Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Approach for Service Function Chain Deployment

Since the popularity and development of Cloud Computing, Network Function Virtualization (NFV) and Service Function Chain (SFC) provisioning have attracted more and more attentions from researchers. With the increasing of the number of users and demands for network resources, network resources are becoming extremely valuable. Therefore, it is necessary for designing an efficient algorithm to provision the SFC with the minimum consumption of bandwidth resources. In this paper, we study the problem of cost efficient deploying for SFCs to reduce the consumption of bandwidth resources. We propose an efficient algorithm for SFC deployment based on the strategies of layering physical network and evaluating physical network nodes to minimize the bandwidth resource consumption (SFCD-LEMB). It aims at deploying the Virtualization Network Functions (VNFs) of the SFC onto appropriate nodes and mapping the SFC onto reasonable path by layering the physical network. Simulation results show that the average gains on bandwidth consumption, acceptance ratio and time efficiency of our algorithm are 50%, 15% and 60%, respectively.
Some Applications of Detailed Wind Profile Data to Launch Vehicle Response Problems

Abstract : The response of a launch vehicle to a number of detailed wind profiles has been determined. The wind profiles were measured by two techniques which are briefly described. One of these techniques uses an angle-of-attack sensor in conjunction with guidance data to measure the wind profile traversed by some particular launch vehicle. The other wind-measuring technique is a photographic triangulation method, whereby two cameras take simultaneous pictures of a vertical trail of smoke left by a launch vehicle or sounding rocket. The response of a vehicle flying these detailed profiles is compared with the response of a vehicle flying these detailed profiles is compared with the response of the same vehicle flying through balloon-measured profiles. The response to the detailed wind profiles, relative to the balloon-measured profiles, is characterized by the large excitation of the rigid pitch and elastic bending modes. This is found to cause higher loads on the launch vehicle structure. Established design criteria which utilize balloon-measured wind profiles have arbitrarily accounted for this increased load by adding a load due to some type of discrete gust.
In Partial Fulfillment of the WPEII Requirement Calculating and Presenting Trust in Collaborative Content

Collaborative functionality is increasingly prevalent in Internet applications. Such functionality permits individuals to add -and sometimes modify -web content, often with minimal barriers to entry. Ideally, large bodies of knowledge can be amassed and shared in this manner. However, such software also provides a medium for biased individuals, spammers, and nefarious persons to operate. By computing trust/reputation for participating agents and/or the content they generate, one can identify quality contributions. In this work, we survey the state-of-the-art for calculating trust in collaborative content. In particular, we examine four proposals from literature based on: (1) content persistence, (2) natural-language processing, (3) metadata properties, and (4) incoming link quantity. Though each technique can be applied broadly, Wikipedia provides a focal point for discussion. Finally, having critiqued how trust values are calculated, we analyze how the presentation of these values can benefit end-users and application security. Comments University of Pennsylvania Department of Computer and Information Science Technical Report No. MSCIS-10-33. This technical report is available at ScholarlyCommons: http://repository.upenn. edu/cis_reports/943 University of Pennsylvania Dept. of Computer and Information Science Philadelphia, Pennsylvania, USA In Partial Fulfillment of the WPEII Requirement Calculating and Presenting Trust in Collaborative Content Author: Andrew G. West Committee Chair: Sampath Kannan Committee Member: Andreas Haeberlen Committee Member: Boon Thau Loo
Going to political extremes in response to boredom

Boredom makes people attempt to re-establish a sense of meaningfulness. Political ideologies, and in particular the adherence to left- versus right-wing beliefs, can serve as a source of meaning. Accordingly, we tested the hypothesis that boredom is associated with a stronger adherence to left- versus right-wing beliefs, resulting in more extreme political orientations. Study 1 demonstrates that experimentally induced boredom leads to more extreme political orientations. Study 2 indicates that people who become easily bored with their environment adhere to more extreme ends of a political spectrum compared with their less easily bored counterparts. Finally, Study 3 reveals that the relatively extreme political orientations among those who are easily bored can be attributed to their enhanced search for meaning. Overall, our research suggests that extreme political orientations are, in part, a function of boredom's existential qualities.
Teaching Writing Informed by Systemic Functional Linguistics: "I Never Would Have Thought of Doing That...".

Teaching Writing Informed by SFL: “I never would have thought of doing that. ” Tracy Hodgson-Drysdale Dissertation Director: Maria Estela Brisk Writing is an essential tool for creating meaningful communication and as such it must be taught beginning in elementary school. Although in the past 100 years writing has become more common in our everyday lives, methods of teaching writing and teacher education have not kept pace with changes (National Commission on Writing, 2003). As a result, teachers are underprepared to teach writing and do not teach it enough (Gilbert & Graham, 2010). The goal of this study is to understand how teacher-researcher relationships can facilitate the development of a teacher’s knowledge of the theoretical foundations of teaching writing through systemic functional linguistics (SFL) and the teaching and learning cycle (TLC), and how that understanding affects the implementation of meaningful writing instruction that supports bilingual students as they
Social Class and Social Worlds

Does access to money predict social behavior? Past work has shown that money fosters self-sufficiency and reduces interest in others. Building on this work, we tested whether income predicts the frequency and type of social interactions. Two studies using large, nationally representative samples of Americans (N = 118,026) and different measures of social contact showed that higher household income was associated with less time spent socializing with others (Studies 1 and 2) and more time spent alone (Study 2). Income also predicted the nature of social contact. People with higher incomes spent less time with their families and neighbors and spent more time with their friends. These findings suggest that income is associated with how and with whom people spend their time.
Temporal sampling helps unravel the genetic structure of naturally occurring populations of a phytoparasitic nematode. 2. Separating the relative effects of gene flow and genetic drift

Studying wild pathogen populations in natural ecosystems offers the opportunity to better understand the evolutionary dynamics of biotic diseases in crops and to enhance pest control strategies. We used simulations and genetic markers to investigate the spatial and temporal population genetic structure of wild populations of the beet cyst nematode Heterodera schachtii on a wild host plant species, the sea beet (Beta vulgaris spp. maritima), the wild ancestor of cultivated beets. Our analysis of the variation of eight microsatellite loci across four study sites showed that (i) wild H. schachtii populations displayed fine‐scaled genetic structure with no evidence of substantial levels of gene flow beyond the scale of the host plant, and comparisons with simulations indicated that (ii) genetic drift substantially affected the residual signals of isolation‐by‐distance processes, leading to departures from migration–drift equilibrium. In contrast to what can be suspected for (crop) field populations, this showed that wild cyst nematodes have very low dispersal capabilities and are strongly disconnected from each other. Our results provide some key elements for designing pest control strategies, such as decreasing passive dispersal events to limit the spread of virulence among field nematode populations.
Transforming Growth Factor-β Signaling Plays a Pivotal Role in the Interplay Between Osteosarcoma Cells and Their Microenvironment

Osteosarcomas are the most frequent form of primary bone tumors and mainly affect children, adolescents, and young adults. Despite encouraging progress in therapeutic management, including the advent of multidrug chemotherapy, the survival rates have remained unchanged for more than four decades: 75% at 5 years for localized disease, but two groups of patients are still at high risk: metastatic at diagnosis (overall survival around 40% at 5 years) and/or poor responders to chemotherapy (20% at 5 years). Because these tumors are classified as “complex genomic,” it is extremely difficult to determine the signaling pathways that might be targeted by specific therapies. A hypothesis has thus emerged, stating that the particular microenvironment of these tumors may interfere with the tumor cells that promote chemoresistance and the dissemination of metastases. The stroma is composed of a large number of cell types (immune cells, endothelial cells, mesenchymal stromal cells, etc.) which secrete growth factors, such as transforming growth factor-β (TGF-β), which favors the development of primary tumors and dissemination of metastases by constituting a permissive niche at primary and distant sites. Rather than targeting the tumor cells themselves, which are very heterogeneous in osteosarcoma, the hypothesis is instead to target the key actors secreted in the microenvironment, such as TGF-βs, which play a part in tumor progression. In the last decade, numerous studies have shown that overexpression of TGF-β is a hallmark of many cancers, including primary bone tumors. In this context, TGF-β signaling has emerged as a crucial factor in the cross talk between tumor cells and stroma cells in poor-prognosis cancers. Secretion of TGF-β by tumor cells or stroma cells can effectively act in a paracrine manner to regulate the phenotype and functions of the microenvironment to stimulate protumorigenic microenvironmental changes. TGF-β can thus exert its protumorigenic function in primary bone tumors by promoting angiogenesis, bone remodeling and cell migration, and by inhibiting immunosurveillance. This review focuses on the involvement of TGF-β signaling in primary bone tumor development, and the related therapeutic options that may be possible for these tumors.
DISTRIBUTED SENSOR AND VEHICLE NETWORKED SYSTEMS FOR ENVIRONMENTAL APPLICATIONS

The recent and exciting possibilities offered by the operation of networked vehicles and distributed sensor systems are reviewed and their applications in environmental field studies are outlined. Networked vehicle systems involving sea, air, and ground autonomous or operator-assisted vehicles are used as platforms for active sensing, such as adaptive sampling for oceanographic field studies. Sensor networks combine data from spatially distributed sensor units which in addition to sensing capabilities have processing, power management, and communication capabilities. The cost of these sensor units is already in the order of some Euros and it is expected to reduce even further in a near future. This allows for the deployment of a high concentration of sensor units in a fairly large geographical area with acceptable costs. The combined operation of networked vehicles and sensor units allows researchers to envision ambitious environmental studies where, for example, a given geographical is monitored in real-time with adjustable resolution. The review is done in the context of the research programme of the Underwater Systems and Technology Laboratory (USTL) from Porto University. Over the last two years the USTL devoted an intense effort to the development of feasible concepts for the networked operation of multiple vehicles and systems, and the first deployments are scheduled for late 2003.
Distance estimation method with snapshot landmark images in the robotic homing navigation

Animals and insects use their own navigating system to return home in various ways. One of the most widely used senses is vision. They use visual information to remember the home snapshot image which is useful in returning home from an arbitrary location. Inspired by behaviours of insects and other animals, there have been many homing algorithms applied to mobile robots. These methods use visual information to choose the moving direction by comparing the current landmark view with the snapshot taken at the nest. In this paper, we suggest a new image-based navigation method which is called landmark navigation with distance estimation. This method computes the distance to each landmark by using only the visual information of an omnidirectional camea. Estimated distance is then used to locate the robot in an environmental map. As a result, this new method shows better performance in returning home from an arbitrary location than other methods. The corresponding robotic experiments will be demonstrated.
A Pilot Study of Inhaled CO Therapy in Neonatal Hypoxia-Ischemia: Carboxyhemoglobin Concentrations and Brain Volumes

Objective: The objective of this pilot study was to start evaluating the efficacy and the safety (i.e., carboxyhemoglobin concentration of carbon monoxide (CO)) as a putative neuroprotective therapy in neonates. Study Design: Neonatal C57BL/6 mice were exposed to CO at a concentration of either 200 or 250 ppm for a period of 1 h. The pups were then sacrificed at 0, 10, 20, 60, 120, 180, and 240 min after exposure to either concentration of CO, and blood was collected for analysis of carboxyhemoglobin. Following the safety study, 7-day-old pups underwent a unilateral carotid ligation. After recovery, the pups were exposed to a humidified gas mixture of 8% oxygen and 92% nitrogen for 20 min in a hypoxia chamber. One hour after the hypoxia exposure, the pups were randomized to one of two groups: air (HI+A) or carbon monoxide (HI+CO). An inhaled dose of 250 ppm of CO was administered to the pups for 1 h per day for a period of 3 days. At 7 days post-injury, the pups were sacrificed and the brains analyzed for cortical and hippocampal volumes. Results: CO exposure at 200 and 250 ppm produced a peak carboxyhemoglobin concentration of 21.52 ± 1.18% and 27.55 ± 3.58%, respectively. The carboxyhemoglobin concentrations decreased rapidly, reaching control concentrations by 60 min post exposure. At 14 days of age (7 days post injury), the HI+CO (treated with 1 h per day of 250 ppm of CO for 3 days post injury) had significant preservation of the ratio of ipsilateral to contralateral cortex (median 1.07, 25% 0.97, 75% 1.23, n = 10) compared the HI+A group (p < 0.05). Conclusion: CO exposure of 250 ppm did not reach carboxyhemoglobin concentrations which would induce acute neurologic abnormalities and was effective in preserving cortical volumes following hypoxic-ischemic injury.
Measuring and Applying Invalid SSL Certificates: The Silent Majority

SSL and TLS are used to secure the most commonly used Internet protocols. As a result, the ecosystem of SSL certificates has been thoroughly studied, leading to a broad understanding of the strengths and weaknesses of the certificates accepted by most web browsers. Prior work has naturally focused almost exclusively on "valid" certificates--those that standard browsers accept as well-formed and trusted--and has largely disregarded certificates that are otherwise "invalid. " Surprisingly, however, this leaves the majority of certificates unexamined: we find that, on average, 65% of SSL certificates advertised in each IPv4 scan that we examine are actually invalid. In this paper, we demonstrate that despite their invalidity, much can be understood from these certificates. Specifically, we show why the web's SSL ecosystem is populated by so many invalid certificates, where they originate from, and how they impact security. Using a dataset of over 80M certificates, we determine that most invalid certificates originate from a few types of end-user devices, and possess dramatically different properties than their valid counterparts. We find that many of these devices periodically reissue their (invalid) certificates, and develop new techniques that allow us to track these reissues across scans. We present evidence that this technique allows us to uniquely track over 6.7M devices. Taken together, our results open up a heretofore largely-ignored portion of the SSL ecosystem to further study.
Spreading Diversity in Multi-cell Neutron-Induced Upsets with Device Scaling

Recent diversity in multicell upset (MCU) of CMOS SRAMs are reviewed and scaling effects are discussed. Space and time domain automatic classification techniques are developed and applied to single event upsets (SEUs) of 130nm SRAM under quasi-mono energetic neutron irradiation at TSL and CYRIC. Tests show very high dependency of MCU features on data patterns, typically "All `0'/`1'" and checkerboard. Three error propagation categories with 41 modes inherent in device architectures are identified. Novel MCU features, in which errors can be corrected by rewriting but Idd increases stepwise depending on MCU multiplicity, are identified. With "All `0'/`1'" pattern, ratio of double bit error is found to be even higher than that of single bit errors. The majority of the double bit error is in nearest neighborhood (NN) position along word line (WL). Underlining basic mechanism can be either charge collection-diffusion or parasitic bipolar actions. But most features can be elucidated only fully by a novel MCU mechanism MCBI (multi-coupled bipolar interaction) proposed by the authors, giving clues for SEU tolerant sub-100nm design
Feature-level sentiment analysis for Chinese product reviews

The sentiment analysis for English product reviews has been widely researched in recent years, followed with many important achievements. Due to the special language traits of Chinese, the study on Chinese product reviews is much more difficult than the former. In this work, we focus on the finer-grained sentiment analysis for Chinese product reviews, that is feature-level based sentiment analysis. We propose a hybrid method which combines association rules and point-wise mutual information to extract the product features, and then take advantage of the sentiment dictionary—HowNet to analyze the opinion orientation expressed on the product features. The experiment result obtained shows the effectiveness and efficiency of our approach.
Parameterized Streaming Algorithms for Vertex Cover

As graphs continue to grow in size, we seek ways to effectively process such data at scale. The model of streaming graph processing, in which a compact summary is maintained as each edge insertion/deletion is observed, is an attractive one. However, few results are known for optimization problems over such dynamic graph streams. In this paper, we introduce a new approach to handling graph streams, by instead seeking solutions for the parameterized versions of these problems where we are given a parameter $k$ and the objective is to decide whether there is a solution bounded by $k$. By combining kernelization techniques with randomized sketch structures, we obtain the first streaming algorithms for the parameterized versions of the Vertex Cover problem. We consider the following three models for a graph stream on $n$ nodes: 1. The insertion-only model where the edges can only be added. 2. The dynamic model where edges can be both inserted and deleted. 3. The \emph{promised} dynamic model where we are guaranteed that at each timestamp there is a solution of size at most $k$. In each of these three models we are able to design parameterized streaming algorithms for the Vertex Cover problem. We are also able to show matching lower bound for the space complexity of our algorithms. (Due to the arXiv limit of 1920 characters for abstract field, please see the abstract in the paper for detailed description of our results)
Statistical Machine Translation between Languages with Significant Word Order Differences

One of the difficulties statistical machine translation (SMT) systems face are differences in word order. When translating from a language with rather fixed SVO word order, such as English, to a language where the preferred word order is dramatically different (such as the SOV order of Urdu, Hindi, Korean, .), the system has to learn long-distance reordering of the words. Higher degree of freedom of the word order of the target language is usually accompanied by higher morphological diversity, i.e. word affixes have to be generated based on the fixed word order in the source sentence. The goal of the thesis is to explore the two mentioned (and possibly other related) classes of problems in practice, and to implement and evaluate techniques expected to help the SMT system to solve them. This includes: 1. Selecting a language pair with word order differences and collecting parallel data for the pair. 2. Training an existing SMT system on the data. 3. Evaluating the performance of the system and analyzing the errors it does. Estimating how much the accuracy of translation is affected by the problems mentioned above, and possibly what are the other types of error causes that dominate the output. 4. Implementing preprocessing and/or other techniques aimed at minimizing the found classes of errors. Evaluating their impact.
Could information theory provide an ecological theory of sensory processing?

The sensory pathways of animals are well adapted to processing a special class of signals, namely stimuli from the animal’s environment. An important fact about natural stimuli is that they are typically very redundant and hence the sampled representation of these signals formed by the array of sensory cells is inefficient. One could argue for some animals and pathways, as we do in this review, that efficiency of information representation in the nervous system has several evolutionary advantages. Consequently, one might expect that much of the processing in the early levels of these sensory pathways could be dedicated towards recoding incoming signals into a more efficient form. In this review, we explore the principle of efficiency of information representation as a design principle for sensory processing. We give a preliminary discussion on how this principle could be applied in general to predict neural processing and then discuss concretely some neural systems where it recently has been shown to be successful. In particular, we examine the fly’s LMC coding strategy and the mammalian retinal coding in the spatial, temporal and chromatic domains.