Miracle-dz/UniFAR-FTUs huggingface dataset:
Simultaneous analog placement and routing with current flow and current density considerations

Current-flow and current-density are two major considerations for placement and routing of analog layout synthesis. The current-flow constraints are specified to the critical nets with monotonic current/signal paths to reduce parasitic impacts. The current-density constraints are usually specified on the nets with variable wire widths to avoid the IR-drop and electromigration problems. In this paper, we propose the first work to simultaneously consider current-flow and current-density constraints while placing and routing the analog circuits with minimized chip area, routed wirelength, bend numbers, via counts, and coupling noise at the same time. We first present an enhanced B*-tree representation to simultaneously model modules and interconnects for an analog circuit. Then a simultaneous placement and routing algorithm is presented to generate a layout while satisfying the current-flow and current-density constraints with minimized chip area, routed wirelength, bend numbers, via counts, and coupling noise. Experimental results show that our approach can obtain better layout results and satisfy all specified constraints while optimizing circuit performance.
Component-based tool development

This paper describes an emerging approach for the construction of software-engineering research tools, which is characterized by the use of preexisting components (e.g., off-the-shelf products, integrated development environments, and domain-specific tools) to realize tool functionalities. This approach can be seen as an instantiation of component-based development for the domain of tool building in academia. Building of tools in this manner is already pursued by many researchers, presumable because this approach promises to be more effective compared to coding a tool from scratch. For example, tools can be quickly prototyped and evolved in response to user input or new research directions. Also, tools can be more usable and adoption friendly. I have explored issues surrounding tool building with components in my dissertation and have found that there is little work that evaluates and reflects on the impact of this approach. However, since this approach has its unique benefits and drawbacks and since it is increasingly employed by researchers, it becomes more and more important to improve upon the current practice, which can be characterized as ad hoc. This paper is a first step in this direction. It introduces and reflects on component-based tool building, identifying suitable components to construct maintenance tools, providing a catalog of tool examples that leverage the identified components, and discussing issues that need to be addressed to advance the state-of-the-art.
A new type of papillomavirus DNA, its presence in genital cancer biopsies and in cell lines derived from cervical cancer.

DNA of a new papillomavirus type was cloned from a cervical carcinoma biopsy. Two EcoRI clones of 7.8 and 6.9 kb in length were obtained, the latter contained a 900‐bp deletion. The BamHI fragments of both clones were used to characterize the DNA. It represents a distinct type of papillomavirus as determined by its size, its cross‐hybridization with DNA of other papillomavirus types under conditions of low stringency only, the co‐linear alignment of its genome with HPV 6 and HPV 16 prototypes and its occasional occurrence as oligomeric episomes. We tentatively propose to designate it as HPV 18. DNA hybridizing with HPV 18 under stringent conditions was detected in 9/36 cervical carcinomas from Africa and Brazil, in 2/13 cervical tumors from Germany and 1/10 penile carcinomas. Benign tumors (17 cervical dysplasias, 29 genital warts), eight carcinomata in situ and 15 biopsies of normal cervical tissue were devoid of detectable HPV 18 DNA. HPV 18‐related DNA was found, however, in cells of the HeLa, KB and C4‐1 lines all derived from cervical cancer. The state of the viral DNA was investigated in four cervical cancer biopsies. The data reveal that the DNA might be integrated into the host cell genome. One tumor provided evidence for head to tail tandem repeats some of which persisted as circular episomes.
Model for collaborative and adaptive multimedia content delivery in a collaborative m-learning environment

Smart mobile devices are already used for everyday communication between people. They have become ubiquitous devices for receiving and sharing important information, but they poses limited capability of storing and processing multimedia content. Considering that mobile devices will always have these mentioned limitations, the proposed solution is to use collaborative, adaptive multimedia content delivery and the cloud computing technology. In order to gain increased perception of quality of m-learning systems, the proposed model delivers three services for selection, transcoding and authoring multimedia content, which should be hosted by SaaS cloud computing model. The proposed model for collaborative and adaptive multimedia content delivery will provide the mobile learners with cloud-based services. These services will facilitate the delivery of the preferred multimedia content across heterogeneous network to various types of mobile devices that learners are using. The advantage of the proposed framework is proved by using a sample mobile application for our case study, which estimates the operation of the service for multimedia content selection and authoring service.
Exploring personality traits and well-being among pre-school and primary school teachers in Croatia

background Pre-school and primary school teachers are directly involved in the education of children. In addition to teachers’ competences, the quality of their work is significantly influenced by their psychological well-being. It is therefore important to focus on their well-being as well as on personality traits they have. The main objective of this study was to examine the relationship between life satisfaction, happiness, optimism and personality traits of pre-school and primary school teachers in Croatia.
A toolbox for real-time subject-independent and subject-dependent classification of brain states from fMRI signals

There is a recent increase in the use of multivariate analysis and pattern classification in prediction and real-time feedback of brain states from functional imaging signals and mapping of spatio-temporal patterns of brain activity. Here we present MANAS, a generalized software toolbox for performing online and offline classification of fMRI signals. MANAS has been developed using MATLAB, LIBSVM, and SVMlight packages to achieve a cross-platform environment. MANAS is targeted for neuroscience investigations and brain rehabilitation applications, based on neurofeedback and brain-computer interface (BCI) paradigms. MANAS provides two different approaches for real-time classification: subject dependent and subject independent classification. In this article, we present the methodology of real-time subject dependent and subject independent pattern classification of fMRI signals; the MANAS software architecture and subsystems; and finally demonstrate the use of the system with experimental results.
Representing movement primitives as implicit dynamical systems learned from multiple demonstrations

This work deals with the problem of parameter estimation of dynamical systems intended to model demonstrated motion profiles for a system of interest. The regression problem is formulated as a constrained nonlinear least squares problem. We present an approach that extends the concept of dynamical movement primitives to account for multiple demonstrations of a motion. We maintain an implicit dynamical system that resembles the demonstrated trajectories in a locally optimal way. This is achieved by solving a quadratic program (that encodes our notion of resemblance) at each sampling time step. Our method guarantees predictable state evolution even in regions of the state space not covered by the demonstrations.
Comparing Voice and Stream Segmentation Algorithms

Voice and stream segmentation algorithms group notes from polyphonic data into relevant units, providing a better understanding of a musical score. Voice segmentation algorithms usually extract voices from the beginning to the end of the piece, whereas stream segmentation algorithms identify smaller segments. In both cases, the goal can be to obtain mostly monophonic units, but streams with poly-phonic data are also relevant. These algorithms usually cluster contiguous notes with close pitches. We propose an independent evaluation of four of these algorithms (Tem-perley, Chew and Wu, Ishigaki et al., and Rafailidis et al.) using several evaluation metrics. We benchmark the algorithms on a corpus containing the 48 fugues of Well-Tempered Clavier by J. S. Bach as well as 97 files of popular music containing actual polyphonic information. We discuss how to compare together voice and stream segmen-tation algorithms, and discuss their strengths and weaknesses.
Finger Vein Recognition Based on (2D)2 PCA and Metric Learning

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. In this paper, (2D)2 PCA is applied to extract features of finger veins, based on which a new recognition method is proposed in conjunction with metric learning. It learns a KNN classifier for each individual, which is different from the traditional methods where a fixed threshold is employed for all individuals. Besides, the SMOTE technology is adopted to solve the class-imbalance problem. Our experiments show that the proposed method is effective by achieving a recognition rate of 99.17%.
A Feminist Ventriloquial Analysis of Hao Gongzuo (“Good Work”): Politicizing Chinese Post-1980s Women's Meanings of Work

ABSTRACT This study examines Chinese post-1980s women’s meanings of work at the intersections of gender, generation, and culture. A feminist ventriloquial approach is used to tease out the enactment of tensions in the communicative constitutions of the colloquialism hao gongzuo (“good work”). Figures such as women’s personal aspirations, gender roles, cultural and generational values, and the material conditions of the Chinese workplace ventriloquize into their everyday constructions. This study finds that post-1980s women are both perpetuators and dissidents of gendered and national-cultural work ideology as they negotiate various tensions to frame good work as wending (stable), timian (face adding, status promoting), and yourenyouyu (fulfilling, achieving). Situated in the context of a transitional developing country rooted in Eastern traditions, this study unpacks how various discursive and material forces engage in tensional constructions of work meanings and sheds light on women’s career socialization and gender equity in the Chinese workplace.
Differential usage of transcriptional start sites and polyadenylation sites in FMR1 premutation alleles

5′- and 3′-untranslated regions (UTRs) are important regulators of gene expression and play key roles in disease progression and susceptibility. The 5′-UTR of the fragile X mental retardation 1 (FMR1) gene contains a CGG repeat element that is expanded (>200 CGG repeats; full mutation) and methylated in fragile X syndrome (FXS), the most common form of inherited intellectual disability (ID) and known cause of autism. Significant phenotypic involvement has also emerged in some individuals with the premutation (55–200 CGG repeats), including fragile X-associated premature ovarian insufficiency (FXPOI) in females, and the neurodegenerative disorder, fragile X-associated tremor/ataxia syndrome (FXTAS), in older adult carriers. Here, we show that FMR1 mRNA in human and mouse brain is expressed as a combination of multiple isoforms that use alternative transcriptional start sites and different polyadenylation sites. Furthermore, we have identified a novel human transcription start site used in brain but not in lymphoblastoid cells, and have detected FMR1 isoforms generated through the use of both canonical and non-canonical polyadenylation signals. Importantly, in both human and mouse, a specific regulation of the UTRs is observed in brain of FMR1 premutation alleles, suggesting that the transcript variants may play a role in premutation-related pathologies.
Loss of Optineurin In Vivo Results in Elevated Cell Death and Alters Axonal Trafficking Dynamics

Mutations in Optineurin have been associated with ALS, glaucoma, and Paget’s disease of bone in humans, but little is known about how these mutations contribute to disease. Most of the cellular consequences of Optineurin loss have come from in vitro studies, and it remains unclear whether these same defects would be seen in vivo. To answer this question, we assessed the cellular consequences of Optineurin loss in zebrafish embryos to determine if they showed the same defects as have been described in the in vitro studies. We found that loss of Optineurin resulted in increased cell death, as well as subtle cell morphology, cell migration and vesicle trafficking defects. However, unlike experiments on cells in culture, we found no indication that the Golgi apparatus was disrupted or that NF-κB target genes were upregulated. Therefore, we conclude that in vivo loss of Optineurin shows some, but not all, of the defects seen in in vitro work.
Réforme des pensions légales: le système de pensions à points

Le gouvernement s'est engage a mettre en place un systeme de pension a points comme propose par la Commission de reforme des pensions 2020-2040. Nous expliquons comment ce systeme fonctionne et sa flexibilite pour integrer la penibilite des metiers et la pension a temps partiel. Nous discutons des mecanismes de pilotage du systeme face au vieillissement et a l'evolution de l'emploi.
A Model Project for Exploring the Role of Sustainability Science in a Citizen-Centered, Collaborative Decision-Making Process

The role of science in society is evolving as we enter the 21st century. The report, Science — The Endless Frontier (Bush 1990[1945]), outlined a model of national scientific research that served the country for 50 years. The contract between science and society established in that report stipulated that science is essential and that basic research meets national needs (Pielke and Byerly 1998). This stipulation and the abundant — seemingly unlimited and unquestioned — funding for research during the Cold War caused many scientists to come to believe that funding for science was an entitlement independent of societal needs. Implicit in this belief is that science alone can solve society’s problems. We now are learning that many policy issues that involve science involve diverse economic, political, social, and aesthetic values as well, and rarely, if ever, is scientific information alone the basis of public policy (e.g., see Sarewitz 1996a, 1996b; Frodeman 1997). Moreover, resources are increasingly more limited and many in society are questioning the value of public-supported science. This reality challenges the scientific community to define a new social contract that is in accord with the social and political conditions that characterize the dawn of the 21st century (e.g., Lubchenco 1998). Under the terms of the new contract, science is still essential. However, national needs now dictate that much of the research undertaken, and funding for science, will not be an entitlement independent of societal issues and concerns. As populations continue to expand, tensions between environmental preservation and economic development will exacerbate land-use conflicts. Quality of life for the 8-10 billion people who will inhabit the planet by the end of the 21st century will depend on how well we as a society resolve these conflicts. This paper addresses one way that a Federal government science agency can engage citizens in a partnership to develop a communitybased decision making process grounded in sound science. The Need for Community-based Projects Grounded in Sound Science
Rare Giant Granular Cell Ameloblastoma: A Case Report and an Immunohistochemical Study

Aims. The aim is to present a case of rare giant granular cell ameloblastoma and to review the pertinent literature highlighting the molecular aspects of its pathogenesis by analyzing the expression of CD-68, Bcl-2, and β-catenin. Methods. H and E stained sections showed large odontogenic islands showing peripheral ameloblast-like cells and central stellate reticulum-like cells with extensive granular cell transformation surrounded by fibrous stroma. Polyclonal rabbit anti-CD 68, anti-Bcl2, and anti-β-catenin were stained immunohistochemically. Results. CD-68 showed a moderate to strong staining intensity in granular cells. Moderate staining of Bcl-2 was expressed by the peripheral columnar cells of tumor islands and negative in the granular cells. Expression of β-catenin was generally weak, except for only the focal areas that showed a moderate staining intensity and weak in peripheral cells. Conclusion. The present case of giant granular cell ameloblastoma is a rare entity. Development of monstrous size is indicative of ameloblastomas persistent growth. Granular cell transformation in ameloblastomas probably occurs as a consequence of extensive molecular changes. Immunohistochemical studies help us to know the pathogenesis of this granular cell ameloblastoma. Therefore, an effort has been made here to study the expression of Bcl-2, CD-68, and β-catenin.
Solving the obstacle neutralization problem using swarm intelligence algorithms

In this study, we tackle the obstacle neutralization problem wherein an agent is supposed to find the shortest path from given points s to t in a mapped hazard field where there are N potential mine discs in the field. In this problem agent has neutralization capability but he/she can neutralize only limited number of discs (K). The neutralization number is limited because of a specific reason such as the load capacity of agent or vehicle. When a disk is neutralized its cost is added to the traversal length of path. This problem is a kind of shortest problem with source constraints and it is NP-Hard. In this study, three important swarm intelligence techniques, namely ant system, ant colony system and migrating birds optimization algorithms, are applied to solve the obstacle neutralization problem and computational research is conducted in order to reveal their performance. Our experiments suggest that the migrating birds optimization algorithm outperforms ant system and ant colony system whereas ant colony system is better than ant system.
Continuous discrete observer with updated sampling period (long version)

This paper is the long version of a published paper in Automatica (and presented to NOLCOS 2013). This paper deals with the design of high gain observers for a class of continuous-time dynamical systems with discrete-time measurements. Indeed, different approaches based on high gain techniques have been followed in the literature to tackle this problem. Contrary to these works, the measurement sampling time is considered to be variable. Moreover, the new idea of the proposed work is to synthesize an observer requiring the less knowledge as possible from the output measurements. This is done by using an updated sampling time observer. The vector fields related to the systems considered in this paper are assumed to be globally Lipschitz. Under this assumption, the asymptotic convergence of the observation error is established. As an application of this approach, a state estimation problem of an academic bioprocess is studied, and its simulation results are discussed.
Network Coding based Interactive Multiview Video Streaming in ICN Networks

In Content Centric Networks (ccn), data transmission is based on content names instead of identifiers as in IP networks. In a ccn network users communicate with their connected neighbours to search for data. This approach can be used for mobile networks. Considering such wireless mobile networks, network coding (nc) is able to improve the throughput in the network. Since mobile Internet traffic is increasing fast, new solutions are required that would increase the overall throughput of the wireless network. In this thesis we consider a ccn network with a free viewpoint video streaming application. We propose two network coding schemes for the delivery of video data and evaluate their performance in terms of the average video quality. Matlab simulations are used to compute the average quality of the users view. With these simulations, we can show that applying nc rules provide a better quality in the displayed views for some communication scenarios.
Modeling Prosody for Speaker Recognition: Why Estimating Pitch May Be a Red Herring

It has long been claimed that spectral envelope features outperform prosodic features on speaker recognition tasks. However, the reasons for such an arrangement are not entirely compelling. In the current work we present some evidence to challenge these claims. We propose that energy found at harmonically related frequencies encodes the acoustic correlates of variables which are typically referred to as prosodic, making harmonic energy summation highly relevant. Its frequent implementation for estimating pitch appears to have gone unnoticed by the speaker recognition community, because pitch estimators quite deliberately discard what they compute, retaining only the abscissa of a maximum. We argue that this latter step renders pitch estimation somewhat ill-suited to speaker recognition tasks. We present the detailed construction of a discrete transform, and a normalization, which are amenable to relatively laconic modeling. With this framework we achieve or exceed the performance of spectral envelope features in nearfield, matched-channel and matched-multisession conditions; performance improves following envelope destruction. We believe these results may have far-reaching consequences. For speech processing in a multitude of applications, they suggest that modeling the harmonic structure in the way we propose is at least as relevant as is modeling other aspects of the signal.
Towards Dynamic Load Balancing Using Page Migration and Loop Re-partitioning on Omni / SCASH

Increasingly large-scale clusters of SMPs continue to become majority platform in HPC field. Such a cluster environment, there may be load imbalances due to several reasons and mis-placement of data which bring performance bottlenecks. To overcome these problems, some dynamic load balancing mechanisms are needed. In this paper, we report our ongoing work on dynamic load balancing extention to Omni/SCASH which is an implementation of OpenMP on Software Distributed Shared Memory, SCASH. Using our dynamic load balancing mechanisms, we expect that programmers can have load imbalances adjusted automatically by the runtime system without explicit definition of data and task placements in a commodity cluster environment with possibly heterogeneous performance nodes.
Can we enhance low-carbon tour intentions through climate science or responsibility sharing information?

In line with social representations theory, our study presents two mediating models to examine the psychological mechanism underlying how tourists’ intentions toward low-carbon tours could be enhanced through a reduction in their ambivalence toward low-carbon tours. Recruiting 767 independent tourists, applying an ordinary-least-square simple regression, and following the mediating testing approach of Baron and Kenny (1986), we have found that using scientific climate information can efficiently strengthen tourists’ travel intentions toward engaging in low-carbon tours and can also reduce tourists’ ambivalence toward low-carbon tours. We found, however, that another tourist education approach, responsibility sharing, did not have a similar effect, owing possibly to the social-loafing effect.