Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural characterization of single nucleotide variants at ligand binding sites and enzyme active sites of human proteins

Functional sites on proteins play an important role in various molecular interactions and reactions between proteins and other molecules. Thus, mutations in functional sites can severely affect the overall phenotype. Progress of genome sequencing projects has yielded a wealth of information on single nucleotide variants (SNVs), especially those with less than 1% minor allele frequency (rare variants). To understand the functional influence of genetic variants at a protein level, we investigated the relationship between SNVs and protein functional sites in terms of minor allele frequency and the structural position of variants. As a result, we observed that SNVs were less abundant at ligand binding sites, which is consistent with a previous study on SNVs and protein interaction sites. Additionally, we found that non-rare variants tended to be located slightly apart from enzyme active sites. Examination of non-rare variants revealed that most of the mutations resulted in moderate changes of the physico-chemical properties of amino acids, suggesting the existence of functional constraints. In conclusion, this study shows that the mapping of genetic variants on protein structures could be a powerful approach to evaluate the functional impact of rare genetic variations.
The Impact of Intelligent Interfaces on the Performance of Knowledge Base Systems

Although Knowledge is recognized as a strategic force in organizations, knowledge creation and management is not simply the capture and storage of items of information. It requires the storage and processing of associations through which meaning can be derived from the information. Association can be represented in explicit and observable forms in a knowledge base. The paper discusses issues relating to design a better quality interactive interface system for human to have a dialog with the knowledge management systems. At the same time, the paper investigates the ease of evaluation and implementation of a knowledge management system. It performs a major role in providing users with capabilities of dealing with underlying systems. Designing a good interface style using knowledge bases can have a profound effect on the nature of the dialog. Interfacing a knowledge base oriented system can be seen as a dialog between the knowledge base and the user. It plays a major role in providing users with capabilities that deal with underlying systems. Designing a good interface style can have a profound effect on the nature of the dialog. Design of a user interface involves determining approaches in which users interact with the knowledge-based system. The design process, can be complex and multifaceted, begins by identifying system users, through classification of them to understanding their characteristics. The study investigates the improvement of performance by performing an actual study of many experimental systems sufficient to provide judgments for taking the right decision. Results confirm that a good interface has a great impact on the performance of knowledge management systems.
Secure anonymous database search

There exist many large collections of private data that must be protected on behalf of the entities that hold them or the clients they serve. However, there are also often many legitimate reasons for sharing that data in a controlled manner. How can two parties decide to share data without prior knowledge of what data they have? For example, two intelligence agencies might be willing to cooperate by sharing documents about a specific case, and need a way of determining which documents might be of interest to each other. We introduce and address the problem of allowing such entities to search each other's data securely and anonymously. We aim to protect the content of the queries, as well as the content of documents unrelated to those queries, while concealing the identity of the participants. Although there exist systems for solving similar problems, to our knowledge we are the first to address this specific need and also the first to present a secure anonymous search system that is practical for real-time querying. In order to achieve this in an efficient manner, we make use of Bloom filters [5], definitions of security for deterministic encryption [22] that we adapt and instantiate in the private key setting and of a novel encryption primitive, reroutable encryption.
Environmental Research and Public Health a New Strategy for Heavy Metal Polluted Environments: a Review of Microbial Biosorbents

Persistent heavy metal pollution poses a major threat to all life forms in the environment due to its toxic effects. These metals are very reactive at low concentrations and can accumulate in the food web, causing severe public health concerns. Remediation using conventional physical and chemical methods is uneconomical and generates large volumes of chemical waste. Bioremediation of hazardous metals has received considerable and growing interest over the years. The use of microbial biosorbents is eco-friendly and cost effective; hence, it is an efficient alternative for the remediation of heavy metal contaminated environments. Microbes have various mechanisms of metal sequestration that hold greater metal biosorption capacities. The goal of microbial biosorption is to remove and/or recover metals and metalloids from solutions, using living or dead biomass and their components. This review discusses the sources of toxic heavy metals and describes the groups of microorganisms with biosorbent potential for heavy metal removal.
FINANCING THE SMALL BUSINESS

Since the time of Socrates a favorite means of analyzing a problem has been through the dramatic device of the dialogue. In exploring some of the problems arising in financing a small business, the authors believe that it will be helpful to use this time-honored approach. Since, however, we are dealing with practical everyday problems which require pragmatic solutions and not with the eternal verities, we will attempt, unlike Socrates, to answer our own questions. We ask the reader to imagine that he is in a lawyer's office when a fantastically successful client comes in to talk about a security issue. The client started in the world with tremendous energy and personality and a little capital. He started in a small way and has now become an industrialist. That is a terrifying term. What it means is a fellow who has expanded his business and become a great success. Lawyer and client reminisce over the various financial transactions which they have run through together; though they speak of events in the past, their answers will be the law of today as we understand it.
A Meta-Analysis of Time-Series Studies of Ozone and Mortality With Comparison to the National Morbidity, Mortality, and Air Pollution Study

Background: Although many time-series studies of ozone and mortality have identified positive associations, others have yielded null or inconclusive results, making the results of these studies difficult to interpret. Methods: We performed a meta-analysis of 144 effect estimates from 39 time-series studies, and estimated pooled effects by lags, age groups, cause-specific mortality, and concentration metrics. We compared results with pooled estimates from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS), a time-series study of 95 large U.S. urban centers from 1987 to 2000. Results: Both meta-analysis and NMMAPS results provided strong evidence of a short-term association between ozone and mortality, with larger effects for cardiovascular and respiratory mortality, the elderly, and current-day ozone exposure. In both analyses, results were insensitive to adjustment for particulate matter and model specifications. In the meta-analysis, a 10-ppb increase in daily ozone at single-day or 2-day average of lags 0, 1, or 2 days was associated with an 0.87% increase in total mortality (95% posterior interval = 0.55% to 1.18%), whereas the lag 0 NMMAPS estimate is 0.25% (0.12% to 0.39%). Several findings indicate possible publication bias: meta-analysis results were consistently larger than those from NMMAPS; meta-analysis pooled estimates at lags 0 or 1 were larger when only a single lag was reported than when estimates for multiple lags were reported; and heterogeneity of city-specific estimates in the meta-analysis were larger than with NMMAPS. Conclusions: This study provides evidence of short-term associations between ozone and mortality as well as evidence of publication bias.
Bidirectional flyback inverter with low output voltage THD

This paper develops a single-phase voltage source inverter mainly containing a high frequency flyback bidirectional DC-DC converter - as a previous stage, and a full-bridge module. The flyback bidirectional converter generates a rectified sinusoidal voltage waveform across the output capacitor. The full bridge transistors switch two times in one AC period in order to transform the output capacitor voltage in an AC waveform. The converter ensures also galvanic insulation between input and output, and a possible high conversion voltage ratio given by transformer. A state-space averaging model for the proposed converter was used for stability analysis and to design a tracking controller for output capacitor voltage. Digital simulations validate inverter proper operations and a low output voltage THD value.
Smart composition of reusable software components in mobile application product lines

Mobile application development opens up several challenges to developers. Among these challenges, possibly the most important one is the porting of applications to the heterogeneous devices available on the market. This requires mobile developers to create and maintain several versions of their applications in order to deal with particular features of each platform, including display size, development libraries, sensors, keypad layout, etc. The Software Product Lines (SPL) approach seems to be an useful technique to support mobile application development. A way to make SPL more effective is automating the software components composition for building mobile applications. We present a software infrastructure called AppSpotter that enables the dynamic and automated composition of software components of mobile applications taking into account the particular features of each mobile device. By means of the devices features, AppSpotter determines the components selection and composition of them to build customized mobile applications.
Mode adaptive reference frame denoising for high fidelity compression in HEVC

A new video coding standard, High Efficiency Video Coding (HEVC), is currently under development. In this paper we propose two relatively low-complex adaptive Wiener schemes for efficient P-frame coding of noisy videos with HEVC. In the proposed in-loop denoising framework the reference frame is noise filtered for P-frame prediction. The introduced algorithms adapt to the HEVC coding structure and thus can efficiently model the noise within the reference frame. The simulation results show that on the one hand considerable compression gains can be achieved using the proposed in-loop denoising framework. On the other hand the developed algorithms decrease the encoder runtime, but at the same time increase the decoder runtime.
Active learning and effort estimation: Finding the essential content of software effort estimation data

Background: Do we always need complex methods for software effort estimation (SEE)? Aim: To characterize the essential content of SEE data, i.e., the least number of features and instances required to capture the information within SEE data. If the essential content is very small, then 1) the contained information must be very brief and 2) the value added of complex learning schemes must be minimal. Method: Our QUICK method computes the euclidean distance between rows (instances) and columns (features) of SEE data, then prunes synonyms (similar features) and outliers (distant instances), then assesses the reduced data by comparing predictions from 1) a simple learner using the reduced data and 2) a state-of-the-art learner (CART) using all data. Performance is measured using hold-out experiments and expressed in terms of mean and median MRE, MAR, PRED(25), MBRE, MIBRE, or MMER. Results: For 18 datasets, QUICK pruned 69 to 96 percent of the training data (median = 89 percent). K = 1 nearest neighbor predictions (in the reduced data) performed as well as CART's predictions (using all data). Conclusion: The essential content of some SEE datasets is very small. Complex estimation methods may be overelaborate for such datasets and can be simplified. We offer QUICK as an example of such a simpler SEE method.
Advance Detour Strategy for Geographic Routing in Wireless Sensor Networks

Location-based routing protocols are known to have high efficiency, robustness and scalability are suitable to be deployed in wireless sensor networks (WSNs). Greedy Forwarding algorithm is an attractive localized routing scheme for WSNs, but the routing void problem is inevitable due to various actual geographical environments, e.g., puddles obstacles, uneven energy consumption or even physical destruction. In order to solve this problem, an advance detour strategy was proposed. If routing void problem appears, detour strategy is adopted. This method can advance detour routing void area, reduce the energy consumptions of nodes. The simulation results show that the strategy is superior to other protocols in terms of packet delivery delay, short routing distance and energy consumptions, adapt to rapid changes network topology dynamic situation.
Optimization of Incremental Queries in the Cloud

—Database and model queries are the foundations of data-driven applications. Their performance is of primary importance in model-driven software engineering (MDE), especially with the evergrowing complexity of software modeling projects. To address the scalability issues of traditional MDE tools, distributed frameworks are being developed – however, query optimization in a distributed context brings a whole new set of challenges, including capacity limits of individual nodes and network communication. In this paper, we aim to address the allocation optimization challenge in the context of distributed incremental query evaluation. Our methods are based on a combination of heuristics-based resource consumption estimations and constraint satisfaction programming. We evaluate the impact of the optimization techniques by conducting benchmark measurements.
A survey of a pampas deer, Ozotoceros bezoarticus leucogaster (Arctiodactyla, Cervidae), population in the Pantanal wetland, Brazil, using the distance sampling technique

A survey of a pampas deer, Ozotoceros bezoarticus leucogaster (Arctiodactyla, Cervidae), population in the Pantanal wetland, Brazil, using the distance sampling technique. � The pampas deer is an endangered South American species which occurs in open grasslands and savannas. This aim of this survey was to evaluate the use of the distance sampling technique to estimate densities of the species in the Pantanal wetland, as well as to analyze the applicability of the method for a monitoring program. The surveys were conducted on roads from vehicles and also on foot along 26 parallel transects in November 1999 and 2000 at Campo Dora ranch, south-central Pantanal, Brazil. Deer densities were estimated using the program DISTANCE, and the program MONITOR was used to run a power analysis to estimate the probability of detection of a decline in the population. The deer density estimated from vehicles, with data from both years, was 9.81±3.8 individual/km2, and 5.53±0.68 individuals/km2 from transects sampled on foot. The power analysis of these data revealed a monitoring program would require at least two surveys per year over seven years to obtain a 90% chance of detecting a 5% decline in the population. Our results also indicate surveys from roads are not recommended for pampas deer counts as the animals appear to keep a relatively safe distance from cars.
Peroxynitrite Reduces Vasodilatory Responses to Reduced Intravascular Pressure, Calcitonin Gene-Related Peptide, and Cromakalim in Isolated Middle Cerebral Arteries

Vasodilatory responses to progressive reductions in intravascular pressure or to calcitonin gene-related peptide (CGRP) or cromakalim were determined in rodent middle cerebral arteries (MCAs) before and after treatment with peroxynitrite (ONOO−). Middle cerebral artery diameters in isolated, pressurized MCAs were measured as intravascular pressure was reduced from 100 to 20 mm Hg in 20-mm Hg increments before and after inactive ONOO−, pH-adjusted ONOO−, or 10, 20, or 40 μmol/L ONOO− was added to the bath. In other MCAs, responses to CGRP (1 × 10−9 −5 × 10−8) or cromakalim (3 × 10−8 −8 × 10−7) were measured before and after the addition of 25 μmol/L ONOO−. Inactive ONOO− (n = 6, P = 0.40), pH-adjusted ONOO− (n = 6, P = 0.29), and 10 μmol/L ONOO− (n = 6, P = 0.88) did not reduce vasodilatory responses to reduced intravascular pressure. Middle cerebral arteries treated with 20 (n = 6, P < 0.0001) and 40 (n = 6, P > 0.0001) μmol/L ONOO− constricted significantly when intravascular pressure was reduced. Vasodilatory responses to CGRP or cromakalim were reduced by ONOO− (P > 0.02, n = 6 and P > 0.01, n = 7, respectively). ONOO− had no effect on vasoconstriction in response to serotonin or vasodilation in response to KCl. These studies demonstrate that ONOO− reduces multiple cerebral vasodilatory responses.
SemFS : A Semantic approach to File Systems

Hard Disk capacity is increasing all the time. This has brought with it a new problem; the task of locating files is getting harder by the day. Retrieving a document from the myriad of files and directories is no longer an easy task. SemFS integrates searching of files based on metadata as a basic function of the file system. SemFS provides Virtual Directories which list the results of a query. The contents of the Virtual Directory are formed at runtime. Virtual Directories are used mainly to facilitate the searching of files. This can also be used by plugins to provide interfaces for accessing the functionality of other processes through the file system.
Bc Meson Spectrum and Hyperfine Splittings in the Shifted Large-N-Expansion Technique

In the framework of potential models for heavy quarkonium, we compute the mass spectrum of the bottom-charmed Bc meson system and spin-dependent splittings from the Schrodinger equation using the shifted-large-N expansion technique. The masses of the lightest vector and pseudoscalar Bc states as well as the higher states below the threshold are estimated. Our predicted result for the ground state energy is MeV and are generally in exact agreement with earlier calculations. Calculations of the Schrodinger energy eigenvalues are carried out up to the third order of the energy series. The parameters of each potential are adjusted to obtain best agreement with the experimental spin-averaged data (SAD). Our findings are compared with the observed data and with the numerical results obtained by other numerical methods.
Architecture-Based Software Reliability Prediction Approach for Component Based Software

Computer software is playing central role in our daily life. Most of industries in various disciplines depend on computer software for their basic functioning. The industries in these disciplines always request high-quality software. The quality of software depends on certain attributes which include reliability, dependability, usability, flexibility, performance, safety, interoperability and security. The reliability attribute is prioritized as the most important quality attributes. Currently, the challenge being faced by reliability is how it can be conducted at the design’s time before the system implementation, while the sources of information for the reliability are limited. Two major problems are, non-availability of technical data about the failure, and the operational profile is not developed yet. This paper defines the whole elements that are needed by the reliability prediction approach of component based software. The research focuses in proposing an initial work of probabilistic dependency graph models as part of the approach. The graph and the parameters are employed as part of the prediction approach. The graph represents and links the system components and their internal states through a set of parameters. Keywords—Reliablity Predection, software architecture, components software.
Exchange rate misalignment and Producer Support Estimates (PSEs) of China

This paper examines the effects of exchange rate misalignment on the agricultural Producer Support Estimates (PSEs) of China. Based on several time series techniques, the equilibrium exchange rate of the Chinese yuan and the corresponding misalignment of the actual rate are estimated and applied to PSE calculations. Our results show that the exchange rate has been significantly undervalued in recent years with subsequent indirect effects on the PSEs. Our model forecasts future appreciations and indicates a slow but uneven process of convergence towards long-run exchange rate equilibrium, which could inflict persistent and sometimes steep adjustment pressure on China’s agricultural sector. We find a high pass-through of exchange rate movements to domestic agricultural prices, so that correction of exchange rate misalignment through appreciations would worsen production incentives to Chinese farmers.
The twentieth‐century pluvial in the western United States

Persistent, widespread wet conditions in the western United States in the early twentieth century have been noted in a number of studies. Here, we investigate the character of this pluvial, which covered a roughly 9‐state region and lasted about 13 years. Paleoclimatic data used to evaluate the period in a long‐term context indicate that the twentieth‐century pluvial is an extremely rare event, as previous studies have suggested, even when assessed in the context of a 1186‐year reconstruction of regional drought. An analysis of twentieth‐century climate data, characterizing precipitation seasonality, intensity, and frequency, shows that the pluvial was primarily a result of winter season, heavy to moderately heavy precipitation events, during a handful of extremely wet winters. Temperatures were also anomalously cool. The combination of duration, intensity, and spatial extent make this an unusual event, not only in twentieth century, but in the past 12 centuries.
Connectivity of Pathology: The Olfactory System as a Model for Network-Driven Mechanisms of Alzheimer’s Disease Pathogenesis

The pathogenesis of Alzheimer’s disease (AD) has been postulated to preferentially impact specific neural networks in the brain. The olfactory system is a well-defined network that has been implicated in early stages of the disease, marked by impairment in olfaction and the presence of pathological hallmarks of the disease, even before clinical presentation. Discovering the cellular mechanisms involved in the connectivity of pathology will provide insight into potential targets for treatment. We review evidence from animal studies on sensory alteration through denervation or enrichment, which supports the notion of using the olfactory system to investigate the implications of connectivity and activity in the spread of pathology in AD.
Calibration of the Volatility Surface

This thesis consists of two parts, one concerning implied volatility and one concerning local volatility. The SABR model and SVI model are investigated to model implied volatility. The performance of the two models were tested on the Eurcap market in March 2008. Two ways of extracting local volatility are reviewed by a test performed on data from European options based on the S&P 500 index. The rst method is a way of solving regularized Dupire's equation and the other one is based on nding the most likely path . Acknowledgements I would like to thank Robert Thorén and his coworkers at Algorithmica Research AB for guiding me during my work. I am also grateful to Professor Anders Forsgren at KTH, who has been my tutor.