Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploratory Visualization for Weather Data Verification

Today weather forecasts assist in the preparation of roads during the winter season to avoid accidents resulting from snow, rain and slipperiness. As with any weather forecast there is always a search for improvement. One way to do this is by verifying the forecasted parameters with the actual weather observed in the forecasted area. To facilitate identification of significant trends and patterns within weather data we have developed an application based on interactive information visualization techniques. The application was created in close collaboration with domain experts from the Swedish Meteorological and Hydrological Institute and initial feedback from a performed user study shows that interactive visualization speeds up the analysis process as well as increases flexibility compared to currently used manual methods.
Microsoft Word - predicting NMR parameters

The spectral parameters of the nuclear magnetic resonance (NMR) spectra are dependent on the chemical environment around the nuclei, making NMR spectroscopy a powerful method for studying molecular structure and dynamics at the atomic level. Conversely, the spectral parameters can be calculated if one knows the molecular structure. The spectral parameter prediction plays a key role in many applications of computational NMR. This thesis presents two NMR parameter prediction approaches for two different purposes. Chemical shifts are the key parameters of the NMR spectrum. In the field of protein NMR, the use of chemical shifts in protein structural studies has been increasing in the last years, driven by improvements in the chemical shift prediction methods. In addition to the protein structure, chemical shifts are dependent on protein dynamics. In order to account for the dynamic effects, a four-dimensional approach for protein chemical shift prediction was developed. Here, the 4th dimension is time and it is mapped by molecular dynamics simulations. The conformational space was further expanded by starting the MD simulations from different conformations of the same protein. From the structural parameters averaged over the conformational space of the MD simulations, chemical shifts prediction models for all backbone and most side chain nuclei were built with principal component regression. In comparison with the non-dynamic models, the dynamic models achieved 13 % lower root-mean-square (RMS) errors for different backbone nuclei, underlining the importance of dynamics in reproducing experimental protein chemical shifts. An additional outcome of the project is the prediction program 4DSPOT, which is freely available for the protein NMR community (www.uef.fi/4dspot). NMR spectra can be simulated and iteratively analyzed with quantum mechanical principles if the parameters are known. The scalar coupling constants are the parameters that give rise to the fine structure of the NMR signals. The second prediction method presented in this thesis targets small molecule couplings to be used in automatic spectrum analysis. Coverage and speed are emphasized in the design of the method. Thus, the method is based on a lightweight hash dictionary search, followed by a k Nearest Neighbors regression to resolve the substituent and conformational dependencies. Despite the growth of databases, there are still many situations when experimental data is too sparse to permit prediction model building. However, recently the accuracy of quantum-mechanical calculation of NMR parameters has greatly improved. Therefore, the use of quantum chemistry as a source of teaching data is discussed and some preliminary results are shown. National Library of Medicine Classification: QU 25 Medical Subject Headings: Nuclear Magnetic Resonance, Biomolecular; Spectrum Analysis; Molecular Conformation; Proteins; Molecular Dynamics Simulation Library of Congress Subject Headings: Nuclear magnetic resonance spectroscopy; Proteins Structure
Cytolytic T cell granules. Isolation, structural, biochemical, and functional characterization

The cytoplasmic, dense granules of cloned T cell lines were isolated and analyzed for their functional and biochemical properties. Isolated granules of approximately 90% homogeneity, in the presence of Ca, effect strong tumoricidal and hemolytic activity. Tumor cell lysis is complete in less than 30 min, with less than 2 micrograms granule protein corresponding to a killer/target ratio of 3-6:1 by assuming 50% yield for granule isolation. The granules contain a set of unique proteins, responsible for cytolytic activity and designated K1 to K6, in the molecular weight range of 14,000 to 75,000, as defined by sodium dodecyl sulfate (SDS) polyacrylamide slab gel analysis under reducing and nonreducing conditions. Cytolysis mediated by isolated granules is accompanied by the assembly of tubular complexes of 160 A (poly P1) and of approximately 70 A width (poly P2) that are inserted into membranes and form ultrastructural membrane lesions. As shown by immunofluorescence and by Percoll gradient fractionation, cytolytic granules are detected in cells of cytolytic T cell lineage and not in the T cell lymphomas E14 and S194. Poly perforin 1 assembled by CTLL-2 upon stimulation with concanavalin A (Con A) and phorbol myristate acetate (PMA) was isolated by detergent extraction and gel filtration. Poly P1 is composed of disulfide-linked subunits that, after reduction, co-migrate with certain granule proteins. The results are compatible with the hypothesis that the dense granules of cytolytic T cells contain cytolytic proteins that polymerize to disulfide-linked tubular poly perforins in a Ca-dependent reaction and may cause cytolysis by membrane insertion and transmembrane channel formation.
Apoptosis Effect of Girinimbine Isolated from Murraya koenigii on Lung Cancer Cells In Vitro

Murraya koenigii Spreng has been traditionally claimed as a remedy for cancer. The current study investigated the anticancer effects of girinimbine, a carbazole alkaloid isolated from Murraya koenigii Spreng, on A549 lung cancer cells in relation to apoptotic mechanistic pathway. Girinimbine was isolated from Murraya koenigii Spreng. The antiproliferative activity was assayed using MTT and the apoptosis detection was done by annexin V and lysosomal stability assays. Multiparameter cytotoxicity assays were performed to investigate the change in mitochondrial membrane potential and cytochrome c translocation. ROS, caspase, and human apoptosis proteome profiler assays were done to investigate the apoptotic mechanism of cell death. The MTT assay revealed that the girinimbine induces cell death with an IC50 of 19.01 μM. A significant induction of early phase of apoptosis was shown by annexin V and lysosomal stability assays. After 24 h treatment with 19.01 μM of girinimbine, decrease in the nuclear area and increase in mitochondrial membrane potential and plasma membrane permeability were readily visible. Moreover the translocation of cytochrome c also was observed. Girinimbine mediates its antiproliferative and apoptotic effects through up- and downregulation of apoptotic and antiapoptotic proteins. There was a significant involvement of both intrinsic and extrinsic pathways. Moreover, the upregulation of p53 as well as the cell proliferation repressor proteins, p27 and p21, and the significant role of insulin/IGF-1 signaling were also identified. Moreover the caspases 3 and 8 were found to be significantly activated. Our results taken together indicated that girinimbine may be a potential agent for anticancer drug development.
Digital Restoration of the Cultural Heritages

Historical objects were often destroyed and tainted with the design from other periods. Computer graphics is widely applied to visualize the historical object in its original form. However, Visualization by 3D models requires much time and great skill. In addition the conventional methods for CAD fail to provide realism into their models. In this paper, we propose the method to easily create 3D models with the realistic touch. Realistic models are obtained by laser scanning the real object. The models are then manipulated to their original forms. Our method easily reconstructed the original shape of the Great Buddha and the main hall of Todaiji Temple(Nara, Japan).
Adaptive facial behaviour using selected methods in machine learning and motor control

In the not so distant future, androids may be part of our everyday lifestyle. There can be a desire not only to make these android do our work, but also to enable communication with humans in a natural way. As a substantial part of human communication is through our body language, natural mimic is essential if arti cial communication is to seem real. Even though this might appear like a trivial problem, there are a lot of obstacles to solve. To achieve physical human appearance, we have to develop arti cial skin that looks and folds naturally. This is far from an easy task, as living tissue has totally di erent characteristics from synthetic materials. Secondly we need some form of arti cial actuators, preferably situated in or behind the synthetic skin. Human muscles have some amazing properties that we are not able to match yet. They are silent, strong, exible, and precise, and last for millions of cycles. At last there is a need for a sensory system of some sort. Humans has an extremely advanced feedback system, providing information about factor such as pressure, temperature, pain etc. This feedback enables humans to make advanced decisions about their surroundings, and adjust their appearance accordingly. Even though all these factors were in place, natural mimic wouldn't be achieved before the android developed adaptive behaviour of its face expressions. A robot could of course be pre-programmed with a xed set of face expressions, but this would undoubtedly restrict the personi cation of such an android. In order to achieve natural mimic and the impression of personality, its essential to make the androids facial expressions adaptive and to make the android learn and create face expressions never shown before. This master thesis addresses some parts of the problem of achieving adaptive facial behaviour, essential for making androids operate in social settings, and obtaining natural communication with humans.
A distributed algorithm for solving a class of multi-agent Markov decision problems

This paper considers a class of infinite horizon Markov decision processes (MDPs) with multiple decision makers, called agents, and a general joint reward structure, but a special decomposable state/action structure such that each individual agent's actions affect the system's state transitions independently from the actions of all other agents. We introduce the concept of "localization," where each agent need only consider a "local" MDP defined on its own state and action spaces. Based on this localization concept, we propose an iterative distributed algorithm that emulates gradient ascent and which converges to a locally optimal solution for the average reward case. The solution is an "autonomous" joint policy such that each agent's action is based on only its local state.
Contrasting space-time schemes for MIMO FSO systems with non-coherent modulation

For the case of multiple-input multiple-output (MIMO) free-space optical (FSO) communication systems, we consider the suitability of the spatial multiplexing scheme when on-off keying modulation is employed. We show that, even with the optimal maximum likelihood detection at the receiver, the performance is worse, compared to the case of repetition coding (RC) under the condition of equal transmission rate. This confirms the quasi-optimality of the RC scheme for MIMO FSO systems.
Enhancing Cognitive Abilities with Comprehensive Training: A Large, Online, Randomized, Active-Controlled Trial

Background A variety of studies have demonstrated gains in cognitive ability following cognitive training interventions. However, other studies have not shown such gains, and questions remain regarding the efficacy of specific cognitive training interventions. Cognitive training research often involves programs made up of just one or a few exercises, targeting limited and specific cognitive endpoints. In addition, cognitive training studies typically involve small samples that may be insufficient for reliable measurement of change. Other studies have utilized training periods that were too short to generate reliable gains in cognitive performance. Methods The present study evaluated an online cognitive training program comprised of 49 exercises targeting a variety of cognitive capacities. The cognitive training program was compared to an active control condition in which participants completed crossword puzzles. All participants were recruited, trained, and tested online (N = 4,715 fully evaluable participants). Participants in both groups were instructed to complete one approximately 15-minute session at least 5 days per week for 10 weeks. Results Participants randomly assigned to the treatment group improved significantly more on the primary outcome measure, an aggregate measure of neuropsychological performance, than did the active control group (Cohen’s d effect size = 0.255; 95% confidence interval = [0.198, 0.312]). Treatment participants showed greater improvements than controls on speed of processing, short-term memory, working memory, problem solving, and fluid reasoning assessments. Participants in the treatment group also showed greater improvements on self-reported measures of cognitive functioning, particularly on those items related to concentration compared to the control group (Cohen’s d = 0.249; 95% confidence interval = [0.191, 0.306]). Conclusion Taken together, these results indicate that a varied training program composed of a number of tasks targeted to different cognitive functions can show transfer to a wide range of untrained measures of cognitive performance. Trial Registration ClinicalTrials.gov NCT-02367898
Management of Temporal Constraints for Factory Scheduling

Abstract : This paper, presents constraint propagation techniques used in the OPIS scheduling system to update schedule descriptions and detect introduced inconsistencies. This approach is summarized as follows: 1) a hierarchical model is used to represent resources and operations to be performed. Schedules are developed and maintained at different levels of precision which are explicitly associated with resources and operations; constraint propagation is correspondingly performed at different levels, 2) Various scheduling constraints are attached to resources and operations, and combined to derive time bound constraints. A description of the original constraints that collectively impose a bound is explicitly recorded, 3) Time bound constraints are maintained by an object-oriented propagation process: through messages, resources and operations communicate constraints and cooperate to compute time bounds, and 4) When time bounds are inconsistent, their origins provide the information required to construct an appropriate description of the conflicting situation. This description provides OPIS with information needed to make reactive decisions.
THE EFFECTS OF THE IONIZING RADIATION BACKGROUND ON GALAXY EVOLUTION

We find that the amount and nature of the assumed ionizing background can strongly affect galaxy formation and evolution. Galaxy evolution simulations typically incorporate an ultraviolet background which falls off rapidly above z = 3; e.g., that of Haardt & Madau. However, this decline may be too steep to fit the Wilkinson Microwave Anistropy Probe constraints on electron scattering optical depth or observations of intermediate redshift (z ∼ 2–4) Lyα forest transmission. As an alternative, we present simulations of the cosmological formation of individual galaxies with UV backgrounds that decline more slowly at high redshift: both a simple intensity rescaling and the background recently derived by Faucher-Giguère, which softens the spectrum at higher redshifts. We also test an approximation of the X-ray background with a similar z dependence. We find for the test galaxies that an increase in either the intensity or hardness of ionizing radiation generically pushes star formation toward lower redshifts: although overall star formation in the simulation boxes is reduced by 10%–25%, the galaxies show a factor of ∼2 increase in the fraction of stars within a 30 kpc radius that are formed after z = 1. Other effects include late gas inflows enhanced up to 30 times, stellar half-mass radii decreased by up to 30%, central velocity dispersions increased up to 40%, and a strong reduction in substructure. The magnitude of the effects depends on the environmental/accretion properties of the particular galaxy.
Parameter identification of plant growth models with stochastic development

Plant architectures generally display structural variations among individuals. Stochastic FSPMs have been developed to capture such feature, but calibrating such models is a challenging issue. For GreenLab model, parameter identification has been achieved on several crops and trees, but the estimation of functional parameters is mostly limited to plants with deterministic development. In this work, we propose a methodological framework allowing the efficient FSPM parameter estimation for stochastic ramified plants. We focus on the randomness in three kinds of meristem activities in plant development: growth, death and branching. Concepts of organic series and potential structure are introduced to build the fitting target as well as corresponding model output. We show that, with a limited set of sampled plants (here from simulation), using a few organic series, the inverse method retrieves well the parameter values (the original parameter set being known here). Requiring the concept of physiological age and the assumption of common biomass pool, the proposed approach provides a solution of solving source-sink functions of complex plant architectures, with a novel simplified way of plant sampling. The proposed parameter estimation frame is promising, since this in silico process mimics the procedure of calibrating model for real plants in a stand. Estimating parameters on stochastic plant architectures opens a new range of coming applications.
Search and the Strategic Formation of Large Networks : When and Why do We See Power Laws and Small Worlds ?

Network structures play a central role in determining outcomes in many important situations. Examples include the world wide web, joint research venture projects among firms, co-author relationships among academics, political alliances, trade networks, the organization of intra-firm management, social networks for transmitting information, and P2P systems for file sharing. Given the large and increasing prevalence of such applications, it is necessary to understand the properties of these networks as these have implications for both individual incentives and collective welfare. Previous research has identified several empirical regularities shared by networks in many of these diverse applications. We concentrate on three reasonably robust and prominent empirical characteristics of large networks that have been observed in a variety of settings.
Dimensioning the packet loss burstiness over wireless channels: a novel metric, its analysis and application

The packet loss burstiness over wireless channels is commonly acknowledged as a key impacting factor on the performance of networking protocols. An accurate evaluation of the packet loss burstiness, which reveals the characteristics and performance of the wireless channels, is crucial to the design of wireless systems and the quality-of-service provisioning to end users. In this paper, a simple yet accurate analytical framework is developed to dimension the packet loss burstiness over generic wireless channels. In specific, we first propose a novel and effective metric to characterize the packet loss burstiness, which is shown to be more compact, effective, and accurate than the metrics proposed in existing literature for the same purpose. With this metric, we then develop an analytical framework and derive the closed-form solutions of the packet loss performance, including the packet loss rate and the loss-burst/loss-gap length distributions. Lastly, as an example to show how the derived results can be applied to the design of wireless systems, we apply the analytical results to devise an adaptive packetization scheme. The proposed packetization scheme adaptively adjusts the packet length of transmissions based on the prediction of the packet loss rate and loss-burst/loss-gap lengths of the wireless channel. Via extensive simulations, we show that with the proposed packetization scheme, the channel throughput can be enhanced by more than 10% than the traditional scheme.Copyright © 2012 John Wiley & Sons, Ltd.
Interface usage measurements in a user interface management system

User Interface Management Systems have provided support for most user interface design personnel with the exception of dialogue evaluators. Potential support that a UIMS can provide to evaluators of user interfaces generated by the UIMS are discussed. Metrics for measuring interactive behavior have been implemented as part of a User Interface Management System. It is shown how the external control and separate dialogue description features of UIMSs make possible such measurements. These metrics are automatically mapped back to the responsible portions of the dialogue description. Reports are generated which aid interface evaluators in locating specific problems in a user interface design.
A theoretical analysis of feedback flow control

Congestion is a longstanding problem in datagram networks. One congestion avoidance technique is feedback flow control, in which sources adjust their transmission rate in response to congestion signals sent (implicitly or explicitly) by network gateways. The goal is to design flow control algorithms which provide time-scale invariant, fair, stable, and robust performance. In this paper we introduce a simple model of feedback flow control, in which sources make synchronous rate adjustments based on the congestion signals and other local information, and apply it to a network of Poisson sources and exponential servers. We investigate two different styles of feedback, aggregate and individual, and two different gateway service disciplines, FIFO and Fair Share. The purpose of this paper is to identify, in the context of our simple model, which flow control design choices allow us to achieve our performance goals. Aggregate feedback flow control, in which congestion signals reflect only the aggregate congestion at the gateways, can provide time-scale invariant and stable performance, but not fair or robust performance. The properties of individual feedback flow control, in which the congestion signals reflect the congestion caused by the individual source, depend on the service discipline used in the gateways. Individual feedback with FIFO gateways can provide time-scale invariant, fair, and stable performance, but not robust performance. Individual feedback with Fair Share gateways can achieve all four performance goals. Furthermore, its stability properties are superior to those of the other two design choices. By making robust and more stable performance possible, gateway service disciplines play a crucial role in realizing effective flow control.