Miracle-dz/UniFAR-FTUs huggingface dataset:
Taxonomies for Reasoning About Cyber-physical Attacks in IoT-based Manufacturing Systems

The Internet of Things (IoT) has transformed many aspects of modern manufacturing, from design to production to quality control. In particular, IoT and digital manufacturing technologies have substantially accelerated product development- cycles and manufacturers can now create products of a complexity and precision not heretofore possible. New threats to supply chain security have arisen from connecting machines to the Internet and introducing complex IoT-based systems controlling manufacturing processes. By attacking these IoT-based manufacturing systems and tampering with digital files, attackers can manipulate physical characteristics of parts and change the dimensions, shapes, or mechanical properties of the parts, which can result in parts that fail in the field. These defects increase manufacturing costs and allow silent problems to occur only under certain loads that can threaten safety and/or lives. To understand potential dangers and protect manufacturing system safety, this paper presents two taxonomies: one for classifying cyber-physical attacks against manufacturing processes and another for quality control measures for counteracting these attacks. We systematically identify and classify possible cyber-physical attacks and connect the attacks with variations in manufacturing processes and quality control measures. Our taxonomies also provide a scheme for linking emerging IoT-based manufacturing system vulnerabilities to possible attacks and quality control measures.
Tuning the Precision of Predictors to Reduce overestimation of protein Disorder over Large Datasets

This is a study on the precision of four known protein disorder predictors, ranked among the best-performing ones: DISOPRED2, PONDR VSL2B, IUPred and ESpritz. We address here the problem of a systematic overestimation of the number of disordered proteins recognized through the use of these predictors, considered as a standard. Some of these predictors, used with their default setting, have a low precision, implying a tendency to overestimate the occurrence of disordered proteins in genome-wide surveys. Moreover, different predictors often disagree on the evaluation of individual proteins. To cope with this problem and in order to propose a simple procedure that enhances precision based on precision-recall curves, we re-tuned the discriminative thresholds of the predictors by training and cross-validating their performance on a cured dataset. After re-tuning, both the disagreement among predictors and the tendency to overestimate the occurrence of disordered proteins are reduced. This is shown in a dedicated study over the human proteome and a set of cancer-related human proteins, with no a priori disorder annotation. Simple quantitative estimates suggest that the occurrence of disorder among cancer-related proteins and other similar large-scale surveys has been overestimated in the past.
The mediating effect of Interpersonal competence between Nursing student's Adult attachment and Adjustment to College life

The purpose of this study was to examine the relationship between adult attachment, adjustment to college life, and interpersonal competence in nursing college students and investigate whether or not interpersonal competence mediates the relationship between adult attachment and adjustment to college life. The subjects of this study were 685 college students located in J-si and M-si, and data were collected for 25 days from November 1 through 25, 2015. The collected data were analyzed by t-test, Pearson correlation coefficients, Hierarchical regression, and Sobel test using SPSS 23.0. As adult attachment increased, adjustment to college life was enhanced (B=.225, p=.027); as interpersonal competence increased, adjustment to college life improved (B=.145, p=.040); and as adult attachment increased, interpersonal competence increased (B=.396, p=.021). In addition, interpersonal competence significantly mediated the relationship between adult attachment and adjustment to college life (Z=3.560, p<.001). To enhance adjustment to college life in nursing college students, adult attachment and interpersonal competence need to be improved.
PCFuzzing: A penetration combinatorial fuzzing framework by simulating attack trace

In essence, fuzzing is a kind of penetration testing by injecting fault to simulate the attacks. However, current fuzzings do not simulate the attacks in a real sense. They pay more attention to the injection of malformed semi-valid data at a single input point. Nevertheless, an attack is usually a set of cooperative aggressive behaviors at multi input points. In this paper, we present PCFuzzing, a penetration combinatorial fuzzing framework for the software in host environment by simulating attack trace at multi input points. Based on the attack attributes plug-in gained by means of static analysis in advance, PCFuzzing uses dynamic taint tracing to automatically find the input vector that influence values used at key program attack points (points where the program may contain an error), uses symbolic execution and constraint solving to identify the constraint boundary of every input in input vector and constraint relationship of the inputs in input vector, uses combinatorial testing strategies to generate and combine the malformed test case vector, and then injects the combinatorial test case vector to find security vulnerabilities in programs according to the attack strategies in the attack attributes plug-in. Our experimental results indicate that our PCFuzzing can not only effectively expose errors located deep within large applications, but also can avoid the combination explosion to a certain extent because taint tracer in framework uses dynamic taint tracing to reduce the number of inputs involved in the combination and constraint collector in framework uses symbolic execution and constraint solving to narrow the value ranges of input data.
COMBINED AND INTERACTIVE EFFECTS OF GLOBAL CLIMATE CHANGE AND TOXICANTS ON POPULATIONS AND COMMUNITIES

Increased temperature and other environmental effects of global climate change (GCC) have documented impacts on many species (e.g., polar bears, amphibians, coral reefs) as well as on ecosystem processes and species interactions (e.g., the timing of predator–prey interactions). A challenge for ecotoxicologists is to predict how joint effects of climatic stress and toxicants measured at the individual level (e.g., reduced survival and reproduction) will be manifested at the population level (e.g., population growth rate, extinction risk) and community level (e.g., species richness, food‐web structure). The authors discuss how population‐ and community‐level responses to toxicants under GCC are likely to be influenced by various ecological mechanisms. Stress due to GCC may reduce the potential for resistance to and recovery from toxicant exposure. Long‐term toxicant exposure can result in acquired tolerance to this stressor at the population or community level, but an associated cost of tolerance may be the reduced potential for tolerance to subsequent climatic stress (or vice versa). Moreover, GCC can induce large‐scale shifts in community composition, which may affect the vulnerability of communities to other stressors. Ecological modeling based on species traits (representing life‐history traits, population vulnerability, sensitivity to toxicants, and sensitivity to climate change) can be a promising approach for predicting combined impacts of GCC and toxicants on populations and communities. Environ. Toxicol. Chem. 2013;32:49–61. © 2012 SETAC
Optimal Algorithmic Complexity of Fuzzy Art Optimal Algorithmic Complexity of Fuzzy Art

We discuss implementations of the Adaptive Resonance Theory (ART) on a serial machine. The standard formulation of ART, which was inspired by recurrent brain structures, corresponds to a recursive algorithm. This induces an algorithmic complexity of order O(N 2) + O(MN) in worst and average case, N being the number of categories, and M the input dimension. It is possible, however, to formulate ART in a non-recursive algorithm such that the complexity is of order O(MN) only.
Rapid, Coordinate Inflammatory Responses after Experimental Febrile Status Epilepticus: Implications for Epileptogenesis

Abstract Epilepsy is a common neurological disorder with many causes. For temporal lobe epilepsy, antecedent insults are typically found. These risk factors include trauma or history of long fever-associated seizures (febrile status epilepticus) in childhood. Whereas the mechanisms by which such insults promote temporal lobe epilepsy are unknown, an extensive body of work has implicated inflammation and inflammatory mediators in both human and animal models of the disorder. However, direct evidence for an epileptogenic role for inflammation is lacking. Here we capitalized on a model where only a subgroup of insult-experiencing rodents develops epilepsy. We reasoned that if inflammation was important for generating epilepsy, then early inflammation should be more prominent in individuals destined to become epileptic compared with those that will not become epileptic. In addition, the molecular and temporal profile of inflammatory mediators would provide insights into which inflammatory pathways might be involved in the disease process. We examined inflammatory profiles in hippocampus and amygdala of individual rats and correlated them with a concurrent noninvasive, amygdalar magnetic resonance imaging epilepsy-predictive marker. We found significant individual variability in the expression of several important inflammatory mediators, but not in others. Of interest, a higher expression of a subset of hippocampal and amygdalar inflammatory markers within the first few hours following an insult correlated with the epilepsy-predictive signal. These findings suggest that some components of the inflammatory gene network might contribute to the process by which insults promote the development of temporal lobe epilepsy.
Modeling agent-based load balancing with time delays

In grid computing, agent-based load balancing is one of the most important problems. In this paper, we present a macroscopic model to describe the dynamics of agent-based load balancing with time delays. We concern the number and size of teams where tasks queue. The time gap, during which a single agent searches a suitable node and transfers a task to the node, is incorporated into balancing process as delay. Our model is composed of functional differential equations. By numerical simulations, we show that variables (the number and size of teams, etc.) in the model remain nonnegative, which is in agreement with the physical background of the variables. We show that although there is a period of oscillation, the dynamic behavior tends to a steady state, which is in agreement with the recent experiments on Anthill. An interesting phenomenon is shown: the larger the delay, the longer the period of oscillation, and the slower the converging speed of load balancing.
Comparative analysis between FFT and Kalman filter approaches for harmonic components detection

This paper presents a numerical comparison between the FFT and the Kalman filter applied for harmonic components detection in different situation of the grid operation. Some pitfalls of the FFT are showed and the results are compared with the Kalman filter approach. It is considered signals with step changes in amplitude, frequency and phase. An analysis of these results is made demonstrating the better behavior of the Kalman filter approach in comparison to the FFT.
Factors Influencing Internal And External Employability Of Employees

The paper aimed at examining factors that influence employees’ employability. Factors that were examined are formal and informal career management practices, training, job experiences, education and tenure with current job. Employability is measured using two dimensions; internal and external employability. Data was collected using questionnaires that were distributed to selected organizations in various industries. Measurement items were adopted and adapted from previous studies. Two hundred and sixty employees participated in the study. Pearson correlation tests indicated that formal career management practices was positively related to external employability and internal employability. Informal career management practices were found only significantly related to external employability. The relationship with internal employability was insignificant. Training received by employees was both related to internal and external employability. On the other hand, job experiences were only significantly related to internal employability. Education and tenure were found only giving significant influence to external employability.
Tools for hierarchical annotation of typed dialogue

We discuss a set of tools for annotating a complex hierarchical and linguistic structure of tutorial dialogue based on the NITE XML Toolkit (NXT) (Carletta et al., 2003). The NXT API supports multi-layered stand-off data annotation and synchronisation with timed and speech data. Using NXT, we built a set of extensible tools for detailed structure annotation of typed tutorial dialogue, collected from a tutor and student typing via a chat interface. There are several corpora of tutoring done with such chat-style communication techniques (Shah et al., 2002; Jordan and Siler, 2002), however, our annotation presents a special problem because of its detailed hierarchical structure. We applied our annotation methodology to annotating corpora in two different tutoring domains: basic electricity and electronics, and symbolic differentiation.
Some Facets of Argument Mining for Opinion Analysis

In this paper, we present some foundational elements related to argument extraction in opinion texts with the objective to further analyse and synthetise user preferences and value systems as they emerge in such texts. We show that (1) within the context of opinionated expressions, a number of evaluative expressions with a ’heavy’ semantic load receive an argumentative interpretation and (2) that the association of an evaluative expression with a discourse structure such as an elaboration, an illustration, or a reformulation must also be interpreted as an argument. We develop a conceptual semantics of these relations and show how they are analyzed using the Dislog programming language on the platform, dedicated to discourse analysis.
Repeated Binge Pattern Ethanol Administration During Adolescence or Adulthood: Long-Term Changes in Voluntary Ethanol Intake and Mesolimbic Dopamine Functionality in Male Rats

v Chapter 1: Background . 1 Alcohol use in humans . 1 Animal model of adolescence . 3 Effects of ethanol on behavior . 3 Adults . 3 Adolescents . 4 Binge drinking during adolescence . 5 Effects of ethanol in the brain . 8 Adults . 8 Adolescents . 9 Long-term neurobehavioral effects of ethanol exposure during adolescence . 10 Functionality of the mesolimbic pathway: opioid system modulation and ethanol alterations . 11 Overview of the present set of experiments . 14 Hypotheses . 15 Chapter 2: Materials and methods . 17 Subjects . 17 Apparatus . 17 Aim 1: Binge pattern ethanol pretreatment and voluntary ethanol intake in adulthood and ethanol metabolism . 18 Handling . 18 Repeated binge pattern ethanol treatment . 19 Abstinence . 19 Adulthood voluntary ethanol intake . 20 Aim 2: Challenge injection and blood ethanol levels . 21 Aim 3: Binge pattern ethanol pretreatment and mesolimbic dopamine functionality in adulthood . 22 Handling . 22 Repeated binge pattern ethanol treatment . 22 Abstinence . 23 Surgery . 23 Recovery . 24 Microdialysis . 24 Neurochemical analysis . 27 ii Design and analysis . 27 Chapter 3: Binge ethanol pretreatment during adolescence increases voluntary ethanol intake in adulthood . 29 0.5 g/kg ethanol pretreatment . 29 1.0 g.kg ethanol pretreatment . 31 2.0 g/kg ethanol pretreatment . 34 Dose comparisons (percent of control) . 37 Chapter 4: Binge ethanol pretreatment dose-dependently alters ethanol metabolism . 41 Chapter 5: Binge ethanol pretreatment during adolescence does not alter mesolimbic dopamine functionality in adulthood . 43 Potassium-stimulated dopamine in nucleus accumbens septi (nM) . 43 Potassium-stimulated dopamine in nucleus accumbens septi (percent of baseline) . 44 Potassium-stimulated DOPAC in nucleus accumbens septi (nM) . 45 Potassium-stimulated DOPAC/DA turnover in nucleus accumbens septi . 47 Chapter 6: Discussion . 48 Aim 1: Voluntary ethanol intake after water or ethanol pretreatment . 48 Aim 2: Ethanol metabolism after water or ethanol pretreatment . 55 Aim 3: Potassium-stimulated dopamine in the nucleus accumbens septi after water or ethanol pretreatment . 57 Summary . 62 References . 64 Appendices . 77 Appendix A: Supplemental Figure . 78
Tear analytical model based on Raman microspectroscopy for investigation of infectious diseases of the ocular surface.

PURPOSE To establish a tear analytical model by using Raman microspectroscopy to assess ocular surface diseases associated with infectious pathogens. METHODS The authors applied confocal Raman microspectroscopy based on the drop-coating deposition method on Ti/Au-coated glass slides to obtain sample spectra from different types of tears, including simplified synthetic tears (SSTs), SSTs mixed with microbes, and human tears. Raman spectra were sampled by a line-mapping procedure and classified into three groups by three different zones in a dried teardrop. To determine the tear model with optimal discrimination, the spectra of the three zones were compared using spectral morphology and principal component analysis. Finally, the optimal tear model was verified by comparing the Raman spectra of human teardrops of patients with ulcerative keratitis and bacterial infection with those of patients without any identifiable infection. RESULTS Nonhomogeneous intensities of Raman spectra collected by a line-mapping sampling procedure were found in different locations of a dried teardrop. This might have been caused by coffee-ring formation and ferny crystallization phenomena. The normalized spectra in the central zone have better discriminative potential than those in the other zones, ring zone, and transitional zone, tested by pure SSTs or SSTs with microbes. The tear model based on normalized Raman spectra in the central zone was discriminative for patients with ulcerative keratitis in the presence or absence of infection. CONCLUSIONS Raman spectra in the central zone of a dried teardrop may serve as useful spectral fingerprints for investigating ocular surface diseases with or without infection.
Fast Processing SPARQL Queries on Large RDF Data

The RDF (Resource Description Framework) datamodel has been used in various domains, such as Web,government, biology etc. Now, the volume of RDF datasets is growing significantly. The explosion on the volume of RDF data raises serious challenges: how to answer SPARQL queries on large RDF data sets efficiently. Here, we present a large-scale RDF data system - TripleParallel, which implements blockbased parallel processing SPARQL queries on RDF data sets with billion triples. The system improves parallelism while strengthening the overlapping data and calculations and reduces the overall execution time of the query. TripleParallel also implements multiple parallel operations for parallel processing joins. Experimental studies with several RDF datasets, including the LUBM and the UniProt collection, demonstrate the performance gains of our approach, outperforming the previous fastest system by more than an order of magnitude.
Solid-State-Drive qualification and reliability strategy

As NAND flash memories have scaled the margin between NAND capability and system requirements have been significantly reduced. Understanding Solid-State-Drive (SSD) reliability and qualification requirements has become more critical since these impact the NAND flash design tradeoffs. Unrealistically high expectations result in excessive margin that could have been used in other areas, while too low of a requirement puts the system at risk for excessive field failure. The reliability and qualification requirements for SSDs will be reviewed and discussed in order to give an overview of what constitutes an effective qualification/reliability strategy for SSDs.
A two-phase iterative pre-copy strategy for live migration of virtual machines

Iterative pre-copy is a major mechanism for achieving live migration of virtual machines. The page duplication activity has an adverse impact on computing internet-related applications. In this paper, a two-phase pre-copy strategy is proposed for reducing the adverse effect. The appropriate timing of changing phase is also provided in this paper. It has been shown that the two-phase strategy reduces the number of duplicated pages without increasing the downtime guaranteed by the typical one-phase strategy.
Dark matter density profiles from the Jeans equation

We make a simple analytical study of radial profiles of dark matter structures, with special attention given to the question of the central radial density profile. We let our theoretical assumptions be guided by results from numerical simulations, and show that at any radius where both the radial density profile, p, and the phase-space-like density profile, ρ/σ∈, are exact power laws, the only allowed density slopes in agreement with the spherically symmetric and isotropic Jeans equation are in the range 1 ≤ β ≤ 3, where β ≡ -d In ρ/d In r. We also allow for a radial variation of these power laws, as well as anisotropy, and show how this allows for more shallow central slopes.
A Multi-objective PSO with Pareto Archive for Personalized E-Course Composition in Moodle Learning System

A velocity-free fully informed particle swarm optimization algorithm is firstly proposed for multi-objective optimization problems in this paper. It finds the non-dominated solutions along the search process using the concept of Pareto dominance and uses an external archive for storing them. Distinct from other multi-objective PSO, particles in swarm only have position without velocity and all personal best positions are considered to update particle position in the algorithm. The theoretical analysis implies that the algorithm will cause the swarm mean converge to the center of the Pareto optimal solution set in a multi-objective search space. Then, the algorithm is applied to the personalized e-course composition in Moodle learning system. The relative experimental results show that the algorithm has better performance and is effective.