Miracle-dz/UniFAR-FTUs huggingface dataset:
Colour image segmentation by the vector-valued Allen-Cahn phase-field model: a multigrid solution

We propose a new method for the numerical solution of a PDE-driven model for colour image segmentation and give numerical examples of the results. The method combines the vector-valued Allen-Cahn phase ﬁeld equation with initial data ﬁtting terms. This method is known to be closely related to the Mumford-Shah problem and the level set segmentation by Chan and Vese. Our numerical solution is performed using a multigrid splitting of a ﬁnite element space, thereby producing an eﬃcient and robust method for the segmentation of large images. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.
Neural Architectures for Robot Intelligence

We argue that direct experimental approaches to elucidate the architecture of higher brains may benefit from insights gained from exploring the possibilities and limits of artificial control architectures for robot systems. We present some of our recent work that has been motivated by that view and that is centered around the study of various aspects of hand actions since these are intimately linked with many higher cognitive abilities. As examples, we report on the development of a modular system for the recognition of continuous hand postures based on neural nets, the use of vision and tactile sensing for guiding prehensile movements of a multifingered hand, and the recognition and use of hand gestures for robot teaching. Regarding the issue of learning, we propose to view real-world learning from the perspective of data-mining and to focus more strongly on the imitation of observed actions instead of purely reinforcement-based exploration. As a concrete example of such an effort we report on the status of an ongoing project in our laboratory in which a robot equipped with an attention system with a neurally inspired architecture is taught actions by using hand gestures in conjunction with speech commands. We point out some of the lessons learnt from this system, and discuss how systems of this kind can contribute to the study of issues at the junction between natural and artificial cognitive systems.
Heuristics and Parse Ranking

There are currently two philosophies for building grammars and parsers – Statistically induced grammars and Wide-coverage grammars. One way to combine the strengths of both approaches is to have a wide-coverage grammar with a heuristic component which is domain independent but whose contribution is tuned to particular domains. In this paper, we discuss a three-stage approach to disambiguation in the context of a lexicalized grammar, using a variety of domain independent heuristic techniques. We present a training algorithm which uses hand-bracketed treebank parses to set the weights of these heuristics. We compare the performance of our grammar against the performance of the IBM statistical grammar, using both untrained and trained weights for the heuristics.
Evaluation of the Coalbed Methane Potential by a GIS-Based Fuzzy AHP Model

Coalbed methane (CBM) potential evaluation is important for choosing the prospective target area for CBM exploration and production. Many unwise evaluations may have induced the high failure ratio of CBM exploration and development in China. Developing a comprehensive model for CBM potential evaluation is also complicated by the diverse geologic and engineering factors. In this paper, a Fuzzy analytic hierarchy (AHP) model for CBM evaluation is proposed, capable of tracking the uncertainty and imprecision and solving the multiple-criteria decision-making problems. The model is applied to evaluate the CBM potential of the eastern parts of Ordos basin. The results indicated that the Fuzzy AHP evaluation system is suggested to be a good tool for evaluating CBM potential.
Sex Differences in the Rate, Timing, and Principal Diagnoses of 30-Day Readmissions in Younger Patients with Acute Myocardial Infarction

Background— Young women (<65 years) experience a 2- to 3-fold greater mortality risk than younger men after an acute myocardial infarction. However, it is unknown whether they are at higher risk for 30-day readmission, and if this association varies by age. We examined sex differences in the rate, timing, and principal diagnoses of 30-day readmissions, including the independent effect of sex following adjustment for confounders. Methods and Results— We included patients aged 18 to 64 years with a principal diagnosis of acute myocardial infarction. Data were used from the Healthcare Cost and Utilization Project-State Inpatient Database for California (07–09). Readmission diagnoses were categorized by using an aggregated version of the Centers for Medicare and Medicaid Services’ Condition Categories, and readmission timing was determined from the day after discharge. Of 42 518 younger patients with acute myocardial infarction (26.4% female), 4775 (11.2%) had at least 1 readmission. The 30-day all-cause readmission rate was higher for women (15.5% versus 9.7%, P<0.0001). For both sexes, readmission risk was highest on days 2 to 4 after discharge and declined thereafter, and women were more likely to present with noncardiac diagnoses (44.4% versus 40.6%, P=0.01). Female sex was associated with a higher rate of 30-day readmission, which persisted after adjustment (hazard ratio, 1.22; 95% confidence interval, 1.15–1.30). There was no significant interaction between age and sex on readmission. Conclusions— In comparison with men, younger women have a higher risk for readmission, even after the adjustment for confounders. The timing of 30-day readmission was similar in women and men, and both sexes were susceptible to a wide range of causes for readmission.
Differential Mitochondrial, Oxidative Stress and Inflammatory Responses to SARS-CoV-2 Spike Protein Receptor Binding Domain in Human Lung Microvascular, Coronary Artery Endothelial and Bronchial Epithelial Cells

Recent evidence indicates that the SARS-CoV-2 spike protein affects mitochondria with a cell type-dependent outcome. We elucidate the effect of the SARS-CoV-2 receptor binding domain (RBD) on the mitochondrial network and cristae morphology, oxygen consumption, mitoROS production, and inflammatory cytokine expression in cultured human lung microvascular (HLMVECs), coronary artery endothelial (HCAECs), and bronchial epithelial cells (HBECs). Live Mito Orange staining, STED microscopy, and Fiji MiNa analysis were used for mitochondrial cristae and network morphometry; an Agilent XFp analyser for mitochondrial/glycolytic activity; MitoSOX fluorescence for mitochondrial ROS; and qRT-PCR plus Luminex for cytokines. HLMVEC exposure to SARS-CoV-2 RBD resulted in the fragmentation of the mitochondrial network, mitochondrial swelling, increased cristae area, reduced cristae density, and suppressed mitochondrial oxygen consumption and glycolysis. No significant mitochondrial morphology or oxygen consumption changes were observed in HCAECs and HBECs. SARS-CoV-2 RBD induced mitoROS-mediated expression of cytokines GM-CSF and IL-1β in all three investigated cell types, along with IL-8 expression in both endothelial cell types. The findings suggest mitochondrial ROS control SARS-CoV-2 RBD-induced inflammation in HLMVECs, HCAECs, and HBECs, with the mitochondria of HLMVECs being more sensitive to SARS-CoV-2 RBD.
IMPACT: Investigation of Mobile-user Patterns Across University Campuses using WLAN Trace Analysis

We conduct the most comprehensive study of WLAN traces to date. Measurements collected from four major university campuses are analyzed with the aim of developing fundamental understanding of realistic user behavior in wireless networks. Both individual user and inter-node (group) behaviors are investigated and two classes of metrics are devised to capture the underlying structure of such behaviors. For individual user behavior we observe distinct patterns in which most users are 'on' for a small fraction of the time, the number of access points visited is very small and the overall on-line user mobility is quite low. We clearly identify categories of heavy and light users. In general, users exhibit high degree of similarity over days and weeks. For group behavior, we define metrics for encounter patterns and friendship. Surprisingly, we find that a user, on average, encounters less than 6% of the network user population within a month, and that encounter and friendship relations are highly asymmetric. We establish that number of encounters follows a biPareto distribution, while friendship indexes follow an exponential distribution. We capture the encounter graph using a small world model, the characteristics of which reach steady state after only one day. We hope for our study to have a great impact on realistic modeling of network usage and mobility patterns in wireless networks.
The Presentation of “Pro-Anorexia” in Online Group Interactions

Although pro-anorexia online support forums and the narratives that occur within them are increasingly the focus of research, none, to date, focuses closely on issues of identity within this online context. Our aim in conducting this study was to examine the presentation of pro-anorexia via an interpretive phenomenological analysis of postings to a pro-anorexia (“pro-ana”) online discussion forum. Analysis indicates that pro-anorexic identities are normalized and strengthened through the normalization of participants' pro-ana thoughts and behaviors, and the group bond created through sharing a secret identity. This process renders participants less likely to reveal their pro-ana identity to friends and family in the real world. The implications of our findings are discussed in relation to the theory of identity demarginalization.
Understanding the Characteristics of Internet Short Video Sharing: YouTube as a Case Study

Established in 2005, YouTube has become the most successful Internet site providing a new generation of short video sharing service. Today, YouTube alone comprises approximately 20% of all HTTP traffic, or nearly 10% of all traffic on the Internet. Understanding the features of YouTube and similar video sharing sites is thus crucial to their sustainable development and to network traffic engineering. In this paper, using traces crawled in a 3-month period, we present an in-depth and systematic measurement study on the characteristics of YouTube videos. We find that YouTube videos have noticeably different statistics compared to traditional streaming videos, ranging from length and access pattern, to their active life span, ratings, and comments. The series of datasets also allows us to identify the growth trend of this fast evolving Internet site in various aspects, which has seldom been explored before. We also look closely at the social networking aspect of YouTube, as this is a key driving force toward its success. In particular, we find that the links to related videos generated by uploaders' choices form a small-world network. This suggests that the videos have strong correlations with each other, and creates opportunities for developing novel caching or peer-to-peer distribution schemes to efficiently deliver videos to end users.
Cascaded Markov Models

This paper presents a new approach to partial parsing of context-free structures. The approach is based on Markov Models. Each layer of the resulting structure is represented by its own Markov Model, and output of a lower layer is passed as input to the next higher layer. An empirical evaluation of the method yields very good results for NP/PP chunking of German newspaper texts.
Application of Project-Based Learning to Improve the 4C Abilities (Critical Thinking, Creativity, Collaboration, and Communication) of Children Aged 5-6 Years

This research aims to improve the 4C (Critical Thinking, Creativity, Collaboration, and Communication) abilities of children aged 5-6 years by using the Project Based Learning (PjBL) learning model. This research uses a type of classroom action research using the Kemmis and Mc Taggart model through 4 stages, namely: 1) planning, 2) Action, 3) Observation, and 4) Reflection. The subjects in this research were children aged 5-6 years at GMIM Sion Tomohon Kindergarten with a total of 23 children. The data collection technique uses observation and non-test techniques which are used to measure the creativity of children aged 5-6 years, namely batik work using natural papaya leaves using the ecoprint technique. Data collection instruments use observation assessments (attitude assessments), work skills assessments work results assessment instruments, as well as questionnaires for assessing children's developmental achievements. The data analysis used in this research is quantitative and qualitative, namely simple descriptive statistics, the data reduction process, data presentation, and conclusion are carried out in the qualitative analysis process. The research results show that there is an increase in the 4C (Critical Thinking, Creativity, Collaboration, and Communication) abilities of children aged 5-6 years through the Project Based Learning (PjBL) learning model. This is proven by the activities of teachers and children who support the 4C indicators.
Novel senescence associated gene, YPEL3, is repressed by estrogen in ER+ mammary tumor cells and required for tamoxifen‐induced cellular senescence

Estrogen signaling plays an important role in breast carcinogenesis. An increased understanding of estrogen gene targets and their effects will allow for more directed and effective therapies for individuals with breast cancer, particularly those with estrogen receptor positive tumors resistant to tamoxifen therapy. Here, we identify YPEL3 as a growth suppressive protein downregulated by estrogen in estrogen receptor positive breast cancer cell lines. Estrogen repression of YPEL3 expression was found to be independent of p53 but dependent on estrogen receptor alpha expression. Importantly, YPEL3 expression, which is induced by the removal of estrogen or treatment with tamoxifen triggers cellular senescence in MCF‐7 cells while loss of YPEL3 increases the growth rate of MCF‐7 cells. Taken together these findings suggest that YPEL3 may represent a potential target for directed hormonal therapy for estrogen receptor positive breast cancer patients.
Eliminating deceptions and mistaken belief to infer conversational implicature

Conversational implicatures are usually described as being licensed by the disobeying or flouting of some principle by the speaker in cooperative dialogue. However, such work has failed to distinguish cases of the speaker flouting such a principle from cases where the speaker is either deceptive or holds a mistaken belief. In this paper, we demonstrate how the three different cases can be distinguished in terms of the beliefs ascribed to the speaker of the utterance. We argue that in the act of distinguishing the speaker's intention and ascribing such beliefs, the intended inference can be made by the hearer. This theory is implemented in ViewGen, a pre-existing belief modelling system used in a medical counselling domain.
Composition attacks and auxiliary information in data privacy

Privacy is an increasingly important aspect of data publishing. Reasoning about privacy, however, is fraught with pitfalls. One of the most significant is the auxiliary information (also called external knowledge, background knowledge, or side information) that an adversary gleans from other channels such as the web, public records, or domain knowledge. This paper explores how one can reason about privacy in the face of rich, realistic sources of auxiliary information. Specifically, we investigate the effectiveness of current anonymization schemes in preserving privacy when multiple organizations independently release anonymized data about overlapping populations. 1. We investigate composition attacks, in which an adversary uses independent anonymized releases to breach privacy. We explain why recently proposed models of limited auxiliary information fail to capture composition attacks. Our experiments demonstrate that even a simple instance of a composition attack can breach privacy in practice, for a large class of currently proposed techniques. The class includes k-anonymity and several recent variants. 2. On a more positive note, certain randomization-based notions of privacy (such as differential privacy) provably resist composition attacks and, in fact, the use of arbitrary side information.This resistance enables "stand-alone" design of anonymization schemes, without the need for explicitly keeping track of other releases. We provide a precise formulation of this property, and prove that an important class of relaxations of differential privacy also satisfy the property. This significantly enlarges the class of protocols known to enable modular design.
Novel BCD adders and their reversible logic implementation for IEEE 754r format

IEEE 754r is the ongoing revision to the IEEE 754 floating point standard and a major enhancement to the standard is the addition of decimal format. This paper proposes two novel BCD adders called carry skip and carry look-ahead BCD adders respectively. Furthermore, in the recent years, reversible logic has emerged as a promising technology having its applications in low power CMOS, quantum computing, nanotechnology, and optical computing. It is not possible to realize quantum computing without reversible logic. Thus, this paper also paper provides the reversible logic implementation of the conventional BCD adder as the well as the proposed carry skip BCD adder using a recently proposed TSG gate. Furthermore, a new reversible gate called TS-3 is also being proposed and it has been shown that the proposed reversible logic implementation of the BCD adders is much better compared to recently proposed one, in terms of number of reversible gates used and garbage outputs produced. The reversible BCD circuits designed and proposed here form the basis of the decimal ALU of a primitive quantum CPU.
Return-Map Cryptanalysis Revisited

As a powerful cryptanalysis tool, the method of return-map attacks can be used to extract secret messages masked by chaos in secure communication schemes. Recently, a simple defensive mechanism was presented to enhance the security of chaotic parameter modulation schemes against return-map attacks. Two techniques are combined in the proposed defensive mechanism: multistep parameter modulation and alternative driving of two different transmitter variables. This paper re-studies the security of this proposed defensive mechanism against return-map attacks, and points out that the security was much over-estimated in the original publication for both ciphertext-only attack and known/chosen-plaintext attacks. It is found that a deterministic relationship exists between the shape of the return map and the modulated parameter, and that such a relationship can be used to dramatically enhance return-map attacks thereby making them quite easy to break the defensive mechanism.
Detection of the old stellar component of the major Galactic bar

We present near-infrared colour–magnitude diagrams and star counts for a number of regions along the Galactic plane. It is shown that along the l=27°, b=0° line of sight there is a feature at 5.7±0.7 kpc with a density of stars at least a factor of 2 and probably more than a factor of 5 times that of the disc at the same position. This feature forms a distinct clump on an H versus J−H diagram and is seen at all longitudes from the bulge to about l=28°, but at no longitude greater than this. The distance to the feature at l=20° is about 0.5 kpc further than at l=27°, and by l=10° it has merged with, or has become, the bulge. Given that at l=27° and l=21° there is also a clustering of very young stars, the only component that can reasonably explain what is seen is a bar with half-length of around 4 kpc and a position angle of about 43°±7°.
EpicRec: Towards Practical Differentially Private Framework for Personalized Recommendation

Recommender systems typically require users' history data to provide a list of recommendations and such recommendations usually reside on the cloud/server. However, the release of such private data to the cloud has been shown to put users at risk. It is highly desirable to provide users high-quality personalized services while respecting their privacy. In this paper, we develop the first Enhanced Privacy-built-In Client for Personalized Recommendation (EpicRec) system that performs the data perturbation on the client side to protect users' privacy. Our system needs no assumption of trusted server and no change on the recommendation algorithms on the server side; and needs minimum user interaction in their preferred manner, which makes our solution fit very well into real world practical use. The design of EpicRec system incorporates three main modules: (1) usable privacy control interface that enables two user preferred privacy controls, overall and category-based controls, in the way they understand; (2) user privacy level quantification that automatically quantifies user privacy concern level from these user understandable inputs; (3) lightweight data perturbation algorithm that perturbs user private data with provable guarantees on both differential privacy and data utility. Using large-scale real world datasets, we show that, for both overall and category-based privacy controls, EpicRec performs best with respect to both perturbation quality and personalized recommendation, with negligible computational overhead. Therefore, EpicRec enables two contradictory goals, privacy preservation and recommendation accuracy. We also implement a proof-of-concept EpicRec system to demonstrate a privacy-preserving personal computer for movie recommendation with web-based privacy controls. We believe EpicRec is an important step towards designing a practical system that enables companies to monetize on user data using high quality personalized services with strong provable privacy protection to gain user acceptance and adoption of their services.
Generalized solution concepts in games with possibly unaware players

Most work in game theory assumes that players are perfect reasoners and have common knowledge of all significant aspects of the game. In earlier work (Halpern and Rêgo 2006, arxiv.org/abs/0704.2014), we proposed a framework for representing and analyzing games with possibly unaware players, and suggested a generalization of Nash equilibrium appropriate for games with unaware players that we called generalized Nash equilibrium. Here, we use this framework to analyze other solution concepts that have been considered in the game-theory literature, with a focus on sequential equilibrium.
Explanation-based learning for Machine Translation

In this paper we present an application of explanation-based learning (EBL) in the parsing module of a real-time English-Spanish machine translation system designed to translate closed captions. We discuss the efficiency/coverage trade-offs available in EBL and introduce the techniques we use to increase coverage while maintaining a high level of space and time efficiency. Our performance results indicate that this approach is effective.
Two Models for the Study of Congested Internet Connections

In this paper, we introduce two deterministic models aimed at capturing the dynamics of congested Internet connections. The first model is a continuous-time model that combines a system of differential equations with a sudden change in one of the state variables. The second model is a discrete-time model with a time step that arises naturally from the system. Results from these models show good agreement with the well-known ns network simulator, better than the results of a previous, similar model. This is due in large part to the use of the sudden change to reflect the impact of lost data packets. We also discuss the potential use of this model in network traffic state estimation.