Miracle-dz/UniFAR-FTUs huggingface dataset:
Migration and inequality in Germany, 1870-1913

Migration and Inequality in Germany 1870-1913 presents a new view of German history in the late nineteenth century. Dr Grant argues that many of the problems of Imperial Germany were temporary ones produced by the strain of rapid industrialisation. Drawing on the tools of development economics he argues that Germany passed through a labour surplus phase as desribed by the Lewis Model. This period came to an end around 1900, creating more favourable conditions for political reform and social reconciliation. But Germany's progress to full political and economic maturity was derailed at the outbreak of war in 1914. Dr Grant bases his argument on an analysis of the economic and demographic forces driving migration in nineteenth-century Germany. High rural-urban migration led to the rapid expansion of German cities. The main factors driving this were social and economic change in the countryside and the process of the demographic transition. The release of surplus labour onto urban labour markets held back wage increases and led to an increase in inequality. The German economy behaved in a way which seemed to bear out the predictions of Karl Marx and this contributed to the appeal of Marxist ideas and the rise of the social democratic vote. However, this was a temporary phase. The labour surplus period was largely over by 1900. The rise in inequality which had begun in the 1820s came to an end, and inequality began to fall. Contrary to received wisdom, Germany was not on the brink of a general socio-economic crisis in 1914; instead it was moving away from one. However, the political system failed to take advantage of this opportunity, and Germany's dependence on imported food and raw materials led to a strategic crisis which combined disastrously with internal political problems.
Minimum VaR and minimum CVaR optimal portfolios: Estimators, confidence regions, and tests

Abstract In this paper, we consider the sample estimators for the expected return, the variance, the value-at-risk (VaR), and the conditional VaR (CVaR) of the minimum VaR and the minimum CVaR portfolio. Their exact distributions are derived. These expressions are used for studying the distributional properties of the estimated characteristics. We prove that the expectation does not exist for the estimated variance, while the second moment does not exist for the estimated expected return. Moreover, expressions for the joint densities and the corresponding dependence measures between the estimators for the expected return and the variance as well as between the estimated expected return and the estimated VaR (CVaR) are derived. Finally, we present a confidence region for the minimum VaR portfolio and the minimum CVaR portfolio in the mean-variance space as well as in the mean-VaR (mean-CVaR) space. The obtained results are illustrated in an empirical study throughout the paper.
Research on the auxiliary panoramic parking technology based on fast image mosaic

The 360° panoramic auxiliary parking system is researched in this paper. Four fisheye cameras are installed around the car body. Zhang Zhengyou calibration method is used for fisheye camera. After distortion correction and overlooking transformation, four images are spliced into a panoramic aerial view. This paper focused on a simple and convenient fast image mosaic algorithm. Test results shows that the method proposed in this paper can generate 360° panoramic view for the car body. It can meet the requirement of observation with time-sensitive. It can provide effective real-time traffic information for the driver as a basis for judgment in the parking process.
Physical laws governing finite tight frames

We give a physical interpretation for finite tight frames along the lines of Columb's Law in Physics. This allows us to use results from classical mechanics to anticipate results in frame theory. As a consequence, we are able to classify those frames for an N-dimensional Hilbert space which are the closest to being tight (in the sense of minimizing potential energy) while having the norms of the frame vectors prescribed in advance. This also yields a fundamental inequality that all finite tight frames must satisfy.
Remarks on Transient Amplitude Analysis of MOS Cross-Coupled Oscillators

In this paper, closed-form analytical equations for the time-domain amplitude of the MOS cross-coupled oscillators are derived. The procedure of the paper is based on estimating an accurate equation for describing the behavior of the cross-coupled MOS configurations and finding a reasonable solution for the nonlinear differential equation governing the circuit. The solution method is presented for a general equation and is valid for all possible second-order oscillators. Both of the long channel and short channel transistor topologies have been investigated. The resulted equations are in a good agreement with simulation results for a wide range of the circuit parameters and enable us to analyze and synthesize the oscillators with the desired transient behavior.
Highway Traffic Safety Management System Based on the Theory of Dissipative Structures and Catastrophe Theory

Highway traffic safety management system is an open complex system, there are so many impact factors which influence highway safety, in this paper highway traffic safety management system is studied based on the theory of dissipative structure and catastrophe theory, it indicate that the highway safety management system will be stable or unstable under different disturbances, there are two different situation when the highway safety management system is unstable, one is the highway safety management system gradually die out when entropy production greater than 0, another one is highway safety management system will develop into more advanced system when entropy production less than 0. There exist mutation in those two process, the aim of highway traffic safety management is prevent highway traffic safety management system from dying out by effective management measure before mutation when entropy production greater than 0, and evolve to be a more advanced system through mutation when entropy production less than 0.
An evaluation of children with Kawasaki disease in Istanbul: a retrospective follow‐up study

BACKGROUND: Kawasaki disease (KD) is an acute, self‐limiting vasculitis of unknown etiology. The incidence of KD is increasing world wide. However, the epidemiological data for KD in Turkey has not been well described. OBJECTIVE: To describe the demographic, clinical, and laboratory features of children with KD who were diagnosed and managed in the American Hospital, Istanbul, Turkey. METHOD: Patients with KD were retrospectively identified from the hospital discharge records between 2002 and 2010. Atypical cases of KD were excluded. A standardized form was used to collect demographic data, clinical information, echocardiography and laboratory results. RESULTS: Thirty‐five patients with KD, with a mean age of 2.5±1.9 years, were identified. Eighty‐five point seven per cent of patients were under 5 years of age. A seasonal pattern favouring the winter months was noticed. In addition to fever and bilateral conjunctival injection, changes in the oral cavity and lips were the most commonly detected clinical signs in our cases. Coronary artery abnormalities were detected in nine patients. The majority of our patients had started treatment with intravenous immunoglobulin in the first 10 days of the onset of fever, and only one patient required systemic steroids for intravenous immunoglobulin‐resistant KD. The coronary artery abnormalities resolved in all nine patients within 8 months. CONCLUSION: This study is the most comprehensive series of children from Turkey with KD included in Medline. As adult‐onset ischemic heart disease may be due to KD in childhood, further prospective clinical investigations are needed to understand the epidemiology, management and long‐term follow‐up of the disease.
Conversational Tutors with Rich Interactive Behaviors that support Collaborative Learning

In addition to presenting relevant instructional content to learners in collaborative learning settings, intelligent conversational tutors must be good communicators to keep the students attentive and engaged. In our recent work, we have shown that tutors capable of performing both task-related (tutoring) as well as social behavior are more effective tutors than tutors that perform only task-related behavior. It is also important to consider that collaborative learning tasks in ill-defined domains (like engineering design) require students to negotiate among competing goals. Thus, automated tutors must be capable of supporting students with different roles and potentially competing goals. In this paper, we will describe the most recent implementation of the CycleTalk tutor using the Basilica architecture that demonstrates these social behavior and role supporting capabilities. Also, we briefly discuss results of an experiment using this tutor that optimizes the amount of social behavior in such learning settings.
Hybrid ARQ with Incremental Redundant Index Assignments for Iterative Source-Channel Decoding

Iterative source-channel decoding (ISCD) exploits the residual redundancy of source codec parameters by using the Turbo principle. In this paper we extend the excellent capabilities of ISCD to a hybrid automatic repeat request (HARQ) scheme by novel incremental redundant index assignments. The incremental redundancy for HARQ is supplied by the source encoder and not the channel encoder. Simulation results show an excellent performance over a wide range of channel conditions, with inherently adapted bandwidth and complexity.
Study of Countermeasures for Content Leaks by Video Recording

The authors have been engaged in the study of countermeasures to prevent the leak of onscreen movies using a digital video camera. One of the studies is the development of a transparent sheet that emits infrared (IR) light, which is applied to the screen and generates optical noise in the onscreen photographic images when recorded. Another study is the development of a method to detect the presence of the IR-cut filter near the display, which compromises the function of the IR emitting sheet as a countermeasure to prevent video recording using the IR-cut filter. This report is prepared as an advance report because it was confirmed that the feasibility of such countermeasures is enhanced.
DotSlash: A Scalable and Efficient Rescue System for Handling Web Hotspots

This paper describes DotSlash, a scalable and efficient rescue system for handling web hotspots. DotSlash allows different web sites to form a mutual-aid community, and use spare capacity in the community to relieve web hotspots experienced by any individual site. As a rescue system, DotSlash intervenes when a web site becomes heavily loaded, and is phased out once the workload returns to normal. It aims to complement existing web server infrastructure such as CDNs to handle short-term load spikes effectively, but is not intended to support a request load constantly higher than a web site’s planned capacity. DotSlash is scalable, cost-effective, easy to use, self-configuring, and transparent to clients. It targets small web sites, although large web site can also benefit from it. We have implemented a prototype of DotSlash on top of Apache. Experiments show that DotSlash can provide an order of magnitude improvement for a web server in terms of the request rate supported and the data rate delivered to clients even if only HTTP redirect is used. Parts of this work may be applicable to other services such as the Grid computational services and media streaming.
Exploration/exploitation in adaptive recommender systems

Interactive information systems are often designed on the basis of little knowledge about users goals and about the final content of the information base. In addition users vary widely in their interests. This makes it useful to give such systems the ability to dynamically adapt to its users. Here we focus on "recommending" systems that help a user navigate through the information system. In particular we consider methods for automatically improving the systems recommendation policy on the basis of feedback from the users. We approach this problem from the framework of rein- forcement learning. One key idea in reinforcement learning is that exploration of unknown areas of a domain is needed to acquire an optimal policy. We demonstrate with a toy problem that this is an essential element for recommender systems that automatically improve their recommending policy.
Learning Chaotic Attractors by Neural Networks

An algorithm is introduced that trains a neural network to identify chaotic dynamics from a single measured time series. During training, the algorithm learns to short-term predict the time series. At the same time a criterion, developed by Diks, van Zwet, Takens, and de Goede (1996) is monitored that tests the hypothesis that the reconstructed attractors of model-generated and measured data are the same. Training is stopped when the prediction error is low and the model passes this test. Two other features of the algorithm are (1) the way the state of the system, consisting of delays from the time series, has its dimension reduced by weighted principal component analysis data reduction, and (2) the user-adjustable prediction horizon obtained by error propagationpartially propagating prediction errors to the next time step. The algorithm is first applied to data from an experimental-driven chaotic pendulum, of which two of the three state variables are known. This is a comprehensive example that shows how well the Diks test can distinguish between slightly different attractors. Second, the algorithm is applied to the same problem, but now one of the two known state variables is ignored. Finally, we present a model for the laser data from the Santa Fe time-series competition (set A). It is the first model for these data that is not only useful for short-term predictions but also generates time series with similar chaotic characteristics as the measured data.
Fair and Effective Transmissions in IEEE 802.11e WLAN

The goal of the Enhanced DCF (EDCF) is to provide a distributed access approach that can support service differentiation in IEEE 802.11e Wireless LAN. In this paper we propose a control mechanism to support fair and effective transmissions in IEEE 802.11e Wireless LAN. Since the proposed mechanism transmits packets using the link states and transmitted contents, higher transmission efficiency can be obtained by reducing unnecessary bandwidth usage. Fairness among mobile hosts also will be considered in this paper. The proposed algorithm uses short-term and long-term transmission times of each traffic classes to control their CWmin for fairness.
Radiation dry bias correction of Vaisala RS92 humidity data and its impacts on historical radiosonde data

AbstractThe Vaisala RS92 radiosonde is the most widely used type of sonde in the current global radiosonde network. One of the largest biases in the RS92 humidity data is its daytime solar radiation dry bias (SRDB). An algorithm [referred to as NCAR radiation bias correction (NRBC)] was developed to correct the SRDB based on a more complicated algorithm developed by the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN). The NRBC to relative humidity (RH) is a function of the measured RH and temperature, and the temperature solar radiation correction. The latter varies with pressure, season, and time of the day. The RH correction has a mean magnitude of about 2%–4% and 6%–8% in the lower–midtroposphere and upper troposphere, respectively. The NRBC is evaluated against the GRUAN-corrected RS92 data and the ground-based GPS-estimated precipitable water (PW). The corrected RH agrees with the GRUAN data within ±0.5% on average, with standard deviations of about 1%–2% and 2%–6% in the l.
Abstract Machine Models and Proxy Architectures for Exascale Computing

To achieve exascale computing, fundamental hardware architectures must change. This will significantly impact scientific applications that run on current high performance computing (HPC) systems, many of which codify years of scientific domain knowledge and refinements for contemporary computer systems. To adapt to exascale architectures, developers must be able to reason about new hardware and determine what programming models and algorithms will provide the best blend of performance and energy efficiency in the future. An abstract machine model is designed to expose to the application developers and system software only the aspects of the machine that are important or relevant to performance and code structure. These models are intended as communication aids between application developers and hardware architects during the co-design process. A proxy architecture is a parameterized version of an abstract machine model, with parameters added to elucidate potential speeds and capacities of key hardware components. These more detailed architectural models enable discussion among the developers of analytic models and simulators and computer hardware architects and they allow for application performance analysis, system software development, and hardware optimization opportunities. In this paper, we present a set of abstract machine models and show how they might be used to help software developers prepare for exascale. We then apply parameters to one of these models to demonstrate how a proxy architecture can enable a more concrete exploration of how well application codes map onto future architectures.
Stargazin and Other Transmembrane AMPA Receptor Regulating Proteins Interact with Synaptic Scaffolding Protein MAGI-2 in Brain

The spatial coordination of neurotransmitter receptors with other postsynaptic signaling and structural molecules is regulated by a diverse array of cell-specific scaffolding proteins. The synaptic trafficking of AMPA receptors by the stargazin protein in some neurons, for example, depends on specific interactions between the C terminus of stargazin and the PDZ [postsynaptic density-95 (PSD-95)/Discs large/zona occludens-1] domains of membrane-associated guanylate kinase scaffolding proteins PSD-93 or PSD-95. Stargazin [Cacng2 (Ca2+ channel γ2 subunit)] is one of four closely related proteins recently categorized as transmembrane AMPA receptor regulating proteins (TARPs) that appear to share similar functions but exhibit distinct expression patterns in the CNS. We used yeast two-hybrid screening to identify MAGI-2 (membrane associated guanylate kinase, WW and PDZ domain containing 2) as a novel candidate interactor with the cytoplasmic C termini of the TARPs. MAGI-2 [also known as S-SCAM (synaptic scaffolding molecule)] is a multi-PDZ domain scaffolding protein that interacts with several different ligands in brain, including PTEN (phosphatase and tensin homolog), dasm1 (dendrite arborization and synapse maturation 1), dendrin, axin, β- and δ-catenin, neuroligin, hyperpolarization-activated cation channels, β1-adrenergic receptors, and NMDA receptors. We confirmed that MAGI-2 coimmunoprecipitated with stargazin in vivo from mouse cerebral cortex and used in vitro assays to localize the interaction to the C-terminal -TTPV amino acid motif of stargazin and the PDZ1, PDZ3, and PDZ5 domains of MAGI-2. Expression of stargazin recruited MAGI-2 to cell membranes and cell–cell contact sites in transfected HEK-293T cells dependent on the presence of the stargazin -TTPV motif. These experiments identify MAGI-2 as a strong candidate for linking TARP/AMPA receptor complexes to a wide range of other postsynaptic molecules and pathways and advance our knowledge of protein interactions at mammalian CNS synapses.
A Comparison between Adaptive Algorithms in Telecommunications Networks Planning

The main goal of this work is to propose a way to compare two nontraditional algorithms by solving topological problems on telecommunications concentrator networks. The algorithms suggested are the simulated annealing algorithm (SA) and the genetic algorithm (GA). The proposed algorithms are used for finding an optimal solution for a small network, the results are being analyzed and some recommendations for the proper use of these algorithms are made
Glutamate Residues Required for Substrate Binding and Cleavage Activity in Mitochondrial Processing Peptidase*

Mitochondrial processing peptidase, a metalloendopeptidase consisting of α- and β-subunits, specifically recognizes a large variety of mitochondrial precursor proteins and cleaves off N-terminal extension peptides. The enzyme requires the basic amino acid residues in the extension peptides for effective and specific cleavage. To elucidate the mechanism involved in the molecular recognition of substrate by the enzyme, several glutamates around the active site of the rat β-subunit, which has a putative metal-binding motif, H56 XXEH60, were mutated to alanines or aspartates, and effects on kinetic parameters, metal binding, and substrate binding of the enzyme were analyzed. None of mutant proteins analyzed was impaired in dimer formation with the α-subunit. Mutation of glutamates at positions 79, 129, and 136, in addition to an active-site glutamate at position 59, resulted in a marked decrease in cleavage efficiency. Together with sequence alignment data, glutamate 136 appears to be involved in metal binding. Glutamate 129 is mostly responsible for the catalysis, as there was a considerable decrease in k cat value by the mutation. Mutation of glutamate 79 led to decrease ink cat value and increase inK m values. Substrate binding experiments using an environmentally sensitive fluorescence probe attached to the peptide showed that the mutation caused a remarkable environmental change at the binding site to the N-terminal region of the substrate peptide and decreased binding of the peptide, thereby suggesting that glutamate 79 participates primarily in substrate binding. Thus, some glutamate residues required for substrate binding and cleavage activity have been identified.
Offloading VoD Server Organized Dynamically Distributed Cache Using P2P Delivery

A characteristic of video-on-demand (VoD) service is the concentration of access to a few popular content files within short time intervals. Focusing on this characteristic, this paper proposes the concept of a chunk group to reduce the load of both storage and networks on the VoD server. The fundamental idea of this method is to dynamically form a group for clients demanding the same content file and off-load the VoD server load to the groups of clients. The VoD server delivers content to only one client in a group of clients, and the clients deliver the content among the group using peer-to-peer (P2P) communication. This method manages the distributed cache of the fragment of a content file with the cooperating VoD server and clients to reduce the server load. Also, the method provides a failure recovery mechanism so that, even when a client in the group leaves the delivery network, other clients of the group continue the playback. A performance evaluation based on a simulation is carried out to predict the effectiveness of the method. The results show that, with a 12 MB cache capacity on a client side, the number of delivery clients can be improved by 50% at an average arrival interval of 3 seconds and by 11% at an average arrival interval of 9 seconds.