Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding the Impact of Change in COTS-Based Systems

The use of commercial off-the-shelf software components (COTS) promises significant advances in terms of greater productivity, reduced time to market and reliability. However, the blackbox nature of these components poses equally significant challenges for managing maintenance, future change to component-based systems and in particular the impact of proposed changes. Unless these challenges are adequately addressed, the use of COTS components may result in the deployment of systems that are almost impossible to maintain safely. We propose a combined approach for helping developers to understand the impact of change which relies on a COTS component-oriented development process and the use of architecture description language (ADL) for documenting component system architectures.
A Framework for Modeling Cyber-Physical Switching Attacks in Smart Grid

Security issues in cyber-physical systems are of paramount importance due to the often safety-critical nature of its associated applications. A first step in understanding how to protect such systems requires an understanding of emergent weaknesses, in part, due to the cyber-physical coupling. In this paper, we present a framework that models a class of cyber-physical switching vulnerabilities in smart grid systems. Variable structure system theory is employed to effectively characterize the cyber-physical interaction of the smart grid and demonstrate how existence of the switching vulnerability is dependent on the local structure of the power grid. We identify and demonstrate how through successful cyber intrusion and local knowledge of the grid an opponent can compute and apply a coordinated switching sequence to a circuit breaker to disrupt operation within a short interval of time. We illustrate the utility of the attack approach empirically on the Western Electricity Coordinating Council three-machine, nine-bus system under both model error and partial state information.
An Efficient Approach for Outlier Detection with Imperfect Data Labels

The task of outlier detection is to identify data objects that are markedly different from or inconsistent with the normal set of data. Most existing solutions typically build a model using the normal data and identify outliers that do not fit the represented model very well. However, in addition to normal data, there also exist limited negative examples or outliers in many applications, and data may be corrupted such that the outlier detection data is imperfectly labeled. These make outlier detection far more difficult than the traditional ones. This paper presents a novel outlier detection approach to address data with imperfect labels and incorporate limited abnormal examples into learning. To deal with data with imperfect labels, we introduce likelihood values for each input data which denote the degree of membership of an example toward the normal and abnormal classes respectively. Our proposed approach works in two steps. In the first step, we generate a pseudo training dataset by computing likelihood values of each example based on its local behavior. We present kernel \(k\) -means clustering method and kernel LOF-based method to compute the likelihood values. In the second step, we incorporate the generated likelihood values and limited abnormal examples into SVDD-based learning framework to build a more accurate classifier for global outlier detection. By integrating local and global outlier detection, our proposed method explicitly handles data with imperfect labels and enhances the performance of outlier detection. Extensive experiments on real life datasets have demonstrated that our proposed approaches can achieve a better tradeoff between detection rate and false alarm rate as compared to state-of-the-art outlier detection approaches.
The usefulness of econometric models with stochastic volatility and long memory : applications for macroeconomic and financial time series

This study aims to examine the usefulness of econometric models with stochastic volatility and long memory in the application of macroeconomic and nancial time series. An ARFIMA-FIAPARCH process is used to estimate the two main parameters driving the degree of persistence in the US real interest rate and its uncertainty. It provides evidence that the US real interest rates exhibit dual long memory and suggests that much more attention needs to be paid to the degree of persistence and its consequences for the economic theories which are still inconsistent with the nding of either near-unit-root or long memory mean-reverting behavior. A bivariate GARCH-type of model with/without long-memory is constructed to concern the issue of temporal ordering of ination, output growth and their respective uncertainties as well as all the possible causal relationships among the four variables in the US/UK, allowing several lags of the conditional variances/levels used as regressors in the mean/variance equations. Notably, the ndings are quite robust to changes in the speci cation of the model. The applicability and out-of-sample forecasting ability of a multivariate constant conditional correlation FIAPARCH model are analysed through a multi-country study of national stock market returns. This multivariate speci cation is generally applicable once power, leverage and long-memory e¤ects are taken into consideration. In addition, both the optimal fractional di¤erencing parameter and power transformation are remarkably similar across countries.
Physical synthesis for FPGA interconnect power reduction by dual-Vdd budgeting and retiming

Field programmable dual-Vdd interconnects are effective in reducing FPGA power. We formulate the dual-Vdd-aware slack budgeting problem as a linear program (LP) and a min-cost network flow problem, respectively. Both algorithms reduce interconnect power by 50% on average compared to single-Vdd interconnects, but the network-flow-based algorithm runs 11x faster on MCNC benchmarks. Furthermore, we develop simultaneous retiming and slack budgeting (SRSB) with flip-flop layout constraints in dual-Vdd FPGAs based on mixed integer linear programming, and speed-up the algorithm by LP relaxation and local legalization. Compared to retiming followed by slack budgeting, SRSB reduces interconnect power by up to 28.8%.
Relationships between trauma and psychosis: a review and integration.

OBJECTIVES This paper examines the research and theoretical literature on potential links between trauma and psychosis. METHODS Three main alternatives are considered; can psychosis cause PTSD, can trauma cause psychosis and could psychosis and PTSD both be part of a spectrum of responses to a traumatic event? The more influential studies considered are critically evaluated and methodological considerations specific to research regarding trauma and psychosis are also examined. RESULTS Evidence is found in support of each of these relationships, and an integrative approach to conceptualizing the relationships is suggested. CONCLUSIONS Recent conceptualizations of PTSD and psychosis are used to inform the consideration of these different pathways, and the implications for theories of psychosis and trauma and the clinical implications for services for psychotic patients are discussed.
Mechanistic Basis and Functional Roles of Long-Term Plasticity in Auditory Neurons Induced by a Brain-Generated Estrogen

The classic estrogen 17β-estradiol (E2) was recently identified as a novel modulator of hearing function. It is produced rapidly, in an experience-dependent fashion, by auditory cortical neurons of both males and females. This brain-generated E2 enhances the efficiency of auditory coding and improves the neural and behavioral discrimination of auditory cues. Remarkably, the effects of E2 are long-lasting and persist for hours after local rises in hormone levels have subsided. The mechanisms and functional consequences of this E2-induced plasticity of auditory responses are unknown. Here, we addressed these issues in the zebra finch model by combining intracerebral pharmacology, biochemical assays, in vivo neurophysiology in awake animals, and computational and information theoretical approaches. We show that auditory experience activates the MAPK pathway in an E2-dependent manner. This effect is mediated by estrogen receptor β (ERβ), which directly associates with MEKK1 to sequentially modulate MEK and ERK activation, where the latter is required for the engagement of downstream molecular targets. We further show that E2-mediated activation of the MAPK cascade is required for the long-lasting enhancement of auditory-evoked responses in the awake brain. Moreover, a functional consequence of this E2/MAPK activation is to sustain enhanced information handling and neural discrimination by auditory neurons for several hours following hormonal challenge. Our results demonstrate that brain-generated E2 engages, via a nongenomic interaction between an estrogen receptor and a kinase, a persistent form of experience-dependent plasticity that enhances the neural coding and discrimination of behaviorally relevant sensory signals in the adult vertebrate brain.
Handovers in wireless ATM networks: in-band signaling protocols and performance analysis

The first part of this paper presents a novel scheme for handover provisioning in wireless asynchronous transfer mode (W-ATM) networks based on in-band signaling. First, the network architecture and principles of in-band signaling are described, discussing advantages and interaction with other procedures and signaling techniques. Then, loss-free protocols for the handover procedures are presented and compared with existing proposals. The second part of the paper is devoted to performance analysis of the handover procedures. A general methodology for evaluating handover delays and required buffer capacity is introduced and exemplified for one of the protocols introduced before. Numerical results give insight into the handover procedure characteristics and are compared with estimates provided by detailed discrete event simulations for validation purposes. Finally, additional simulation results are presented for parallel, concurrent handovers, evaluating the requirements posed to the network by different handover procedures.
Relational Exploration - Reconciling Plato and Aristotle

We provide an interactive method for knowledge acquisition combining approaches from description logic and formal concept analysis. Based on present data, hypothetical rules are formulated and checked against a description logic theory. We propose an abstract framework (Logical Domain Exploration) for this kind of exploration technique before presenting a concrete instantiation: Relational Exploration. We give a completeness result and provide an overview about some application fields for our approach: machine learning, data mining, and ontology engineering.
Parental Involvement and Students’ Educational Achievement: A Phenomenological Study

To abide with the system of united support for students’, schools need to build partnership and develop mutual responsibility with parents, for students’ success in the educational system. In this way, parental engrossment increases, parents’ effort to support schools encourages, and they directly make a positive influence to a successful educational system. Considering the importance of parents’ participation and involvement in school, in this paper, we will look into the effects of parental contribution on students’ academic achievements, the factors that interrupt parental involvement and the role that the school management is playing to promote parental involvement. Qualitative Data was collected through semi structured interview from nine parents to find out their involvement in their child’s education. The data was then analyzed to deduct themes. Results of the study reveals that effective parent involvement contributes to greater academic achievements by their children. Educational achievement is a joint responsibility of the school, student and parent. It is recommended that the school management should encourage greater parental involvement by arranging parent training sessions.
Physical Activity and Sedentary Behaviors Modify the Association between Melanocortin 4 Receptor Gene Variant and Obesity in Chinese Children and Adolescents

Effects of MC4R variants in previous Chinese population studies were inconsistent. Gene-environment interactions might influence the effect of MC4R variants on obesity, which was still unclear. We performed the study to clarify the association of variants near MC4R gene with obesity-related phenotypes and gene-environment interactions in Chinese children and adolescents. Two common variants (rs12970134 and rs17782313) near MC4R were genotyped in 2179 children and adolescents aged 7–18 years in Beijing of China. Associations between the variants and obesity-related phenotypes together with gene-environment interactions were analyzed. The A-alleles of rs12970134 were nominally associated with risk of overweight/obesity (Odds Ratios (OR) = 1.21, 95%CI: 1.03–1.44, P = 0.025) and BMI (β = 0.33 kg/m2, 95%CI: 0.02–0.63, P = 0.025), respectively. The rs12970134 was also associated with HDL-C (β = -0.03mmol/L per A-allele, 95%CI: -0.05, -0.01, P = 0.013) independent of BMI. In the further analysis, we found the significant interaction of rs12970134 and physical activity/sedentary behaviors on BMI (Pinteraction = 0.043). The rs12970134 was found to be associated with BMI only in children with physical activity<1h/d and sedentary behaviors ≥2h/d (BMI: β = 1.27 kg/m2, 95%CI: 0.10–2.45, P = 0.034). The association was not detected in their counterparts with physical activity≥1h/d or sedentary behaviors <2h/d. We identified the effect of MC4R rs12970134 on overweight/obesity and BMI, and we also found physical activity and sedentary behaviors modified the association between the rs12970134 and BMI in Chinese children and adolescents.
Suggestive Hatching

We present a method for drawing lines on an object that depict both the shape and shading of the object. To do so, we construct a gradient field of the diffuse intensity of the surface to guide a set of adaptively spaced lines. The shape of these lines reflect the lighting under which the object is being viewed and its shape. When the light source is placed at the viewer's location, these lines emanate from silhouettes and naturally extend Suggestive Contours. By using a hierarchical proximity grid, we can also improve the quality of these lines as well as control their density over the image. We also provide a method for detecting and removing ridge lines in the intensity field, which lead to artifacts in the line drawings.
Averaging, renormalization group and criticality in cosmology

Several problems in physics, in particular the averaging problem in gravity, can be described in a formalism derived from the real-space Renormalization Group (RG) methods. It is shown that the RG flow is provided by the Ricci-Hamilton equations which are thereby provided with a {\it physical} interpretation. The connection between a manifold deformation according to these equations and Thurston's conjecture is exhibited. The significance of criticality which naturally appears in this framework is briefly discussed. This article summarizes also recent work with M. Carfora. Moreover, a report on some work in progress is given and some open issues in the averaging problem pointed out.
Effects of Nickel Treatment on H3K4 Trimethylation and Gene Expression

Occupational exposure to nickel compounds has been associated with lung and nasal cancers. We have previously shown that exposure of the human lung adenocarcinoma A549 cells to NiCl(2) for 24 hr significantly increased global levels of trimethylated H3K4 (H3K4me3), a transcriptional activating mark that maps to the promoters of transcribed genes. To further understand the potential epigenetic mechanism(s) underlying nickel carcinogenesis, we performed genome-wide mapping of H3K4me3 by chromatin immunoprecipitation and direct genome sequencing (ChIP-seq) and correlated with transcriptome genome-wide mapping of RNA transcripts by massive parallel sequencing of cDNA (RNA-seq). The effect of NiCl(2) treatment on H3K4me3 peaks within 5,000 bp of transcription start sites (TSSs) on a set of genes highly induced by nickel in both A549 cells and human peripheral blood mononuclear cells were analyzed. Nickel exposure increased the level of H3K4 trimethylation in both the promoters and coding regions of several genes including CA9 and NDRG1 that were increased in expression in A549 cells. We have also compared the extent of the H3K4 trimethylation in the absence and presence of formaldehyde crosslinking and observed that crosslinking of chromatin was required to observe H3K4 trimethylation in the coding regions immediately downstream of TSSs of some nickel-induced genes including ADM and IGFBP3. This is the first genome-wide mapping of trimethylated H3K4 in the promoter and coding regions of genes induced after exposure to NiCl(2). This study may provide insights into the epigenetic mechanism(s) underlying the carcinogenicity of nickel compounds.
Securing Mobile Cloud Data with Personalized Attribute-Based Meta Information

With the spread of fast mobile Internet connections, such as 3G and LTE and the increasing processor power of mobile devices accessing cloud computing services on-the-go is common among all users. Sharing private information with friends and family members are options of popular cloud services, such as storage and social media services. But recent headlines show that the access to private information is often not sufficiently secured on the service level. The approach presented in this paper aims to use attribute-based meta-information to secure data on the level of files without relying on additional functionality of third-party services. A mobile device app is used to access and alter the meta-information. Attribute-based encryption mechanisms secure the private data and define access policies for friends and other users simultaneously.
Mining Call Center Conversations Exhibiting Similar Affective States

Automatic detection and identifying emotions in large call center calls are essential to spot conversations that require further action. Most often statistical models generated using annotated emotional speech are used to design an emotion detection system. But annotation requires substantial amount of human intervention and cost; and may not be available for call center calls because of the infrastructure issues. Therefore detection systems use models that are generated form the readily available annotated emotional (clean) speech datasets and produce erroneous output due to mismatch in training-testing datasets. Here we propose a framework to automatically identify the similar affective spoken utterances in large number of call center calls by using the emotion models that are trained with the freely available acted emotional speech. Further, to reliably detect the emotional content, we incorporate the available knowledge associated with the call (time lapse of the utterances in a call, the contextual information derived from the linguistic contents, and speaker information). For each audio utter-ance, the emotion recognition system generates similarity measures (likelihood scores) in arousal and valence dimension using pre-trained emotional models, and further they are combined with the scores from the contextual knowledge-based systems, which are used to reliably detect the similar affective contents in large number of calls. Experiments demonstrate that there is a signiﬁcant improvement in detection accuracy when the knowledge-based framework is used.
A Novel Hybrid Algorithm Based on Baldwinian Learning and PSO

In the paper, a novel hybrid algorithm based on Baldwinian learning and PSO (BLPSO) is proposed to increase the diversity of the particles and to prevent premature convergence of PSO. Firstly, BLPSO adopts the Baldwinian operator to simulate the learning mechanism among the particles and employs the information of the swarm to alter the search space adaptively. Secondly, a mutation operation is introduced to make the particles leap the local optimum and enhance the chance to find out the global optimum. Finally, the proposed BLPSO is used to solve some complex optimization problems, the experiment results illustrate the efficiency of the proposed method.
Angiotensin-(1-7) Counterregulates Angiotensin II Signaling in Human Endothelial Cells

Angiotensin (Ang)-(1-7), acting through the Mas receptor, opposes the actions of Ang II. Molecular mechanisms for this are unclear. Here we sought to determine whether Ang-(1-7) influences Ang II signaling in human endothelial cells, focusing specifically on Src homology 2-containing inositol phosphatase 2 (SHP-2) and its interaction with c-Src. Ang II–induced phosphorylation of c-Src, extracellular signal regulated kinase (ERK)1/2, and SHP-2 and activation of NAD(P)H oxidase were assessed in the absence and presence of Ang-(1-7) (10−6 mol/L, 15 minutes) by immunoblotting and lucigenin-enhanced chemiluminescence, respectively. (D-Ala7)-Ang I/II (1-7) (Ang fragment 1-7 receptor antagonist) was used to block Ang-(1-7) effects. Association between SHP-2 and c-Src was assessed by immunoprecipitation/immunoblotting studies. Ang II significantly increased activation of c-Src, ERK1/2, and NAD(P)H oxidase and reduced phosphorylation of SHP-2 (P<0.05) in human endothelial cells. These effects were abrogated in cells pre-exposed to Ang-(1-7). Ang fragment 1-7 receptor antagonist pretreatment blocked the negative modulatory actions of Ang-(1-7) on Ang II–induced signaling. Ang-(1-7) alone did not significantly alter phosphorylation of c-Src, ERK1/2, and SHP-2 and had no effect on basal activity of NAD(P)H oxidase. SHP-2 and c-Src were physically associated in the basal state. This association was increased by Ang-(1-7) and blocked by Ang fragment 1-7 receptor antagonist. Our findings demonstrate that, in human endothelial cells, Ang-(1-7) negatively modulates Ang II/Ang II type 1 receptor–activated c-Src and its downstream targets ERK1/2 and NAD(P)H oxidase. We also show that SHP-2-c-Src interaction is enhanced by Ang-(1-7). These phenomena may represent a protective mechanism in the endothelium whereby potentially deleterious effects of Ang II are counterregulated by Ang-(1-7).