor drug transportation across the blood–brain barrier and the existence of glioma stem cells. We prepared a new kind of targeted liposomes in order to improve the drug delivery system onto the glioma cells and induce the apoptosis of glioma stem cells afterward. In this experiment, curcumin was chosen to kill gliomas, while quinacrine was used to induce apoptosis of the glioma stem cells. Also, p-aminophenyl-α-D-mannopyranoside could facilitate the transport of liposomes across the blood–brain barrier and finally target the brain glioma cells. The cell experiments in vitro indicated that the targeted liposomes could significantly improve the anti-tumor effects of the drugs, while enhancing the uptake effects, apoptosis effects, and endocytic effects of C6 glioma cells and C6 glioma stem cells. Given the animal experiments in vivo, we discovered that the targeted liposomes could obviously increase the survival period of brain glioma-bearing mice and inhibit the growth of gliomas. In summary, curcumin and quinacrine liposomes modified with p-aminophenyl-α-D-mannopyranoside is a potential preparation to treat brain glioma cells and brain glioma stem cells.
Collecting unused processing capacity: an analysis of transient distributed systems

Distributed systems having large numbers of idle computers and workstations are analyzed using a very simple model of a distributed program (a fixed amount of work) to see how the use of transient processors affects the program's service time. The probability density of the length of time it takes to finish a fixed amount of work is determined. An equation is given for the main result for an M-processor network. Simulations confirm that Brownian motion with drift is an accurate model of system performance. With large programs that run for a long time relative to the length of available and nonavailable periods, the central limit-theorem applies, and the Brownian-motion-with-drift model remains good regardless of the distributions of the available and the nonavailable periods. Under these assumptions, the distribution of finishing time is very tight about its mean and well approximated by a normal distribution. <<ETX>>
Bidirectional Rule Learning

Hiermit versichere ich, die vorliegende Bachelor-Thesis ohne Hilfe Dritter nur mit den angegebenen Quellen und Hilfsmitteln angefertigt zu haben. Alle Stellen, die aus Quellen entnommen wurden, sind als solche kenntlich gemacht. Diese Arbeit hat in gleicher oder ähnlicher Form noch keiner Prüfungsbehörde vorgelegen.
A Core Calculus for Mixin-Types

The programming construct mixinwas invented to implement modules that provide the mechanism of abstracting uniform extensions and modifications to superclasses. One approach to implement a mixin is to parameterize a superclass of a generic class using a type parameter; however, this approach lacks the ability to declare a mixin that is also used as a type. In this paper, we propose a programming language McJava, an extension of Java that is equipped with mixin-types, a mechanism to declare a mixin that is also used as a type. Then, we develop Core McJava, a core language for McJava, and show its type soundness theorem. This core language is based on Featherweight Java (FJ), a minimum core calculus for Java. FJ is a very small subset of Java. Focusing on a few key issues, we have developed a flexible subtyping relation among mixin compositions.
Adding value to WSN simulation using the IoT-LAB experimental platform

Validation of protocols and mechanisms is an essential step to the development of object networks in critical domains. Most papers still provide evaluation either obtained through theoretical analysis or simulations campaigns. Yet, simulators and formal models fail to precisely reproduce the unique specificities of the deployment environments those networks have to evolve in. Also, by putting no limits to code complexity and execution, those tools prevent users to apprehend the actual limits of WSN nodes and to propose realistic communication protocols and applications. In this paper, we highlight to what extent the addition of experimentations can significantly improve the value of performance evaluation campaigns. Along with the recent tendency to have algorithmic and protocol proposals facing real environments, it is questionable whether the so obtained results should be considered as scientific or empirical ones. In the former case, reproducibility, stability over time, topology management to cite a few, are a must have for testbeds and real deployments that are used. In the latter, the results should be viewed as a proof-of-concept only, far from independent of the used hardware and encountered conditions at the experimentation time but still critical from the development cycle standpoint. Through some experiments over the IoT-LAB testbed, we aim at demonstrating to what extent some of the simulation setup and conditions from reality could be emulated. We also provide insight on how to obtain the best out of it in a quick and efficient manner. We show that such testbeds would satisfy many expectations (e.g. scientific tool and proof-of-concept validator), thus minding and bridging some of the gaps between theory and practice in WSN. To this end, we here give an overview of available simulation tools, and guidelines on how to transpose simulation setups to the open large-scale IoT-LAB platform.
Proof linking: modular verification of mobile programs in the presence of lazy, dynamic linking

Although mobile code systems typically employ link-time code verifiers to protect host computers from potentially malicious code, implementation flaws in the verifiers may still leave the host system vulnerable to attack. Compounding the inherent complexity of the verification algorithms themselves, the need to support lazy, dynamic linking in mobile code systems typically leads to architectures that exhibit strong interdependencies between the loader, the verifier, and the linker. To simplify verifier construction and provide improved assurances of verifier integrity, we propose a modular architecture based on the concept of proof linking. This architecture encapsulates the verification process and removes dependencies between the loader, the verifier, and the linker. We also formally model the process of proof linking and establish properties to which correct implementations must conform. As an example, we instantiate our architecture for the problem of Java bytecode verification and assess the correctness of this instantiation. Finally, we briefly discuss alternative mobile code verification architectures enabled by the proof-linking concept.
Automatic compression for image sets using a graph theoretical framework

A new automatic compression scheme that adapts to any image set is presented in this thesis. The proposed scheme requires no a priori knowledge on the properties of the image set. This scheme is obtained using a unified graph-theoretical framework that allows for compression strategies to be compared both theoretically and experimentally. This strategy achieves optimal lossless compression by computing a minimum spanning tree of a graph constructed from the image set. For lossy compression, this scheme is near-optimal and a performance guarantee relative to the optimal one is provided. Experimental results demonstrate that this compression strategy compares favorably to the previously proposed strategies, with improvements up to 7% in the case of lossless compression and 72% in the case of lossy compression. This thesis also shows that the choice of underlying compression algorithm is important for compressing image sets using the proposed scheme.
IMU-based solution for automatic detection and classification of exercises in the fitness scenario

Causal relationship between physical activity and prevention of several diseases has been known for some time. Recently, attempts to quantify dose-response relationship between physical activity and health show that automatic tracking and quantification of the exercise efforts not only help in motivating people but improve health conditions as well. However, no commercial devices are available for weight training and calisthenics. This work tries to overcome this limit, exploiting machine learning technique (particularly Linear Discriminant Analysis, LDA) for analyzing data coming from wearable inertial measurement units, (IMUs) and classifying/counting such exercises. Computational requirements are compatible with embedded implementation and reported results confirm the feasibility of the proposed approach, offering an average accuracy in the detection of exercises on the order of 85%.
Generation of Radiosity Texture Atlas for Realistic Real-Time Rendering

Radiosity methods are a both physically correct and efficient way to compute the global illumination giving the visual atmosphere to a 3D scene. In this paper, we present a new approach to optimizing the visualization of meshed models illuminated using these methods. Our approach is based on a texture atlas, which makes it possible to store the global illumination in a set of textures, that can be mapped in real-time onto the model by the graphics hardware. Our contribution is a new robust atlas generation method well adapted to the visualization of illuminated complex meshed models, and based on a tight cooperation between the segmentation and the parameterization algorithms. In our segmentation method, the combinatorial information of the mesh is systematically preferred over the geometry whenever possible, which makes the algorithm both simpler and more robust. Large industrial models with complex topologies and poor mesh qualities can be efficiently processed. The paper concludes with some results, showing our method applied to architectural and car design industry models, and demonstrating that it both speeds up the visualization and is easy to integrate into existing advanced rendering software.
Improving Visual Behavior Research in Communication Science: An Overview, Review, and Reporting Recommendations for Using Eye-Tracking Methods

ABSTRACT Eye tracking offers researchers an opportunity to collect an objective assessment of visual behavior. Visual behavior—referring broadly to metrics and measures of gaze positioning and movement—has been used to assess variables including exposure time, cognitive processing, prominence, and (visual) attention. Over the past decade, communication science researchers have increased their use of eye-tracking methods in published articles. During that same period, technological innovations have made eye-tracking units more affordable and accessible to interested researchers increasing the likelihood that eye-tracking research will continue to increase in the field. In this article, we provide information on eye tracking in hopes of improving the quality and reporting of eye-tracking research in communication. The article first provides an overview of basic eye-tracking information followed by a systematic review on the reporting of eye-tracking methods in communication-relevant research. We then provide eye-tracking research reporting recommendations and some ideas about how eye tracking might be integrated into scholarly work moving forward with the aim of improving the transparency and replicability of eye-tracking research in communication science.
Chemically-resolved aerosol eddy covariance flux measurements in urban Mexico City during MILAGRO 2006

As part of the MILAGRO 2006 field campaign, the exchange of atmospheric aerosols with the urban land- scape was measured from a tall tower erected in a heav- ily populated neighborhood of Mexico City. Urban submi- cron aerosol fluxes were measured using an eddy covari- ance method with a quadrupole aerosol mass spectrometer during a two week period in March, 2006. Nitrate and am- monium aerosol concentrations were elevated at this loca- tion near the city center compared to measurements at other urban sites. Significant downward fluxes of nitrate aerosol, averaging 0.2 µg m 2 s 1 , were measured during daytime. The urban surface was not a significant source of sulfate aerosols. The measurements also showed that primary or- ganic aerosol fluxes, approximated by hydrocarbon-like or- ganic aerosols (HOA), displayed diurnal patterns similar to CO2 fluxes and anthropogenic urban activities. Overall, 47 % of submicron organic aerosol emissions were HOA, 35 % were oxygenated (OOA) and 18 % were associated with biomass burning (BBOA). Organic aerosol fluxes were bi- directional, but on average HOA fluxes were 0.1 µg m 2 s 1 , OOA fluxes were 0.03 µg m 2 s 1 , and BBOA fluxes were 0.03 µg m 2 s 1 . After accounting for size differences (PM1 vs PM2.5) and using an estimate of the black carbon component, comparison of the flux measurements with the 2006 gridded emissions inventory of Mexico City, showed that the daily-averaged total PM emission rates were essen- tially identical for the emission inventory and the flux mea- surements. However, the emission inventory included dust and metal particulate contributions, which were not included in the flux measurements. As a result, it appears that the in- ventory underestimates overall PM emissions for this loca- tion.
DBRIS at ImageCLEF 2012 Photo Annotation Task

For our participation in the ImageCLEF 2012 Photo Annotation Task we develope an image annotation system and test several combinations of SIFT-based descriptors with bow-based image representations. Our focus is on the comparison of two image representation types which include spatial layout: the spatial pyramids and the visual phrases. The experiments on the training and test set show that image representations based on visual phrases significantly outperform spatial pyramids.