Miracle-dz/UniFAR-FTUs huggingface dataset:
CERIAS Tech Report 2004-48 PROVIDING PROCESS ORIGIN INFORMATION TO AID IN COMPUTER FORENSIC INVESTIGATIONS by Florian Buchholz and Clay Shields Center for Education and Research in Information Assurance and Security, Purdue University, West Lafayette, IN 47907-2086 Providing Process Origin Informati

The number of computer attacks has been growing dramatically as the Internet has grown. Attackers currently have little or no disincentive to conducting attacks because they are able to hide their location effectively by creating a chain of connections through a series of hosts. This method is effective because most current host audit systems do not maintain enough information to allow association of incoming and outgoing network connections. In this paper, we introduce an inexpensive method that allows both on-line and forensic matching of incoming and outgoing network traffic. Our method makes small modifications to the operating system that associate origin information with each process in the system process table, and enhances the audit information by logging the origin and destination of network sockets. We present implementation results, show that our method can effectively record origin information about a variety of attacks, and describe the limitations of our approach.
On postulates for general quantum mechanics

A collection of postulates for the observable quantities in a general quantum mechanical system has been given by Segal, [4]. In this system, the observables form a real Banach space S which is partially ordered by a closed convex positive cone P, and which has a unit element e interior to the positive cone, all satisfying Pf(e-P) =S1(e)CSi(0), where Sr(x) is the solid sphere of radius r, center x. Alternatively, S is a partially ordered linear space with an element e>O which is a Banach space under the norm llxi =min {X: -Xe ? x <Xe }, where the minimum is attained. Let us call such a space a partially ordered Banach space with unit. We shall show that any such Banach space S with order unit e can be given the algebraic structure postulated by Segal, in possibly different ways. In this proof it is very useful to have an alternative formulation of Segal's postulates stated in terms of the partial ordering alone. We are then able to give examples of such systems with various pathologies and to classify the three dimensional ones. Finally we shall give a necessary and sufficient condition that a system of operators satisfying these postulates be a C* special Jordan algebra: the system of hermitean elements of a C* algebra. DEFINITION. A spectral function L on a partially ordered Banach space S with order unit e is a function assigning to each point x ES a
Pathomechanics of Post-Traumatic OA Development in the Military Following Articular Fracture

Abstract : The objective of the proposed research is to develop new models for predicting the risk of post-traumatic osteoarthritis (PTOA) following intra-articular fracture (IAF). Aim 1, pursued this year, involves evaluating pre- and post-treatment CT data from patients with combat-related IAFs to measure fracture severity and post-reduction contact stress exposure. We first established a CRADA between the University of Iowa and the U.S. Army Institute of Surgical Research (USAISR). Then IRB approval for access to the patient data from the military medical record was obtained. Our partner at USAISR is screening the DoDTR to identify and enroll subjects. The imaging data for 42 subjects were forwarded to Iowa for analysis, with another 16 subjects identified and their imaging studies requested. As part of an unrelated grant from the NIH, civilian patient data were equivalently analyzed this year, which required refining existing methodologies. Analysis was completed for 31 tibial plafond, 61 tibial plateau, and 17 intra-articular calcaneal fracture cases. We published two papers based on results from those civilian data. Success in analyzing these cases supports our belief that we will be successful in analyzing military CT scan data as they become available.
Copper, lead and cadmium loads and behavior in urban stormwater runoff in Curitiba, Brazil

We investigate the presence and behavior of Cu, Pb, and Cd in runoff waters from a residential area located in the city of Curitiba, Brazil. Samples were collected in twenty-one stormwater events in an intermediate traffic way located in the Bacacheri watershed. Metal concentrations were similar to range values compiled worldwide and followed the order: Pb>Cu>>Cd. Unit loads were estimated to the watershed, which cover an area of 30 km2, revealing values of 1520, 950, 25 kg for Pb, Cu, and Cd, respectively. Among the three metals, lead showed the greatest affinity for the suspended solids (82%) followed by Cd (66%) and Cu (48%). Meanwhile, an association of the metals with the organic matter in the dissolved phase, following the order Cu>Pb>Cd. Metal loads and behavior in urban runoff also depends on factors such as the first flush and the dry period preceding a storm event.
Real-Time Predictive Modeling of Key Quality Characteristics Using Regularized Regression : SAS ® Procedures GLMSELECT and LASSO

This paper describes the merging of designed experiments and regularized regression to find the significant factors to use for a real-time predictive model. The real-time predictive model is used in a Weyerhaeuser modified fiber mill to estimate the value of several key quality characteristics. The modified fiber product is accepted or rejected based on the model prediction or the predicted values deviation from lab tests. To develop the model, a designed experiment was needed at the mill. The experiment was planned by a team of engineers, managers, operators, lab techs, and a statistician. The data analysis used the actual values of the process variables manipulated in the designed experiment. There were instances of the set point not being achieved or maintained for the duration of the run. The lab tests of the key quality characteristics were used as the responses. The experiment was designed with JMP® 64-bit Edition 11.2. 0 and estimated the two-way interactions of the process variables. It was thought that one of the process variables was curvilinear and this effect was also made estimable. The LASSO method, as implemented in the SAS® GLMSELECT procedure, was used to analyze the data after cleaning and validating the results. Cross validation was used as the variable selection operator. The resulting prediction model passed all the predetermined success criteria. The prediction model is currently being used real time in the mill for product quality acceptance.
Fast approximate simulation of seismic waves with deep learning

We simulate the response of acoustic seismic waves in horizontally layered media using a deep neural network. In contrast to traditional finite-difference modelling techniques our network is able to directly approximate the recorded seismic response at multiple receiver locations in a single inference step, without needing to iteratively model the seismic wavefield through time. This results in an order of magnitude reduction in simulation time from the order of 1 s for FD modelling to the order of 0.1 s using our approach. Such a speed improvement could lead to real-time seismic simulation applications and benefit seismic inversion algorithms based on forward modelling, such as full waveform inversion. Our proof of concept deep neural network is trained using 50,000 synthetic examples of seismic waves propagating through different 2D horizontally layered velocity models. We discuss how our approach could be extended to arbitrary velocity models. Our deep neural network design is inspired by the WaveNet architecture used for speech synthesis. We also investigate using deep neural networks for simulating the full seismic wavefield and for carrying out seismic inversion directly.
Differences in Perceived Benefit, Use, and Learner Satisfaction between Open Source LMS and Proprietary LMS

Currently, many institutions are using expensive proprietary learning management systems (LMSs). Open source LMSs have been introduced to offer affordable solutions; however, these solutions have not been fully embraced. The researchers undertook a study to examine the differences between these two types of LMSs. This study used a survey to collect data pertaining to perceived benefit, LMS use, and learner satisfaction. The survey sample comprised 608 information technology (IT) major undergraduates from two Malaysian universities. Two groups were set up based on the LMSs used, where the first group (n = 290) and the second group (n = 318) used the proprietary and open source solutions, respectively. Students were asked to fill out a questionnaire to elicit their opinions concerning constructs perceived benefit, use, and learner satisfaction, and data were analyzed using SPSS (ver. 19). Independent sample t-tests were performed, indicating that there were significant differences in the three constructs, which favored the open source solution. Correla‐ tional analysis showed that each construct correlated significantly with each other, suggesting that each contributes to the overall effectiveness of the system. These findings reinforce the imperative of deploying open source learning solutions that are not only affordable but also effective to support students’ needs for effective online learning.
Second-law-like inequalities with information and their interpretations

In a thermodynamic process with measurement and feedback, the second law of thermodynamics is no longer valid. In its place, various second-law-like inequalities have been advanced that each incorporate a distinct additional term accounting for the information gathered through measurement. We quantitatively compare a number of these information measures using an analytically tractable model for the feedback cooling of a Brownian particle. We find that the information measures form a hierarchy that reveals a web of interconnections. To untangle their relationships, we address the origins of the information, arguing that each information measure represents the minimum thermodynamic cost to acquire that information through a separate, distinct measurement procedure.
Banking Supervision: Quality and Governance

This paper examines the relationship between the quality of banking supervision and governance of the supervisory agency, based on assessments of the Basel Core Principles and the IMF Code on Transparency in Financial Policies, covering 116 and 53 countries, respectively, with 51 common to both. We find a positive correlation between the transparency of the supervisor and the effectiveness of banking supervision; moreover, better accountability and integrity practices of the banking supervisors are associated with higher independence, which in turn is associated with better compliance with the Basel Core Principles. These results are largely robust to different stages of financial development.
History and Applications of Hydrogels

Hydrogels have existed for more than half century, providing one of the earliest records of crosslinked hydroxyethyl methacrylate (HEMA) hydrogels. Today, hydrogels still fascinate material scientists and biomedical researchers and great strides have been made in terms of their formulations and applications. As a class of material, hydrogels are unique, they consist of a self-supporting, water-swollen three-dimensional (3D) viscoelastic network which permits the diffusion and attachment of molecules and cells. However, hydrogels have recently drawn great attention for use in a wide variety of biomedical applications such as cell therapeutics, wound healing, cartilage/bone regeneration and the sustained release of drugs. This is due to their biocompatibility and the similarity of their physical properties to natural tissue. This review aims to give an overview of the historic and the recent design concept of hydrogels and their several applications based on the old and the most recent publications in this field.
Gly→Ala Point Mutation and Conformation of Poly-Ala Stretch of PABPN1: A Molecular Dynamics Study

Single nucleotide replacing mutations in genes cause a number of diseases, but sometimes these mutations mimic other genetic mutations such as trinucleotide repeats expansions. A mutation in codon GGG→GCG results in Gly→Ala at the N-terminal of PABPN1 protein that mimics the trinucleotide repeat expansion disease called Oculopharyngeal muscular dystrophy (OPMD). Molecular dynamics simulations in water with peptide models having sequence Ac-A10-GA2GG-NHme (peptide A) and Ac-A10A3GG-NHme (peptide B) reveal an increase in the length of helical segment in peptide B. The α-helical length is found to be stable in peptide B with starting geometry of a right handed helix, while in the case peptide A, the helical length is short. The interactions of water molecules at terminals, side chain-backbone interactions and hydrogen bonds provide stability to resultant conformation. The adopted helix by the poly-Ala stretch may lead to masking some other active parts of the PABPN1 that may trigger the aggregation, decrease in degradation and/or impaired function of protein. Hence, further studies with N-terminal may be helpful to understand unclear disease mechanism.
A Novel Ontology Metric Approach for Code Clone Detection Using FusionTechnique

—Cloning of Code is effective way of identifying the faults in the software, code duplication has been a wide research area in the field of software engineering to identify clones and analysis the clones. Clones software is a region of source which give use to identify high similarity. The region of identity is named clones. Cloning of software is the regions in identifying the similarities in a software code, an identification of duplicate in a code are called clones, class clones, or pair clones. In our paper, we present a fusion method based on metric with a combination of text method in detection of clones and reporting it is proposed. The work of proposed is categorized into two different stages, selection of clone potential and clone potential comparing based on text comparison. The technique of proposed is detected using clones exact basis on match metric and text matches.
Much Ado About Text Content . Learning Text Types Solely by Structural Differentiae — Extended Abstract —

In text linguistics and related disciplines, textual units are distinguished in terms of their structure, content and function [6]. From a text technological point of view we may add the layout of texts apart from their logical document structure as a further starting-point of differentiation [3, 26]. These four reference points open different perspectives on text classification which are not necessarily orthogonal. Generally speaking, text classification belongs to explorative data analysis which aims at automatically dividing sets of objects into classes of maximum internal homogeneity and external heterogeneity. According to Bock [5], any such approach is related to at least five questions:
Locating the Starburst in the SCUBA Galaxy SMM J14011+0252

We present new, multiwavelength, high-resolution imaging of the luminous, submillimeter galaxy SMM J14011+0252, an interacting starburst at z = 2.56. Our observations comprise optical imaging from the Hubble Space Telescope, sensitive radio mapping from the Very Large Array, and CO observations from the Owens Valley Radio Observatory and Berkeley-Illinois-Maryland Association array. Aided by well-constrained gravitational amplification, we use these new data to map the distribution of gas and both obscured and unobscured starlight. The maps show that the gas and star formation are extended on scales of ≳10 kpc, much larger than starbursts seen in local ultraluminous galaxies and larger than the rest-frame UV-bright components of SMM J14011+0252, J1/J2. The most vigorous star formation is marked by peaks in both the molecular gas and radio emission, ~1'' north of J1/J2, in the vicinity of J1n, an apparent faint extension of J1. Using new sub-0. ″5 K-band imaging from the United Kingdom Infrared Telescope, we identify J1n as an extremely red object. We suggest that while J1 and J2 are clearly associated with the submillimeter source, they are merely windows through the dust, or unobscured companions to a large and otherwise opaque star-forming system. Hence, their rest-frame UV properties are unlikely to be relevant for understanding the detailed internal physics of the starburst.
Big visual data analytics for damage classification in civil engineering

Visual data provide a wealth of information to better understand the world around us. A tremendous amount of visual data is collected in civil engineering applications through efforts such as scientific experiments, field surveys, resource management, and reconnaissance missions. Among these efforts, visual data generate crucial and abundant information evaluating the condition of a civil structure. As a typical example, during a disaster such as a natural catastrophe or industrial explosion, vast amounts of perishable image data are collected that may be used to generate new knowledge from the consequences of that event. However, not only does this process require timeconsuming data collection by human engineers, it is also tedious and expensive to manually search through these data sets to find the most informative images. Autonomous collection, processing and analysis offer great potential to support structural evaluation. In this study, we propose a novel autonomous evaluation method to examine large volumes of images. Recent deep convolutional neural network (CNN) algorithms are applied to extract visual information from the collected images. Task-oriented engineering knowledge and experience are incorporated into the procedures to increase accuracy. The target application addressed in this study is post-disaster building damage evaluation. Illustration of the technique and capabilities for collapse classification is demonstrated using large-scale images gathered from past earthquake events.
joThe Yoyo-Man

The paper reports on two results issued from a multidisciplinary research action tending to explore the motor synergies of anthropomorphic walking. By combining biomechanics, neurophysiology and robotics perspectives, it is intended to better understand the human locomotion with the ambition to better design bipedal robot architectures. The motivation of the research starts from the simple observation that humans may stumble when following a simple reflex-based locomotion on uneven terrains. The rationale combines two well established results in robotics and neuroscience respectively: • Passive robot walkers, which are very efficient in terms of energy consumption, can be modelled by a simple rotating rimless wheel; • Humans and animals stabilize their head when moving. The seminal hypothesis is then to consider a wheel equipped with a stabilized mass on top of it as a plausible model of bipedal walking. The two results presented in the paper comfort the hypothesis: • From a motion capture data basis of twelve human walkers, we show that the motions of the feet are organized around a geometric center, which is the center of mass, and surprisingly not the hip. • After introducing a ground texture model that allows to quantify the stability performance of walker control schemes, we show how compass-like passive walkers are better controlled when equipped with a stabilized 2-degree-of-freedom moving mass on top of them. CoM and head then play complementary roles that define what we call the Yoyo-Man. Beyond the two results presented in the paper, the Yoyo-Man model opens new perspectives to explore the computational foundations of anthropomorphic walking.
Discovered just before extinction? The first endemic ant from the Balearic Islands (Lasius balearicus sp. nov.) is endangered by climate change

We analyse the taxonomic status, phylogenetic relationships, distribution and age of a newly discovered ant taxon found in the mountaintops of the island of Mallorca (Spain). We also consider the potential impact of short‐term climate change on the survival of this ant and make proposals on its conservation status, risks and management.
Title: Individual differences in rhythmic skills: links with neural consistency and linguistic ability

Durational patterns provide cues to linguistic structure, and so variations in rhythm skills may have consequences for language development. Understanding individual differences in rhythm skills, therefore, could help explain variability in language ability across the population. We investigated the neural foundations of rhythmic proficiency and its relation to language skills in young adults. We hypothesized that rhythmic abilities can be characterized by at least two constructs, which are tied to independent language abilities and neural profiles. Specifically, we hypothesized that rhythm skills that require integration of information across time rely upon the consistency of slow, low-frequency auditory processing, which we measured using the evoked cortical response. On the other hand, we hypothesized that rhythmic skills that require fine temporal precision rely upon the consistency of fast, higher-frequency auditory processing, which we measured using the frequency following response. Performance on rhythm tests aligned with two constructs: rhythm sequencing and synchronization. Rhythm sequencing and synchronization were linked to the consistency of slow cortical and fast frequency-following responses, respectively. Furthermore, while rhythm sequencing ability was linked to verbal memory, reading, and nonverbal auditory temporal processing, synchronization ability was linked only to nonverbal auditory temporal processing. Thus, rhythm perception at different time scales reflects distinct abilities, which rely on distinct auditory neural resources. In young adults slow rhythmic processing makes the more extensive contribution to language skill.
Predictive modelling of NBI wall loads in W7-X scenarios exhibiting vanishing bootstrap current

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Memetic-based schedule synthesis for communication on time-triggered embedded systems

Time-triggered systems play an important role in industrial embedded systems. The time-triggered network is deployed on the time-triggered network-on-chip implementation. It ensures the safety-critical industrial communication for real-time embedded multiprocessor systems. To guarantee the safety-critical requirements for communication, each message is transmitted by a predefined static schedule. However, synthesizing a feasible schedule is a challenge because both spatial and temporal constraints should be considered. This article presents a novel memetic-based schedule synthesis algorithm to derive a feasible schedule by determining the offset of messages on the time-triggered network-on-chip. Memetic-based schedule synthesis algorithm is based on memetic algorithm, which incorporates local search in the iterations of general genetic algorithm. We compare memetic-based schedule synthesis algorithm with genetic algorithm in different scale of time-triggered network-on-chip and number of messages. The experimental results show that the memetic-based schedule synthesis algorithm is effective to synthesize a feasible schedule, and the failure schedule synthesized by memetic-based schedule synthesis algorithm is only 34.2% in average compared to the conventional genetic algorithm.