Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermally induced changes in intracellular pH and modulators of phosphofructokinase in trout white muscle

The intracellular pH (pHi) and the concentrations of lactate and selected modulators of phosphofructokinase (PFK; EC 2.7.1.11) were measured in white epaxial muscle of 15 °C-acclimated rainbow trout (Oncorhynchus mykiss) maintained at 8, 15 or 22 °C for 48 h and sampled at rest and after 10 min of exhaustive exercise. The lactate accumulation resulting from exercise was 13 % smaller at 22 °C than at 8 and 15 °C. The estimated duration of burst performance was shorter at cold than at warm temperatures, whereas the average rate of lactate accumulation during burst performance was higher at 8 °C than at 15 and 22 °C. pHi rose when temperature decreased, but less than predicted by the imidazole alphastat hypothesis of Reeves. The effects of temperature on the pre-exercise concentrations of PFK modulators [adenylates, fructose 6-phosphate (F6P) and fructose 1,6-bisphosphate (FBP)] were generally negligible. In exhausted trout, adenylate concentrations were almost unaffected by temperature. In contrast, post-exercise FBP and F6P concentrations were significantly higher at low than at high temperatures. We interpret the response of F6P to temperature as an indication that the covariation of pHi and temperature is insufficient to prevent a cold-enhancement of PFK inhibition. Since F6P is a potent activator of PFK, we conclude that, in trout white muscle, thermally induced changes in F6P concentration probably help buffer the effects of temperature change on PFK activity.
Fault simulation and test generation for small delay faults

Delay faults are an increasingly important test challenge. Traditional delay fault models are incomplete in that they model only a subset of delay defect behaviors. To solve this problem, a more realistic delay fault model has been developed which models delay faults caused by the combination of spot defects and parametric process variation. According to the new model, a realistic delay fault coverage metric has been developed. Traditional path delay fault coverage metrics result in unrealistically low fault coverage, and the real test quality is not reflected. The new metric uses a statistical approach and the simulation based fault coverage is consistent with silicon data. Fast simulation algorithms are also included in this dissertation. The new metric suggests that testing the K longest paths per gate (KLPG) has high detection probability for small delay faults under process variation. In this dissertation, a novel automatic test pattern generation (ATPG) methodology to find the K longest testable paths through each gate for both combinational and sequential circuits is presented. Many techniques are used to reduce search space and CPU time significantly. Experimental results show that this methodology is efficient and able to handle circuits with an exponential number of paths, such as ISCAS85 benchmark circuit c6288. The ATPG methodology has been implemented on industrial designs. Speed binning has been done on many devices and silicon data has shown significant benefit of the KLPG test, compared to several traditional delay test approaches.
Drivers within Natural Drinking Groups: An Exploration of Role Selection, Motivation, and Group Influence on Driver Sobriety

Young people consume alcohol almost exclusively in social contexts, but natural drinking group dynamics are poorly understood. Our research focuses on the drivers' role within natural drinking groups. We conducted breath-test surveys of existing groups of young people at the US/Mexico border crossing before they headed to Tijuana bars, and surveyed them again upon their return. Results indicated an individual's perception of other group member's drinking plans predicts drinking intentions to a greater degree for passengers than drivers. Additionally, drivers who anticipated heavy drinking among other group members returned to the United States with BACs nearly identical to drivers who reported that other group members would not drink at all. This suggests drivers were resistant to normative pressures to drink. Evidence that group-dynamic variables may impact drinking behavior underscores the importance of systematic exploration of natural drinking groups. Furthermore, the knowledge gleaned from studying the dynamics and decision making processes of natural drinking groups could be used to design intervention designed to increase designated driver use and to reduce drinking among designated drivers.
CDK5-dependent Phosphorylation of the Rho Family GTPase TC10α Regulates Insulin-stimulated GLUT4 Translocation*

Insulin stimulation results in the activation of cyclin-dependent kinase-5 (CDK5) in lipid raft domains via a Fyn-dependent phosphorylation on tyrosine residue 15. In turn, activated CDK5 phosphorylates the Rho family GTP-binding protein TC10α on threonine 197 that is sensitive to the CDK5 inhibitor olomoucine and blocked by small interfering RNA-mediated knockdown of CDK5. The phosphorylation deficient mutant T197A-TC10α was not phosphorylated and excluded from the lipid raft domain, whereas the phosphorylation mimetic mutant (T197D-TC10α) was lipid raft localized. Insulin resulted in the GTP loading of T197D-TC10α but not T197A-TC10α and in parallel, T197D-TC10α but not T197A-TC10α depolymerized cortical actin and inhibited insulin-stimulated GLUT4 translocation. These data demonstrate that CDK5-dependent phosphorylation maintains TC10α in lipid raft compartments thereby disrupting cortical actin, whereas subsequent dephosphorylation of TC10α through inactivation of CDK5 allows for the re-assembly of F-actin. Because cortical actin reorganization is required for insulin-stimulated GLUT4 translocation, these data are consistent with a CDK5-dependent TC10α cycling between lipid raft and non-lipid raft compartments.
From Blocks to Granules: An Alternative Approach to Designing Learning Objects

The idea of creating learning objects, making them reusable and storing them in databases for further use is blooming and becoming a new kind of challenge for instructional designers to quest how to design ldquoreusable, interoperable, and accessiblerdquo learning objects and to put them in a sequence in e-learning environments. On of the challenges is to determine the size of a learning object and a necessary requirement for them to be shared across networks and reused in different learning environments. This paper proposes a model to overcome this challenge by suggesting designing learning objects based on concept and skill ontologies developed from K-12 curricula. By using the learning space as a metaphor, design granules of a learning object has been modeled by separating expectations as skills and concepts.
Visualization and analysis of multi-variate data: a technique for all fields

A technique is presented for plotting large multivariate data sets that involves the mapping of n independent variable dimensions on to a single hierarchical horizontal axis with a single dependent variable being plotted on the vertical axis. The emphasis is on visual statistical analysis of either discrete variables or continuous variables that have been sampled on, or binned to, a regular n-dimensional lattice. The general applicability of the technique is discussed, and ways are explored of representing the hierarchical data-driven symbols that are particularly well suited to a variety of visual analysis tasks. <<ETX>>
Fuzzy similarity measure-based hybrid image filter for color image restoration: multimethodology evolutionary computation

A fuzzy similarity measure-based hybrid image filter (FHF) is proposed for color image restoration in this paper. Operation is carried out in three steps: parameter optimization, hybrid image filter setup, and image restoration. For parameter optimization, a multimethodology evolutionary computation (MMEC) is presented for real-parameter optimization problems. Then, FHF with a fuzzy-based similarity measure is introduced for noise reduction. Finally, a color image is restored with an experience-based construction of FHF which has been optimized via MMEC. Experimental results show the proposed FHF achieves a high peak signal-to-noise ratio and mean structural similarity by effectively reducing Gaussian, impulse, and mixed-noise.
A method to identify dynamic zones for efficient control of HVAC systems

Energy Management System (EMS) in Smart Buildings is responsible for providing thermal comfort to its occupants in an energy efficient manner. To achieve this, the EMS usually divides the floor of a building into multiple zones with predefined static boundaries. Next, it derives the optimal Heating Ventilation and Air Conditioning (HVAC) control parameters based on the average environmental characteristics (e.g. average temperature, humidity and occupancy) for each zone. Because the HVAC acts based on the average conditions in a zone, static zones can display considerable variation within their boundaries from the desired ambient conditions. A more adaptive approach is therefore called for in order to reduce deviations from desired ambient conditions. In this paper, we propose a graph theoretic region growing approach to dynamically identify zones with similar ambient conditions. The boundary of these dynamic zones can be adapted continuously as the environmental conditions change. In this manner, the HVAC parameters can be adapted to zones with smaller variations, thereby achieving the desired ambient conditions across the floor with higher accuracy. The efficacy of the proposed approach is demonstrated for a single floor in a building using real time data collected from various sensors (humidity and temperature) and occupancy. Finally, dynamic zone information can be used to save energy. Simulation results indicate considerable energy savings.
Nuclear actin and RNA export in conidial cells of Neurospora crassa

We have recently reponed the cytochalasin Bsensitive actin-mediated nuclear RNA export in germinating conidia of Neurospora crassa (Barja and Turian, 1994). We were then led to assume the still undocumented intranuclear presence of actin in nuclei of fungi except slime molds (ref. in LeStourgeon, 1978) contrarily to the long list of references about animal cells (see Milankov and De Boni, 1993). We now have obtained a first, but indirect evidence of it by the radioautographic localization of tritiated cytochalasin B, a technique based on the well-known capacity of this mycotoxin to bind to actin thereby inhibiting its polymerization (Tannenbaum, 1978; Sampath and Pollard, 1991). First to use this technique, Tannenbaum et al. (1973) with [3H]CD, Mayhew et al. (1974) with [3H]CB, showed a localization of Ag grains, and therefore of actin, in animal cells. Direct evidence of nuclear actin in Neurospora, preliminarily obtained by immunoblotting gel separation of extracts from nuclei isolated from normal as well as cytochalasintreated cells, confirms our radioautographies.
Structural Controllability Condition of a Class of RFSS and its Application to a Linear System

In this paper, some concepts on reducibility are presented. The structural controllability condition of a class of rational function systems (RFSs) is derived. An application example of a DC governor system is analyzed to show the structural controllability condition is significant to a linear system from the viewpoint of physics.
Transmission of Borrelia gariniiOspA Serotype 4 to BALB/c Mice by Ixodes ricinus Ticks Collected in the Field

ABSTRACT In Europe, Borrelia garinii OspA serotype 4 has been isolated from the cerebrospinal fluid of patients but, up to now, has never been identified among culture isolates from Ixodes ricinus ticks. This information raises the question of whether OspA serotype 4 is transmitted by I. ricinus in nature. In the present study, I. ricinus nymphs collected in an area of endemicity in southern Germany were allowed to feed on mice. Cultivation of ear biopsy specimens showed that six of seven B. garinii-infected mice were infected by OspA serotype 4. In contrast, very few B. garinii OspA serotype 4 organisms were isolated directly from the ticks which infected the mice; most isolates were B. afzelii. The infected mice transmitted mainly OspA serotype 4 to xenodiagnostic ticks, preferentially in combination with B. afzelii.
A Hybrid Kernel-Based Change Detection Method for Remotely Sensed Data in a Similarity Space

Detection of damages caused by natural disasters is a delicate and difficult task due to the time constraints imposed by emergency situations. Therefore, an automatic Change Detection (CD) algorithm, with less user interaction, is always very interesting and helpful. So far, there is no existing CD approach that is optimal and applicable in the case of (a) labeled samples not existing in the study area; (b) multi-temporal images being corrupted by either noise or non-normalized radiometric differences; (c) difference images having overlapped change and no-change classes that are non-linearly separable from each other. Also, a low degree of automation is not optimal for real-time CD applications and also one-dimensional representations of classical CD methods hide the useful information in multi-temporal images. In order to resolve these problems, two automatic kernel-based CD algorithms (KCD) were proposed based on kernel clustering and support vector data description (SVDD) algorithms in high dimensional Hilbert space. In this paper (a( a new similarity space was proposed in order to increase the separation between change and no-change classes, and also to decrease the processing time, (b) three kernel-based approaches were proposed for transferring the multi-temporal images from spectral space into high dimensional Hilbert space, (c) automatic approach was proposed to extract the precise labeled samples; (d) kernel parameter was selected automatically by optimizing an improved cost function and (e) initial value of the kernel parameter was estimated by a statistical method based on the L2-norm distance. Two different datasets including Quickbird and Landsat TM/ETM+ imageries were used for the accuracy of analysis of proposed methods. The comparative analysis showed the accuracy improvements of kernel clustering based CD and SVDD based CD methods with respect to the conventional CD techniques such as Minimum Noise Fraction, Independent Component Analysis, Spectral Angle Mapper, Simple Image differencing and Image Rationing, and also the computational cost analysis showed that implementation of the proposed CD method in similarity space decreases the processing runtime.
A comprehensive review on sparse representation for image classification in remote sensing

The main objective of this paper is to provide a comprehensive study on Sparse Representation based feature extraction techniques in the image classification domain. Sparse Representation (SR) plays a vital role in both theoretical research and practical applications. The Sparse Representation being image dependent has become a broadly used feature extraction technique that represents the signal or image under study. Considering the feature extraction techniques, this review article includes the work involving Multikernel Fusion Sparse Representation. A successful classification of remote sensing data is a huge challenge because many factors belong to the appropriate selection of remote sensing data, image pre-processing and processing methods may result in improper results. This issue demands a detailed collection of information extraction algorithms which would be remarkably valuable for the researchers who are new to the field of high resolution remote sensing data in selecting a suitable classification technique. This paper concentrates on recapitulating all the possible information extraction techniques for image classification in remote sensing images.
Germicidal Action of Some Metals/Metal Ions in Combating E. coli Bacteria in Relation to Their Electro-Chemical Properties

The germicidal properties of some metals and metal compounds were investigated in relation to their electro-chemical properties that may play a role in the inactivation of E. coli bacteria. These properties included the atomic and ionic radii, ionization energy, oxidation state, energy of formation with hydro-sulfide groups, and the redox potential of the metals. Cultures of E. coli bacteria with predetermined numbers of colony-forming units (CFU’s) were brought in contact with the metals as well as metal compounds, using Eosin methylene blue agar medium and sterilized, distilled water. The rate of inactivation was determined by counting the CFU’s at predefined intervals of time after inoculation. The experimental results showed that the rate of inactivation increases with increasing ionization energy of the metals. While the rate of inactivation increases with decreasing atomic radii for some of the transition metals, there is no apparent relationship between ionic radius and rate of inactivation for the metal compounds. In addition, non-transition group III metals such as aluminum and indium showed higher rates of inactivation that are comparable to the action of silver. This is probably due to the increase in coagulation potential and the resulting adsorption of bacteria, because a larger number of ions are able electrons carried by these atoms. In general, there is a difference between the atoms and the ions in terms of their rate of inactivation. This difference increases amongst the transition metals that have lower oxidation potential, lower ionization potential as well as larger ionic radius. The results also showed that for the metals, adsorption through coagulation is an important fact or that is responsible for inactivation of E. coli. For the metal compounds, additional mechanisms such as direct reaction through complex formation, physico-chemical distortion of the cell structure through direct entry of the ions into the cell, may contribute towards greater inactivation.
Succinate transport by free-living forms of Rhizobium japonicum

We have demonstrated that the transport of succinate into the cells of Rhizobium japonicum strains USDA 110 and USDA 217 is severely inhibited by cyanide, azide, and 2,4-dinitrophenol, but not by arsenate. These results suggest an active mechanism of transport that is dependent on an energized membrane, but does not directly utilize ATP. The apparent Km for succinate was 3.8 microM for strain USDA 110 and 1.8 microM for strain USDA 217; maximal transport velocities were 1.5 and 3.3 nmol of succinate per min per mg of protein, respectively. The expression of the succinate uptake activity was inducible rather than constitutive, with succinate and structurally related compounds being the most effective inducers. The mechanism showed some specificity for succinate and similar organic acids; fumarate and L-malate were classical competitive inhibitors of the system. In general, the best competing compounds were also the best carbon substrates for induction of succinate uptake activity. EDTA inhibited the transport of succinate, implying a role for divalent cations in the system. When various divalent cations were used to reconstitute EDTA-inhibited activity, Ca2+ was most effective, followed by Mg2+, which restored activity at about half the efficiency of Ca2+. Growth media that were supplemented with increased Ca2+ concentration supported more rapid growth with succinate as the carbon substrate, and cells from such media showed higher specific activities of succinate transport.
Combining Semantic Technologies and Data Mining to Endow BSS/OSS Systems with Intelligence - Particularization to an International Telecom Company Tariff System

Businesses need to "reduce costs" and improve their “time-to-market" to compete in a better position. Systems must contribute to these two goals through good designs and technologies that give them agility and flexibility towards change. Semantics and Data Mining are two key pillars to evolve the current legacy systems towards smarter systems that adapt to changes better. In this article we present some solutions to evolve the existing systems, where the end user has the possibility of modifying the functioning of the systems incorporating new business rules in a Knowledge Base.
Digitally controlled CMOS quadrature ring oscillator with improved FoM for GHz range all-digital phase-locked loop applications

This paper presents a 14-bit digitally controlled ring oscillator (DCO) with operating frequency up to 3.4 GHz in 0.18 µm CMOS technology. Digital control is employed to control the transistor operation to obtain higher voltage swing and lower flicker (1/f) noise that in turn results in the lowest phase noise in a ring oscillator. Furthermore, sub-feedback topology is used to obtain the stable quadrature outputs from even number of stages. The DCO has a frequency tuning from 523 MHz to 3.405 GHz. Phase noise at 4 MHz offset is −134.82 dBc/Hz. This results in figure of merit (FoM) to be −169.9 dBc/Hz which is 7.7 dB improvement over its recently published analog counterpart.
Unit Roots and Structural Change

This paper employs time-series analysis to investigate the price dynamics of the house price indices included in the S&P/Case–Shiller Composite10 index and the validity of the ‘ripple effect’, following the approach outlined by Meen (1999). More specifically, the paper first considers the time-series properties of the capital gain from the sale of houses. That is, it examines whether shocks to the capital gain series produce permanent or transitory changes. In general, the findings lack uniformity and depend upon the assumptions imposed by the testing procedures. Secondly, it considers the time-series properties of the ratio of regional house price indices to the Composite10 index. That is, it examines whether shocks to these house price ratios exhibit trend reversion. The tests of this ‘ripple effect’ also display conflicting evidence.
Comparison of Turnip Crinkle Virus RNA-Dependent RNA Polymerase Preparations Expressed in Escherichia coli or Derived from Infected Plants

ABSTRACT Turnip crinkle virus (TCV) is a small, plus-sense, single-stranded RNA virus of plants. A virus-coded protein, p88, which is required for replication has been expressed and purified from Escherichia coli. In vitro assays revealed that the recombinant p88 has an RNA-dependent RNA polymerase (RdRp) activity and can also bind to RNA. Deletion of the N-terminal region in p88 resulted in a more active RdRp, while further deletions abolished RdRp activity. Comparison of the E. coli-expressed p88, the N-terminal deletion mutant of p88, and a TCV RdRp preparation obtained from infected plants revealed that these preparations show remarkable similarities in RNA template recognition and usage. Both the recombinant and the plant TCV RdRp preparations are capable of de novo initiation on both plus- and minus-strand satC and satD templates, which are small parasitic RNAs associated with TCV infections. In addition, these RdRp preparations can efficiently recognize the related Tomato bushy stunt virus promoter sequences, including the minus- and plus-strand initiation promoters. Heterologous viral and artificial promoters are recognized poorly by the recombinant and the plant TCV RdRps. Further comparison of the single-component recombinant TCV RdRp and the multicomponent plant TCV RdRp will help dissect the functions of various components of the TCV replicase.