Miracle-dz/UniFAR-FTUs huggingface dataset:
Cloning, sequence analysis, and hyperexpression of the genes encoding phosphotransacetylase and acetate kinase from Methanosarcina thermophila

The genes for the acetate-activating enzymes, acetate kinase and phosphotransacetylase (ack and pta), from Methanosarcina thermophila TM-1 were cloned and sequenced. Both genes are present in only one copy per genome, with the pta gene adjacent to and upstream of the ack gene. Consensus archaeal promoter sequences are found upstream of the pta coding region. The pta and ack genes encode predicted polypeptides with molecular masses of 35,198 and 44,482 Da, respectively. A hydropathy plot of the deduced phosphotransacetylase sequence indicates that it is a hydrophobic polypeptides; however, no membrane-spanning domains are evident. Comparison of the amino acid sequences deduced from the M. thermophila and Escherichia coli ack genes indicate similar subunit molecular weights and 44% identity (60% similarity). The comparison also revealed the presence of several conserved arginine, cysteine, and glutamic acid residues. Arginine, cysteine, and glutamic acid residues have previously been implicated at or near the active site of the E. coli acetate kinase. The pta and ack genes were hyperexpressed in E. coli, and the overproduced enzymes were purified to homogeneity with specific activities higher than those of the enzymes previously purified from M. thermophila. The overproduced phosphotransacetylase and acetate kinase migrated at molecular masses of 37,000 and 42,000 Da, respectively. The activity of the acetate kinase is optimal at 65 degrees C and is protected from thermal inactivation by ATP. Diethylpyrocarbonate and phenylglyoxal inhibited acetate kinase activity in a manner consistent with the presence of histidine and arginine residues at or near the active site; however, the thiol-directed reagents 5,5'-dithiobis (2-nitrobenzoic acid) and N-ethylmaleimide were ineffective.
Increased Biocompatibility and Bioactivity after Energetic PVD Surface Treatments

Ion implantation, a common technology in semiconductor processing, has been applied to biomaterials since the 1960s. Using energetic ion bombardment, a general term which includes conventional ion implantation plasma immersion ion implantation (PIII) and ion beam assisted thin film deposition, functionalization of surfaces is possible. By varying and adjusting the process parameters, several surface properties can be attuned simultaneously. Extensive research details improvements in the biocompatibility, mainly by reducing corrosion rates and increasing wear resistance after surface modification. Recently, enhanced bioactivity strongly correlated with the surface topography and less with the surface chemistry has been reported, with an increased roughness on the nanometer scale induced by self-organisation processes during ion bombardment leading to faster cellular adhesion processes.
Imaging under the edges of salt bodies: Analysis of an Elf North Sea dataset

Depth imaging techniques still face diculties under the edges of salt bodies. Elf encountered such a problem in a 3-D survey in the North Sea where they hoped to image a reector that lays beneath a salt body. Based on the 3-D data, Elf created 2-D synthetic model of the salt body and surrounding subsurface. By analyzing this synthetic model using Kircho depth migration and raytracing techniques, it became clear that the problem is largely due to poor illumination. The portion of the reector under the edge of the salt dome only received illumination from a limited range of osets. In addition to further analysis of both the synthetic and real datasets, investigations of possible solutions such as weighting appropriate osets, inversion and/or the use of common reection angle gathers seem warranted.
Minimum Mutual Information-Based Linearly Constrained Broadband Signal Extraction

In this contribution, the problem of broadband acoustic signal extraction is treated as a specific source separation problem, where the desired signal components are to be separated from all remaining undesired components. For this, we exploit the generic TRIple-N Independent component analysis for CONvolutive mixtures (TRINICON) framework. The TRINICON optimization criterion is complemented with linear constraints leading to the Linearly Constrained Minimum Mutual Information (LCMMI) criterion for desired signal extraction. A general linearly constrained update rule for iterative filter optimization is derived, which can efficiently be realized in a novel Minimum Mutual Information (MMI)-Generalized Sidelobe Canceler (GSC). The general treatment of the signal extraction problem using an MMI criterion provides several advantages: Firstly, new insights into the signal extraction problem can be derived by establishing links to both the original GSC and the Multichannel Wiener Filter (MWF). Secondly, by exploiting fundamental properties characteristic for speech and audio signals, complicated and often unreliable Voice Activity Detection (VAD)-based control mechanisms become unnecessary. Thirdly, the overall realization requires only prior information of the desired source position. An evaluation of the MMI-GSC for the double-talk situation with two concurrently active speech sources under reverberant and noisy conditions demonstrates the effectiveness of this novel approach.
Distortion minimization via adaptive digital and analog transmission for energy harvesting-based wireless sensor networks

This paper studies wireless sensor networks with energy harvesting in which a transmitter collects the observed source signals from the sensors and send to a fusion center using the energy harvested from an ambient environment. The main objective is to minimize the distortion between the source signal observed by the sensors and that recovered by the fusion center. We introduce a novel adaptive transmission approach in which the transmitter can use either analog or digital transmission according to the dynamics of the energy harvesting process. We formulate the optimization problem as a Markov decision process (MDP) and derive the optimal policy that can minimize the long-term discounted distortion for the fusion center. Numerical results show that our proposed approach can significantly improve the network performance under different situations.
Security Considerations on Processing of Geospatial Information in the Cloud

The strength of cloud computing is that it dramatically reduces the investment costs for users, required for processing high-volume geospatial data. But in order to have confidential or even classified geospatial data processed in the cloud, service level agreements must ensure the seamless protection of the data. This paper introduces standards for the implementation of security requirements applicable to cloud computing and discusses the concerns towards secure processing of information in the cloud.
Disinhibition Opens the Gate to Pathological Pain Signaling in Superficial Neurokinin 1 Receptor-Expressing Neurons in Rat Spinal Cord

Blockade of local spinal cord inhibition mimics the behavioral hypersensitivity that manifests in chronic pain states. This suggests that there is a pathway capable of mediating allodynia/hyperalgesia that exists but is normally under strong inhibitory control. Lamina I and III neurokinin 1 (NK1) receptor expressing (NK1R+) dorsal horn neurons, many of which are projection neurons, are required for the development of this hypersensitivity and are therefore likely to be a component of this proposed pathway. To investigate, whole-cell patch-clamp recordings were made from lamina I and III NK1R+ neurons in the spinal cord slice preparation with attached dorsal root. Excitatory postsynaptic currents were recorded in response to electrical stimulation of the dorsal root. Lamina I NK1R+ neurons were shown to receive high-threshold (Aδ/C fiber) monosynaptic input, whereas lamina III NK1R+ neurons received low-threshold (Aβ fiber) monosynaptic input. In contrast, lamina I neurons lacking NK1 receptor (NK1R−) received polysynaptic A fiber input. Blockade of local GABAergic and glycinergic inhibition with bicuculline (10 μm) and strychnine (300 nm), respectively, revealed significant A fiber input to lamina I NK1R+ neurons that was predominantly Aβ fiber mediated. This novel A fiber input was polysynaptic in nature and required NMDA receptor activity to be functional. In lamina I NK1R− and lamina III NK1R+ neurons, disinhibition enhanced control-evoked responses, and this was also NMDA receptor dependent. These disinhibition-induced changes, in particular the novel polysynaptic low-threshold input onto lamina I NK1R+ neurons, may be an underlying component of the hypersensitivity present in chronic pain states.
A Priority Queue Algorithm for the Replication Task in HBase

The replication of the non-structure data from one data center to another is an urgent task in HBase. The paper studies the priority growth probability of the priority replication queue and proposed a dynamic priority replication task queue algorithm based on the earliest deadline first algorithm (EDF). The experiment results show that the proposed algorithm can balance the replication overhead between the high and low priority tasks and avoid the low priority task starving to death as well as ensure the high priority task’s interests.
Spatial independent component analysis of functional MRI time‐series: To what extent do results depend on the algorithm used?

Independent component analysis (ICA) has been successfully employed to decompose functional MRI (fMRI) time‐series into sets of activation maps and associated time‐courses. Several ICA algorithms have been proposed in the neural network literature. Applied to fMRI, these algorithms might lead to different spatial or temporal readouts of brain activation. We compared the two ICA algorithms that have been used so far for spatial ICA (sICA) of fMRI time‐series: the Infomax (Bell and Sejnowski [ 1995 ]: Neural Comput 7:1004–1034) and the Fixed‐Point (Hyvärinen [ 1999 ]: Adv Neural Inf Proc Syst 10:273–279) algorithms. We evaluated the Infomax‐ and Fixed Point‐based sICA decompositions of simulated motor, and real motor and visual activation fMRI time‐series using an ensemble of measures. Log‐likelihood (McKeown et al. [ 1998 ]: Hum Brain Mapp 6:160–188) was used as a measure of how significantly the estimated independent sources fit the statistical structure of the data; receiver operating characteristics (ROC) and linear correlation analyses were used to evaluate the algorithms' accuracy of estimating the spatial layout and the temporal dynamics of simulated and real activations; cluster sizing calculations and an estimation of a residual gaussian noise term within the components were used to examine the anatomic structure of ICA components and for the assessment of noise reduction capabilities. Whereas both algorithms produced highly accurate results, the Fixed‐Point outperformed the Infomax in terms of spatial and temporal accuracy as long as inferential statistics were employed as benchmarks. Conversely, the Infomax sICA was superior in terms of global estimation of the ICA model and noise reduction capabilities. Because of its adaptive nature, the Infomax approach appears to be better suited to investigate activation phenomena that are not predictable or adequately modelled by inferential techniques. Hum. Brain Mapping 16:146–157, 2002. © 2002 Wiley‐Liss, Inc.
Perceiving Patterns of Play in Dynamic Sport Tasks: Investigating the Essential Information Underlying Skilled Performance

The perceptual-cognitive information used to support pattern-recognition skill in soccer was examined. In experiment 1, skilled players were quicker and more accurate than less-skilled players at recognising familiar and unfamiliar soccer action sequences presented on film. In experiment 2, these action sequences were converted into point-light displays, with superficial display features removed and the positions of players and the relational information between them made more salient. Skilled players were more accurate than less-skilled players in recognising sequences presented in point-light form, implying that each pattern of play can be defined by the unique relations between players. In experiment 3, various offensive and defensive players were occluded for the duration of each trial in an attempt to identify the most important sources of information underpinning successful performance. A decrease in response accuracy was observed under occluded compared with non-occluded conditions and the expertise effect was no longer observed. The relational information between certain key players, team-mates and their defensive counterparts may provide the essential information for effective pattern-recognition skill in soccer. Structural feature analysis, temporal phase relations, and knowledge-based information are effectively integrated to facilitate pattern recognition in dynamic sport tasks.
A New Class of Detail-Preserving Filters for Image Processing

A new class of median type filters for image processing is proposed. In the filters, linear FIR substructures are used in conjunction with the median operation. The root signals and noise attenuation properties of the FIR-median hybrid filters are analyzed and compared to representative edge preserving filtering operations. The concept of multilevel median operation is introduced to improve the detail preserving property of conventional median and the FIR-median hybrid filters. In the multilevel filters there exists a tradeoff between noise attenuation and detail preservation. The analysis and examples indicate that FIR-median hybrid filters preserve details better and are computationally much more efficient than the conventional median and the K-nearest neighbor averaging filters.
Intelligent metasearch engine for knowledge management

The explosive growth of available information sources and the resulting information overload pose several problems for users in many business organizations and educational institutions. First, searching through several information sources, one at a time, is a source of enormous frustration for users. Second, top-ranked documents in search results are frequently irrelevant to what users are interested in. To address these problems, we have developed ixmeta™, a powerful metasearch engine that gathers, evaluates, ranks, and reports the most relevant results from multiple information sources, including library catalogs, proprietary databases, intranets, and Web search engines. In addition to basic metasearch capabilities, ixmetafind uses personalization and clustering techniques to find the most relevant results for users. In this paper, we briefly describe technologies used in ixmetafind and present pinpoint™ from Sagebrush Corporation, the smart research tool™ in the kindergarten through twelfth grade (K-12) school environment. Pinpoint showcases ixmetafind in the knowledge management domain of the K-12 school environment.
Stability and persistence analysis of large scale interconnected positive systems

This paper is concerned with the analysis of large-scale interconnected systems constructed from positive subsystems and a nonnegative interconnection matrix. We first show that the interconnected system is admissible and stable if and only if a Metzler matrix built from the coefficient matrices of the positive subsystems and the interconnection matrix is Hurwitz stable. By means of this key lemma, we further provide several results that characterize the admissibility and stability of interconnected systems in terms of the weighted L1-induced norm of each positive subsystem and the Frobenius eigenvalue of the interconnection matrix. Moreover, in the case where every subsystem is SISO, we provide explicit conditions under which the interconnected system has the property of persistence, i.e., the state of the interconnected system converges to a unique strictly positive vector (up to a strictly positive constant multiplicative factor) irrespective of nonnegative and nonzero initial states. We illustrate the effectiveness of the persistence results via formation control of multi-agent systems.
IT Alternatives to Social Control in Organizations

This paper extends theories of control as an organization design tool and empirically explores the efficacy of delegation technologies in providing the equivalent of social (clan) control for effort-averse agents engaged in low programmable, low outcome measurement task environments. The exploratory evaluation of delegation technologies suggests new control alternatives that are trust building and therefore offer alternative organizational design possibilities in lieu of social control.
Received signal strength prediction using Gaussian process

Gaussian Process (GP) is a statistical tool where observations are considered normally distributed random variables. The technique uses previous observations and their covariances or similarities to analyze and predict future data. In this paper, the Gaussian random variable is the Received Signal Strength (RSS) between one anchor and one mobile station. In the training phase, the positions of anchor and mobile station together with the RSS between them are known. GP will use these data to predict the RSS at any other location of the mobile station. Experiment is conducted to validate the algorithm.
Trajectory planning of tracked vehicles

The motions of planar tracked vehicles are governed by three force and moment equations. The force equation perpendicular to the tracks represents a dynamic nonholonomic constraint which is explicitly dependent on vehicle speed. It couples path planning with trajectory planning. The nominal track forces required to follow a specified data at desired speeds are determined. The problem is reduced to computing vehicle orientations along the path that are consistent with the nonholonomic constraint. The computation of vehicle orientations is formulated as a parameter optimization that minimizes the violation of the equality constraint. The method is demonstrated for planar motions along a circular path on plate and inclined planes. <<ETX>>
Patients’ Expectations Impact Their Satisfaction following Total Hip or Knee Arthroplasty

Introduction The objective of this study was to assess the number and magnitude of preoperative expectations and to correlate them with the degree of satisfaction expressed one year after Total Hip Arthroplasty (THA) or Total Knee Arthroplasty (TKA), in patients with severe and painful osteoarthritis (OA). Materials and Methods Preoperative expectations (within 20 days prior to surgery) and postoperative satisfaction (one year after the intervention) were measured using the previously validated French version of the Hospital for Special Surgery Hip or Knee Replacement Expectations Survey. Postoperative satisfaction was measured using a specific scale, following the same methodology as that used for the assessment of expectations. Prediction of the satisfaction of the patients was performed using multivariate linear regression modelling. Results A total of 138 patients (80 THA and 58 TKA) completed the two parts of the study. The expectations score (mean ± SD) (range 0–100) was 72.58 ± 12.63 before THA and 69.10 ± 13.72 before TKA (p = 0.13). The number of expectations expressed was 14.34 ± 1.32 (out of a potential maximum of 18) before THA and 14.70 ± 2.29 (out of a potential maximum of 19) before TKA. After 1 year, THA generated a significantly higher degree of satisfaction compared to TKA (69.70 ± 14.46 v 60.44 ± 17.54, p<0.001) (range 0–100). The pre-operative expectations score was the single best positive predictor of the post-surgery satisfaction assessment both for TKA and THA. Conclusion Patients undergoing total joint arthroplasty for end-stage OA have a high level of expectations, before both THA and TKA. While both types of interventions significantly improve essential and non-essential activities, the rate of satisfaction is significantly greater post THA. Preoperative expectations are a major contributor to the final degree of satisfaction, one year after surgery. These results re-emphasize the need for an optimal preoperative interaction between health care providers and patients, to allow patients a chance to foresee a reasonable outcome after TJA.
Classification of cooperative and competitive overlaps in speech using cues from the context, overlapper, and overlappee

One of the major properties of overlapping speech is that it can be perceived as competitive or cooperative. For the development of real-time spoken dialog systems and the analysis of affective and social human behavior in conversations, it is important to (automatically) distinguish between these two types of overlap. We investigate acoustic characteristics of cooperative and competitive overlaps with the aim to develop automatic classifiers for the classification of overlaps. In addition to acoustic features, we also use information from gaze and head movement annotations. Contexts preceding and during the overlap are taken into account, as well as the behaviors of both the overlapper and the overlappee. We compare various feature sets in classification experiments that are performed on the AMI corpus. The best performances obtained lie around 27%–30% EER.
A Decision Tree Framework for Spatiotemporal Sequence Prediction

We study the problem of learning to predict a spatiotemporal output sequence given an input sequence. In contrast to conventional sequence prediction problems such as part-of-speech tagging (where output sequences are selected using a relatively small set of discrete labels), our goal is to predict sequences that lie within a high-dimensional continuous output space. We present a decision tree framework for learning an accurate non-parametric spatiotemporal sequence predictor. Our approach enjoys several attractive properties, including ease of training, fast performance at test time, and the ability to robustly tolerate corrupted training data using a novel latent variable approach. We evaluate on several datasets, and demonstrate substantial improvements over existing decision tree based sequence learning frameworks such as SEARN and DAgger.
State estimation of the vinyl acetate reactor using unscented Kalman filters (UKF)

The main objective of our research is to develop several unscented transform techniques (UTT) to estimate the state of the nonlinear processes such as an improvement of an extended Kalman filter (EKF) approach. The extended Kalman filter (EKF) has become a standard nonlinear estimation technique in control systems and parameter estimation for nonlinear system identification. The unscented Kalman filter (UKF) developed in this paper is a superior alternative to the extended Kalman filter for the most of estimation and control applications. We tried to figure out in this paper that the UKF algorithm performs slightly superior compared to EKF algorithm based on the state estimation of the nonlinear vinyl acetate reactor developed well in N. Tudoroiu, 1990. These results are encouraging for us and we want to explore the possibility of extension of its applicability to the other possible applications such as state and parameter estimation, neural network identification, and fault detection, diagnosis and isolation (FDDI) of the nonlinear control systems