Miracle-dz/UniFAR-FTUs huggingface dataset:
Relative source location using coda-wave interferometry: Method, code package, and application to mining-induced earthquakes

A wide range of applications requires the relative locations of sources of energy to be known accurately. Most conventional location methods are either subject to errors that depend strongly on inaccuracy in the model of propagation velocity used or demand a well-distributed network of surrounding seismic stations to produce reliable results. A new source location method based on coda-wave interferometry (CWI) is relatively insensitive to the number of seismic stations and to the source-to-station azimuthal coverage. Therefore, it opens new avenues for research, for applications in areas with unfavorable recording geometries, and for applications that require a complementary method. This method uses CWI to estimate distances between pairs of seismic events with a similar source mechanism recorded at the same station. These separation estimates are used to solve for the locations of clusters of events relative to one another within a probabilistic framework through optimization. It is even possible to find the relative locations of clusters of events with one single-channel station. Given these advantages, it is likely that one reason that the method is not used more widely is the lack of reliable code that implements this multistage method. Therefore, we have developed a well-commented MATLAB code that does so, and we evaluate examples of its applications. It can be used with seismic data from a single-station channel, and it enables data recorded by different channels and stations to be used simultaneously. It is therefore possible to combine data from permanent yet sparse networks and from temporary arrays closer to the source region. We use the code to apply the location method to a selected data set of the New Ollerton earthquakes in England to demonstrate the validity of the code. The worked example is provided within the package. A way to assess the quality of the location results is also provided.
Human Nutrition and Metabolism Addition of Eicosapentaenoic Acid to g-Linolenic Acid – Supplemented Diets Prevents Serum Arachidonic Acid Accumulation in Humans 1

Previous studies reveal that supplementation of human diets with g-linolenic acid (GLA) reduces the generation of lipid mediators of inflammation and attenuates clinical symptoms of chronic inflammatory disorders such as rheumatoid arthritis. However, we have shown that supplementation with this same fatty acid also causes a marked increase in serum arachidonate (AA) levels, a potentially harmful side effect. The objective of this study was to design a supplementation strategy that maintained the capacity of GLA to reduce lipid mediators without causing elevations in serum AA levels. Initial in vitro studies utilizing HEP-G2 liver cells revealed that addition of eicosapentaenoic acid (EPA) blocked D-5-desaturase activity, the terminal enzymatic step in AA synthesis. To test the in vivo effects of a GLA and EPA combination in humans, adult volunteers consuming controlled diets supplemented these diets with 3.0 g/d of GLA and EPA. This supplementation strategy significantly increased serum levels of EPA, but did not increase AA levels. EPA and the elongation product of GLA, dihomo-g-linolenic acid (DGLA) levels in neutrophil glycerolipids increased significantly during the 3-wk supplementation period. Neutrophils isolated from volunteers fed diets supplemented with GLA and EPA released similar quantities of AA, but synthesized significantly lower quantities of leukotrienes compared with their neutrophils before supplementation. This study revealed that a GLA and EPA supplement combination may be utilized to reduce the synthesis of proinflammatory AA metabolites, and importantly, not induce potentially harmful increases in serum AA levels. J. Nutr. 130: 1925–1931, 2000.
DISCRETE-TIME SLIDING MODE CONTROL WITH INTEGRAL COMPENSATION OF OUTPUT ERROR Summary

In this paper, a simple new design method of the sliding mode control based on the integral compensation of an output error is described. The key to this method is to obtain a control with a switching function. The proposed linear control input is robust against plant parameter deviations and external disturbances. We confirmed the effectiveness of the proposed method through simulation of a second and a third order plant.
Delay-time distribution in the scattering of time-narrow wave packets. (I)

This is the first of two subsequent publications where the probability distribution of delay-times in scattering of wave packets is discussed. The probability distribution is expressed in terms of the on-shell scattering matrix, the dispersion relation of the scattered beam and the wave packet envelope. In the monochromatic limit (poor time resolution) the mean delay-time coincides with the expression derived by Eisenbud and Wigner and generalized by Smith more than half a century ago. In the opposite limit, and within the semi-classical approximation, the resulting distribution coincides with the result obtained using classical mechanics or geometrical optics. The general expression interpolates smoothly between the two extremes. An application for the scattering of electromagnetic waves in networks of RF transmission lines will be discussed in the next paper to illustrate the method in an experimentally relevant context.
Human immunodeficiency virus type 1 interaction with the membrane of CD 4 ÷ cells induces the synthesis and nuclear translocation of 70 K heat shock protein

In the last few years a growing body of experimental evidence has indicated that the interaction of human immunodeficiency virus type 1 (HIV-1) surface glycoprotein (gpl20) with the membrane ofCD4 + cells may deliver negative signals, eventually leading to programmed cell death (apoptosis) of either mature CD4 + lymphocytes or CD34 ÷ haematopoietic progenitor cells, in the absence of cell infection with HIV-1. However, information on the possible activation of the classical signal transduction pathway through gpl20 engagement of cell surface CD4 is contradictory. Heat shock proteins (hsp) or' stress' proteins' are involved in protecting cells from the deleterious effects of heat and other stresses and perform various cell roles. In mammalian cells there is evidence that hsp70 is involved in the transport of proteins to lysosomes, mitochondria and the nucleus. The results obtained in our study demonstrate that early (3 h) after the exposure of permissive CD4 + cells to HIV1 (or to purified recombinant gpl20) a peak of increased synthesis and nuclear translocation of a 70K hsp (and possibly other proteins) is observed. These data indicate that gpl20 possesses the capacity to trigger a cascade of events through a transmembrane signalling activity.
Child Abuse & Neglect omparing physically abusive , neglectful , and non-maltreating parents uring interactions with their children : A meta-analysis of bservational studies

Objective: To clarify the nature and extent of differences in the ways that physically abusive, neglectful, and non-maltreating parents communicate during interactions with their children. Method: A meta-analysis was conducted of 33 observational studies comparing parent–child interactions in families where parents have a documented history of physical abuse or neglect vs. where parents have no history of child maltreatment. Parental behaviors were grouped into three clusters (positivity, aversiveness, and involvement) for comparison across studies. Results: When comparing maltreating (physically abusive or neglectful) vs. nonmaltreating parents, mean weighted effect sizes for the three behavioral clusters range from d = . 46 to . 62. Physically abusive parents are distinguished from non-maltreating parents more so than neglectful parents in terms of aversive behavior, whereas the reverse is true for involvement. Publication date, parent and child age, and task structure moderate the magnitude, though not direction, of differences. Conclusion: Parents with a documented history of child physical abuse or child neglect also are distinguished from non-maltreating parents by the levels of aversiveness, positivity, and involvement they display during interactions that constitute the parent–child relationship. Practice implications: Researchers and practitioners need to carefully consider sample size, length and setting of observation, and interaction tasks when using observational methods. © 2008 Elsevier Ltd. All rights reserved.
Explorer Psip 1 / Ledgf p 75 restrains Hox gene expression by recruiting both trithorax and polycomb group proteins

Trithorax and polycomb group proteins are generally thought to antagonize one another. The trithorax family member MLL (myeloid/lymphoid or mixedlineage leukemia) is presumed to activate Hox expression, counteracting polycomb-mediated repression. PC4 and SF2 interacting protein 1 (PSIP1)/p75, also known as LEDGF, whose PWWP domain binds to H3K36me3, interacts with MLL and tethers MLL fusion proteins to HOXA9 in leukaemias. Here we show, unexpectedly, that Psip1/p75 regulates homeotic genes by recruiting not only MLL complexes, but also the polycomb group protein Bmi1. In Psip1−/− cells binding of Mll1/2, Bmi1 and the co-repressor Ctbp1 at Hox loci are all abrogated and Hoxa and Hoxd mRNA expression increased. Our data not only reveal a potential mechanism of action for Psip1 in the regulation of Hox genes but also suggest an unexpected interplay between proteins usually considered as transcriptional activators and repressors.
Evaluation of selected physical and microbiological parameters of air in a box-stall stable

The aim of the study was to evaluate selected physical and microbiological air parameters. The analysis was conducted during the spring, summer, fall and winter in a box-stall stable with Wielkopolski horses. The physical air parameters were measured according to generally established methods used in livestock science. The air was evaluated for microbial contamination by the impaction method; 12 samplings were carried out using a SAS 100 sampler located in three sampling sites of the stable: the initial, middle, and end part of the building. The numbers of the following microbes were determined in the analyzed air: total bacteria, Enterobacteriaceae cells, streptococci, mannitol positive staphylococci, hemolytic bacteria, actinomycetes and total molds and yeast-like fungi. Measurements of temperature and humidity parameters showed that the average air temperature in the stables was lowest in the winter, 8.2°C with humidity 76.2%, whereas the highest average air temperatures, which averaged 21.2°C with the lowest relative humidity of 60.2%, were recorded in the summer. The other air physical parameters corresponded to the minimum requirements for horses. Microbiological analyses of air samples revealed the presence of bacteria belonging to the Enterobacteriaceae family, staphylococci, streptococci, as well as fungi that can adversely affect the health of horses and people in the stables. We the found air microbial contamination above the standard level, and it depended on microclimate conditions and the season.
Application of automatic speech recognition technologies to singing

The research field of Music Information Retrieval is concerned with the automatic analysis of musical characteristics. One aspect that has not received much attention so far is the automatic analysis of sung lyrics. On the other hand, the field of Automatic Speech Recognition has produced many methods for the automatic analysis of speech, but those have rarely been employed for singing. This thesis analyzes the feasibility of applying various speech recognition methods to singing, and suggests adaptations. In addition, the routes to practical applications for these systems are described. Five tasks are considered: Phoneme recognition, language identification, keyword spotting, lyrics-to-audio alignment, and retrieval of lyrics from sung queries. The main bottleneck in almost all of these tasks lies in the recognition of phonemes from sung audio. Conventional models trained on speech do not perform well when applied to singing. Training models on singing is difficult due to a lack of annotated data. This thesis offers two approaches for generating such data sets. For the first one, speech recordings are made more “song-like”. In the second approach, textual lyrics are automatically aligned to an existing singing data set. In both cases, these new data sets are then used for training new acoustic models, offering considerable improvements over models trained on speech. Building on these improved acoustic models, speech recognition algorithms for the individual tasks were adapted to singing by either improving their robustness to the differing characteristics of singing, or by exploiting the specific features of singing performances. Examples of improving robustness include the use of keyword-filler HMMs for keyword spotting, an i-vector approach for language identification, and a method for alignment and lyrics retrieval that allows highly varying durations. Features of singing are utilized in various ways: In an approach for language identification that is well-suited for long recordings; in a method for keyword spotting based on phoneme durations in singing; and in an algorithm for alignment and retrieval that exploits known phoneme confusions in singing.
ITERATING SYMMETRIC EXTENSIONS

Abstract The notion of a symmetric extension extends the usual notion of forcing by identifying a particular class of names which forms an intermediate model of $ZF$ between the ground model and the generic extension, and often the axiom of choice fails in these models. Symmetric extensions are generally used to prove choiceless consistency results. We develop a framework for iterating symmetric extensions in order to construct new models of $ZF$. We show how to obtain some well-known and lesser-known results using this framework. Specifically, we discuss Kinna–Wagner principles and obtain some results related to their failure.
Building reconstruction from airborne laser scanning data

The research on building model reconstruction has been a long-term hot topic in both the photogrammetry and computer vision areas. The airborne laser scanning technique provides new opportunities for building model reconstruction. Despite many investigations on building reconstruction using point clouds, there are still many unresolved problems that need further research, especially fully automatic methods and intelligent user-friendly operations. This article surveys the methods, tools and problems of building model reconstruction using point clouds data. The article also points out some important but unnoticed problems in building reconstruction according to our previous experience. We hope our comments article can be helpful for researchers in understanding their position and for new researcher in acquiring general information.
Efficient encrypted image retrieval in IoT-cloud with multi-user authentication

Encryption is one of the best methods to safeguard the security and privacy of an image. However, looking through encrypted data is difficult. A number of techniques for searching encrypted data have been devised. However, certain security solutions may not be used in smart devices in IoT-cloud because such solutions are not lightweight. In this article, we present a lightweight scheme that can enable a content-based search through encrypted images. In particular, images are represented using local features. We develop and validate a secure scheme for measuring the Euclidean distance between two feature vectors. In addition, we use a hashing method, namely, locality-sensitive hashing, to devise the searchable index. The use of an locality-sensitive hashing index increases the proficiency and effectiveness of a system, thereby allowing the retrieval of only relevant images with a minimum number of distance evaluations. Refining vector techniques are used to refine relevant results efficiently and securely. Our index construction process ensures that stored data and trapdoors are kept private. Our system also efficiently supports multi-user authentication by avoiding the expensive traditional method, which enables data owners to define who can search for a specific image. Compared with other similarity-based encryption methods predicated upon searchability, the option presented in this study offers superior search speed and storage efficiency.
Ahead-of-time algebraic compilation for safety-critical Java

In recent years Java has been increasingly considered as a language for safety-critical embedded systems. However, some features of Java are unsuitable for such systems. This has resulted in the creation of Safety-Critical Java (SCJ), which facilitates the development of certifiable real-time and embedded Java programs. SCJ uses different scheduling and memory management models to standard Java, so it requires a specialised virtual machine (SCJVM). A common approach is to compile Java bytecode program to a native language, usually C, ahead-of-time for greater performance on low-resource embedded systems. Given the safety-critical nature of the applications, it must be ensured that the virtual machine is correct. However, so far, formal verification has not been applied to any SCJVM. This thesis contributes to the formal verification of SCJVMs that utilise ahead-of-time compilation by presenting a verification of compilation from Java bytecode to C. The approach we adopt is an adaptation of the algebraic approach developed by Sampaio and Hoare. We start with a formal specification of an SCJVM executing the bytecodes of a program, and transform it, through the application of proven compilation rules, to a representation of the target C code. Thus, our contributions are a formal specification of an SCJVM, a set of compilation rules with proofs, and a strategy for applying those compilation rules. Our compilation strategy can be used as the basis for an implementation of an ahead-of-time compiling SCJVM, or verification of an existing implementation. Additionally, our formal model of an SCJVM may be used as a specification for creating an interpreting SCJVM. To ensure the applicability of our results, we base our work on icecap, the only currently available SCJVM that is open source and up-to-date with the SCJ standard.
A novel GIS-based decision-making framework for the school bus routing problem

The school bus routing problem (SBRP) is a central issue in transportation planning and optimization systems. SBRP seeks to plan an efficient schedule for a fleet of school buses where each bus picks up students from various bus stops and delivers them to their designated schools while satisfying various constraints such as the maximum capacity of a bus, and the time window of a school. Due to its inherent complexity, many heuristics have been proposed to solve this combinatorial problem in an effective way. In this paper, a novel geographic information systems (GIS)-based decision-making framework that combines GIS, clustering techniques, network cutting techniques, and a hybrid ant colony optimization metaheuristic with the iterated Lin–Kernighan local improvement heuristic is proposed for solving the SBRP as a split delivery vehicle routing problem (SDVRP). Experiments were conducted for evaluating the proposed framework by comparing the results for solving 11 routing problems using both the proposed decision-making framework and ArcGIS 9.2 Network Analyst which uses the greedy Dijkstra’s algorithm. The reported results of the proposed framework generally outperform that of the ArcGIS Network Analyst. In addition, the proposed decision-making framework was applied to solve a real life SBRP to demonstrate its application.
A Systematic Mapping Study on Soft Skills in Software Engineering

To participate in software development projects, team members may need to perform different roles and be skilled in diverse methodologies, tools and techniques. However, other skills, usually known as “soft skills” are also necessary. We report the results of a systematic mapping study to identify existing research on soft skills in software engineering and to determine what soft skills are considered relevant to the practice of software engineering. After applying an explicit mapping protocol, 44 papers were finally selected, and 30 main categories of soft skills were identified. At least half of the studies selected mention five skills: communication, teamwork, analytical, organizational, and interpersonal skills. We also identified the data collection methods commonly used for research on this topic: job advertisements and surveys were the main ones. The results of this work are of interest to researchers in human aspects of software engineering, to those responsible for Human Resource in software development companies, and to curriculum designers in careers related to software engineering and development.
Shapelet transforms for univariate and multivariate time series classification

Time Series Classification (TSC) is a growing field of machine learning research. One particular algorithm from the TSC literature is the Shapelet Transform (ST). Shapelets are a phase independent subsequences that are extracted from times series to form discriminatory features. It has been shown that using the shapelets to transform the datasets into a new space can improve performance. One of the major problems with ST, is that the algorithm is O(n2m4), where n is the number of time series and m is the length of the series. As a problem increases in sizes, or additional dimensions are added, the algorithm quickly becomes computationally infeasible. The research question addressed is whether the shapelet transform be improved in terms of accuracy and speed. Making algorithmic improvements to shapelets will enable the development of multivariate shapelet algorithms that can attempt to solve much larger problems in realistic time frames. In support of this thesis a new distance early abandon method is proposed. A class balancing algorithm is implemented, which uses a one vs. all multi class information gain that enables heuristics which were developed for two class problems. To support these improvements a large scale analysis of the best shapelet algorithms is conducted as part of a larger experimental evaluation. ST is proven to be one of the most accurate algorithms in TSC on the UCR-UEA datasets. Contract classification is proposed for shapelets, where a fixed run time is set, and the number of shapelets is bounded. Four search algorithms are evaluated with fixed run times of one hour and one day, three of which are not significantly worse than a full enumeration. Finally, three multivariate shapelet algorithms are developed and compared to benchmark results and multivariate dynamic time warping.