Miracle-dz/UniFAR-FTUs huggingface dataset:
Children as Consumers: Advertising and Marketing

Marketing and advertising support the U.S. economy by promoting the sale of goods and services to consumers, both adults and children. Sandra Calvert addresses product marketing to children and shows that although marketers have targeted children for decades, two recent trends have increased their interest in child consumers. First, both the discretionary income of children and their power to influence parent purchases have increased over time. Second, as the enormous increase in the number of available television channels has led to smaller audiences for each channel, digital interactive technologies have simultaneously opened new routes to narrow cast to children, thereby creating a growing media space just for children and children's products.Calvert explains that paid advertising to children primarily involves television spots that feature toys and food products, most of which are high in fat and sugar and low in nutritional value. Newer marketing approaches have led to online advertising and to so-called stealth marketing techniques, such as embedding products in the program content in films, online, and in video games.All these marketing strategies, says Calvert, make children younger than eight especially vulner-able because they lack the cognitive skills to understand the persuasive intent of television and online advertisements. The new stealth techniques can also undermine the consumer defenses even of older children and adolescents.Calvert explains that government regulations implemented by the Federal Communications Commission and the Federal Trade Commission provide some protection for children from advertising and marketing practices. Regulators exert more control over content on scarce television airwaves that belong to the public than over content on the more open online spaces. Overall, Calvert concludes, children live and grow up in a highly sophisticated marketing environment that influences their preferences and behaviors.
An experimental analysis of acquired impulse control among adult humans intolerant to alcohol

Significance We find that alcohol intolerance, which occurs randomly and leads affected people systematically to resist the impulse to consume alcohol, enables improved impulse control in another behavioral domain. Our findings show that impulse control can develop in adult populations as a result of exercising routine behaviors in naturally occurring environments. This finding is important because the ability to control tempting impulses significantly impacts the health and well-being of people at all ages. Our findings complement theory by providing rigorous empirical evidence that simple lifestyle changes may have significant personal well-being benefits. In particular, small acts of self-control, such as resisting drinking or always waking at the same time, can increase one’s overall ability to resist selfish temptations. The ability to control tempting impulses impacts health, education, and general socioeconomic outcomes among people at all ages. Consequently, whether and how impulse control develops in adult populations is a topic of enduring interest. Although past research has shed important light on this question using controlled intervention studies, here we take advantage of a natural experiment in China, where males but not females encounter substantial social pressure to consume alcohol. One-third of our sample, all of whom are Han Chinese, is intolerant to alcohol, whereas the remaining control sample is observationally identical but alcohol tolerant. Consistent with previous literature, we find that intolerant males are significantly more likely to exercise willpower to limit their alcohol consumption than alcohol-tolerant males. In view of the strength model of self-control, we hypothesize that this enables improved impulse control in other contexts as well. To investigate this hypothesis, we compare decisions in laboratory games of self-control between the tolerant and intolerant groups. We find that males intolerant to alcohol and who regularly encounter drinking environments control their selfish impulses significantly better than their tolerant counterparts. On the other hand, we find that female Han Chinese intolerant to alcohol do not use self-control to limit alcohol consumption more than tolerant females, nor do the tolerant and intolerant females exhibit differences in self-control behaviors. Our research indicates that impulse control can be developed in adult populations as a result of self-control behaviors in natural environments, and shows that this skill has generalizable benefits across behavioral domains.
Möbius voting for surface correspondence

The goal of our work is to develop an efficient, automatic algorithm for discovering point correspondences between surfaces that are approximately and/or partially isometric. Our approach is based on three observations. First, isometries are a subset of the Möbius group, which has low-dimensionality -- six degrees of freedom for topological spheres, and three for topological discs. Second, computing the Möbius transformation that interpolates any three points can be computed in closed-form after a mid-edge flattening to the complex plane. Third, deviations from isometry can be modeled by a transportation-type distance between corresponding points in that plane. Motivated by these observations, we have developed a Möbius Voting algorithm that iteratively: 1) samples a triplet of three random points from each of two point sets, 2) uses the Möbius transformations defined by those triplets to map both point sets into a canonical coordinate frame on the complex plane, and 3) produces "votes" for predicted correspondences between the mutually closest points with magnitude representing their estimated deviation from isometry. The result of this process is a fuzzy correspondence matrix, which is converted to a permutation matrix with simple matrix operations and output as a discrete set of point correspondences with confidence values. The main advantage of this algorithm is that it can find intrinsic point correspondences in cases of extreme deformation. During experiments with a variety of data sets, we find that it is able to find dozens of point correspondences between different object types in different poses fully automatically.
Fault tolerant deployment and topology control in wireless networks

This paper investigate fault tolerance for wireless ad hoc networks. We consider a large-scale of wireless networks whose nodes are distributed randomly in a unit-area square region. Given <i>n</i> wireless nodes <i>V</i>, each with transmission range <i>r<sub>n</sub></i>, the wireless networks are often modeled by graph <i>G(V,r<sub>n</sub>)</i> in which two nodes are connected if their Euclidean distance is no more than <i>r<sub>n</sub></i>. We first consider how the transmission range is related with the number of nodes in a fixed area such that the resulted network can sustain <i>k</i> fault nodes with high probability. We show that, for a unit-area square region, the probability that the network <i>G(V,r<inf>n</inf>)</i> is <i>(k+1)</i>-connected is at least <i>e<sup>-e<sup>-α</sup></sup></i> when the transmission radius <i>r<sub>n</sub> </i> satisfies <i>n</i> π r<sub>n</sub><sup>2</sup> ≥ ln <i>n</i> + (2k-1) ln ln <i>n -2ln k! + 2α</i> for <i>k>0</i> and <i>n</i> sufficiently large. This result also applies to mobile networks when the moving of wireless nodes always generates randomly distributed positions. Our simulations show that <i>n</i> should be larger than <i>500</i> if <i>k=2</i> or <i>3</i> and <i>α = log n</i> and <i>n</i> should be larger than <i>2500</i> if <i>k=2</i> or <i>3</i> and <i>α = log log n</i>. We then present a localized method to control the network topology given a <i>(k+1)</i>-faults tolerant deployment <i>G(V,r<sub>n</sub>)</i> of wireless nodes such that the resulting topology is still <i>(k+1)</i>-faults tolerant but with <i>O(kn)</i> communication links maintained. We show that the constructed topology is also a length spanner. Here a subgraph <i>H</i> is spanner of graph <i>G</i>, if for any two nodes, the length of the shortest path connecting them in <i>H</i> is no more than a small constant factor of the length of the shortest path connecting them in <i>G</i>. Finally, we conduct some simulations to study the practical transmission range to achieve certain probability of <i>k</i>-connected when <i>n</i> is not large enough.
Order Preserving Key Compression

:~. \:. ;;~ , . :' OJ ~L. : Abstract;:. ;". 1.10,,'(1 Order preserving data compression can improve sorting and searching performance, and hence the performance of database systems. We describe a new parsing (tokenization) technique that can be effectively applied to "keys", producing substantial compression. It can be applied to both the uncompressed and compressed strings, permiting a more flexible choice of variable length dictionary entries and their compressed forms. The key notion is that the way that entries partition the space of strings determines how the entries are to be parsed. The result is economy in the number of encodings that are needed in order to preserve order and great flexibility in how they are encoded. We illustrate one use of order preserving compression, padding character compression for multifield keys. This demonstrates the dramatic gains possible with the new technique, some of which cannot be achieved by any other method.
Reinforcement-Based Learning for Process Classification Task

In this work, we present a reinforcement-based learning algorithm that includes the automatic classification of both sensors and actions. The classification process is prior to any application of reinforcement learning. If categories are not at the adequate abstraction level, the problem could be not learnable. The classification process is usually done by the programmer and is not considered as part of the learning process. However, in complex tasks, environments, or agents, this manual process could become extremely difficult. To solve this inconvenience, we propose to include the classification into the learning process. We apply an algorithm to automatically learn to achieve a task through reinforcement learning that works without needing a previous classification process. The system is called Fish or Ship (FOS) assigned the task of inducing classification rules for classification task described in terms of 6 attributes. The task is to categorize an object that has one or more of the following features: Sail, Solid, Big, Swim, Eye, Fins into one of the following: fish, or ship. First results of the application of this algorithm are shown Reinforcement learning techniques were used to implement classification task with interesting properties such as provides guidance to the system and shortening the number of cycles required to learn.
Gene Expression Profiling Revealed Survivin as a Target of 3 , 3 V-Diindolylmethane-Induced Cell Growth Inhibition and Apoptosis in Breast Cancer Cells

The phytochemical indole-3-carbinol (I3C), found in cruciferous vegetables, and its major acid-catalyzed reaction product 3,3V-diindolylmethane (DIM) showed anticancer activity mediated by its pleiotropic effects on cell cycle progression, apoptosis, carcinogen bioactivation, and DNA repair. To further elucidate the molecular mechanism(s) by which 3,3V-diindolylmethane exerts its effects on breast cancer cells, we have used microarray gene expression profiling analysis. We found a total of 1,238 genes altered in 3,3V-diindolylmethane-treated cells, among which 550 genes were downregulated and 688 genes were up-regulated. Clustering analysis showed significant alterations in some genes that are critically involved in the regulation of cell growth, cell cycle, apoptosis, and signal transduction, including downregulation of survivin. Previous studies have shown that antiapoptotic protein survivin is overexpressed in many human cancers, including breast cancer. However, very little or no information is available regarding the consequence of down-regulation of survivin for cancer therapy. We, therefore, hypothesized that down-regulation of survivin as observed by 3,3V-diindolylmethane could be an important approach for the treatment of breast cancer. We have tested our hypothesis using multiple molecular approaches and found that 3,3V-diindolylmethane inhibited cell growth and induced apoptosis in MDA-MB-231 breast cancer cells by downregulating survivin, Bcl-2, and cdc25A expression and also caused up-regulation of p21 expression, which could be responsible for cell cycle arrest. Down-regulation of survivin by small interfering RNA before 3,3V-diindolylmethane treatment resulted in enhanced cell growth inhibition and apoptosis, whereas overexpression of survivin by cDNA transfection abrogated 3,3V-diindolylmethane-induced cell growth inhibition and apoptosis. These results suggest that targeting survivin by 3,3V-diindolylmethane could be a new and novel approach for the prevention and/or treatment of breast cancer. (Cancer Res 2006; 66(9): 4952-60)
Inspiration from genetics to promote recognition and protection within ad hoc sensor networks

This work illustrates potentials for recognition within ad hoc sensor networks if their nodes possess individual inter-related biologically inspired genetic codes. The work takes ideas from natural immune systems protecting organisms from infection. Nodes in the present proposal have individual gene sets tting into a self organised phylogenetic tree. Members of this population are genetically "relatives". Outsiders cannot easily copy or introduce a new node in the network without going through a process of conception between two nodes in the population. Related nodes can locally decide to check each other for their genetic relation without directly revealing their gene sets. A copy/clone of a gene sequence or a random gene set will appear as alien. Nodes go through a cycle of introduction (conception or "birth") with parents in the network and later exit from it ("death"). Hence the phylogenetic tree is dynamic or possesses a genetic drift. Typical lifetimes of gene sets and number of ospring from dierent parents aect this genetic drift and the level of correlation between gene sets. The frequency of mutations similarly aects the gene pool. Correlation between genes of the nodes implies a common secret for cryptographic material for communication and consistency check facilitating intrusion detection and tracing of events. A node can by itself (non-specically) recognise an adversary if it does not respond properly according to its genes. Nodes can also collaborate to recognise adversaries by communicating response from intruders to check for consistency with the whole gene pool (phylogenetic tree).
Thermal variation, thermal extremes and the physiological performance of individuals

ABSTRACT In this review we consider how small-scale temporal and spatial variation in body temperature, and biochemical/physiological variation among individuals, affect the prediction of organisms' performance in nature. For ‘normal’ body temperatures – benign temperatures near the species' mean – thermal biology traditionally uses performance curves to describe how physiological capabilities vary with temperature. However, these curves, which are typically measured under static laboratory conditions, can yield incomplete or inaccurate predictions of how organisms respond to natural patterns of temperature variation. For example, scale transition theory predicts that, in a variable environment, peak average performance is lower and occurs at a lower mean temperature than the peak of statically measured performance. We also demonstrate that temporal variation in performance is minimized near this new ‘optimal’ temperature. These factors add complexity to predictions of the consequences of climate change. We then move beyond the performance curve approach to consider the effects of rare, extreme temperatures. A statistical procedure (the environmental bootstrap) allows for long-term simulations that capture the temporal pattern of extremes (a Poisson interval distribution), which is characterized by clusters of events interspersed with long intervals of benign conditions. The bootstrap can be combined with biophysical models to incorporate temporal, spatial and physiological variation into evolutionary models of thermal tolerance. We conclude with several challenges that must be overcome to more fully develop our understanding of thermal performance in the context of a changing climate by explicitly considering different forms of small-scale variation. These challenges highlight the need to empirically and rigorously test existing theories. Summary: We review how temporal, spatial and physiological variation have potentially synergistic effects on the thermal performance of individuals and conclude that several challenges must be overcome to fully incorporate small-scale variation into predictions of climate change.
Predicting Download Directories for Web Resources

Browsing the web is one of the most common activities that users engage in nowadays, and downloading web resources of interest, such as images, documents, music, etc., is part of this process. However, users would rather temporarily save that resource to a default path that they have easy access to (e.g. their "Desktop") than select the actual directory where they would eventually place it. This clearly implies that existing user interfaces are not as effective for this particular task as the users would like them to be. Instead of proposing a different User Interface, in this paper, we try to address the problem at its core, and propose a methodology to suggest the most likely directory where the file would (eventually) be saved by the user. By doing so, future interfaces can also benefit from our technique. We provide a formal definition of the problem and propose a classification framework to tackle it. We present our overall solution to this problem, namely Directory Download PrediCtor, or DiDoCtor for short. We give experimental evidence of its effectiveness, by implementing our approach as part of a widely used browser and evaluate it with real user activity. We also discuss lessons learned from this process, regarding the efficiency perspective.
A novel hybrid memory architecture for high-speed packet buffers in network nodes

Routers are the prevalent type of network nodes in today’s Internet. A router processes incoming packets and forwards them towards their destination. Core routers, i. e. , routers that operate in the core of the Internet, contain up to hundreds and more ports to be able to interconnect many network segments. Temporary unbalanced traffic between the ports of a router can lead to overload situations. To minimize packet loss routers contain packet buffers to hold packets during times of congestion. To be able to provide the large buffering capacities required packet buffers are typically implemented with DRAM (Dynamic Random Access Memory). One major problem of building high-speed packet buffers is that line rates and therewith the packet rates grow much faster than the random access time of DRAM decreases. The random access time of a memory bounds the rate of individual accesses to the memory device. At a line rate of 10Gbps DRAM random access time was just short enough to meet the required access time. Since then, the gap between these values steadily increases. For example, on a 100Gbps link an Ethernet frame can arrive every 6.7 ns but DRAM random access time is approx. 50 ns. Using a hybrid memory architecture can close this gap by combining the strengths of both major memory technologies: short random access time of SRAM (Static Random Access Memory) and large capacity of DRAM. However, the architecture proposals in literature that provide a deterministic bandwidth suffer from high memory resource requirements and inefficient memory resource utilization. The main reasons for this are fragmentation, inefficient DRAM data bus utilization, and large required SRAM capacities. These properties limit scalability and increase costs and power consumption. This thesis proposes a novel hybrid memory architecture for high-speed packet buffers that delivers deterministic bandwidth. The novelty of the architecture is that it significantly reduces the memory resources compared to related architectures from literature, while it provides the same functionality. Memory resources refer to the required SRAM and DRAM capacity and bandwidth, as well as to the DRAM data bus pin count. The feasibility of the architecture in hardware at high line rates is shown by a prototypical packet buffer implementation. The thesis introduces at first fundamentals of packet buffering. It addresses the potential locations to place a packet buffer in a router, defines the term packet buffer, and introduces its basic building blocks. It also quantifies the requirements a packet buffer has to suffice and compares them to cutting-edge SRAM and DRAM devices. Then focus is set on hybrid memory architectures and the necessary metrics to evaluate these. Architecture proposals from literature are surveyed and their pros and cons are discussed.
Media, Politics and the Network Society

Acknowledgments. Introduction. Chapter 1. What is the Network Society? Chapter 2. The Informationisation of Media and Culture Chapter 3. Addicted to Digital: The Wired World Chapter 4. Life.com Chapter 5. Civil Society and the Network Society. Chapter 6. Tactical Media. Chapter 7. A Networked Civil Society? Glossary. Bibliography. Index.
Embedded Systems Passive Localization with Visible Light

Indoor localization is a topic of significant interest for academic and industrial. For outdoors, we have Global Positioning System (GPS) working very well, but GPS does not work indoors and we spend more than 90% of the time indoors. Thus, there is a great need to find solution for this problem. Many technologies have been proposed for indoor localization based on radio frequency, infrared and ultrasonic sensors. Recently, researchers have been using light as a means to achieve indoor localization. LED lights inside our buildings can transmit information and they can be seen as “internal GPS satellites” playing the role of localization anchors. But most of these works require the user to have an electronic device. In this thesis, we would like to achieve indoor localization with visible light but in a passive manner. By passive, we mean that the object of interest would have no electronic device or tag. This thesis takes the first step in developing such a system and our contributions are three-fold: we develop a system and a mathematical model to analyze it, we show a scaled-down application in the order of decimeters and we also show a more realistic application in the order of meters. Our work shows that this is a promising way to achieve accurate indoor localization in a passive manner.