Miracle-dz/UniFAR-FTUs huggingface dataset:
Macro Markets: Creating Institutions for Managing Society's Largest Economic Risks

Macro Markets puts forward a unique and authoritative set of detailed proposals for establishing new markets for the management of the biggest economic risks facing society. Our existing financial markets are seen as being inadequate in dealing with such risks and Professor Shiller suggests major new markets as solutions to the problem. Shiller argues that although some risks, such as natural disaster or temporary unemployment, are shared by society, most risks are borne by the individual and standards of living determined by luck. He investigates whether a new technology of markets could make risk-sharing possible, and shows how new contracts could be designed to hedge all manner of risks to the individual's living standards. He proposes new international markets for perpetual claims on national incomes, and on components and aggregates of national incomes, concluding that these markets may well dwarf our stock markets in their activity and significance. He also argues for new liquid international markets for residential and commercial property. Establishing such unprecedented new markets presents some important technical problems which Shiller attempts to solve with proposals for implementing futures markets on perpetual claims on incomes, and for the construction of index numbers for cash settlement of risk management contracts. These new markets could fundamentally alter and diminish international economic fluctuations, and reduce the inequality of incomes around the world.
Functional MRI of cerebral activation during encoding and retrieval of words

The aims of the present study were to identify the cerebral structures associated with encoding and retrieval of verbal material. To circumvent the inherent disadvantages of the conventional block designs used in functional magnetic resonance imaging (MRI), an event‐related design compared activation related to randomly intermixed old and new words during recognition. To support the validity of results, both nonparametric analyses in regions of interest (ROI) and statistical parametric mapping (SPM 96) were used. Twelve healthy volunteers, ages 22–35 years, performed three tasks: intentional encoding of words, recognition of old (previously learned) words, and discrimination between words and nonwords, a task to control for visual input and motor output during recognition. Echo‐planar magnetic resonance imaging of blood‐level, oxygen‐dependent, task‐related changes was used to compare cerebral activity under active and resting conditions as well as to detect event‐related activity within blocks of trials. Comparable results were obtained following nonparametric statistical analysis of selected ROI and SPM. Encoding of words was associated with increased activity in the left inferior frontal gyrus, including Broca's area and in the left parietal association cortex. Event‐related data analysis revealed activation of the right medial frontal gyrus, the right anterior cingulate gyrus, and parietal association cortices during recognition of previously presented words. In the lexical decision task, words in comparison with nonwords were associated with activation of the left parietal association cortex. The right medial frontal gyrus, the right anterior cingulate gyrus, and the right parietal association cortex are likely to be involved in episodic memory functions during recognition of previously presented verbal material. The comparison of event‐related activation occurring within one trial block instead of among several trial blocks may significantly improve the performance of memory studies. Hum. Brain Mapping 8:157–169, 1999. © 1999 Wiley‐Liss, Inc.
Judgment as a Guide to Belief *

What is the role of consciousness in our introspective lives? In this paper, I will focus on the role of conscious judgment in giving us access to our standing non-conscious beliefs. The view I will defend is a special case of a more general position in the epistemology of introspection. I will start by sketching the general view, and then give the details of my particular position. One plank of the general position concerns specialness: our self-ascriptions of mental states can be justified in a way that our ascriptions of mental states to others are not. Another plank of the position concerns fallibility: we can nevertheless make justified mistakes about what mental states we are in. For example, if you hallucinate that something yellow is present, with no indication that anything is going wrong, you can be justified in believing that you are in the relational mental state of seeing something yellow, even though you are not in that state. The moderate position says that our introspective beliefs are sometimes justified in a both fallible and non-inferential way. Accepting this position is, I think, an attractive way of
Connecting the World : Building a social network recommation system for both local and global connectedness

We all share the same home this pale blue dot we call Earth. Yet we allow ourselves to be thoroughly divided by things such as cultures, skin color, and invisible lines on the ground. How can we nurture new relationships, new understanding, and new perspectives in this disconnected world? As one possible piece of the solution, with the rise of online social networks, we are able to instantly connect with people anywhere around the world no longer just people only in our city, state, or even country. However, such connections are relatively few and far between, even given that the infrastructure is certainly there. Thus, to improve on this, here we build a foundation for a social network recommendation system that can encourage diverse, distant, and yet relevant relationships between users across the globe, in addition to our familiar nearby neighbors and friends. Our system leverages properties and tools of/for social graphs, user geolocation information, and machine learning to provide meaningful friend/follower/contact suggestions to users, with some desirable balance between more local/typical recommendations and more distant/global suggestions. In doing all this, we hope that such connections can foster novel and otherwise unlikely and impractical communication and information exchange, which in turn can nudge us to move forward in our ability to comprehend, accept, and grow with people from different locations, backgrounds, and cultures across the world. We hope that related future work can provide some contribution, even if minimal, to creating truly global (as well as local) connectedness between people across the world, facilitating people to realize how different yet the same we all are on this single spaceship we call home.
Measuring Aggressive Driving Behavior Using a Driving Simulator: An Exploratory Study

Aggressive driving is typically stimulated by impatience, frustration, or anger and manifests itself through unsafe driving behaviors such as running red lights, traffic weaving, or tailgating. Studying aggressive driving behavior is important since such behavior has been shown to be a major cause of traffic accidents and quantifying it and its determinants can help design programs that aim at reducing aggressive driving behavior. This paper studies aggressive driving behavior of university students by using a driving simulator to generate certain events in the traffic \environment and evaluate drivers’ reactions to those events. The study aims at testing two hypotheses. The first hypothesis is that a series of frustrating events in the driving environment may instigate drivers to drive aggressively even if they may be non-aggressive by nature. The second hypothesis is that the level of trait aggressiveness influences the extent to which drivers react aggressively to frustrating events in the traffic environment. To test these hypotheses, an experimental procedure is used whereby a sample of student subjects at the American University of Beirut are recruited to drive through traffic scenarios represented in the driving simulator and aiming at instigating the subjects’ aggressiveness. Overall, the results indicate that there is evidence to support both hypotheses.
Scale Effects, An Error of Aggregation Not Specification: Empirical Evidence

In a set of influential papers, Charles Jones (1995a, 1995b, 1999) argued that R&D based endogenous growth models are inconsistent with the data. He showed, in a very striking manner, that the scale effects prediction of early endogenous growth models (e.g. Romer, 1986 and 1990, Grossman and Helpman, 1991, and Aghion and Howitt, 1992) is not borne out in the data. Standard endogenous growth models attribute constant or increasing returns in the stock of knowledge or technology to the aggregate level of resources. This assumption leads to the counterfactual prediction that the rate of productivity growth should be increasing in the aggregate amount of resources devoted to accumulating knowledge. This paper presents empirical evidence in support of R&D based endogenous growth models without scale effects (e.g. Young, 1998, Howitt, 1999, Thompson, 2001, and Peretto and Smulders, 2002). In these models the average level of workers or R&D workers per firm drives growth as opposed to the aggregate level and do not share the scale effects property in the limit. Using data for the US covering 1964-2001, we show that when the number of employees or scientists/engineers are scaled down on a per establishment basis, the empirics support the latter version of endogenous growth models. Specifically, the long-run size of establishments is stable, neither declining or growing in the long-run, where size is measured in two ways: by workers per establishment and R&D workers per establishment. Second, we demonstrate a positive effect running from average establishment size to productivity growth as predicted by the theories.
Non-Boolean Computing Benchmarking for Beyond-CMOS Devices Based on Cellular Neural Network

This paper presents a uniform benchmarking methodology for non-Boolean computation based on the cellular neural network (CNN) for a variety of beyond-CMOS device technologies, including charge-based and spintronic devices. Three types of CNN implementations are investigated using analog, digital, and spintronic circuits. Monte Carlo simulations are performed to quantify the impact of the input noise, thermal noise, and the number of bits representing the weights of synapses on the overall recall probability and delay. The results demonstrate that the recall probability improves significantly as the number of synapses increase. Using a 4-b resolution for synapse weights provides the best tradeoff between the required numbers of synapses and synapse bits for a target recall rate. Finally, three types of CNN implementations with various device technologies are benchmarked for a given input noise and recall accuracy target. It is shown that spintronic devices are promising candidates to implement CNNs, where up to $3\times $ energy-delay product improvement is predicted in domain wall devices compared to its conventional CMOS counterpart.
Sensorless position and speed estimation with improved integrator for PMLSM drive

This paper describes a sensorless position and speed detection algorithm designed for permanent magnet linear synchronous motor (PMLSM) drive. Measured line currents and terminal voltages are used to estimate the flux of the α-β axis in stator frame, integrating the back electromotive force (EMF). Position and speed signals are derived from angle of the flux linkage and its change rate. A new improved integrator is presented and analyzed for compensate DC offsets and drift, which invariably exist in any practical implementation based on combination of low-pass filter, highpass filter and PI regulator. Experimental results are presented to show the realization of the objectives.
Notice of RetractionParticle Filter Tracking Algorithm Based on Multi-Information Fusion

Traditional color histogram-based PF was unstable only using the color information. The particle filter tracking algorithm proposed in our paper is based on multi-information fusion, which combining structural similarity index (SSIM)and scale invariant feature transform (SFIT), SSIM was used to measure target similarity between two frames in correlation tracking and the color distribute the particle weighting comprehensively, through SIFT we extract the object's local keypoints, what may based on to update the particle weighting by distance kernel function, dealing with in the condition of cluttered background, object and the background's color similarity and illumination changes etc, tracking the interested object accurately. The experiments present that our algorithm can track the targets more robustly and adaptively than the traditional algorithm using the same particles.
EXACT SOLUTION FOR PROBABILITY DENSITY FUNCTION OF SIGNAL TO INTERFERENCE RATIO IN A CIRCULAR CELL

Signal to interference ratio (SIR) is a key factor to measure the quality of the received signal. In a wireless system parameters such as cell size, coverage, quality of service (QoS), and etc are controlled using SIR. In this paper, exact solution of probability density function (PDF) for SIR is evaluated analytically in a circular cell taking into consideration the randomness of users and channel characteristics. PDF of SIR is evaluated in the presence of large scale fading characterized by loss propagation and shadowing, when there is one interferer base station. This result is a solid foundation to evaluate SIR for multiple interferers. Finally, simulation performed shows good agreement with analytical results obtained.
Code, Camera, Action: How Software Developers Document and Share Program Knowledge Using YouTube

Creating documentation is a challenging task in software engineering and most techniques involve the laborious and sometimes tedious job of writing text. This paper explores an alternative to traditional text-based documentation, the screen-cast, which captures a developer's screen while they narrate how a program or software tool works. We conducted a study to investigate how developers produce and share developer-focused screen casts using the You Tube social platform. First, we identified and analyzed a set of development screen casts to determine how developers have adapted to the medium to meet the demands of development-related documentation needs. We also explored the techniques and strategies used for sharing software knowledge. Second, we interviewed screen cast producers to understand their motivations for creating screen casts, and to uncover the perceived benefits and challenges in producing code-focused videos. Our findings reveal that video is a useful medium for communicating program knowledge between developers, and that developers build their online personas and reputation by sharing videos through social channels.
Corporate governance handbook

Corporate Governance Handbook offers invaluable advice on how to ensure your company functions within the required legal and ethical parameters. This new edition has been comprehensively updated to take account of the significant changes brought in by the Companies Act 2006 with regard to responsibilities of Boards and responsibilities of directors, the revised Turnbull Guidance and amended EC Directives as well as myriad other changes. This indispensable handbook shows you how to implement developments in corporate governance using accepted best practice standards with useful precedents, checklists bullet point summaries and references to legislation/codes of practice throughout.
China's Copyright System: Rising to the Spirit of Trips Requires an Internal Focus and WTO Membership

This Note examines the current state of China’s intellectual property rights protection as it relates to copyright. Part I evaluates existing measures used in enforcing copyright protection in China, such as the General Agreement on Tariffs and Trade (”GATT”), the Agreement on TradeRelated Aspects of Intellectual Property Rights (”TRIPs”), and various U.S. trade sanctions. Part II describes major policies affecting China’s copyright system and address the inherent factors underlying China’s inability to enforce copyright protection, including a lack of cultural and economic incentives and difficulties in administrative enforcement. Part II then proceeds to discuss China’s judicial system and education as alternative methods to solving China’s problem of copyright piracy. In addition, Part II introduces joint ventures as defined in China’s laws and implicated in SinoU.S. intellectual property agreement. Finally, Part II explores the mechanisms involved in WTO’s dispute resolution system. Part III argues that TRIPs and U.S. trade sanctions are no longer the appropriate tools for combating China’s piracy problems. In light of the country’s present intellectual property environment, strategies such as education and joint ventures, and the enhancement of the judicial system will serve as effective cures to the piracy problem. Part III further argues that WTO membership is beneficial to the future enforcement of copyright protection in China. CHINA'S COPYRIGHT SYSTEM: RISING TO THE SPIRIT OF TRIPS REQUIRES AN INTERNAL FOCUS AND WTO MEMBERSHIP
Sequential-Context-Dependent Hippocampal Activity Is Not Necessary to Learn Sequences with Repeated Elements

Learning sequences of events (e.g., a-b-c) is conceptually a simple problem that can be solved using asymmetrically linked cell assemblies [e.g., “phase sequences” (Hebb, 1949)], provided that the elements of the sequence are unique. When elements repeat within the sequence, however (e.g., a-b-c-d-b-e), the same element belongs to two separate “contexts,” and a more complex sequence encoding mechanism is required to differentiate between the two contexts. Some neural structure must form sequential-context-dependent, or “differential,” representations of the two contexts (i.e., b as an element of “a-b-c” as opposed to “d-b-e”) to allow the correct choice to be made after the repeated element. To investigate the possible role of hippocampus in complex sequence encoding, rats were trained to remember repeated-location sequences under three conditions: (1) reward was given at each location; (2) during training, moveable barriers were placed at the entry and exit of the repeated segment to direct the rat and were removed once the sequence was learned; and (3) reward was withheld at the entry and exit of the repeated segment. In the first condition, hippocampal ensemble activity did not differentiate the sequential context of the repeated segment, indicating that complex sequences with repeated segments can be learned without differential encoding within the hippocampus. Differential hippocampal encoding was observed, however, under the latter two conditions, suggesting that long-term memory for discriminative cues present only during training, working memory of the most recently visited reinforcement sites, or anticipation of the subsequent reinforcement site can separate hippocampal activity patterns at the same location.
Least mean square, finite length, predictive digital filters

Useful analytic solutions of the discrete Wiener-Hopf (W-H) matrix equation (using the method of undetermined coefficients (UC)) are presented for general rational input spectra. For the specific case of N sinusoids in white noise, the W-H equation is transformed via the UC method into a set of N coupled linear equations which decouple as the filter length becomes large. For all pole input spectra, the W-H equation transforms into a pxp Vandermonde matrix equation where p is the number of poles in the input spectra.
The Political Economy of Financial Repression in Transition Economies

Financial systems in developing countries tend to be"restricted"or"repressed"through burdensome reserve requirements, interest-rate ceilings, foreign-exchange regulations, rules about the composition of bank balance sheets, or heavy taxation of the financial sector. Why are governments drawn to regulate financial markets to the point of financial repression? To address this question, the authors explore preliminary evidence from the post-Communist economies of Eastern Europe and the former Soviet Union, where financial regulations have rarely been examined systematically. They find that public-finance framework has limited ability to explain financial repression in the transition economies, given the peculiar financial lineage of the socialist state. The weak distinction between"public"and"private"spheres of finance in transition economies means that the deficit often conveys little information about the governments'real fiscal activities. It is more fruitful to examine how political institutions, by shaping the incentives politicians face, affect financial policy. Their findings suggest that post-Communist governments may adopt repressive financial controls - not to finance deficits more cheaply than would be the caseunder financial liberalization, but to maintain the authority and ensure the survival of those in power. In countries where pre-reform elites are plentiful in legislative bodies, where interparty competition is low, and where government parties are well-represented in parliaments, elites have been able to perpetuate a system of implicit subsidies by"softening up"the financial sector - especially commercial banks - to ensure the continued flow of cheap credit to specific borrowers. The main beneficiaries of these policies - large formerly state-owned industries with tight financial links to the largest commercial banks - are thus able to convert their well-established claims on public resources into preferential access to credit lines. In other words, financial repression in transition economies may simply serve to solidify main-bank, main-firm relations. These results would lend support to the claim of smaller, cash-starved Eastern European entrepreneurs that the commercial banks have"taken over the role of the old planning ministries. "
Depth from Shading Based on 2D Maximum Entropy

Depth from shading is an open problem in computer vision. During the estimation of object depth or shape, integrability constraint is enforced to regularize the solution. In this paper, we introduced a regularizing term of smoothness constraint employing the 2D maximum entropy to enforce the integrability. The test on synthetic image shows the proposed method has the better performance than the available methods. It is also robust to the noise, so there is a good application foreground for the method.
Irrelevant Updates and Self-maintainability in Transitive Closure Views

Irrelevant updates are updates to source data that do not aaect a view deened over the source data. Self-maintainable updates are ones for which the view can be updated, without having to access source data, when the source data from which the view is derived is updated. In this paper we derive necessary and suucient conditions for an update to be irrelevant or self-maintainable when the source data is a graph and the view is deened to be the transitive closure of the graph.
Allergy and Parasites

It is estimated that at least one-fifth of the world’s population suffers from allergic diseases (atopic asthma and allergic rhinitis are the most common). Different factors contribute to the development of allergies; a predisposing genetic background is needed; however, environmental factors play an important role, among them is the exposure to infectious agents.