Miracle-dz/UniFAR-FTUs huggingface dataset:
Template‐based modeling and free modeling by I‐TASSER in CASP7

We developed and tested the I‐TASSER protein structure prediction algorithm in the CASP7 experiment, where targets are first threaded through the PDB library and continuous fragments in the threading alignments are exploited to assemble the global structure. The final models are obtained from the progressive refinements started from the last round structure clusters. A majority of the targets in the template‐based modeling (TBM) category have the templates drawn closer to the native structure by more than 1 Å within the aligned regions. For the free‐modeling (FM) targets, I‐TASSER builds correct topology for 7/19 cases with sequence up to 155 residues long. For the first time, the automated server prediction generates models as good as the human‐expert does in all the categories, which shows the robustness of the method and the potential of the application to genome‐wide structure prediction. Despite the success, the accuracy of I‐TASSER modeling is still dominated by the similarity of the template and target structures with a strong correlation coefficient (∼0.9) between the root‐mean‐squared deviation (RMSD) to native of the templates and the final models. Especially, there is no high‐resolution model below 2 Å for the FM targets. These problems highlight the issues that need to be addressed in the next generation of atomic‐level I‐TASSER development especially for the FM target modeling. Proteins 2007. © 2007 Wiley‐Liss, Inc.
1 Systems Biology : Toward System-levelUnderstanding of Biological Systems

Systems biology is a new field in biology that aims at system-level understanding of biological systems. While molecular biology has led to remarkable progress in our understanding of biological systems, the current focus is mainly on identification of genes and functions of their products which are components of the system. The next major challenge is to understand at the system level biological systems that are composed of components revealed by molecular biology. This is not the first attempt at system-level understanding, since it is a recurrent theme in the scientific community. Nevertheless, it is the first time that we may be able to understand biological systems grounded in the molecular level as a consistent framework of knowledge. Now is a golden opportunity to uncover the essential principles of biological systems and applications backed up by indepth understanding of system behaviors. In order to grasp this opportunity, it is essential to establish methodologies and techniques to enable us to understand biological systems in their entirety by investigating: (1) the structure of the systems, such as genes, metabolism, and signal transduction networks and physical structures, (2) the dynamics of such systems, (3) methods to control systems, and (4) methods to design and modify systems for desired properties. This chapter gives an overview of the field of systems biology that will provide a system-level understanding of life.
The therapeutic effects of music in children following cardiac surgery.

OBJECTIVE To investigate, both objectively and subjectively, the effect of music on children in a pediatric cardiac intensive care unit following heart surgery, in conjunction with standard care. METHODS Randomized clinical trial with placebo, assessing 84 children, aged 1 day to 16 years, during the first 24 hours of the postoperative period, given a 30 minute music therapy session with classical music and observed at the start and end of the session, recording heart rate, blood pressure, mean blood pressure, respiratory rate, temperature and oxygen saturation, plus a facial pain score. Statistical significance was set at 5%. RESULTS Five of the initial 84 patients (5.9%) refused to participate. The most common type of heart disease was acyanotic congenital with left-right shunt (41% of cases: 44.4% of controls). Statistically significant differences were observed between the two groups after the intervention in the subjective facial pain scale and the objective parameters heart rate and respiratory rate (p < 0.001, p = 0.04 and p = 0.02, respectively). CONCLUSIONS A beneficial effect from music was observed with children during the postoperative period of heart surgery, by means of certain vital signs (heart rate and respiratory rate) and in reduced pain (facial pain scale). Nevertheless, there are gaps to be filled in this area, and studies in greater depth are needed.
Behavioral Analyses of Sugar Processing in Choice, Feeding, and Learning in Larval Drosophila

Gustatory stimuli have at least 2 kinds of function: They can support immediate, reflexive responses (such as substrate choice and feeding) and they can drive internal reinforcement. We provide behavioral analyses of these functions with respect to sweet taste in larval Drosophila. The idea is to use the dose–effect characteristics as behavioral “fingerprints” to dissociate reflexive and reinforcing functions. For glucose and trehalose, we uncover relatively weak preference. In contrast, for fructose and sucrose, preference responses are strong and the effects on feeding pronounced. Specifically, larvae are attracted to, and feeding is stimulated most strongly for, intermediate concentrations of either sugar: Using very high concentrations (4 M) results in weakened preference and suppression of feeding. In contrast to such an optimum function regarding choice and feeding, an asymptotic dose–effect function is found for reinforcement learning: Learning scores reach asymptote at 2 M and remain stable for a 4-M concentration. A similar parametric discrepancy between the reflexive (choice and feeding) and reinforcing function is also seen for sodium chloride (Niewalda T, Singhal S, Fiala A, Saumweber T, Wegener S, Gerber B, in preparation). We discuss whether these discrepancies are based either on inhibition from high-osmolarity sensors upon specifically the reflexive pathways or whether different sensory pathways, with different effective dose–response characteristics, may have preferential access to drive either reflex responses or modulatory neurons mediating internal reinforcement, respectively.
Multivariable GA-Based Identification of TS Fuzzy Models: MIMO Distillation Column Model Case Study

In this paper, a nonlinear fuzzy identification approach based on genetic algorithm (GA) and Takagi-Sugeno (TS) fuzzy system is presented for fuzzy modeling of a multi-input, multi-output (MIMO) dynamical system. In this approach, GA is used for tuning the parameters of the membership functions of the antecedent parts of IF-THEN rules and Recursive Least-Squares (RLS) algorithm is employed for parameter estimation of the consequent linear sub-model parts of the TS fuzzy rules. The presented method is implemented on a simulated nonlinear MIMO distillation column. The results show that the presented method gives a more accurate model in comparison with the conventional TS fuzzy identification approach.
Evaluating, Comparing and Combining Density Forecasts Using the Klic with an Application to the Bank of England and Niesr 'Fan' Charts of Inflation

This paper proposes and analyses the Kullback–Leibler information criterion (KLIC) as a unified statistical tool to evaluate, compare and combine density forecasts. Use of the KLIC is particularly attractive, as well as operationally convenient, given its equivalence with the widely used Berkowitz likelihood ratio test for the evaluation of individual density forecasts that exploits the probability integral transforms. Parallels with the comparison and combination of point forecasts are made. This and related Monte Carlo experiments help draw out properties of combined density forecasts. We illustrate the uses of the KLIC in an application to two widely used published density forecasts for UK inflation, namely the Bank of England and NIESR ‘fan’ charts.
Carcinoma-Associated Fibroblasts Are a Promising Therapeutic Target

Human carcinomas frequently exhibit significant stromal reactions such as the so-called “desmoplastic stroma” or “reactive stroma”, which is characterised by the existence of large numbers of stromal cells and extracellular matrix proteins. Carcinoma-associated fibroblasts (CAFs), which are rich in activated fibroblast populations exemplified by myofibroblasts, are among the predominant cell types present within the tumour-associated stroma. Increased numbers of stromal myofibroblasts are often associated with high-grade malignancies with poor prognoses in humans. CAF myofibroblasts possess abilities to promote primary tumour development, growth and progression by stimulating the processes of neoangiogenesis as well as tumour cell proliferation, survival, migration and invasion. Moreover, it has been demonstrated that CAFs serve as a niche supporting the metastatic colonisation of disseminated carcinoma cells in distant organs. Their contribution to primary and secondary malignancies makes these fibroblasts a potential therapeutic target and they also appear to be relevant to the development of drug resistance and tumour recurrence. This review summarises our current knowledge of tumour-promoting CAFs and discusses the therapeutic feasibility of targeting these cells as well as disrupting heterotypic interactions with other cell types in tumours that may improve the efficacy of current anti-tumour therapies.
Faster Algorithms Parameterized by Clique-width

Many NP-hard problems, such as Dominating Set, are FPT parameterized by clique-width. For graphs of clique-width k given with a kexpression, Dominating Set can be solved in 4knO(1) time. However, no FPT algorithm is known for computing an optimal k-expression. For a graph of clique-width k, if we rely on known algorithms to compute a (23k − 1)expression via rank-width and then solving Dominating Set using the (23k − 1)-expression, the above algorithm will only give a runtime of 42 3k nO(1). There have been results which overcome this exponential jump; the best known algorithm can solve Dominating Set in time 2O(k 2)nO(1) by avoiding constructing a k-expression [Bui-Xuan, Telle, and Vatshelle. Fast dynamic programming for locally checkable vertex subset and vertex partitioning problems. Theoret. Comput. Sci., 2013. doi: 10.1016/j.tcs. 2013.01. 009]. We improve this to 2O(k log k)nO(1). Indeed, we show that for a graph of clique-width k, a large class of domination and partitioning problems (LC-VSP), including Dominating Set, can be solved in 2O(k log k)nO(1). Our main tool is a variant of rank-width using the rank of a 0-1 matrix over the rational field instead of the binary field.
Dynamics of Populations of Integrate-and-Fire Neurons, Partial Synchronization and Memory

We study the dynamics of completely connected populations of refractory integrate-and-fire neurons in the presence of noise. Solving the master equation based on a mean-field approach, and by computer simulations, we find sustained states of activity that correspond to fixed points and show that for the same value of external input, the system has one or two attractors. The dynamic behavior of the population under the influence of external input and noise manifests hysteresis effects that might have a functional role for memory. The temporal dynamics at higher temporal resolution, finer than the transmission delay times and the refractory period, are characterized by synchronized activity of subpopulations. The global activity of the population shows aperiodic oscillations analogous to experimentally found field potentials.
Towards a model for estimating image difficulty in X-ray screening

In this study, we developed a first computational model for estimating image difficulty of X-ray images of passenger bags. Based on Schwaninger (2003) three image-based factors are proposed as predictors of image difficulty; view difficulty of the threat item, superposition by other objects, and bag complexity (i.e. clutter and transparency of the bag). First, these factors were validated using detection experiments. We then developed computer-based algorithms to estimate the image-based factors automatically. Finally, we could show that our computational model can better explain human performance than human ratings of the image-based factors
An optimal power flow (OPF) method with improved power system stability

This paper proposes an optimal power flow (OPF) method taking into account small signal stability as additional constraints. Particle swarm optimization (PSO) algorithm is adopted to realize the OPF process. The method is programmed in MATLAB and implemented to a nine-bus test power system which has large-scale wind power integration. The results show the ability of the proposed method to find optimal (or near-optimal) operating points in different cases. Based on these results, the analysis of the impacts of wind power integration on the system small signal stability has been conducted.
DETERMINATION OF INHIBITION IN THE ENZYMATIC HYDROLYSIS OF CELLOBIOSE USING HYBRID NEURAL MODELING

Neural networks and hybrid models were used to study substrate and product inhibition observed in the enzymatic hydrolysis of cellobiose at 40oC, 50oC and 55oC, pH 4.8, using cellobiose solutions with or without the addition of exogenous glucose. Firstly, the initial velocity method and nonlinear fitting with StatisticaO were used to determine the kinetic parameters for either the uncompetitive or the competitive substrate inhibition model at a negligible product concentration and cellobiose from 0.4 to 2.0 g/L. Secondly, for six different models of substrate and product inhibitions and data for low to high cellobiose conversions in a batch reactor, neural networks were used for fitting the product inhibition parameter to the mass balance equations derived for each model. The two models found to be best were: 1) noncompetitive inhibition by substrate and competitive by product and 2) uncompetitive inhibition by substrate and competitive by product; however, these models correlation coefficients were quite close. To distinguish between them, hybrid models consisting of neural networks and first principle equations were used to select the best inhibition model based on the smallest norm observed, and the model with noncompetitive inhibition by substrate and competitive inhibition by product was shown to be the best predictor of cellobiose hydrolysis reactor behavior.
Knowledge Sharing Interactions in Collaborative Software Maintenance Environment

In collaborative Software Maintenance (SM) environment, knowledge sharing is vital to ensure various parties have the necessary information to perform SM tasks. However, patterns of knowledge sharing interactions within the networked organization of SM Community of Practice (CoP) and factors that influence these interactions are yet to be established. We study the dialogues captured in the Software Configuration Management (SCM) tool used by a global SM organization and use Pajek, a Social Network Analysis (SNA) tool, to map the interactions among users and maintenance personnel. The results revealed technical, planning and domain information as most shared information. Network bottlenecks are also identified, which evolves around a key development manager, a development team leader and a systems analyst. Also, there are lack of direct interactions between programmers and domain knowledge providers. As such, the SM environment could benefit from process automations on selected tasks of the above bottleneck areas to ensure knowledge are shared across the board.
The Bacterial Actin MamK

Background: The bacterial actin MamK is involved in the organization of bacterial organelles called magnetosomes. Results: MamK is an ATPase and assembles into filaments with a unique architecture. Conclusion: MamK shares features of structure and assembly with other bacterial actin homologs, and it has some unique features of its own. Significance: This work will guide future studies to unravel molecular mechanisms underlying MamK function in vivo. It is now recognized that actin-like proteins are widespread in bacteria and, in contrast to eukaryotic actins, are highly diverse in sequence and function. The bacterial actin, MamK, represents a clade, primarily found in magnetotactic bacteria, that is involved in the proper organization of subcellular organelles, termed magnetosomes. We have previously shown that MamK from Magnetospirillum magneticum AMB-1 (AMB-1) forms dynamic filaments in vivo. To gain further insights into the molecular mechanisms that underlie MamK dynamics and function, we have now studied the in vitro properties of MamK. We demonstrate that MamK is an ATPase that, in the presence of ATP, assembles rapidly into filaments that disassemble once ATP is depleted. The mutation of a conserved active site residue (E143A) abolishes ATPase activity of MamK but not its ability to form filaments. Filament disassembly depends on both ATPase activity and potassium levels, the latter of which results in the organization of MamK filaments into bundles. These data are consistent with observations indicating that accessory factors are required to promote filament disassembly and for spatial organization of filaments in vivo. We also used cryo-electron microscopy to obtain a high resolution structure of MamK filaments. MamK adopts a two-stranded helical filament architecture, but unlike eukaryotic actin and other actin-like filaments, subunits in MamK strands are unstaggered giving rise to a unique filament architecture. Beyond extending our knowledge of the properties and function of MamK in magnetotactic bacteria, this study emphasizes the functional and structural diversity of bacterial actins in general.
Mechanical characterization of totally optical tactile sensor oriented on bio-applications

A new class of optical pressure sensors in a robot tactile sensing system based on PDMS (Polydimethylsiloxane) is presented. The sensor consists of a tapered optical fiber, where optical signal goes across, embedded into a PDMS-gold nanocomposite material. By applying different pressure forces onto the PDMS-based nanocomposite, changes of the optical transmittivity of the fiber can be detected in real time due to the coupling between the gold nanocomposite material and the tapered fiber region. The intensity reduction of the transmitted light is correlated to the pressure force magnitude. A sensitivity in the order of 5 grams is checked. As preliminary results, the sensor is efficiently used for detecting small notches on a beam. The experimental results are very encouraging for foreseeing successful use of this new sensor in medical robotic applications especially for sensing system to measure tactile information such as softness and smoothness of biological tissues.
P-RPF: Pixel-Based Random Parameter Filtering for Monte Carlo Rendering

In this paper we propose Pixel-based Random Parameter Filtering (P-RPF) for efficiently denoising images generated from complex illuminations with a high sample count. We design various operations of our method to have time complexity that is independent from the number of samples per pixel. We compute feature weights by measuring the functional relationships between MC inputs and output in a sample basis. To accelerate this sample-basis process we propose to use an up sampling method for feature weights. We have applied our method to a wide variety of models with different rendering effects. Our method runs significantly faster than the original RPF, while maintaining visually pleasing and numerically similar results. As a result, our method shows more visually pleasing and numerically better results than RPF in an equal-time comparison.
Parameter estimation in enzyme-kinetics with consideration of heteroscedasticity and low dose data

In this paper we propose a simulation study in order to discuss four statistical models dealing with the problem of parameter estimation in enzyme-kinetics. The pseudo-maximumlikelihood estimators for the transform-both-sides-model and the weighted TBS-model are compared with least-square-estimators of the classical nonlinear regression model and the linearized Eadie-Hofstee-plot. Due to heteroscedasticity of enzyme-kinetic data in low dose experiments the proposed estimators are investigated.
The dynamics of subduction and trench migration for viscosity stratification

SUMMARY Although subduction plays a dominant role in plate tectonics, related processes such as trench migration are not well understood. We investigate the influence of viscosity stratification and different flow boundary conditions on the trench migration dynamics of a subducting lithosphere in a 2-D model using a finite-difference code. Subduction and mantle flow are driven by a compositionally prescribed density contrast between the high-viscosity slab and the ambient mantle; no overriding plate is assumed. The model rheology is viscoplastic at shallow, and viscous at greater depth; the mantle is stratified with a higher viscosity in the lower part of the computational domain. The plastic rheology allows the plate to decouple from the top of the box and is described by a simplified friction law to mimic the brittle deformation of the shallow lithosphere. The flow patterns and slab morphologies differ as a function of the velocity boundary conditions (BCs). For reflective BCs, we model either a plate which is fixed on the box side or a plate that can freely move. A slab with periodic BCs is always laterally free. We find that, when the slabs interact with the highly viscous lower mantle, the slab with reflective BCs is more folded than the periodic one, due to the confinement of mantle flow around the slab. In general, the trench is observed to roll back toward the oceanic plate. For free slabs with reflective BCs the trench retreat velocity deceases after the interaction with the lower mantle. In contrast, for the free slab with periodic BCs it is nearly constant or even increases with time if described in a reference frame fixed to the lower mantle. The free slab with periodic BCs exerts a force on the lower mantle, which causes a net differential flow between the upper and lower mantle. We also carried out additional experiments with different mechanical slab properties and thicknesses. Stiffer, free slabs subduct more steeply and are able to penetrate straight into the lower mantle. After penetration into the lower mantle the trench moves toward the continent. Thinner slabs deform more easily and are folded for all boundary conditions. We can generalize the rollback systematics for free slabs by normalizing trench velocities by the plate speed. Free slabs, being more representative of the West Pacific subduction zones, show large temporal variations of normalized trench velocities ranging between a retreat value of 1.0 to an advancing value of −0.3.