Miracle-dz/UniFAR-FTUs huggingface dataset:
Substrate recognition and cleavage-site selection by a single-subunit protein-only RNase P

RNase P is the enzyme that removes 5′ extensions from tRNA precursors. With its diversity of enzyme forms—either protein- or RNA-based, ranging from single polypeptides to multi-subunit ribonucleoproteins—the RNase P enzyme family represents a unique model system to compare the evolution of enzymatic mechanisms. Here we present a comprehensive study of substrate recognition and cleavage-site selection by the nuclear single-subunit proteinaceous RNase P PRORP3 from Arabidopsis thaliana. Compared to bacterial RNase P, the best-characterized RNA-based enzyme form, PRORP3 requires a larger part of intact tRNA structure, but little to no determinants at the cleavage site or interactions with the 5′ or 3′ extensions of the tRNA. The cleavage site depends on the combined dimensions of acceptor stem and T domain, but also requires the leader to be single-stranded. Overall, the single-subunit PRORP appears mechanistically more similar to the complex nuclear ribonucleoprotein enzymes than to the simpler bacterial RNase P. Mechanistic similarity or dissimilarity among different forms of RNase P thus apparently do not necessarily reflect molecular composition or evolutionary relationship.
Information theoretic measure of complexity and stock market analysis : using the JSE as a case study

Bozdogan [8] [6] [7] developed a new model selection criteria called information measure of complexity (ICOMP) for model selection. In contrast to Akaike’s [1] information criterion (AIC) and other AIC type criteria that are traditionally used for regression analysis, ICOMP takes into account the interdependencies of the parameter estimates. This paper is divided into two parts. In the first part we compare and contrast ICOMP with AIC and other AIC type selection criterion for model selection in regression analysis involving stock market securities. While in the second part we apply the definition of information theoretic measure of complexity to portfolio analysis. We compare the complexity of a portfolio of securities with its’ measure of diversification (PDI) and examine the similarities and differences between the two quantities as it affects portfolio management.
An improved method for hydrofracture induced microseismic event detection and phase picking

The ability to detect small microearthquakes and identify their P- and S-phase arrivals is a key issue in hydrofracture downhole monitoring because of the low signal-to-noise ratios S/N. An array-based waveform correlation approach matched filter is applied to improve the detectability of smallmagnitudeeventswithmechanismsandlocationssimilar to a nearby master event.After detecting the weak events, a transformed spectrogram method is used to identify the phase arrivals. The technique has been tested on a downhole monitoring data set of the microseismic events induced by hydraulic fracturing. It is shown that, for this case, one event with a S/N around 6 dB, which is barely detectable using an array-stacked short-time average/long-time average STA/ LTA detector under a reasonable false alarm rate, is readily detected on the array-stacked correlation traces. The transformedspectrogramanalysisofthedetectedeventsimproves P-andS-phasepicking.
Understanding the small business owner: what they really aim at and how this relates to firm performance

Purpose – The purpose of this paper is to examine how business owners in microbusinesses perceive success and how that perception may influence the growth of their enterprise.Design/methodology/approach – The results of three separate studies were analysed. The data were collected with questionnaires and interviews among microbusinesses in the industries of craft and rural tourism in the area of North Karelia, Eastern Finland. Both quantitative and qualitative methods were used in the analysis.Findings – The paper found that the motives and goals of the small business owners were not oriented towards growth, but to quality of life, job satisfaction and satisfied clientele. Consequently, business success was measured by the respect and satisfaction of the customers, job satisfaction and the quality of product. From an economic perspective, making a reasonable living, not growth, constituted a measure of success.Research limitations/implications – Generalisation is affected by the fact that the study concer.
In Vitro Osteogenic Properties of Two Dental Implant Surfaces

Current dental implant research aims at understanding the biological basis for successful implant therapy. The aim of the study was to perform a full characterization of the effect of two commercial titanium (Ti) surfaces, OsseoSpeed and TiOblast, on the behaviour of mouse preosteoblast MC3T3-E1 cells. The effect of these Ti surfaces was compared with tissue culture plastic (TCP). In vitro experiments were performed to evaluate cytotoxicity, cell morphology and proliferation, alkaline phosphatase activity, gene expression, and release of a wide array of osteoblast markers. No differences were observed on cell viability and cell proliferation. However, changes were observed in cell shape after 2 days, with a more branched morphology on OsseoSpeed compared to TiOblast. Moreover, OsseoSpeed surface increased BMP-2 secretion after 2 days, and this was followed by increased IGF-I, BSP, and osterix gene expression and mineralization compared to TiOblast after 14 days. As compared to the gold standard TCP, both Ti surfaces induced higher osteocalcin and OPG release than TCP and differential temporal gene expression of osteogenic markers. The results demonstrate that the gain of using OsseoSpeed surface is an improved osteoblast differentiation and mineralization, without additional effects on cell viability or proliferation.
Syntactic N-gram Collection from a Large-Scale Corpus of Internet Finnish

In this paper, we report on the development of a large-scale Finnish Internet parsebank, currently consisting of 1.5 billion tokens in 116 million sentences. The data is fully morphologically and syntactically analyzed and it has been used to extract flat and syntactic n-gram collections, as well as verb-argument and nounargument n-grams. Additionally, distributional vector space representations of the words are induced using the word2vec method. All n-gram collections as well as the vector space models are made available under an open license.
Managing User Irritation in Wireless VoIP Using Noncooperative Games

Wireless voice over IP (VoIP) is subject to unpredictable link conditions which directly contribute to user irritation. Standard technological means available to the network provider to remedy wireless link problems require additional radio resources to be allocated. Given that radio resource is limited, it is not clear whether such allocation strategies to reduce user irritation are economically rewarding for the wireless providers. We model the resource allocation dilemma to reduce user irritation as a noncooperative game between the provider and the VoIP user suffering from a link quality problem. We demonstrate that providers implementing Nash equilibrium can expect to optimize their revenues and avoid potential churning.
Language Mobile Learning Design: The Tamazight Language

Even though Tamazight language in Morocco has been legitimate for eleven years and official for almost two years, its learning needs a huge effort to successfully make it in this enormous batch of existing unformatted documents. In this article, we present a method for learning the Tamazight language in a mobile environment. The mobile is chosen to free the learner from the constraints of time and space. Indeed, the use of mobile devices allows it to be anywhere and anytime. An immediate question is how to involve the learner in the learning process, which is why we propose to put him in real or fictitious situations that are part of his experience and to which he is used to react. At the end of this article, we also present a prototype of a mobile application implementing our method.
Metamodel-Based Inference of Inter-Model Correspondence

Many software engineering processes produce series of related models. They describe the designed system from different viewpoints, each emphasizing a particular concern. Models are produced by individual teams and sometimes third party developers, and sometimes they are synthesized using tools. It is unlikely that they are developed within a single modeling repository or share common repository identifiers. To reason about the models, a correspondence relationship needs to be established between model elements representing the same concepts. Current approaches for inferring correspondence use fixed semantics built into the algorithms and derived from small modeling language subsets. This paper presents a flexible approach for inferring correspondence. The rules are generated based on a Meta-Object Facility compliant metamodel specifying modeling language of the compared model instances. They can be refined with additional domain specific rules. The approach can be used as a basis for comparing, merging and reconciling models
Performance Impact of Streaming Doppler Radar Data on a Geospatial Visualization System

A geospatial visualization tool that is capable of visualizing weather data in conjunction with the terrain and object data typical of GIS visualization tools provides an important advancement in the study severe weather formation by providing a tool for weather scientists to study of the impact of land topography and human changes. In particular, unlike the plains region, tornados in the Southeast form quickly, are generally small, and are short lived. Weather scientists would like to understand the impact that high human population density areas, such as metro Atlanta, and topography have on tornado formation. Such an understanding could lead to better and earlier tornado predictions. The visualization of doppler radar data raises interesting questions for the particular geographic visualization tool we are working with, the Virtual Geographic Information System (VGIS). In particular, doppler radar data is streaming, that is, it arrives as a continuous stream in near real-time. GIS visualization sytems such as VGIS are often designed under the assumption that the data to be visualized is relatively static. In this paper we assess the performance impact of visualizing doppler radar with VGIS, and propose a novel data structure and indexing scheme that reduces the performance overhead of retrieving and visualizing streaming data.
Experienced travel time prediction for freeway systems

Travel time is considered as one of the most important performance measures for roadway systems, and dissemination of travel time information can help travelers to make reliable travel decisions such as route choice or time departure. Since the traffic data collected in real time reflects the past or the current conditions on the roadway, a predictive travel time methodology should be used to obtain the information to be disseminated. However, an important part of the literature either uses instantaneous travel time assumption, and sums the travel time of roadway segments at the starting time of the trip, or uses statistical forecasting algorithms to predict the future travel time. This study benefits from the available traffic flow essentials (e.g. shockwave analysis, bottleneck identification), and makes use of both historical and real time traffic information to provide travel time prediction. The experimental results based on the loop detector data on Californian freeways indicate that the proposed method provides promising travel time predictions under varying traffic conditions.
Strategies to Improve Performance in the IA 64 Architecture

The Intel Itanium® 64 bit architecture is designed to reach high levels of performance using two main goals. The use of explicit parallelism (EPIC), where the compiler is able to express inherent parallelism in the instruction sequence, and the improvement of cache and register file use, to decrease the data miss penalties. However, to take real advantage of the model, compilers must be radically changed and optimized to use predication, speculative execution, and a set of novel features. This communication explores how these main goals of the IA64 can be feasible, and how they were architectural implemented, turning them a potential solution to improve performance.
Gradient Based Image Edge Detection

—Due to the importance of image edge detection in image analysis, object recognition and many applications, many edge detection algorithms are used to detect edges of objects in the image. Edges typically occur on the boundary between two different regions in the image. There are a number of algorithms for this, but these may be classified as derivative based where the algorithm takes first or second derivative on each pixel, or gradient based where a gradient of consecutive pixels is taken in x and y direction. In our paper we address the problem of gradient based image edge detection, several algorithms are tested, as a result of these algorithms binary images are produced, which represent objects and their background which then helps interpreting the content of the considered images, several medical(for different and the same organ) as well as natural images are used to evaluate the performance of the algorithms and their suitability for both kinds of images.
A Spherical Cover Algorithm to Reconstruct 3D Face Model

In this paper, we propose a face reconstruction algorithm from CT images based on a spherical cover algorithm. First we present an algorithm to simplify the data points of CT data. Then we use the simplified data to reconstruct 3D face model based on a spherical cover algorithm. We define a function to determine the radii of the covering spheres and then connect the centers of the spheres to reconstruct one 3D face model, which is an entry of our face database. Finally Principal Component Analysis is used to generate a statistical face model. By changing the parameters of the statistical model, a specific face can be deformed from the statistical model. The experimental results have showed great effects compared to other algorithm.
Work-Life Conflict Among IT Professionals

Work-life balance has importance in forming employee attitudes towards their organization. One of the elements for work-nonwork interfaces is the conflict that a person may experience between the work role and other life responsibilities. Employees' strong support for the importance of achieving a successful work-life balance has remained relatively constant in Information Technology (IT) industry in India. The present research examines the sources of conflict from work responsibilities across demographic characteristics and also analyzes the impact of work-life imbalance on organizational commitment for employees of IT and ITES Industry. Statistics on burnout cited clearly show that IT workers experience time, strain and role-based conflicts, and these conflicts have implications for the satisfaction and organizational commitment. The present study reveals that work-life imbalance is negatively associated with job commitment in IT-ITES industries.
Behavior of the Firm Under Regulatory Constraint

A recent article by Akira Takayama discusses an earlier paper by Harvey Averch and Leland L. Johnson on fair rate of return regulation of public utilities. Although Takayama (p. 255) agrees with Averch and Johnson's general conclusions "that a firm will tend to increase its investment with the introduction of an active constraint" on its rate of return, he criticizes the A-J argument as being "confusing, ambiguous, and in error. " Takayama then attempts a clarification, and presents a new formulation which leads to the A-J result quoted above. This comment will discuss several of Takayama's criticisms in addition to showing that the so-called "A-J Effect" cannot be derived from the basic assumptions made by both Averch and Johnson and Takayama.1 We will show that the very assumptions used to prove the A-J Effect, by defining the region of X, require an assumption that the A-J Effect exists in the first place.
Adhesion molecules in skeletogenesis: II. Neural cell adhesion molecules mediate precartilaginous mesenchymal condensations and enhance chondrogenesis

Neural cell adhesion molecules (NCAM) was expressed transiently by mesenchymal cells in precartilaginous condensations of the embryonic chicken limb but was lost upon differentiation into cartilage. Consequently, NCAM was present in the periphery of the limb anlagen but was absent in the cartilaginous center of the growing limb. To determine NCAM function in limb bud chondrogenesis we incubated dissociated stage 22/23 distal mesenchymal limb bud cells with Fab' fragments of antibodies to NCAM. Cell aggregation was inhibited by incubating the cells with anti‐NCAM Fab'. These results suggest that NCAM may mediate the formation of precartilaginous condensations. This hypothesis was further tested using micromass cultures. NCAM expression in micromass cultures in vitro recapitulated that in vivo. NCAM was enriched in condensations of 2 day cultures, but was diminished and concentrically distributed around cartilage nodules in 4 day cultures. Anti‐NCAM Fab' fragments reduced the area occupied by precartilaginous condensations and the degree of chondrogenic differentiation. Control antibody against chicken embryo fibroblasts had no effect. The effect of overexpressing NCAM was analyzed by electroporating expression vectors directing the synthesis of chicken NCAM. Limb bud cells cultured after electroporation with an NCAM expression vector displayed larger cartilage nodules and greater chondrogenic differentiation than cells electroporated with vector alone. The expression of NCAM in electroporated cells also increased. Control experiments using plasmids encoding β‐galactosidase indicated that approximately 10% of the limb bud cells were transfected under these conditions. The results suggest that NCAM is involved in the chondrogenesis pathway by mediating the formation of precartilaginous condensations. © 1993 Wiley‐Liss, Inc.
The video capture and processing research on Smart car road information based on OV7620 camera

In this paper, the road information collection systems and processing algorithms of video signal was researched based on vision sensor, the processor of Smart car used MC9S12XS128, the hardware of Sampling system using OV7620 digital camera; The key of software part is the turn of double-array storage and processing technology, which made the Acquisition system has higher efficiency, more in line with the requirements of real-time. Experiments have proved that the algorithm has good real-time performance, reliability and robustness.
Carbon nanotube-based programmable devices for adaptive architectures

We show that optic ally-gated carbon nanotube field effect transistors can be used as 2-terminal like devices with light sensitivity and memory capabilities. In particular, their channel resistivity can be adjusted precisely, within a large range and memorized. These devices can thus be used as synapses in neural network type of circuits. We demonstrate experimentally these properties, build a device model and propose a circuit architecture, which allows very efficient parallel learning.
Rapid simplification of multi-attribute meshes

We present a rapid simplification algorithm for meshes with multiple vertex attributes, targeted at rendering acceleration for realtime applications. Such meshes potentially feature normals, tangents, one or more texture coordinate sets, and animation information, such as blend weights and indices. Simplification algorithms in the literature typically focus on position-based meshes only, though extensions to handle surface attributes have been explored for those techniques based on iterative edge contraction. We show how to achieve the same goal for the faster class of algorithms based on vertex clustering, despite the comparative lack of connectivity information available. In particular, we show how to handle attribute discontinuities, preserve thin features, and avoid animation-unfriendly contractions, all issues which prevent the base algorithm from being used in a production situation. Our application area is the generation of multiple levels of detail for player-created meshes at runtime, while the main game process continues to run. As such the robustness of the simplification algorithm employed is key; ours has been run successfully on many millions of such models, with no preprocessing required. The algorithm is of application anywhere rapid mesh simplification of standard textured and animated models is desired.
Exposure to Acute Stress Blocks the Induction of Long-Term Potentiation of the Amygdala–Prefrontal Cortex Pathway In Vivo

In recent years, attention has been given to the interaction between the emotional state of the animal and its ability to learn and remember. Studies into the neural mechanisms underlying these interactions have focused on stress-induced synaptic plasticity impairments in the hippocampus. However, other brain areas, including the amygdala and the prefrontal cortex (PFC), have been implicated in relation to stress-mediated effects on memory. The present study examined whether stress, which impairs hippocampal long-term potentiation (LTP), also affects LTP of the basolateral amygdala (BLA)–PFC pathway in vivo. We first confirmed that the stress protocol we used, i.e., the elevated platform stress, was effective in blocking LTP in the CA1 area of the hippocampus. We then characterized activity and established the ability to induce LTP at the BLA–PFC pathway. Finally, we examined the effects of an exposure to the elevated platform stress on the ability to induce LTP in this pathway. The results indicate that, at the same time when LTP is blocked in the hippocampus, it is also inhibited in the BLA–medial PFC pathway. These results call for a shift from a focused attention on the effects of stress on plasticity in the hippocampus to a system level approach that emphasizes the possible modification of interactions between relevant brain areas after an exposure to a stressful experience.
On the advantage of serving first in a tennis set: four years at Wimbledon

A novel antibiotic compoudn 3-(6-isocyano-3,7-dioxatricyclo[4.1.0.02,4]hept-4-yl)propenoic acid is produced by a newly isolated microorganism belonging to the genus Penicillium.
Iterative detection for overloaded OFDMA with spatial diversity

Orthogonal Frequency Division Multiple Access (OFDMA) systems have built-in mechanisms to mitigate the effects of the wireless multipath channel but are limited in system capacity to available bandwidth. This shortcoming can be worked around through the process of "overloading," where users are additionally multiplexed in the spatial domain to each frequency resource. To efficiently resolve non-orthogonally multiplexed users within the system, sophisticated multiple antenna receivers with multiuser detection methods are necessary. The focus of this thesis will be the formulation of an iterative multiple antenna receiver framework for overloaded uplink OFDMA systems. Specifically, we formulate optimal MAP and reduced complexity MMSE symbol detection algorithms for the multiuser detection and single user decoding turbo loop. We verify the performance of each algorithm through Monte Carlo simulation with randomly generated multipath MIMO channels. From the results we determine the tradeoffs of algorithm complexity with performance and the effect of channel correlation on the supportable user load. Our MMSE algorithm with soft interference cancellation is observed to closely approach single user performance in low to moderately correlated MIMO channels after turbo loop iteration. Additionally, we observe that increasing the number of antennas relative to the number of overloaded users can mitigate the effects of moderate correlation to provide acceptable error performance. Thesis Supervisor: Moe Z. Win Title: Associate Professor